Tag Archives: Thought Leadership

Architecting for Sustainability at AWS re:Invent 2022

Post Syndicated from Thomas Burns original https://aws.amazon.com/blogs/architecture/architecting-for-sustainability-at-aws-reinvent-2022/

AWS re:Invent 2022 featured 24 breakout sessions, chalk talks, and workshops on sustainability. In this blog post, we’ll highlight the sessions and announcements and discuss their relevance to the sustainability of, in, and through the cloud.

First, we’ll look at AWS’ initiatives and progress toward delivering efficient, shared infrastructure, water stewardship, and sourcing renewable power.

We’ll then summarize breakout sessions featuring AWS customers who are demonstrating the best practices from the AWS Well-Architected Framework Sustainability Pillar.

Lastly, we’ll highlight use cases presented by customers who are solving sustainability challenges through the cloud.

Sustainability of the cloud

The re:Invent 2022 Sustainability in AWS global infrastructure (SUS204) session is a deep dive on AWS’ initiatives to optimize data centers to minimize their environmental impact. These increases in efficiency provide carbon reduction opportunities to customers who migrate workloads to the cloud. Amazon’s progress includes:

  • Amazon is on path to power its operations with 100% renewable energy by 2025, five years ahead of the original target of 2030.
  • Amazon is the largest corporate purchaser of renewable energy with more than 400 projects globally, including recently announced projects in India, Canada, and Singapore. Once operational, the global renewable energy projects are expected to generate 56,881 gigawatt-hours (GWh) of clean energy each year.

At re:Invent, AWS announced that it will become water positive (Water+) by 2030. This means that AWS will return more water to communities than it uses in direct operations. This Water stewardship and renewable energy at scale (SUS211) session provides an excellent overview of our commitment. For more details, explore the Water Positive Methodology that governs implementation of AWS’ water positive goal, including the approach and measuring of progress.

Sustainability in the cloud

Independent of AWS efforts to make the cloud more sustainable, customers continue to influence the environmental impact of their workloads through the architectural choices they make. This is what we call sustainability in the cloud.

At re:Invent 2021, AWS launched the sixth pillar of the AWS Well-Architected Framework to explain the concepts, architectural patterns, and best practices to architect sustainably. In 2022, we extended the Sustainability Pillar best practices with a more comprehensive structure of anti-patterns to avoid, expected benefits, and implementation guidance.

Let’s explore sessions that show the Sustainability Pillar in practice. In the session Architecting sustainably and reducing your AWS carbon footprint (SUS205), Elliot Nash, Senior Manager of Software Development at Amazon Prime Video, dives deep on the exclusive streaming of Thursday Night Football on Prime Video. The teams followed the Sustainability Pillar’s improvement process from setting goals to replicating the successes to other teams. Implemented improvements include:

  • Automation of contingency switches that turn off non-critical customer features under stress to flatten demand peaks
  • Pre-caching content shown to the whole audience at the end of the game

Amazon Prime Video uses the AWS Customer Carbon Footprint Tool along with sustainability proxy metrics and key performance indicators (KPIs) to quantify and track the effectiveness of optimizations. Example KPIs are normalized Amazon Elastic Compute Cloud (Amazon EC2) instance hours per page impression or infrastructure cost per concurrent stream.

Another example of sustainability KPIs was presented in the Build a cost-, energy-, and resource-efficient compute environment (CMP204) session by Troy Gasaway, Vice President of Infrastructure and Engineering at Arm—a global semiconductor industry leader. Troy’s team wanted to measure, track, and reduce the impact of Electronic Design Automation (EDA) jobs. They used Amazon EC2 instances’ vCPU hours to calculate KPIs for Amazon EC2 Spot adoption, AWS Graviton adoption, and the resources needed per job.

The Sustainability Pillar recommends selecting Amazon EC2 instance types with the least impact and taking advantage of those designed to support specific workloads. The Sustainability and AWS silicon (SUS206) session gives an overview of the embodied carbon and energy consumption of silicon devices. The session highlights examples in which AWS silicon reduced the power consumption for machine learning (ML) inference with AWS Inferentia by 92 percent, and model training with AWS Trainium by 52 percent. Two effects contributed to the reduction in power consumption:

  • Purpose-built processors use less energy for the job
  • Due to better performance fewer instances are needed

David Chaiken, Chief Architect at Pinterest, shared Pinterest’s sustainability journey and how they complemented a rigid cost and usage management for ML workloads with data from the AWS Customer Carbon Footprint Tool, as in the figure below.

David Chaiken, Chief Architect at Pinterest, describes Pinterest’s sustainability journey with AWS

Figure 1. David Chaiken, Chief Architect at Pinterest, describes Pinterest’s sustainability journey with AWS

AWS announced the preview of a new generation of AWS Inferentia with the Inf2 instances, and C7gn instances. C7gn instances utilize the fifth generation of AWS Nitro cards. AWS Nitro offloads the host CPU to specialized hardware for a more consistent performance with lower CPU utilization. The new Nitro cards offer 40 percent better performance per watt than the previous generation.

Another best practice from the Sustainability Pillar is to use managed services. AWS is responsible for a large share of the optimization for resource efficiency for AWS managed services. We want to highlight the launch of AWS Verified Access. Traditionally, customers protect internal services from unauthorized access by placing resources into private subnets accessible through a Virtual Private Network (VPN). This often involves dedicated on-premises infrastructure that is provisioned to handle peak network usage of the staff. AWS Verified Access removes the need for a VPN. It shifts the responsibility for managing the hardware to securely access corporate applications to AWS and even improves your security posture. The service is built on AWS Zero Trust guiding principles and validates each application request before granting access. Explore the Introducing AWS Verified Access: Secure connections to your apps (NET214) session for demos and more.

In the session Provision and scale OpenSearch resources with serverless (ANT221) we announced the availability of Amazon OpenSearch Serverless. By decoupling compute and storage, OpenSearch Serverless scales resources in and out for both indexing and searching independently. This feature supports two key sustainability in the cloud design principles from the Sustainability Pillar out of the box:

  1. Maximizing utilization
  2. Scaling the infrastructure with user load

Sustainability through the cloud

Sustainability challenges are data problems that can be solved through the cloud with big data, analytics, and ML.

According to one study by PEDCA research, data centers in the EU consume approximately 3 percent of the EU’s energy generated. While it’s important to optimize IT for sustainability, we must also pay attention to reducing the other 97 percent of energy usage.

The session Serve your customers better with AWS Supply Chain (BIZ213) introduces AWS Supply Chain that generates insights into the data from your suppliers and your network to forecast and mitigate inventory risks. This service provides recommendations for stock rebalancing scored by distance to move inventory, risks, and also an estimation of the carbon emission impact.

The Easily build, train, and deploy ML models using geospatial data (AIM218) session introduces new Amazon SageMaker geospatial capabilities to analyze satellite images for forest density and land use changes and observe supply chain impacts. The AWS Solutions Library contains dedicated Guidance for Geospatial Insights for Sustainability on AWS with example code.

Some other examples for driving sustainability through the cloud as covered at re:Invent 2022 include these sessions:

Conclusion

We recommend revisiting the talks highlighted in this post to learn how you can utilize AWS to enhance your sustainability strategy. You can find all videos from the AWS re:Invent 2022 sustainability track in the Customer Enablement playlist. If you’d like to optimize your workloads on AWS for sustainability, visit the AWS Well-Architected Sustainability Pillar.

Let’s Architect! Architecture tools

Post Syndicated from Luca Mezzalira original https://aws.amazon.com/blogs/architecture/lets-architect-architecture-tools/

Tools, such as diagramming software, low-code applications, and frameworks, make it possible to experiment quickly. They are essential in today’s fast-paced and technology-driven world. From improving efficiency and accuracy, to enhancing collaboration and creativity, a well-defined set of tools can make a significant impact on the quality and success of a project in the area of software architecture.

As an architect, you can take advantage of a wide range of resources to help you build solutions that meet the needs of your organization. For example, with tools in the likes of the Amazon Web Services (AWS) Solutions Library and Serverless Land, you can boost your knowledge and productivity while working on event-driven architectures, microservices, and stateless computing.

In this Let’s Architect! edition, we explore how to incorporate these patterns into your architecture, and which tools to leverage to build solutions that are scalable, secure, and cost-effective.

How AWS Application Composer helps your team build great apps

In this re:Invent 2022 session, Chase Douglas, Principal Engineer at AWS, speaks about AWS Application Composer, a newly launched service.

This service has the potential to change the way architects design solutions—without writing a single line of code! The service is user-friendly, intuitive, and requires no prior coding experience. It allows users to scaffold a serverless architecture, defining a CloudFormation template visually with drag-and-drop. A detailed AWS Compute Blog post takes readers through the process of using AWS Application Composer.

Take me to this re:Invent 2022 video!

How an architecture can be designed with AWS Application Composer

How an architecture can be designed with AWS Application Composer

AWS design + build tools

When migrating to the cloud, we suggest referencing these four tried-and-true AWS resources that can be used to design and build projects.

  1. AWS Workshops are created by AWS teams to provide opportunities for hands-on learning to develop practical skills. Workshops are available in multiple categories and for skill levels 100-400.
  2. AWS Architecture Center contains a collection of best practices and architectural patterns for designing and deploying cloud-based solutions using AWS services. Furthermore, it includes detailed architecture diagrams, whitepapers, case studies, and other resources that provide a wealth of information on how to design and implement cloud solutions.
  3. Serverless Land (an Amazon property) brings together various patterns, workflows, code snippets, and blog posts pertaining to AWS serverless architectures.
  4. AWS Solutions Library provides customers with templates, tools, and automated workflows to easily deploy, operate, and manage common use cases on the AWS Cloud.
Inside event-driven architectures designed by David Boyne on Serverless Land

Inside event-driven architectures designed by David Boyne on Serverless Land

The Well-Architected way

In this session, the AWS Well-Architected provides guidance on how to implement the architectural models reported in the AWS Well-Architected Framework within your organization at scale.

Discover a customer story and understand how to use the features of the AWS Well-Architected Tool and APIs to receive recommendations based on your workload and measure your architectural metrics. In the Framework whitepaper, you can explore the six pillars of Well-Architected (operational excellence, security, reliability, performance efficiency, cost optimization, and sustainability) and best practices to achieve them.

Understanding the key design pillars can help architects make informed design decisions, leading to more robust and efficient solutions. This knowledge also enables architects to identify potential problems early on in the design process and find appropriate patterns to address those issues.

Take me to the Well-Architected video!

Discover how the AWS Well-Architected Framework can help you design scalable, maintainable, and reusable solutions

Discover how the AWS Well-Architected Framework can help you design scalable, maintainable, and reusable solutions

See you next time!

Thanks for exploring architecture tools and resources with us!

Join us next time when we’ll talk about data mesh architecture!

To find all the posts from this series, check out the Let’s Architect! page of the AWS Architecture Blog.

Author Spotlight: Eduardo Monich Fronza, Senior Partner Solutions Architect, Linux and IBM

Post Syndicated from Elise Chahine original https://aws.amazon.com/blogs/architecture/author-spotlight-eduardo-monich-fronza-senior-partner-sa-linux-and-ibm/

The Author Spotlight series pulls back the curtain on some of AWS’s most prolific authors. Read on to find out more about our very own Eduardo Monich Fronza’s journey, in his own words!

I have been a Partner Solutions Architect at Amazon Web Services (AWS) for just over two years. In this period, I have had the opportunity to work in projects from different partners and customers across the globe, in multiple industry segments, using a wide variety of technologies.

At AWS, we are obsessed with our customers, and this influences all of our activities. I enjoy diving deep to understand our partners’ motivations, as well as their technical and business challenges. Plus, I work backwards from their goals, helping them build innovative solutions using AWS services—solutions that they can successfully offer to their customers and achieve their targeted business results.

Before joining AWS, I worked mainly in Brazil for many years as a middleware engineer and, later, a cloud migration architect. During this period, I travelled to my customers in North America and Europe. These experiences taught me a lot about customer-facing engagements, how to focus on customers problems, and how to work backwards from those.

When I joined AWS, I was exposed to so many new technologies and projects that I have never had any previous experience with! This was a very exciting, as it provided me with many opportunities to dive deep and learn. A couple of the places I love to go to learn new content are our AWS Architecture Blog and AWS Reference Architecture Diagrams library.

The other thing I’ve realized during my tenure is how amazing it is to work with other people at AWS. I can say that I feel very fortunate to work with a wide range of intelligent and passionate problem-solvers. My peers are always willing to help and work together to provide the best possible solutions for our partners. I believe this collaboration is one of the reasons why AWS has been able to help partners and customer be so successful in their journeys to the cloud.

AWS encourages us to dive deep and specialize in technology domains. My background as a middleware engineer has influenced my decisions, and I am passionate about application modernization and containers areas in particular. A couple of topics that I am particularly interested in are Red Hat OpenShift Service on AWS (ROSA) and IBM software on AWS.

Eduardo presenting on the strategic partnership between AWS and IBM at IBM Think London 2022

Eduardo presenting on the strategic partnership between AWS and IBM at IBM Think London 2022

This also shows how interesting it is to work with ISVs like Red Hat and IBM. It demonstrates, yet again, how AWS is customer-obsessed and works backwards from what customers need to be successful in their own rights. Regardless of if they are using AWS native services or an ISV solution on AWS, we at AWS always focus on what is right for our customers.

I am also very fond of running workshops, called Immersion Days, for our customers. And, I have recently co-authored an AWS modernization workshop with IBM, which shows how customers can use IBM Cloud Pak for Data on AWS along with AWS services to create exciting Analytics and AI/ML workloads!

In conclusion, working as a Partner Solutions Architect at AWS has been an incredibly rewarding experience for me. I work with great people, a wide range of industries and technologies, and, most importantly, help our customers and partners innovate and find success on AWS. If you are considering a career at AWS, I would highly recommend it: it’s an unparalleled working experience, and the are no shortages of opportunities to take part in exciting projects!

Eduardo’s favorite blog posts!

Deploying IBM Cloud Pak for Data on Red Hat OpenShift Service on AWS

Alright, I will admit: I am being a bit biased. But, hey, this was my first blog at AWS! Many customers are looking to adopt IBM Data and AI solutions on AWS, particularly on how to use ROSA to deploy IBM Cloud Pak for Data.

So, I created a how-to deployment guide, demonstrating how a customer can take advantage of ROSA, without having to manage the lifecycle of Red Hat OpenShift Container Platform clusters. Instead, I focus on developing new solutions and innovating faster, using IBM’s integrated data and artificial intelligence platform on AWS.

IBM Cloud Pak for Integration on ROSA architecture

IBM Cloud Pak for Integration on ROSA architecture

Unleash Mainframe Applications by Augmenting New Channels on AWS with IBM Z and Cloud Modernization Stack

Many AWS customers use the IBM mainframe for their core business-critical applications. These customers are looking for ways to build modern cloud-native applications on AWS, that often require access to business-critical data on their IBM mainframe.

This AWS Partner Network (APN) Blog post shows how these customers can integrate cloud-native applications on AWS, with workloads running on mainframes, by exposing them as industry standard RESTful APIs with a no-code approach.

Mainframe-to-AWS integration reference architecture.

Mainframe-to-AWS integration reference architecture.

Migrate and Modernize Db2 Databases to Amazon EKS Using IBM’s Click to Containerize Tool

This blog shows customers, who are exploring ways to modernize their IBM Db2 databases, can move their databases quickly and easily to Amazon Elastic Kubernetes Service (Amazon EKS), ROSA and IBM’s Cloud Pak for Data products on AWS.

Scenario showing move from instance to container

Scenario showing move from instance to container

Self-service AWS native service adoption in OpenShift using ACK

This Containers Blog post demonstrates how customers can use AWS Controllers for Kubernetes (ACK) to define and create AWS resources directly from within OpenShift. It allows customers to take advantage of AWS-managed services to complement the application workloads running in OpenShift, without needing to define resources outside of the cluster or run services that provide supporting capabilities like databases or message queues.

ACK is now integrated into OpenShift and being used to provide a broad collection of AWS native services presently available on the OpenShift OperatorHub.

AWS Controllers for Kubernetes workflow

AWS Controllers for Kubernetes workflow

AWS Security Profile: Jana Kay, Cloud Security Strategist

Post Syndicated from Roger Park original https://aws.amazon.com/blogs/security/aws-security-profile-jana-kay-cloud-security-strategist/

In the AWS Security Profile series, we interview Amazon Web Services (AWS) thought leaders who help keep our customers safe and secure. This interview features Jana Kay, Cloud Security Strategist. Jana shares her unique career journey, insights on the Security and Resiliency of the Cloud Tabletop Exercise (TTX) program, thoughts on the data protection and cloud security landscape, and more.

How long have you been at AWS and what do you do in your current role?
I’ve been at AWS a little over four years. I started in 2018 as a Cloud Security Strategist, and in my opinion, I have one of the coolest jobs at AWS. I get to help customers think through how to use the cloud to address some of their most difficult security challenges, by looking at trends and emerging and evolving issues, and anticipating those that might still be on the horizon. I do this through various means, such as whitepapers, short videos, and tabletop exercises. I love working on a lot of different projects, which all have an impact on customers and give me the opportunity to learn new things myself all the time!

How did you get started in the security space? What about it piqued your interest?
After college, I worked in the office of a United States senator, which led me to apply to the Harvard Kennedy School for a graduate degree in public policy. When I started graduate school, I wasn’t sure what my focus would be, but my first day of class was September 11, 2001, which obviously had a tremendous impact on me and my classmates. I first heard about the events of September 11 while I was in an international security policy class, taught by the late Dr. Ash Carter. My classmates and I came from a range of backgrounds, cultures, and professions, and Dr. Carter challenged us to think strategically and objectively—but compassionately—about what was unfolding in the world and our responsibility to effect change. That experience led me to pursue a career in security. I concentrated in international security and political economy, and after graduation, accepted a Presidential Management Fellowship in the Office of the Secretary of Defense at the Pentagon, where I worked for 16 years before coming to AWS.

What’s been the most dramatic change you’ve seen in the security industry?
From the boardroom to builder teams, the understanding that security has to be integrated into all aspects of an organization’s ecosystem has been an important shift. Acceptance of security as foundational to the health of an organization has been evolving for a while, and a lot of organizations have more work to do, but overall there is prioritization of security within organizations.

I understand you’ve helped publish a number of papers at AWS. What are they and how can customers find them?
Good question! AWS publishes a lot of great whitepapers for customers. A few that I’ve worked on are Accreditation Models for Secure Cloud Adoption, Security at the Edge: Core Principles, and Does data localization cause more problems than it solves? To stay updated on the latest whitepapers, see AWS Whitepapers & Guides.

What are your thoughts on the security of the cloud today?
There are a lot of great technologies—such as AWS Data Protection services—that can help you with data protection, but it’s equally important to have the right processes in place and to create a strong culture of data protection. Although one of the biggest shifts I’ve seen in the industry is recognition of the importance of security, we still have a ways to go for people to understand that security and data protection is everyone’s job, not just the job of security experts. So when we talk about data protection and privacy issues, a lot of the conversation focuses on things like encryption, but the conversation shouldn’t end there because ultimately, security is only as good as the processes and people who implement it.

Do you have a favorite AWS Security service and why?
I like anything that helps simplify my life, so AWS Control Tower is one of my favorites. It has so much functionality. Not only does AWS Control Tower help you set up multi-account AWS environments, you can use it to help identify which of your resources are compliant. The dashboard, which allows for visibility of provisioned accounts, controls enabled policy enforcement and can help you detect noncompliant resources.

What are you currently working on that you’re excited about?
Currently, my focus is the Security and Resiliency of the Cloud Tabletop Exercise (TTX). It’s a 3-hour interactive event about incident response in which participants discuss how to prevent, detect, contain, and eradicate a simulated cyber incident. I’ve had the opportunity to conduct the TTX in South America, the Middle East, Europe, and the US, and it’s been so much fun meeting customers and hearing the discussions during the TTX and how much participants enjoy the experience. It scales well for groups of different sizes—and for a single customer or industry or for multiple customers or industries—and it’s been really interesting to see how the conversations change depending on the participants.

How does the Security and Resiliency of the Cloud Tabletop Exercise help security professionals hone their skills?
One of the great things about the tabletop is that it involves interacting with other participants. So it’s an opportunity for security professionals and business leaders to learn from their peers, hear different perspectives, and understand all facets of the problem and potential solutions. Often our participants range from CISOs to policymakers to technical experts, who come to the exercise with different priorities for data protection and different ideas on how to solve the scenarios that we present. The TTX isn’t a technical exercise, but participants link their collective understanding of what capabilities are needed in a given scenario to what services are available to them and then finally how to implement those services. One of the things that I hope participants leave with is a better understanding of the AWS tools and services that are available to them.

How can customers learn more about the Security and Resiliency of the Cloud Tabletop Exercise?
To learn more about the TTX, reach out to your account manager.

Is there something you wish customers would ask you about more often?
I wish they’d ask more about what they should be doing to prepare for a cyber incident. It’s one thing to have an incident response plan; it’s another thing to be confident that it’s going to work if you ever need it. If you don’t practice the plan, how do you know that it’s effective, if it has gaps, or if everyone knows their role in an incident?

How about outside of work—any hobbies?
I’m the mother of a teenager and tween, so between keeping up with their activities, I wish I had more time for hobbies! But someday soon, I’d like to get back to traveling more for leisure, reading for fun, and playing tennis.

 
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Roger Park

Roger Park

Roger is a Senior Security Content Specialist at AWS Security focusing on data protection. He has worked in cybersecurity for almost ten years as a writer and content producer. In his spare time, he enjoys trying new cuisines, gardening, and collecting records.

Author

Jana Kay

Since 2018, Jana has been a cloud security strategist with the AWS Security Growth Strategies team. She develops innovative ways to help AWS customers achieve their objectives, such as security table top exercises and other strategic initiatives. Previously, she was a cyber, counter-terrorism, and Middle East expert for 16 years in the Pentagon’s Office of the Secretary of Defense.

How to Connect Business and Technology to Embrace Strategic Thinking (Book Review)

Post Syndicated from Danilo Poccia original https://aws.amazon.com/blogs/aws/how-to-connect-business-and-technology-to-embrace-strategic-thinking-book-review/

The Value Flywheel Effect: Power the Future and Accelerate Your Organization to the Modern Cloud
by David Anderson with Mark McCann and Michael O’Reilly

With this post, I’d like to share a new book that got my attention. It’s a book at the intersection of business, technology, and people. This is a great read for anyone who wants to understand how organizations can evolve to maximize the business impact of new technologies and speed up their internal processes.

The Value FlyWheel Effect book with David Anderson and Danilo Poccia

Last year at re:Invent, I had the opportunity to meet David Anderson. As Director of Technology at Liberty Mutual, he drove the technology change when the global insurance company, founded in 1912, moved its services to the cloud and adopted a serverless-first strategy. He created an environment where experimentation was normal, and software engineers had time and space to learn. This worked so well that, at some point, he had four AWS Heroes in his extended team.

A few months before, I heard that David was writing a book with Mark McCann and Michael O’Reilly. They all worked together at Liberty Mutual, and they were distilling their learnings to help other organizations implement a similar approach. The book was just out when we met, and I was curious to learn more, starting from the title. We met in the expo area, and David was kind enough to give me a signed copy of the book.

The book is published by IT Revolution, the same publisher behind some of my favorite books such as The Phoenix Project, Team Topologies, and Accelerate. The book is titled The Value Flywheel Effect because when you connect business and technology in an organization, you start to turn a flywheel that builds momentum with each small win.

The Value Flywhell
The four phases of the Value Flywheel are:

  1. Clarity of Purpose – This is the part where you look at what is really important for your organization, what makes your company different, and define your North Star and how to measure your distance from it. In this phase, you look at the company through the eyes of the CEO.
  2. Challenge & Landscape – Here you prepare the organization and set up the environment for the teams. We often forget the social aspect of technical teams and great focus is given here on how to set up the right level of psychological safety for teams to operate. This phase is for engineers.
  3. Next Best Action – In this phase, you think like a product leader and plan the next steps with a focus on how to improve the developer experience. One of the key aspects is that “code is a liability” and the less code you write to solve a business problem, the better it is for speed and maintenance. For example, you can avoid some custom implementations and offload their requirements to capabilities offered by cloud providers.
  4. Long-Term Value – This is the CTO perspective, looking at how to set up a problem-preventing culture with well-architected systems and a focus on observability and sustainability. Sustainability here is not just considering the global environment but also the teams and the people working for the organization.

As you would expect from a flywheel, you should iterate on these four phases so that every new spin gets easier and faster.

Wardley Mapping
One thing that I really appreciate from the book is how it made it easy for me to use Wardley mapping (usually applied to a business context) in a technical scenario. Wardley maps, invented by Simon Wardley, provide a visual representation of the landscape in which a business operates.

Each map consists of a value chain, where you draw the components that your customers need. The components are connected to show how they depend on each other. The position of the components is based on how visible they are to customers (vertical) and their evolution status from genesis to being a product or a commodity (horizontal). Over time, some components evolve from being custom-built to becoming a product or being commoditized. This displays on the map with a natural movement to the right as things evolve. For example, data centers were custom-built in the past, but then they became a standard product, and cloud computing made them available as a commodity.

Wardley mapping – Basic elements of a map

Basic elements of a map – Provided courtesy of Simon Wardley, CC BY-SA 4.0.

With mapping, you can more easily understand what improvements you need and what gaps you have in your technical solution. In this way, engineers can identify which components they should focus on to maximize their impact and what parts are not strategic and can be offloaded to a SaaS solution. It’s a sort of evolutionary architecture where mapping gives a way to look ahead at how the system should evolve over time and where inertia can slow down the evolution of part of the system.

Sometimes it seems the same best practices apply everywhere but this is not true. An advantage of mapping is that it helps identify the best team and methodology to use based on a component evolution status as described by its horizontal position on a map. For example, an “explorer” attitude is best suited for components in their genesis or being custom built, a “villager” works best on products, and when something becomes a commodity you need a “town planner.”

More Tools and Less Code
The authors look at many available tools and frameworks. For example, the book introduces the North Star Framework, a way to manage products by first identifying their most important metric (the North Star), and Gojko Adzic‘s Impact Mapping, a collaborative planning technique that focuses on leading indicators to help teams make a big impact with their software products. By the way, Gojko is also an AWS Serverless Hero.

Another interesting point is how to provide engineers with the necessary time and space to learn. I specifically like how internal events are called out and compared to public conferences. In internal events, engineers have a chance to use a new technology within their company environment, making it easier to demonstrate what can be done with all the limits of an actual scenario.

Finally, I’d like to highlight this part that clearly defines what the book intends by the statements, “code is a liability”:

“When you ask a software team to build something, they deliver a system, not lines of code. The asset is not the code; the asset is the system. The less code in the system, the less overhead you have bought. Some developers may brag about how much code they’ve written, but this isn’t something to brag about.”

This is not a programming book, and serverless technologies are used as examples of how you can speed up the flywheel. If you are looking for a technical deep dive on serverless technologies, you can find more on Serverless Land, a site that brings together the latest information and learning resources for serverless computing, or have a look at the Serverless Architectures on AWS book.

Now that every business is a technology business, The Value Flywheel Effect is about how to accelerate and transform an organization. It helps set the right environment, purpose, and stage to modernize your applications as you adopt cloud computing and get the benefit of it.

You can meet David, Mark, and Michael at the Serverless Edge, where a team of engineers, tech enthusiasts, marketers, and thought leaders obsessed with technology help learn and communicate how serverless can transform a business model.

— Danilo

Let’s Architect! Architecting for sustainability

Post Syndicated from Luca Mezzalira original https://aws.amazon.com/blogs/architecture/lets-architect-architecting-for-sustainability/

Sustainability is an important topic in the tech industry, as well as society as a whole, and defined as the ability to continue to perform a process or function over an extended period of time without depletion of natural resources or the environment.

One of the key elements to designing a sustainable workload is software architecture. Think about how event-driven architecture can help reduce the load across multiple microservices, leveraging solutions like batching and queues. In these cases, the main traffic is absorbed at the entry-point of a cloud workload and ease inside your system. On top of architecture, think about data patterns, hardware optimizations, multi-environment strategies, and many more aspects of a software development lifecycle that can contribute to your sustainable posture in the Cloud.

The key takeaway: designing with sustainability in mind can help you build an application that is not only durable but also flexible enough to maintain the agility your business requires.

In this edition of Let’s Architect!, we share hands-on activities, case studies, and tips and tricks for making your Cloud applications more sustainable.

Architecting sustainably and reducing your AWS carbon footprint

Amazon Web Services (AWS) launched the Sustainability Pillar of the AWS Well-Architected Framework to help organizations evaluate and optimize their use of AWS services, and built the customer carbon footprint tool so organizations can monitor, analyze, and reduce their AWS footprint.

This session provides updates on these programs and highlights the most effective techniques for optimizing your AWS architectures. Find out how Amazon Prime Video used these tools to establish baselines and drive significant efficiencies across their AWS usage.

Take me to this re:Invent 2022 video!

Prime Video case study for understanding how the architecture can be designed for sustainability

Prime Video case study for understanding how the architecture can be designed for sustainability

Optimize your modern data architecture for sustainability

The modern data architecture is the foundation for a sustainable and scalable platform that enables business intelligence. This AWS Architecture Blog series provides tips on how to develop a modern data architecture with sustainability in mind.

Comprised of two posts, it helps you revisit and enhance your current data architecture without compromising sustainability.

Take me to Part 1! | Take me to Part 2!

An AWS data architecture; it’s now time to account for sustainability

An AWS data architecture; it’s now time to account for sustainability

AWS Well-Architected Labs: Sustainability

This workshop introduces participants to the AWS Well-Architected Framework, a set of best practices for designing and operating high-performing, highly scalable, and cost-efficient applications on AWS. The workshop also discusses how sustainability is critical to software architecture and how to use the AWS Well-Architected Framework to improve your application’s sustainability performance.

Take me to this workshop!

Sustainability implementation best practices and monitoring

Sustainability implementation best practices and monitoring

Sustainability in the cloud with Rust and AWS Graviton

In this video, you can learn about the benefits of Rust and AWS Graviton to reduce energy consumption and increase performance. Rust combines the resource efficiency of programming languages, like C, with memory safety of languages, like Java. The video also explains the benefits deriving from AWS Graviton processors designed to deliver performance- and cost-optimized cloud workloads. This resource is very helpful to understand how sustainability can become a driver for cost optimization.

Take me to this re:Invent 2022 video!

Discover how Rust and AWS Graviton can help you make your workload more sustainable and performant

Discover how Rust and AWS Graviton can help you make your workload more sustainable and performant

See you next time!

Thanks for joining us to discuss sustainability in the cloud! See you in two weeks when we’ll talk about tools for architects.

To find all the blogs from this series, you can check the Let’s Architect! list of content on the AWS Architecture Blog.

Let’s Architect! Designing event-driven architectures

Post Syndicated from Luca Mezzalira original https://aws.amazon.com/blogs/architecture/lets-architect-designing-event-driven-architectures/

During the design of distributed systems, we have to identify a communication strategy to exchange information between different services while keeping the evolutionary nature of the architecture in mind. Event-driven architectures are based on events (facts that happened in a system), which are asynchronously exchanged to implement communication across different services while having a high degree of decoupling. This paradigm also allows us to run code in response to events, with benefits like cost optimization and sustainability for the entire infrastructure.

In this edition of Let’s Architect!, we share architectural resources to introduce event-driven architectures, how to build them on AWS, and how to approach the design phase.

AWS re:Invent 2022 – Keynote with Dr. Werner Vogels

re:Invent 2022 may be finished, but the keynote given by Amazon’s Chief Technology Officer, Dr. Werner Vogels, will not be forgotten. Vogels not only covered the announcements of new services but also event-driven architecture foundations in conjunction with customers’ stories on how this architecture helped to improve their systems.

Take me to this re:Invent 2022 video!

Dr. Werner Vogels presenting an example of architecture where Amazon EventBridge is used as event bus

Dr. Werner Vogels presenting an example of architecture where Amazon EventBridge is used as event bus

Benefits of migrating to event-driven architecture

In this blog post, we enumerate clearly and concisely the benefits of event-driven architectures, such as scalability, fault tolerance, and developer velocity. This is a great post to start your journey into the event-driven architecture style, as it explains the difference from request-response architecture.

Take me to this Compute Blog post!

Two common options when building applications are request-response and event-driven architecture

Two common options when building applications are request-response and event-driven architectures

Building next-gen applications with event-driven architectures

When we build distributed systems or migrate from a monolithic to a microservices architecture, we need to identify a communication strategy to integrate the different services. Teams who are building microservices often find that integration with other applications and external services can make their workloads tightly coupled.

In this re:Invent 2022 video, you learn how to use event-driven architectures to decouple and decentralize application components through asynchronous communication. The video introduces the differences between synchronous and asynchronous communications before drilling down into some key concepts for designing and building event-driven architectures on AWS.

Take me to this re:Invent 2022 video!

How to use choreography to exchange information across services plus implement orchestration for managing operations within the service boundaries

How to use choreography to exchange information across services plus implement orchestration for managing operations within the service boundaries

Designing events

When starting on the journey to event-driven architectures, a common challenge is how to design events: “how much data should an event contain?” is a typical first question we encounter.

In this pragmatic post, you can explore the different types of events, watch a video that explains even further how to use event-driven architectures, and also go through the new event-driven architecture section of serverlessland.com.

Take me to Serverless Land!

An example of events with sparse and full state description

An example of events with sparse and full state description

See you next time!

Thanks for reading our first blog of 2023! Join us next time, when we’ll talk about architecture and sustainability.

To find all the blogs from this series, visit the Let’s Architect! section of the AWS Architecture Blog.

Journey to adopt Cloud-Native DevOps platform Series #2: Progressive delivery on Amazon EKS with Flagger and Gloo Edge Ingress Controller

Post Syndicated from Purna Sanyal original https://aws.amazon.com/blogs/devops/journey-to-adopt-cloud-native-devops-platform-series-2-progressive-delivery-on-amazon-eks-with-flagger-and-gloo-edge-ingress-controller/

In the last post, OfferUp modernized its DevOps platform with Amazon EKS and Flagger to accelerate time to market, we talked about hypergrowth and the technical challenges encountered by OfferUp in its existing DevOps platform. As a reminder, we presented how OfferUp modernized its DevOps platform with Amazon Elastic Kubernetes Service (Amazon EKS) and Flagger to gain developer’s velocity, automate faster deployment, and achieve lower cost of ownership.

In this post, we discuss the technical steps to build a DevOps platform that enables the progressive deployment of microservices on Amazon Managed Amazon EKS. Progressive delivery exposes a new version of the software incrementally to ingress traffic and continuously measures the success rate of the metrics before allowing all of the new traffics to a newer version of the software. Flagger is the Graduate project of Cloud Native Computing Foundations (CNCF) that enables progressive canary delivery, along with bule/green and A/B Testing, while measuring metrics like HTTP/gRPC request success rate and latency. Flagger shifts and routes traffic between app versions using a service mesh or an Ingress controller

We leverage Gloo Ingress Controller for traffic routing, Prometheus, Datadog, and Amazon CloudWatch for application metrics analysis and Slack to send notification. Flagger will post messages to slack when a deployment has been initialized, when a new revision has been detected, and if the canary analysis failed or succeeded.

Prerequisite steps to build the modern DevOps platform

You need an AWS Account and AWS Identity and Access Management (IAM) user to build the DevOps platform. If you don’t have an AWS account with Administrator access, then create one now by clicking here. Create an IAM user and assign admin role. You can build this platform in any AWS region however, I will you us-west-1 region throughout this post. You can use a laptop (Mac or Windows) or an Amazon Elastic Compute Cloud (AmazonEC2) instance as a client machine to install all of the necessary software to build the GitOps platform. For this post, I launched an Amazon EC2 instance (with Amazon Linux2 AMI) as the client and install all of the prerequisite software. You need the awscli, git, eksctl, kubectl, and helm applications to build the GitOps platform. Here are the prerequisite steps,

  1. Create a named profile(eks-devops)  with the config and credentials file:

aws configure --profile eks-devops

AWS Access Key ID [None]: xxxxxxxxxxxxxxxxxxxxxx

AWS Secret Access Key [None]: xxxxxxxxxxxxxxxxxx

Default region name [None]: us-west-1

Default output format [None]:

View and verify your current IAM profile:

export AWS_PROFILE=eks-devops

aws sts get-caller-identity

  1. If the Amazon EC2 instance doesn’t have git preinstalled, then install git in your Amazon EC2 instance:

sudo yum update -y

sudo yum install git -y

Check git version

git version

Git clone the repo and download all of the prerequisite software in the home directory.

git clone https://github.com/aws-samples/aws-gloo-flux.git

  1. Download all of the prerequisite software from install.sh which includes awscli, eksctl, kubectl, helm, and docker:

cd aws-gloo-flux/eks-flagger/

ls -lt

chmod 700 install.sh ecr-setup.sh

. install.sh

Check the version of the software installed:

aws --version

eksctl version

kubectl version -o json

helm version

docker --version

docker info

If the docker info shows an error like “permission denied”, then reboot the Amazon EC2 instance or re-log in to the instance again.

  1. Create an Amazon Elastic Container Repository (Amazon ECR) and push application images.

Amazon ECR is a fully-managed container registry that makes it easy for developers to share and deploy container images and artifacts. ecr setup.sh script will create a new Amazon ECR repository and also push the podinfo images (6.0.0, 6.0.1, 6.0.2, 6.1.0, 6.1.5 and 6.1.6) to the Amazon ECR. Run ecr-setup.sh script with the parameter, “ECR repository name” (e.g. ps-flagger-repository) and region (e.g. us-west-1)

./ecr-setup.sh <ps-flagger-repository> <us-west-1>

You’ll see output like the following (truncated).

###########################################################

Successfully created ECR repository and pushed podinfo images to ECR #

Please note down the ECR repository URI          

xxxxxx.dkr.ecr.us-west-1.amazonaws.com/ps-flagger-repository                                                   

Technical steps to build the modern DevOps platform

This post shows you how to use the Gloo Edge ingress controller and Flagger to automate canary releases for progressive deployment on the Amazon EKS cluster. Flagger requires a Kubernetes cluster v1.16 or newer and Gloo Edge ingress 1.6.0 or newer. This post will provide a step-by-step approach to install the Amazon EKS cluster with managed node group, Gloo Edge ingress controller, and Flagger for Gloo in the Amazon EKS cluster. Now that the cluster, metrics infrastructure, and Flagger are installed, we can install the sample application itself. We’ll use the standard Podinfo application used in the Flagger project and the accompanying loadtester tool. The Flagger “podinfo” backend service will be called by Gloo’s “VirtualService”, which is the root routing object for the Gloo Gateway. A virtual service describes the set of routes to match for a set of domains. We’ll automate the canary promotion, with the new image of the “podinfo” service, from version 6.0.0 to version 6.0.1. We’ll also create a scenario by injecting an error for automated canary rollback while deploying version 6.0.2.

  1. Use myeks-cluster.yaml to create your Amazon EKS cluster with managed nodegroup. myeks-cluster.yaml deployment file has “cluster name” value as ps-eks-66, region value as us-west-1, availabilityZones as [us-west-1a, us-west-1b], Kubernetes version as 1.24, and nodegroup Amazon EC2 instance type as m5.2xlarge. You can change this value if you want to build the cluster in a separate region or availability zone.

eksctl create cluster -f myeks-cluster.yaml

Check the Amazon EKS Cluster details:

kubectl cluster-info

kubectl version -o json

kubectl get nodes -o wide

kubectl get pods -A -o wide

Deploy the Metrics Server:

kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/components.yaml

kubectl get deployment metrics-server -n kube-system

Update the kubeconfig file to interact with you cluster:

# aws eks update-kubeconfig --name <ekscluster-name> --region <AWS_REGION>

kubectl config view

cat $HOME/.kube/config

  1. Create a namespace “gloo-system” and Install Gloo with Helm Chart. Gloo Edge is an Envoy-based Kubernetes-native ingress controller to facilitate and secure application traffic.

helm repo add gloo https://storage.googleapis.com/solo-public-helm

kubectl create ns gloo-system

helm upgrade -i gloo gloo/gloo --namespace gloo-system

  1. Install Flagger and the Prometheus add-on in the same gloo-system namespace. Flagger is a Cloud Native Computing Foundation project and part of Flux family of GitOps tools.

helm repo add flagger https://flagger.app

helm upgrade -i flagger flagger/flagger \

--namespace gloo-system \

--set prometheus.install=true \

--set meshProvider=gloo

  1. [Optional] If you’re using Datadog as a monitoring tool, then deploy Datadog agents as a DaemonSet using the Datadog Helm chart. Replace RELEASE_NAME and DATADOG_API_KEY accordingly. If you aren’t using Datadog, then skip this step. For this post, we leverage the Prometheus open-source monitoring tool.

helm repo add datadog https://helm.datadoghq.com

helm repo update

helm install <RELEASE_NAME> \

    --set datadog.apiKey=<DATADOG_API_KEY> datadog/datadog

Integrate Amazon EKS/ K8s Cluster with the Datadog Dashboard – go to the Datadog Console and add the Kubernetes integration.

  1. [Optional] If you’re using Slack communication tool and have admin access, then Flagger can be configured to send alerts to the Slack chat platform by integrating the Slack alerting system with Flagger. If you don’t have admin access in Slack, then skip this step.

helm upgrade -i flagger flagger/flagger \

--set slack.url=https://hooks.slack.com/services/YOUR/SLACK/WEBHOOK \

--set slack.channel=general \

--set slack.user=flagger \

--set clusterName=<my-cluster>

  1. Create a namespace “apps”, and applications and load testing service will be deployed into this namespace.

kubectl create ns apps

Create a deployment and a horizontal pod autoscaler for your custom application or service for which canary deployment will be done.

kubectl -n apps apply -k app

kubectl get deployment -A

kubectl get hpa -n apps

Deploy the load testing service to generate traffic during the canary analysis.

kubectl -n apps apply -k tester

kubectl get deployment -A

kubectl get svc -n apps

  1. Use apps-vs.yaml to create a Gloo virtual service definition that references a route table that will be generated by Flagger.

kubectl apply -f ./apps-vs.yaml

kubectl get vs -n apps

[Optional] If you have your own domain name, then open apps-vs.yaml in vi editor and replace podinfo.example.com with your own domain name to run the app in that domain.

  1. Use canary.yaml to create a canary custom resource. Review the service, analysis, and metrics sections of the canary.yaml file.

kubectl apply -f ./canary.yaml

After a couple of seconds, Flagger will create the canary objects. When the bootstrap finishes, Flagger will set the canary status to “Initialized”.

kubectl -n apps get canary podinfo

NAME      STATUS        WEIGHT   LASTTRANSITIONTIME

podinfo   Initialized   0        2023-xx-xxTxx:xx:xxZ

Gloo automatically creates an ELB. Once the load balancer is provisioned and health checks pass, we can find the sample application at the load balancer’s public address. Note down the ELB’s Public address:

kubectl get svc -n gloo-system --field-selector 'metadata.name==gateway-proxy'   -o=jsonpath='{.items[0].status.loadBalancer.ingress[0].hostname}{"\n"}'

Validate if your application is running, and you’ll see an output with version 6.0.0.

curl <load balancer’s public address> -H "Host:podinfo.example.com"

Trigger progressive deployments and monitor the status

You can Trigger a canary deployment by updating the application container image from 6.0.0 to 6.01.

kubectl -n apps set image deployment/podinfo  podinfod=<ECR URI>:6.0.1

Flagger detects that the deployment revision changed and starts a new rollout.

kubectl -n apps describe canary/podinfo

Monitor all canaries, as the promoted status condition can have one of the following statuses: initialized, Waiting, Progressing, Promoting, Finalizing, Succeeded, and Failed.

watch kubectl get canaries --all-namespaces

curl < load balancer’s public address> -H "Host:podinfo.example.com"

Once canary is completed, validate your application. You can see that the version of the application is changed from 6.0.0 to 6.0.1.

{

  "hostname": "podinfo-primary-658c9f9695-4pqbl",

  "version": "6.0.1",

  "revision": "",

  "color": "#34577c",

  "logo": "https://raw.githubusercontent.com/stefanprodan/podinfo/gh-pages/cuddle_clap.gif",

  "message": "greetings from podinfo v6.0.1",

}

[Optional] Open podinfo application from the laptop browser

Find out both of the IP addresses associated with load balancer.

dig < load balancer’s public address >

Open /etc/hosts file in the laptop and add both of the IPs of load balancer in the host file.

sudo vi /etc/hosts

<Public IP address of LB Target node> podinfo.example.com

e.g.

xx.xx.xxx.xxx podinfo.example.com

xx.xx.xxx.xxx podinfo.example.com

Type “podinfo.example.com” in your browser and you’ll find the application in form similar to this:

Figure 1: Greetings from podinfo v6.0.1

Automated rollback

While doing the canary analysis, you’ll generate HTTP 500 errors and high latency to check if Flagger pauses and rolls back the faulted version. Flagger performs automatic Rollback in the case of failure.

Introduce another canary deployment with podinfo image version 6.0.2 and monitor the status of the canary.

kubectl -n apps set image deployment/podinfo podinfod=<ECR URI>:6.0.2

Run HTTP 500 errors or a high-latency error from a separate terminal window.

Generate HTTP 500 errors:

watch curl -H 'Host:podinfo.example.com' <load balancer’s public address>/status/500

Generate high latency:

watch curl -H 'Host:podinfo.example.com' < load balancer’s public address >/delay/2

When the number of failed checks reaches the canary analysis threshold, the traffic is routed back to the primary, the canary is scaled to zero, and the rollout is marked as failed.

kubectl get canaries --all-namespaces

kubectl -n apps describe canary/podinfo

Cleanup

When you’re done experimenting, you can delete all of the resources created during this series to avoid any additional charges. Let’s walk through deleting all of the resources used.

Delete Flagger resources and apps namespace
kubectl delete canary podinfo -n  apps

kubectl delete HorizontalPodAutoscaler podinfo -n apps

kubectl delete deployment podinfo -n   apps

helm -n gloo-system delete flagger

helm -n gloo-system delete gloo

kubectl delete namespace apps

Delete Amazon EKS Cluster
After you’ve finished with the cluster and nodes that you created for this tutorial, you should clean up by deleting the cluster and nodes with the following command:

eksctl delete cluster --name <cluster name> --region <region code>

Delete Amazon ECR

aws ecr delete-repository --repository-name ps-flagger-repository  --force

Conclusion

This post explained the process for setting up Amazon EKS cluster and how to leverage Flagger for progressive deployments along with Prometheus and Gloo Ingress Controller. You can enhance the deployments by integrating Flagger with Slack, Datadog, and webhook notifications for progressive deployments. Amazon EKS removes the undifferentiated heavy lifting of managing and updating the Kubernetes cluster. Managed node groups automate the provisioning and lifecycle management of worker nodes in an Amazon EKS cluster, which greatly simplifies operational activities such as new Kubernetes version deployments.

We encourage you to look into modernizing your DevOps platform from monolithic architecture to microservice-based architecture with Amazon EKS, and leverage Flagger with the right Ingress controller for secured and automated service releases.

Further Reading

Journey to adopt Cloud-Native DevOps platform Series #1: OfferUp modernized DevOps platform with Amazon EKS and Flagger to accelerate time to market

About the authors:

Purna Sanyal

Purna Sanyal is a technology enthusiast and an architect at AWS, helping digital native customers solve their business problems with successful adoption of cloud native architecture. He provides technical thought leadership, architecture guidance, and conducts PoCs to enable customers’ digital transformation. He is also passionate about building innovative solutions around Kubernetes, database, analytics, and machine learning.

Three key security themes from AWS re:Invent 2022

Post Syndicated from Anne Grahn original https://aws.amazon.com/blogs/security/three-key-security-themes-from-aws-reinvent-2022/

AWS re:Invent returned to Las Vegas, Nevada, November 28 to December 2, 2022. After a virtual event in 2020 and a hybrid 2021 edition, spirits were high as over 51,000 in-person attendees returned to network and learn about the latest AWS innovations.

Now in its 11th year, the conference featured 5 keynotes, 22 leadership sessions, and more than 2,200 breakout sessions and hands-on labs at 6 venues over 5 days.

With well over 100 service and feature announcements—and innumerable best practices shared by AWS executives, customers, and partners—distilling highlights is a challenge. From a security perspective, three key themes emerged.

Turn data into actionable insights

Security teams are always looking for ways to increase visibility into their security posture and uncover patterns to make more informed decisions. However, as AWS Vice President of Data and Machine Learning, Swami Sivasubramanian, pointed out during his keynote, data often exists in silos; it isn’t always easy to analyze or visualize, which can make it hard to identify correlations that spark new ideas.

“Data is the genesis for modern invention.” – Swami Sivasubramanian, AWS VP of Data and Machine Learning

At AWS re:Invent, we launched new features and services that make it simpler for security teams to store and act on data. One such service is Amazon Security Lake, which brings together security data from cloud, on-premises, and custom sources in a purpose-built data lake stored in your account. The service, which is now in preview, automates the sourcing, aggregation, normalization, enrichment, and management of security-related data across an entire organization for more efficient storage and query performance. It empowers you to use the security analytics solutions of your choice, while retaining control and ownership of your security data.

Amazon Security Lake has adopted the Open Cybersecurity Schema Framework (OCSF), which AWS cofounded with a number of organizations in the cybersecurity industry. The OCSF helps standardize and combine security data from a wide range of security products and services, so that it can be shared and ingested by analytics tools. More than 37 AWS security partners have announced integrations with Amazon Security Lake, enhancing its ability to transform security data into a powerful engine that helps drive business decisions and reduce risk. With Amazon Security Lake, analysts and engineers can gain actionable insights from a broad range of security data and improve threat detection, investigation, and incident response processes.

Strengthen security programs

According to Gartner, by 2026, at least 50% of C-Level executives will have performance requirements related to cybersecurity risk built into their employment contracts. Security is top of mind for organizations across the globe, and as AWS CISO CJ Moses emphasized during his leadership session, we are continuously building new capabilities to help our customers meet security, risk, and compliance goals.

In addition to Amazon Security Lake, several new AWS services announced during the conference are designed to make it simpler for builders and security teams to improve their security posture in multiple areas.

Identity and networking

Authorization is a key component of applications. Amazon Verified Permissions is a scalable, fine-grained permissions management and authorization service for custom applications that simplifies policy-based access for developers and centralizes access governance. The new service gives developers a simple-to-use policy and schema management system to define and manage authorization models. The policy-based authorization system that Amazon Verified Permissions offers can shorten development cycles by months, provide a consistent user experience across applications, and facilitate integrated auditing to support stringent compliance and regulatory requirements.

Additional services that make it simpler to define authorization and service communication include Amazon VPC Lattice, an application-layer service that consistently connects, monitors, and secures communications between your services, and AWS Verified Access, which provides secure access to corporate applications without a virtual private network (VPN).

Threat detection and monitoring

Monitoring for malicious activity and anomalous behavior just got simpler. Amazon GuardDuty RDS Protection expands the threat detection capabilities of GuardDuty by using tailored machine learning (ML) models to detect suspicious logins to Amazon Aurora databases. You can enable the feature with a single click in the GuardDuty console, with no agents to manually deploy, no data sources to enable, and no permissions to configure. When RDS Protection detects a potentially suspicious or anomalous login attempt that indicates a threat to your database instance, GuardDuty generates a new finding with details about the potentially compromised database instance. You can view GuardDuty findings in AWS Security Hub, Amazon Detective (if enabled), and Amazon EventBridge, allowing for integration with existing security event management or workflow systems.

To bolster vulnerability management processes, Amazon Inspector now supports AWS Lambda functions, adding automated vulnerability assessments for serverless compute workloads. With this expanded capability, Amazon Inspector automatically discovers eligible Lambda functions and identifies software vulnerabilities in application package dependencies used in the Lambda function code. Actionable security findings are aggregated in the Amazon Inspector console, and pushed to Security Hub and EventBridge to automate workflows.

Data protection and privacy

The first step to protecting data is to find it. Amazon Macie now automatically discovers sensitive data, providing continual, cost-effective, organization-wide visibility into where sensitive data resides across your Amazon Simple Storage Service (Amazon S3) estate. With this new capability, Macie automatically and intelligently samples and analyzes objects across your S3 buckets, inspecting them for sensitive data such as personally identifiable information (PII), financial data, and AWS credentials. Macie then builds and maintains an interactive data map of your sensitive data in S3 across your accounts and Regions, and provides a sensitivity score for each bucket. This helps you identify and remediate data security risks without manual configuration and reduce monitoring and remediation costs.

Encryption is a critical tool for protecting data and building customer trust. The launch of the end-to-end encrypted enterprise communication service AWS Wickr offers advanced security and administrative controls that can help you protect sensitive messages and files from unauthorized access, while working to meet data retention requirements.

Management and governance

Maintaining compliance with regulatory, security, and operational best practices as you provision cloud resources is key. AWS Config rules, which evaluate the configuration of your resources, have now been extended to support proactive mode, so that they can be incorporated into infrastructure-as-code continuous integration and continuous delivery (CI/CD) pipelines to help identify noncompliant resources prior to provisioning. This can significantly reduce time spent on remediation.

Managing the controls needed to meet your security objectives and comply with frameworks and standards can be challenging. To make it simpler, we launched comprehensive controls management with AWS Control Tower. You can use it to apply managed preventative, detective, and proactive controls to accounts and organizational units (OUs) by service, control objective, or compliance framework. You can also use AWS Control Tower to turn on Security Hub detective controls across accounts in an OU. This new set of features reduces the time that it takes to define and manage the controls required to meet specific objectives, such as supporting the principle of least privilege, restricting network access, and enforcing data encryption.

Do more with less

As we work through macroeconomic conditions, security leaders are facing increased budgetary pressures. In his opening keynote, AWS CEO Adam Selipsky emphasized the effects of the pandemic, inflation, supply chain disruption, energy prices, and geopolitical events that continue to impact organizations.

Now more than ever, it is important to maintain your security posture despite resource constraints. Citing specific customer examples, Selipsky underscored how the AWS Cloud can help organizations move faster and more securely. By moving to the cloud, agricultural machinery manufacturer Agco reduced costs by 78% while increasing data retrieval speed, and multinational HVAC provider Carrier Global experienced a 40% reduction in the cost of running mission-critical ERP systems.

“If you’re looking to tighten your belt, the cloud is the place to do it.” – Adam Selipsky, AWS CEO

Security teams can do more with less by maximizing the value of existing controls, and bolstering security monitoring and analytics capabilities. Services and features announced during AWS re:Invent—including Amazon Security Lake, sensitive data discovery with Amazon Macie, support for Lambda functions in Amazon Inspector, Amazon GuardDuty RDS Protection, and more—can help you get more out of the cloud and address evolving challenges, no matter the economic climate.

Security is our top priority

AWS re:Invent featured many more highlights on a variety of topics, such as Amazon EventBridge Pipes and the pre-announcement of GuardDuty EKS Runtime protection, as well as Amazon CTO Dr. Werner Vogels’ keynote, and the security partnerships showcased on the Expo floor. It was a whirlwind week, but one thing is clear: AWS is working harder than ever to make our services better and to collaborate on solutions that ease the path to proactive security, so that you can focus on what matters most—your business.

For more security-related announcements and on-demand sessions, see A recap for security, identity, and compliance sessions at AWS re:Invent 2022 and the AWS re:Invent Security, Identity, and Compliance playlist on YouTube.

If you have feedback about this post, submit comments in the Comments section below.

Anne Grahn

Anne Grahn

Anne is a Senior Worldwide Security GTM Specialist at AWS based in Chicago. She has more than a decade of experience in the security industry, and has a strong focus on privacy risk management. She maintains a Certified Information Systems Security Professional (CISSP) certification.

Author

Paul Hawkins

Paul helps customers of all sizes understand how to think about cloud security so they can build the technology and culture where security is a business enabler. He takes an optimistic approach to security and believes that getting the foundations right is the key to improving your security posture.

Author Spotlight: Luca Mezzalira, Principal Serverless Specialist Solutions Architect

Post Syndicated from Elise Chahine original https://aws.amazon.com/blogs/architecture/author-spotlight-luca-mezzalira-principal-serverless-specialist-solutions-architect/

The Author Spotlight series pulls back the curtain on some of AWS’s most prolific authors. Read on to find out more about our very own Luca Mezzalira’s journey, in his own words!

My name is Luca, and I’m a Principal Serverless Specialist Solutions Architect—probably the longest job title I’ve ever had in my 20-year career in the tech industry. One thing you have to know about me upfront: I love challenges. I tread an unconventional path, on which I found several hurdles, but, after a few years, I grew to love them.

Since I joined Amazon Web Services (AWS) in January 2021, I discovered (and continue to discover) all the challenges I’ve always dreamed of. I can also find solutions for customers, industries, and communities—what better place is there for a challenge-hunter like me!

I am self-taught. I learned my foundational skills from the developer communities I joined out of a thirst for knowledge. Fast-forward 20 years later, I still try to pay my “debt” to them by sharing what I learn and do on a regular basis.

Luca Mezzalira during the opening talk at JS Poland 2022

Luca Mezzalira during the opening talk at JS Poland 2022

AWS gave me the opportunity to first help our Media & Entertainment industry customers in the UK and Ireland and, now, to follow my passion working as a Serverless Specialist.

“Passionate” is another word that characterizes me, both personally and professionally: I’m Italian and there is a lot of passion under our skin. I don’t consider what I do a job but, rather, something I just love to do.

During these past couple of years with AWS, I have been able to use all 360° of my knowledge. With customers experimenting with new ideas and solutions, with colleagues urging customers outside their comfort zone and onto new horizons or into new adventures with AWS, I am blurring the edges of different worlds. With each passing day, I provide new perspectives for solving existing challenges! With internal and external communities, I support and organize events for spreading our ever-growing knowledge and creating new, meaningful connections.

Another great passion of mine is software architecture. Design patterns, distributed systems, team topology, domain-driven design, and any topic related to software architecture is what I deeply love. Do you know why? Because there isn’t right or wrong in architecture—it’s just trade-offs! The challenge is to find the least-worse decision for making a project successful.

Moreover, architectures are like living organisms. They evolve, requiring care and attention. Many might think that architecting is only a technical concern, but it is deeply connected with the organizational structure, as well the communication and engineering practices. When we acknowledge these aspects and work across these dimensions, the role of an architect is one of the best you can have—or at least it is for me!

What’s on my mind

There are two main topics I am focusing on at the moment: (1) distributed architecture on the frontend (i.e., micro-frontends); and (2) educating our builders on thinking in patterns, choosing the right solution to implement at the right moment.

In both cases, I create a lot of content trying to bridge the gap between the technical implementation and the architecture characteristics a company wants to optimize for.

My favorite blog posts

Developing evolutionary architecture with AWS Lambda

The first contribution I wanted to provide in AWS was without any doubt architectural. Hexagonal architecture (or ports and adapters) is not a new topic by any stretch, however, I wasn’t able to find solid resources with a simplified explanation of this approach. Once in place, hexagonal architectures can help the portability of your business logic across different AWS services or even on a hybrid-cloud. Using this architecture on Lambda functions has generated a lot of interest inside the serverless community.

If you want to know more, I leave you to the re:Invent talk I delivered in 2021.

Let’s Architect!

The second resource I am extremely proud of is a collaboration with AWS’s Zamira Jaupaj, Laura Hyatt, and Vittorio Denti… the Let’s Architect! team.

I met them in my first year in AWS, and they share a similar passion for helping people and community engagement. Moreover, we all want to learn something new.
Together, we created Let’s Architect!, a blog series that publishes a fortnightly post on a specific topic since January 2022. For example, serverless, containers, or data architectures are explored, gathering four different AWS content pieces that provide an architect’s perspective on why that content is relevant (or still relevant).

This initiative has had a strong influence, and we now have customers and even many of our colleagues awaiting our upcoming posts. If you want to discover more, check out the AWS Architecture Blog.

Let's Architect

Let’s Architect!

Server-Side Rendering Micro-Frontends in AWS

The last resource is part of my dream to lead the frontend community in their discovery of AWS services.

The frontend community is exposed to a lot of new frameworks and libraries, however, I believe they should look to the cloud as well, as they can unlock a variety of new possibilities.

Considering my expertise on micro-frontends and serverless, I started with a reference architecture to build distributed frontend using serverless. I recently started a new series on the AWS Compute Blog explaining the reasoning behind this reference architecture and how to approach server-side rendering micro-frontends using serverless. Read my first post on server-side rendering micro-frontends.

AWS Named as a Leader in the 2022 Gartner Cloud Infrastructure & Platform Services (CIPS) Magic Quadrant for the 12th Consecutive Year

Post Syndicated from Sébastien Stormacq original https://aws.amazon.com/blogs/aws/aws-named-as-a-leader-in-the-2022-gartner-cloud-infrastructure-platform-services-cips-magic-quadrant-for-the-12th-consecutive-year/

This year, and for the twelfth consecutive year, AWS has been named as a Leader in the 2022 Magic Quadrant for Cloud Infrastructure and Platform Services (CIPS). Per Gartner, AWS is the longest-running CIPS Magic Quadrant Leader.

AWS was among the first cloud providers when we launched Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Simple Storage Service (Amazon S3) 16 years ago. Our APIs have been adopted by the whole industry and often copied by others.

We believe this report validates AWS’s ability to innovate and deliver the broadest and deepest set of services for cloud computing. I encourage you to read the full report to appreciate the details.

As Jeff Bezos wrote in his first letter to shareholders in 1997 (reprinted at the end of each annual letter since then), Amazon makes decisions and weighs trade-offs differently than some companies. We focus on the long-term value rather than short-term profits, we make bold rather than timid investment decisions, and most importantly, we relentlessly focus on you: our customers. As a matter of fact, 90 percent of AWS’s roadmap for new services and capabilities is directly driven by your feedback and requests.

I work with AWS service teams every day. These teams work hard to innovate on your behalf. They make bold investments to invent, build, and operate services that help you innovate and build amazing experiences for your customers. The entire team is proud to see these efforts recognized by Gartner.

Our teams closely work with the vibrant AWS Partner Network. AWS has the largest and most dynamic community, with millions of active customers every month and more than 100,000 partners from over 150 countries—with almost 70% headquartered outside the United States. There is a real network effect when you use AWS.

The Magic Quadrant for CIPS, showing Amazon Web Services as a leader.

The full Gartner report has details about the features and factors they reviewed. It explains the methodology used and the results. This report can serve as a guide when choosing a cloud provider that helps you innovate on behalf of your customers.

— seb

Gartner, Magic Quadrant for Cloud Infrastructure and Platform Services, 19 October 2022, Raj Bala, et. al.


The Magic Quadrant graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from AWS.
Gartner does not endorse any vendor, product or service depicted in our research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
Gartner and Magic Quadrant are registered trademarks of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.

 

Author Spotlight: Rostislav Markov, Principal Architect in Strategic Industries

Post Syndicated from Elise Chahine original https://aws.amazon.com/blogs/architecture/author-spotlight-rostislav-markov-principal-architect-in-strategic-industries/

The Author Spotlight series pulls back the curtain on some of AWS’s most prolific authors. Read on to find out more about our very own Rostislav Markov’s journey, in his own words!

At Amazon Web Services (AWS), we obsess over customers, and this drives our daily operations. As an architect, I always look for innovative solutions to common problems our AWS users face. One of my favorite things about my work is the opportunity to influence our services roadmap by taking feedback from our customers. Every topic I write about comes from my work with AWS customers and our service teams.

Since joining in 2017, I have worked on projects ranging from Cloud Foundations to migration and modernization, to new development initiatives. I worked with companies in automotive, banking and insurance, chemicals, healthcare and life sciences, manufacturing, media and entertainment. Throughout my journey, I have observed first-hand that every company—big and small—has its own journey to the cloud, and there are always common patterns from one experience to the next. The good news is if you face a challenge, chances are somebody has already experienced the same difficulty and found a solution. This is why I love reading about common patterns in the AWS Architecture Blog.

In 2020, my AWS journey took me from Munich, Germany, to New York, US, where I currently live. I still visit my first AWS customers but, now, in their US offices, and have meanwhile worked with many other companies. After 5 years in AWS, I am still constantly learning about our services and innovative solutions for multiple industry issues. Occasionally, I write about them on the AWS Architecture Blog or present at our public conferences.

One of my favorite moments was 4 years ago at the AWS Summit Berlin. I presented together with Kathleen DeValk, former Chief Architect at Siemens, about IoT at Siemens and designing microservices for very large scale. This year, I was back on stage with Christos Dovas, Head of Cloud-Native Automation at BMW Group, talking about BMW’s journey to DevOps.

Left: Rostislav Markov and Kathleen DeValk / Right: Christos Dovas and Rostislav Markov

What’s on my mind lately

My current focus at work is on modern application principles. I work with AWS customers on elevating their application deployment standards and creating solutions for common enterprise use cases in strategic industries. I look forward to writing more blogs on those and many other topics—stay tuned!

My favorite blog posts

Queue Integration with Third-party Services on AWS

I wrote this blog post in 2021 while working with scientific research teams in healthcare and life sciences. It addresses third-party services that do not natively support AWS APIs and best practices, such as polling, that require a fault-tolerant integration layer.

As Werner Vogels, CTO of Amazon, said at AWS re:Invent in 2019, “Everything fails, all the time.” In this solution, the RunTask API was used to explain how retry and error handling can be added to your application.

Special thanks go to Sam Dengler, former Principal Developer Advocate with the AWS Compute Services team, who helped me find the right focus for this blog post, and from whom I still learn today.

Figure 1. On-premises and AWS queue integration for third-party services using AWS Lambda

On-premises and AWS queue integration for third-party services using AWS Lambda

Save time and effort in assessing your teams’ architectures with pattern-based architecture reviews

This post summarized my lessons working with 500 developers of a global industrial manufacturing company. Their IoT solution had to go live within 6 months, but they did not have prior AWS experience.

By using a pattern-based approach to architecting and building applications, we were able to complete the reviews within 2 weeks and make the architecture reviews fun, inspiring, and a team-based experience.

I have reused this pattern-based development approach on the majority of my projects, including the one I am currently working on: deciding on the V1 AWS design patterns with the data center exits of a large life sciences company. If you are curious and want to learn more, explore the AWS whitepaper on Cloud-Driven Enterprise Transformation on AWS.

Proposed AWS services for use by development teams

Proposed AWS services for use by development teams

Point-in-time restore for Amazon S3 buckets

One of the best things about working with AWS is receiving meaningful customer feedback all the time and having the means to act on it. This blog post is an example of customer feedback in manufacturing, media, and entertainment industries using one of my favorite AWS services—Amazon Simple Storage Service (Amazon S3).

Customers requested a simple way to do point-in-time restoration at the bucket level. My colleague, Gareth Eagar, Senior Solutions Architect, and I worked with the service team to influence the service roadmap and published a solution with this blog post.

I love going back to basics, here with Amazon S3 versioning, and learning more about our foundational services, while having a ton of fun with my colleague along the way.

Point-in-time restore for Amazon S3 buckets

Split your monolithic Apache Kafka clusters using Amazon MSK Serverless

Post Syndicated from Ali Alemi original https://aws.amazon.com/blogs/big-data/split-your-monolithic-apache-kafka-clusters-using-amazon-msk-serverless/

Today, many companies are building real-time applications to improve their customer experience and get immediate insights from their data before it loses its value. As the result, companies have been facing increasing demand to provide data streaming services such as Apache Kafka for developers. To meet this demand, companies typically start with a small- or medium-sized, centralized Apache Kafka cluster to build a global streaming service. Over time, they scale the capacity of the cluster to match the demand for streaming. They choose to keep a monolithic cluster to simplify staffing and training by bringing all technical expertise in a single place. This approach also has cost benefits because it reduces the technical debt, overall operational costs, and complexity. In a monolithic cluster, the extra capacity is shared among all applications, therefore it usually reduces the overall streaming infrastructure cost.

In this post, I explain a few challenges with a centralized approach, and introduce two strategies for implementing a decentralized approach, using Amazon MSK Serverless. A decentralized strategy enables you to provision multiple Apache Kafka clusters instead of a monolithic one. I discuss how this strategy helps you optimize clusters per your application’s security, storage, and performance needs. I also discuss the benefits of a decentralized model and how to migrate from a monolithic cluster to a multi-cluster deployment model.

MSK Serverless can reduce the overhead and cost of managing Apache Kafka clusters. It automatically provisions and scales compute and storage resources for Apache Kafka clusters and automatically manages cluster capacity. It monitors how the partitions are distributed across the backend nodes and reassigns the partitions automatically when necessary. It integrates with other AWS services such as Amazon CloudWatch, where you can monitor the health of the cluster. The choice of MSK Serverless in this post is deliberate, even though the concepts can be applied to the Amazon MSK provisioned offering as well.

Overview of solution

Apache Kafka is an open-source, high-performance, fault-tolerant, and scalable platform for building real-time streaming data pipelines and applications. Apache Kafka simplifies producing and consuming streaming data by decoupling producers from the consumers. Producers simply interact with a single data store (Apache Kafka) to send their data. Consumers read the continuously flowing data, independent from the architecture or the programming language of the producers.

Apache Kafka is a popular choice for many use cases, such as:

  • Real-time web and log analytics
  • Transaction and event sourcing
  • Messaging
  • Decoupling microservices
  • Streaming ETL (extract, transform, and load)
  • Metrics and log aggregation

Challenges with a monolithic Apache Kafka cluster

Monolithic Apache Kafka saves companies from having to install and maintain multiple clusters in their data centers. However, this approach comes with common disadvantages:

  • The entire streaming capacity is consolidated in one place, making capacity planning difficult and complicated. You typically need more time to plan and reconfigure the cluster. For example, when preparing for sales or large campaign events, it’s hard to predict and calculate an aggregation of needed capacity across all applications. This can also inhibit the growth of your company because reconfiguring a large cluster for a new workload often takes longer than a small cluster.
  • Organizational conflicts may occur regarding the ownership and maintenance of the Apache Kafka cluster, because a monolithic cluster is a shared resource.
  • The Apache Kafka cluster becomes a single point of failure. Any downtime means the outage of all related applications.
  • If you choose to increase Apache Kafka’s resiliency with a multi-datacenter deployment, then you typically must have a cluster with the same size (as large) in the other data center, which is expensive.
  • Maintenance and operation activities, such as version upgrades or installing OS patches, take significantly longer for larger clusters due to the distributed nature of Apache Kafka architecture.
  • A faulty application can impact the reliability of the whole cluster and other applications.
  • Version upgrades have to wait until all applications are tested with the new Apache Kafka version. This limits any application from experimenting with Apache Kafka features quickly.
  • This model makes it difficult to attribute the cost of running the cluster to the applications for chargeback purposes.

The following diagram shows a monolithic Apache Kafka architecture.

diagram shows a monolithic Apache Kafka architecture.

Decentralized model

A decentralized Apache Kafka deployment model involves provisioning, configuring, and maintaining multiple clusters. This strategy generally isn’t preferred because managing multiple clusters requires heavy investments in operational excellence, advanced monitoring, infrastructure as code, security, and hardware procurement in on-premises environments.

However, provisioning decentralized Apache Kafka clusters using MSK Serverless doesn’t require those investments. It can scale the capacity and storage up and down instantly based on the application requirement, adding new workloads or scaling operations without the need for complex capacity planning. It also provides a throughput-based pricing model, and you pay for the storage and throughput that your applications use. Moreover, with MSK Serverless, you no longer need to perform standard maintenance tasks such as Apache Kafka version upgrade, partition reassignments, or OS patching.

With MSK Serverless, you benefit from a decentralized deployment without the operational burden that usually comes with a self-managed Apache Kafka deployment. In this strategy, the DevOps managers don’t have to spend time provisioning, configuring, monitoring, and operating multiple clusters. Instead, they invest more in building more operational tools to onboard more real-time applications.

In the remainder of this post, I discuss different strategies for implementing a decentralized model. Furthermore, I highlight the benefits and challenges of each strategy so you can decide what works best for your organization.

Write clusters and read clusters

In this strategy, write clusters are responsible for ingesting data from the producers. You can add new workloads by creating new topics or creating new MSK Serverless clusters. If you need to scale the size of current workloads, you simply increase the number of partitions of your topics if the ordering isn’t important. MSK Serverless manages the capacity instantly as per the new configuration.

Each MSK Serverless cluster provides up to 200 MBps of write throughput and 400 MBps of read throughput. It also allocates up to 5 MBps of write throughput and 10 MBps of read throughput per partition.

Data consumers within any organization can usually be divided to two main categories:

  • Time-sensitive workloads, which need data with very low latency (such as millisecond or subsecond) and can only tolerate a very short Recovery Time Objective (RTO)
  • Time-insensitive workloads, which can tolerate higher latency (sub-10 seconds to minute-level latency) and longer RTO

Each of these categories also can be further divided into subcategories based on certain conditions, such as data classification, regulatory compliance, or service level agreements (SLAs). Read clusters can be set up according to your business or technical requirements, or even organizational boundaries, which can be used by the specific group of consumers. Finally, the consumers are configured to run against the associated read cluster.

To connect the write clusters to read clusters, a data replication pipeline is necessary. You can build a data replication pipeline many ways. Because MSK Serverless supports the standard Apache Kafka APIs, you can use the standard Apache Kafka tools such as MirrorMaker 2 to set up replications between Apache Kafka clusters.

The following diagram shows the architecture for this strategy.

diagram shows the architecture for this strategy.

This approach has the following benefits:

  • Producers are isolated from the consumers; therefore, your write throughput can scale independently from your read throughput. For example, if you have reached your max read throughput with existing clusters and need to add a new consumer group, you can simply provision a new MSK Serverless cluster and set up replication between the write cluster and the new read cluster.
  • It helps enforce security and regulatory compliance. You can build streaming jobs that can mask or remove the sensitive fields of data events, such as personally identifiable information (PII), while replicating the data.
  • Different clusters can be configured differently in terms of retention. For example, read clusters can be configured with different maximum retention periods, to save on storage cost depending on their requirements.
  • You can prioritize your response time for outages for certain clusters over the others.
  • For implementing increased resiliency, you can have fewer clusters in the backup Region by only replicating the data from the write clusters. Other clusters such as read clusters can be provisioned when the workload failover is invoked. In this model, with the MSK Serverless pricing model, you pay additionally for what you use (lighter replica) in the backup Region.

There are a few important notes to keep in mind when choosing this strategy:

  • It requires setting up multiple replications between clusters, which comes with additional operational and maintenance complexity.
  • Replication tools such as MirrorMaker 2 only support at-least-once processing semantics. This means that during failures and restarts, data events can be duplicated. If you have consumers that can’t tolerate data duplication, I suggest building data pipelines that support the exactly-once processing semantic for replicating the data, such as Apache Flink, instead of using MirrorMaker 2.
  • Because consumers don’t consume data directly from the write clusters, the latency is increased between the writers and the readers.
  • In this strategy, even though there are multiple Apache Kafka clusters, ownership and control still reside with one team, and the resources are in a single AWS account.

Segregating clusters

For some companies, providing access to Apache Kafka through a central data platform can create scaling, ownership, and accountability challenges. Infrastructure teams may not understand the specific business needs of an application, such as data freshness or latency requirements, security, data schemas, or a specific method needed for data ingestion.

You can often reduce these challenges by giving ownership and autonomy to the team who owns the application. You allow them to build and manage their application and needed infrastructure, rather than only being able to use a common central platform. For instance, development teams are responsible for provisioning, configuring, maintaining, and operating their own Apache Kafka clusters. They’re the domain experts of their application requirements, and they can manage their cluster according to their application needs. This reduces overall friction and puts application teams accountable to their advertised SLAs.

As mentioned before, MSK Serverless minimizes the operation and maintenance work associated with Apache Kafka clusters. This enables the autonomous application teams to manage their clusters according to industry best practices, without needing to be an expert in running highly available Apache Kafka clusters on AWS. If the MSK Serverless cluster is provisioned within their AWS account, they also own all the costs associated with operating their applications and the data streaming services.

The following diagram shows the architecture for this strategy.

diagram shows the architecture for this strategy.

This approach has the following benefits:

  • MSK Serverless clusters are managed by different teams; therefore, the overall management work is minimized.
  • Applications are isolated from each other. A faulty application or downtime of a cluster doesn’t impact other applications.
  • Consumers read data directly with low latency from the same cluster where the data is written.
  • Each MSK Serverless cluster scales differently per its write and read throughput.
  • Simple cost attribution means that application teams own their infrastructure and its cost.
  • Total ownership of the streaming infrastructure allows developers to adopt streaming faster and deliver more functionalities. It may also help shorten their response time to failures and outages.

Compared to the previous strategy, this approach has the following disadvantages:

  • It’s difficult to enforce a unified security or regulatory compliance across many teams.
  • Duplicate copies of the same data may be ingested in multiple clusters. This increases the overall cost.
  • To increase resiliency, each team individually needs to set up replications between MSK Serverless clusters.

Moving from a centralized to decentralized strategy

MSK Serverless provides AWS Command Line Interface (AWS CLI) tools and support for AWS CloudFormation templates for provisioning clusters in minutes. You can implement any of the strategies that I mentioned earlier via the methods AWS provides, and migrate your producers and consumers when the new clusters are ready.

The following steps provide further guidance on implementation of these strategies:

  1. Begin by focusing on the current issues with the monolithic Apache Kafka. Next, compare the challenges with the benefits and disadvantages, as listed under each strategy. This helps you decide which strategy serves your company the best.
  2. Identify and document each application’s performance, resiliency, SLA, and ownership requirements separately.
  3. Attempt grouping applications that have similar requirements. For example, you may find a few applications that run batch analytics; therefore, they’re not sensitive to data freshness and also don’t need access to sensitive (or PII) data. If you decide segregating clusters is the right strategy for your company, you may choose to group applications by the team who owns them.
  4. Compare each group of applications’ storage and streaming throughput requirements against the MSK Serverless quotas. This helps you determine whether one MSK Serverless cluster can provide the needed aggregated streaming capacity. Otherwise, further divide larger groups to smaller ones.
  5. Create MSK Serverless clusters per each group you identified earlier via the AWS Management Console, AWS CLI, or CloudFormation templates.
  6. Identify the topics that correspond to each new MSK Serverless cluster.
  7. Choose the best migration pattern to Amazon MSK according to the replication requirements. For example, when you don’t need data transformation, and duplicate data events can be tolerated by applications, you can use Apache Kafka migration tools such as MirrorMaker 2.0.
  8. After you have verified the data is replicating correctly to the new clusters, first restart the consumers against the new cluster. This ensures no data will be lost as the result of the migration.
  9. After the consumers resume processing data, restart the producers against the new cluster, and shut down the replication pipeline you created earlier.

As of this writing, MSK Serverless only supports AWS Identity and Access Management (IAM) for authentication and access control. For more information, refer to Securing Apache Kafka is easy and familiar with IAM Access Control for Amazon MSK. If your applications use other methods supported by Apache Kafka, you need to modify your application code to use IAM Access Control instead or use the Amazon MSK provisioned offering.

Summary

MSK Serverless eliminates operational overhead, including the provisioning, configuration, and maintenance of highly available Apache Kafka. In this post, I showed how splitting Apache Kafka clusters helps improve the security, performance, scalability, and reliability of your overall data streaming services and applications. I also described two main strategies for splitting a monolithic Apache Kafka cluster using MSK Serverless. If you’re using Amazon MSK provisioned offering, these strategies are still relevant when considering moving from a centralized to a decentralized model. You can decide the right strategy depending on your company’s specific needs.

For further reading on Amazon MSK, visit the official product page.

About the Author

About the author Ali AlemiAli Alemi is a Streaming Specialist Solutions Architect at AWS. Ali advises AWS customers with architectural best practices and helps them design real-time analytics data systems that are reliable, secure, efficient, and cost-effective. He works backward from customers’ use cases and designs data solutions to solve their business problems. Prior to joining AWS, Ali supported several public sector customers and AWS consulting partners in their application modernization journey and migration to the cloud.

AWS Security Profile: CJ Moses, CISO of AWS

Post Syndicated from Maddie Bacon original https://aws.amazon.com/blogs/security/aws_security_profile_cj_moses_ciso_of_aws/

AWS Security Profile: CJ Moses, CISO of AWS

In the AWS Security Profile series, I interview the people who work in Amazon Web Services (AWS) Security and help keep our customers safe and secure. This interview is with CJ Moses—previously the AWS Deputy Chief Information Security Officer (CISO), he began his role as CISO of AWS in February of 2022.

How did you get started in security? What about it piqued your interest?

I was serving in the United States Air Force (USAF), attached to the 552nd Airborne Warning and Control (AWACS) Wing, when my father became ill. The USAF reassigned me to McGuire Air Force Base (AFB) in New Jersey so that I’d be closer to him in New York. Because I was an unplanned resource, they added me to the squadron responsible for base communications. I ended up being the Base CompuSec (Computer Security) Manager, who was essentially the person who had to figure out what a firewall was and how to install it. That role required me to have a lot of interaction with the Air Force Office of Special Investigations (AFOSI), which led to me being recruited as a Computer Crime Investigator (CCI). Normally, when I’m asked what kind of plan I followed to get where I am today, I like to say, one modeled after Forrest Gump.

How has your time in the Air Force influenced your approach to cybersecurity?

It provided a strong foundation that I’ve built on with each and every experience since. My years as a CCI had me chasing hackers around the world on what was the “Wild West” of the internet. I’ve been kicked out of countries, asked (told) never to come back to others, but in the end the thing that stuck is that there is always a human on the other side of the connection. Keyboards don’t type for themselves, and therefore understanding your opponent and their intent will inform the measures you must put in place to deal with them. In the early days, we were investigating Advanced Persistent Threats (APTs) long before anyone had created that acronym, or given the actors names or fancy number designators. I like to use that experience to humanize the threats we face.

You were recently promoted to CISO of AWS. What are you most excited about in your new role?

I’m most excited by the team we have at AWS, not only the security team I’m inheriting, but also across AWS. As a CISO, it’s a dream to have an organization that truly believes security is the top priority, which is what we have at AWS. This company has a strong culture of ownership, which allows the security team to partner with the service owners to enable their business, rather than being the office of, “no, you can’t do that.” I prefer my team to answer questions with “Yes, but” or “Yes, and,” and then talk about how they can do what they need in a more secure manner.

What’s the most challenging part of being CISO?

There’s a right balance I’m working to find between how much time I’m able to spend focusing on the details and doing security, and communicating with customers about what we do. I lean on our Office of the CISO (OCISO) team to make sure we keep up a high level of customer engagement. I strive to keep the right balance between involvement in details, leading our security efforts, and engaging with our customers.

What’s your short- and long-term vision for AWS Security?

In the short term, my vision is to continue on the strong path that Steve Schmidt, former CISO of AWS and current chief security officer of Amazon, provided. In the longer term, I intend to further mechanize, automate, and scale our abilities, while increasing visibility and access for our customers.

If you could give one piece of advice to all AWS customers at scale, what would it be?

My advice to customers is to take advantage of the robust security services and resources we offer. We have a lot of content that is available for little to no cost, and an informed customer is less likely to encounter challenging security situations. Enabling Amazon GuardDuty on a customer’s account can be done with only a few clicks, and the threat detection monitoring it offers will provide organization-wide visibility and alerting.

What’s been the most dramatic change you’ve seen in the industry?

The most dramatic change I’ve seen is the elevated visibility of risk to the C-suite. These challenges used to be delegated lower in the organization to someone, maybe the CISO, who reported to the chief information officer. In companies that have evolved, you’ll find that the CISO reports to the CEO, with regular visibility to the board of directors. This prioritization of information security ensures the right level of ownership throughout the company.

Tell me about your work with military veterans. What drives your passion for this cause?

I’ve aligned with an organization, Operation Motorsport, that uses motorsports to engage with ill, injured, and wounded service members and disabled veterans. We present them with educational and industry opportunities to aid in their recovery and rehabilitation. Over the past few years we’ve sponsored a number of service members across our race teams, and I’ve personally seen the physical, and even more importantly, mental improvements for the beneficiaries who have become part of our race teams. Having started my military career during Operation Desert Shield/Storm (the buildup to and the first Gulf War), I can connect with these vets and help them to find a path and a new team to be part of.

If you had to pick any other industry, what would you want to do?

Professional motorsports. There is an incredible and not often visible alignment between the two industries. The use of data analytics (metrics focus), the culture, leadership principles, and overall drive to succeed are in complete alignment, and I’ve applied lessons learned between the two interchangeably.

What are you most proud of in your career?

I am very fortunate to come from rather humble beginnings and I’m appreciative of all the opportunities provided for me. Through those opportunities, I’ve had the chance to serve my country and, since joining AWS, to serve many customers across disparate industries and geographies. The ability to help people is something I’m passionate about, and I’m lucky enough to align my personal abilities with roles that I can use to leave the world a better place than I found it.

 
If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, contact AWS Support.

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Author

Maddie Bacon

Maddie (she/her) is a technical writer for AWS Security with a passion for creating meaningful content. She previously worked as a security reporter and editor at TechTarget and has a BA in Mathematics. In her spare time, she enjoys reading, traveling, and all things Harry Potter.

CJ Moses

CJ Moses

CJ Moses is the Chief Information Security Officer (CISO) at AWS. In his role, CJ leads product design and security engineering for AWS. His mission is to deliver the economic and security benefits of cloud computing to business and government customers. Prior to joining Amazon in 2007, CJ led the technical analysis of computer and network intrusion efforts at the U.S. Federal Bureau of Investigation Cyber Division. CJ also served as a Special Agent with the U.S. Air Force Office of Special Investigations (AFOSI). CJ led several computer intrusion investigations seen as foundational to the information security industry today.

Building your brand as a Solutions Architect

Post Syndicated from Clare Holley original https://aws.amazon.com/blogs/architecture/building-your-brand-as-a-solutions-architect/

As AWS Solutions Architects, we use our business, technical, and people skills to help our customers understand, implement, and refine cloud-based solutions. We keep up-to-date with always-evolving technology trends and use our technical training to provide scalable, flexible, secure, and resilient cloud architectures that benefit our customers.

Today, each of us will examine how we’ve established our “brand” as Solutions Architects.

“Each of us has a brand, but we have to continuously cultivate and refine it to highlight what we’re passionate about to give that brand authenticity and make it work for us.” – Bhavisha Dawada, Enterprise Solutions Architect at AWS

We talk about our journeys as Solutions Architects and show you the specific skills and techniques we’ve sought out, learned, and refined to help set you on the path to success in your career as a Solutions Architect. We’ll share tips on how to establish yourself when you’re just starting out and how to move forward if you’re already a few years in.

Establishing your brand

As a Solutions Architect, there are many resources available to help you establish your brand. You can pursue specific training or attend workshops to develop your business and technical acumen. You’ll also have opportunities to attend or even speak at industry conferences about trends and innovation in the tech industry.

Learning, adapting, and constantly growing is how you’ll find your voice and establish your brand.

Bhavisha Dawada, Enterprise Solutions ArchitectBhavisha Dawada

Bhavisha helps customers solve business problems using AWS technology. She is passionate about working in the field of technology and helping customers build and scale enterprise applications.

What helped her move forward in her career? “When I joined AWS, I had limited cloud experience and was overwhelmed by the quantity of services I had to learn in order to advise my customers on scalable, flexible, secured, and resilient cloud architectures.

To tackle this challenge, I built a learning plan for areas I was interested in and I wanted to go deeper. AWS offers several resources to help you cultivate your skills, such as AWS blogs, AWS Online Tech Talks, and certifications to keep your skills updated and relevant.”

Jyoti Tyagi, Enterprise Solutions Architect Jyoti Tyagi

Jyoti is passionate about artificial intelligence and machine learning. She helps customers to architect securely with best practices of the cloud.

What helped her move forward in her career? “Working closely with mentor and specialist helped me quickly ramp up with necessary business and technical skills.

I also took part in shadow programs and speaking opportunities to further enhance my skills. My advice? Focus on your strengths, and then build a plan to work on where you’re not as strong.”

Clare Holley, Senior Solutions Architect

Clare helps customers achieve their business outcomes on their cloud journey. With more than 20 years of experience in the IT discipline, she helps customers build highly resilient and scalable architectures.Clare Holley

What helped her move forward in her career? “Coming from the database discipline, I wanted to learn more about helping customers with migrations. I took online courses and attended workshops on the various services to help our customers.

I went through a shadowing process on diving deeper on the services. Eventually, I was comfortable with the topics and even began conducting these workshops myself and providing support.

This can be a repeatable pattern. We are encouraged to experiment, learn, and iterate new ways to meet and stay ahead of our customer’s needs. Identify quarterly realistic goals. Adjust time on your calendar to learn and be curious, since self-learning is essential for success.”

Maintaining work-life balance

As a woman in tech, work-life balance is key. Despite being career driven, you also have a life beyond your job. It’s not always easy, but by maintaining a healthy boundary between work and life, you’ll likely be more productive.

Sujatha Kuppuraju, Senior Solutions ArchitectSujatha Kuppuraju

Sujatha engages with customers to create innovative and secured solutions that address customer business problems and accelerate the adoption of AWS services.

What helps her maintain a healthy work-life balance? “As a mother, a spouse, and working woman, finding the right balance between family and work is important to me.

Expectations at work and with my family fluctuate, so I have to stay flexible. To re-prioritize my schedule, I analyze the impact, reversibility, raise critical feedback before jumping into a task. This allows me to control where I spend my time.

In this growing technology industry, we have innovative and improved ways to solve problems. I invest time to empower customers and team members to execute changes by themselves. This not only reduces the dependencies on me, it also helps to scale changes and get quick returns on benefits.”

Reach out and connect to others

To continue to succeed as a Solutions Architect, in addition to technical and business knowledge, it is important to discuss ideas and learn from like-minded peers.

Clare highlights the importance of growing your network. “When I joined AWS, I looked into joining several affinity groups. These groups allow people who identify with a cause the opportunity to collaborate. They provide an opportunity for networking, speaking engagements, leadership and career growth opportunities, as well as mentorship. In these affinity groups, I met so many awesome women who inspired me to be authentic, honest, and push beyond my comfort zone.”

Women in tech have unfortunately experienced lack of representation. Bhavisha says having connections in the field helped her feel less alone in the field. “When I was interviewing for AWS, I networked with other women to know more about the company’s culture and learn about their journey at AWS. Learning about this experience helped me feel confident in my career choice.”

Continue your journey

Take the AWS Certified Solution Architect – Associate certification to build your technical skills. This course validates your ability to design and deploy well-architected solutions on AWS that meet customer requirements.

We also encourage you to attend our virtual coffee events, which provide a unique opportunity to engage with AWS leaders, career opportunities, and insight into our approach to serving customers.

Ready to get started?

Interested in applying for a Solutions Architecture role?

We’ve got more content for International Women’s Day!

For more than a week we’re sharing content created by women. Check it out!

Other ways to participate

Breaking the Bias – Women at AWS Developer Relations

Post Syndicated from Rashmi Nambiar original https://aws.amazon.com/blogs/aws/breaking-the-bias-women-at-aws-developer-relations/

Today for International Women’s Day we’re joined by a special guest writer, Rashmi Nambiar. She’s here to share her conversations with a few other members of the AWS Developer Relations team, talking about their work and experience as women in tech. Enjoy!

– The AWS News Blog Team

When I was contemplating joining AWS, many warned me about boarding the “rocket ship.” But I took the leap of faith. It has been four years since then. Now when I look back, the growth trajectory is something that I am proud of, from starting my AWS journey with a regional role in India to going global and now driving the Worldwide Developer Marketing Strategy. #HereatAWS, I get to choose the direction of my career and prioritize my time between family and work.

At AWS, we believe that the future of technology is accessible, flexible, and inclusive. So we take it very seriously when we say, “All Builders Welcome.” As a woman in tech, I have felt that strong sense of belonging with the team and acceptance for who I am.

Being part of the AWS Developer Relations (DevRel) team, I get to meet and work with awesome builders within and outside of the organization who are changing the status quo and pushing technological boundaries. This International Women’s Day, I took the opportunity to talk to some of the women at AWS DevRel about their role as tech/dev advocates.

Veliswa Boya

Headshot of Veliswa Boya

Veliswa Boya, Senior Developer Advocate

What is it that you like about being a developer advocate at AWS?
“Becoming a developer advocate is something I didn’t even dare to dream about. Some of us go through life and at some point admit that some dreams are just not meant for us. That today I am a developer advocate at AWS working with the builder community of sub-Saharan Africa and beyond is one of the most fulfilling and exciting roles I can recall throughout my entire tech career. I especially enjoy working with those new to AWS and new to tech in general, so my role spans technical content creation and delivery all the way to the mentoring of community members. I enjoy working for an organization that’s at the forefront of innovation, but at the same time not innovating for the sake of innovating, but always being customer obsessed and innovating on behalf of the customer.”

You are an icon of possibilities with many titles. How did the transition from AWS Hero to AWS employee work out for you?
“I became an AWS Hero in May 2020, and with that, I became the first woman out of Africa to ever be named an AWS Hero. I have always enjoyed sharing knowledge. Every little bit I learn, I always make sure to share. I believe that this—and more—led to my nomination. Joining AWS as a developer advocate is awesome. I continue to live the passion that led to me being a Hero, sharing knowledge with others and at the same time learning from both the community and my wonderful peers.”

Antje Barth

Headshot photo of Antje Barth

Antje Barth, Principal Developer Advocate – AI/ML

What do you like about your role as an AI/ML specialist on the AWS Developer Relations Team?
“I’ve always been excited about technology and the speed of innovation in this field. What I like most about my role as a principal developer advocate for AI/ML is that I get to share this passion and enable customers, developers, and students to build amazing things. I recently organized a hackathon asking participants to think about creative ways of using machine learning to improve disaster response. And I was simply blown away by all the ideas the teams came up with.”

You have authored books like Data Science on AWS. What is your guidance for someone planning to get on the publishing path?
“The piece of advice I would give anyone interested in becoming a book author: Find the topic you are really passionate about, dive into the topic, and start developing content—whether it’s blog posts, code samples, or videos. Become a subject matter expert and make yourself visible. Speak at meetups, submit a talk to a conference. Grow your network. Find peers, discuss your ideas, ask for feedback, make sure the topic is relevant for a large audience group. And eventually, reach out to publishers, share your content ideas and collected feedback, and put together a book proposal.”

Lena Hall

Headshot photo of Lena Hall

Lena Hall, Head of Developer Relations – North America

What excites you about AWS Developer Relations?
“I love it because AWS culture empowers anyone at AWS, including developer advocates, to always advocate for the customer and the community. While doing that, no matter how hard it is or how much friction you run into, you can be confident in doing the right thing for our customers and community. This translates to our ability to influence internally across the company, using strong data and logical narratives to support our improvement proposals.”

You have recently joined the team as the DevRel Head for North America. What does it take to lead a team of builders?
“It is important to recognize that people on your team have unique strengths and superpowers. I found it valuable to identify those early on and offer paths to develop them even more. In many cases, it leads to a bigger impact and improved motivation. It is also crucial to listen to your team, be supportive and welcoming of ideas, and protective of their time.”

Rohini Gaonkar

Headshot photo of Rohini Gaonkar

Rohini Gaonkar, Senior Developer Advocate

You have been with AWS for over eight years. What attracted you to developer advocacy?
“As a developer advocate, I love being autonomous, and I have the freedom to pick the tech of my choice. The other fun part is to work closely with the community—my efforts, however small, help someone in their career, and that is the most satisfying part of my work.”

You have worked in customer support, solutions architect, and technical evangelist roles. What’s your tip on developing multiple technical skills?
“Skills are like flowers in your bouquet; you should keep adding beautiful colors to it. Sometimes it takes months to years to develop a skill, so keep an eye on your next thing and start adding the skills for it today. Interestingly, at AWS, the ‘Learn and be curious’ leadership principle encourages us to always find ways to improve ourselves, to explore new possibilities and act on them.”

Jenna Pederson

Headshot photo of Jenna Pederson

Jenna Pederson, Senior Developer Advocate

What is your reason for taking up a developer advocate role at AWS?
“I like being a developer advocate at AWS because it lets me scale my impact. I get to work with and help so many more builders gain knowledge, level up their skills, and bring their ideas to life through technology.”

It is such a delight to watch your presentations and demo at events and other programs. What is your advice to people who want to get into public speaking?
“If you’re a new speaker, talk about what you’re learning, even if you think everyone is talking about the same thing. You will have a fresh perspective on whatever it is.”

Kris Howard

Headshot photo of Kris Howard

Kris Howard, DevRel Manager

Why did you join the Developer Relations Team?
“I joined DevRel because I love being on stage and sharing my creativity and passion for tech with others. The most rewarding part is when someone tells you that you inspired them to learn a new skill, or change their career, or stretch themselves to reach a new goal.”

Since you have worked in different geographies, what would you say to someone who is exploring working in different countries?
“The last two years have really emphasized that if you want to see the world, you should take advantage of every opportunity you get. That’s one of the benefits of Amazon: that there are so many career paths available to you in lots of different places! As a hiring manager, I was always excited to get applications from internal transfers, and in 2020 I got the chance to experience it from the other side when I moved with my partner from Sydney to Munich. It was a challenging time to relocate, but in retrospect, I’m so glad we did.”

Join Us!

Interested in working with DevRel Team? Here are some of the available opportunities.

Celebrate International Women’s Day all week with the Architecture Blog

Post Syndicated from Bonnie McClure original https://aws.amazon.com/blogs/architecture/celebrate-international-womens-day-with-us-on-the-architecture-blog/

Companies committed to diversity (gender or otherwise) tend to be more creative and innovative and have higher retention and engagement rates. Diverse leadership can provide excellent role models for younger people looking for a career in STEM, those who are transitioning into the industry from an “unconventional” career path, or those who are returning to work.

This International Women’s Day, we’re featuring more than a week’s worth of posts that highlight female builders and leaders. We’re showcasing women in the industry who are building, creating, and, above all, inspiring, empowering, and encouraging everyone—especially women and girls—in tech.

Though the number of women in tech roles is slowly increasing, they are still underrepresented. As shown in the graph that follows, women worldwide hold, on average, 21% of IT and technical roles.

Female representation in technology organizations in 2021, selected countries

Female representation in technology organizations in 2021, selected countries

This number drops to 12% when you look at cloud computing roles like Developers/Engineers, Data Engineers, System Administrators, DevOps Engineers, and Architects.

Share of male and female workers across professional clusters

Share of male and female workers across professional clusters

The technology industry has a challenge—but also an opportunity—when it comes to equal gender representation. By highlighting the work that women are doing right now to slowly but steadily change what it looks like (literally and figuratively) to work in tech and with continued commitment and effort, we can create a path to success for everyone.

She Builds Tech Skills re:Invent Roundup

AWS She Builds Tech Skills is a skill development program aimed for builders and cloud enthusiasts to create an inclusive environment to learn and develop cloud skills. Their mission is to build a community with world class leaders and influence diversity representation amongst technical roles in technology.

To kick off this week, we’re featuring a video from She Builds Tech Skills, hosted by Mai Nishitani and May Kyaw, Solutions Architects at AWS. In the video, they chat with six female Solutions Architects from around the world about their favorite services and features from re:Invent 2021, and they give advice on how to get started using these services in your architectures.

As a bonus, Mai and May followed up with these women to chat about how they’re celebrating International Women’s Day this week and every week.

Poornima Chand, Senior Solutions ArchitectPoornima Chand

Poornima Chand is a Senior Solutions Architect in the Strategic Accounts Solutions team at AWS. She works with customers to help solve their unique challenges using AWS technology solutions. She enjoys architecting and building scalable solutions. Her focus areas include Serverless, High Performance Computing and Machine Learning.

How does she encourage and mentor women in tech and beyond? Poornima is an active mentor in the AWS She Builds CloudUp program. She loves to celebrate women’s achievements and plans to spend International Women’s Day interacting with and learning from Women@Amazon and women from customer teams.

Ai-Linh Le, Solutions ArchitectAi-Linh Li

Ai-Linh Le is a Solutions Architect based in Sydney, Australia. She started her career as a software engineer and still likes to be hands-on in developing and building solutions and demos. She enjoys working with customers and helping them to build solutions and solve challenges. Her areas of focus include data analytics, machine learning, and DevOps.

How does she encourage and mentor women in tech and beyond? Ai-Linh is passionate about continuous learning and exploring new technologies, and is a mentor in the AWS She Builds CloudUp program.

Nelli Lovchikova, Enterprise Solutions ArchitectNelli Lovchikova

Nelli has nearly twenty years of experience helping companies build amazing things as a software engineer and architect. She strongly believes in engineering excellence and continuous learning and improvement.

How does she encourage and mentor women in tech and beyond? Nelli constantly researches and experiments with bleeding-edge technologies and ideas and is always happy to take other people on that journey with me, share my findings, and inspiration.

Natalie White, Enterprise Solutions ArchitectNatalie White

Natalie White is an Enterprise Solutions Architect in southern California. Her 15-year software development career across four industry verticals prior to joining AWS and her advocacy for AWS Developer Tools and Infrastructure as Code services help her earn trust with her customers’ builders and executive stakeholders and accelerate their time to done.

How does she encourage and mentor women in tech and beyond? Natalie is an active member in the Society of Women Engineers and a leader of her daughter’s Girl Scout troop, so she will celebrate International Women’s Day with Women@Amazon and across engineering domains, industry verticals, and age groups.

Deval Parikh. Senior Enterprise Solutions ArchitectDeval S Parikh

Deval Parikh is a Sr Enterprise Solutions Architect at AWS based out of Los Angeles. She is passionate about helping enterprises re-imagine their businesses in the cloud by leading them with strategic architectural guidance and building prototypes as an AWS expert.

How does she encourage and mentor women in tech and beyond? Deval is passionate about helping women STEM roles. She leads various affinity groups in AWS North America, including Women At Solutions Architecture and YouthTech. On weekends, she teaches high school and middle school students programming in Python and Spark. Outside of work, she loves to paint with oil on canvas and hiking with her friends. You can view some of her artwork at www.devalparikh.com.

Viktoria Semaan, Senior Partner Solutions ArchitectSemaan

As a Senior Partner Solutions Architect, Viktoria is helping AWS Strategic ISV Partners to build joint innovative solutions on AWS. She has 13+ years of experience in solutions architecture, leading multi-site automation and transformation projects. She is a public speaker and content creator and often shares learning opportunities on social media.

How does she encourage and mentor women in tech and beyond? Viktoria is passionate about coaching, talent development, and mentoring others. She is a mentor at the AWS She Builds CloudUp program, which focuses on empowering women and helps them to learn AWS services and products and become AWS Certified.

Would you like to know more?

If you want to hear more about AWS She Builds Tech Skills, please reach out to May or Mai on LinkedIn for more information, subscribe to their YouTube channel for the latest videos.

We’ve got more content for International Women’s Day!

Tomorrow we have a technical post, Deploying service-mesh-based architectures using AWS App Mesh and Amazon ECS from Kesha Williams, an AWS Hero and award-winning software engineer.

Later this week, we’ll share:

  • A collection of several blog posts written and co-authored by women
  • Curated content from the Let’s Architect! team and a live Twitter chat
  • A post on Women at AWS – Diverse Backgrounds, Common Goal of Becoming Solutions Architects
  • Another post on Building your brand as a SA

Enjoy!

Other ways to participate

Top 2021 AWS Security service launches security professionals should review – Part 1

Post Syndicated from Ryan Holland original https://aws.amazon.com/blogs/security/top-2021-aws-security-service-launches-part-1/

Given the speed of Amazon Web Services (AWS) innovation, it can sometimes be challenging to keep up with AWS Security service and feature launches. To help you stay current, here’s an overview of some of the most important 2021 AWS Security launches that security professionals should be aware of. This is the first of two related posts; Part 2 will highlight some of the important 2021 launches that security professionals should be aware of across all AWS services.

Amazon GuardDuty

In 2021, the threat detection service Amazon GuardDuty expanded the internal AWS security intelligence it consumes to use more of the intel that AWS internal threat detection teams collect, including additional nation-state threat intelligence. Sharing more of the important intel that internal AWS teams collect lets you quickly improve your protection. GuardDuty also launched domain reputation modeling. These machine learning models take all the domain requests from across all of AWS, and feed them into a model that allows AWS to categorize previously unseen domains as highly likely to be malicious or benign based on their behavioral characteristics. In practice, AWS is seeing that these models often deliver high-fidelity threat detections, identifying malicious domains 7–14 days before they are identified and available on commercial threat feeds.

AWS also launched second generation anomaly detection for GuardDuty. Shortly after the original GuardDuty launch in 2017, AWS added additional anomaly detection for user behavior analytics and monitoring for unusual activity of AWS Identity and Access Management (IAM) users. After receiving customer feedback that the original feature was a little too noisy, and that it was difficult to understand why some findings were generated, the GuardDuty analytics team rebuilt this functionality on an entirely new machine learning model, considerably reducing the number of detections and generating a more accurate positive-detection rate. The new model also added additional context that security professionals (such as analysts) can use to understand why the model shows findings as suspicious or unusual.

Since its introduction, GuardDuty has detected when AWS EC2 Role credentials are used to call AWS APIs from IP addresses outside of AWS. Beginning in early 2022, GuardDuty now supports detection when credentials are used from other AWS accounts, inside the AWS network. This is a complex problem for customers to solve on their own, which is why the GuardDuty team added this enhancement. The solution considers that there are legitimate reasons why a source IP address that is communicating with AWS services APIs might be different than the Amazon Elastic Compute Cloud (Amazon EC2) instance IP address, or a NAT gateway associated with the instance’s VPC. The enhancement also considers complex network topologies that route traffic to one or multiple VPCs—for example, AWS Transit Gateway or AWS Direct Connect.

Our customers are increasingly running container workloads in production; helping to raise the security posture of these workloads became an AWS development priority in 2021. GuardDuty for EKS Protection is one recent feature that has resulted from this investment. This new GuardDuty feature monitors Amazon Elastic Kubernetes Service (Amazon EKS) cluster control plane activity by analyzing Kubernetes audit logs. GuardDuty is integrated with Amazon EKS, giving it direct access to the Kubernetes audit logs without requiring you to turn on or store these logs. Once a threat is detected, GuardDuty generates a security finding that includes container details such as pod ID, container image ID, and associated tags. See below for details on how the new Amazon Inspector is also helping to protect containers.

Amazon Inspector

At AWS re:Invent 2021, we launched the new Amazon Inspector, a vulnerability management service that continually scans AWS workloads for software vulnerabilities and unintended network exposure. The original Amazon Inspector was completely re-architected in this release to automate vulnerability management and to deliver near real-time findings to minimize the time needed to discover new vulnerabilities. This new Amazon Inspector has simple one-click enablement and multi-account support using AWS Organizations, similar to our other AWS Security services. This launch also introduces a more accurate vulnerability risk score, called the Inspector score. The Inspector score is a highly contextualized risk score that is generated for each finding by correlating Common Vulnerability and Exposures (CVE) metadata with environmental factors for resources such as network accessibility. This makes it easier for you to identify and prioritize your most critical vulnerabilities for immediate remediation. One of the most important new capabilities is that Amazon Inspector automatically discovers running EC2 instances and container images residing in Amazon Elastic Container Registry (Amazon ECR), at any scale, and immediately starts assessing them for known vulnerabilities. Now you can consolidate your vulnerability management solutions for both Amazon EC2 and Amazon ECR into one fully managed service.

AWS Security Hub

In addition to a significant number of smaller enhancements throughout 2021, in October AWS Security Hub, an AWS cloud security posture management service, addressed a top customer enhancement request by adding support for cross-Region finding aggregation. You can now view all your findings from all accounts and all selected Regions in a single console view, and act on them from an Amazon EventBridge feed in a single account and Region. Looking back at 2021, Security Hub added 72 additional best practice checks, four new AWS service integrations, and 13 new external partner integrations. A few of these integrations are Atlassian Jira Service Management, Forcepoint Cloud Security Gateway (CSG), and Amazon Macie. Security Hub also achieved FedRAMP High authorization to enable security posture management for high-impact workloads.

Amazon Macie

Based on customer feedback, data discovery tool Amazon Macie launched a number of enhancements in 2021. One new feature, which made it easier to manage Amazon Simple Storage Service (Amazon S3) buckets for sensitive data, was criteria-based bucket selection. This Macie feature allows you to define runtime criteria to determine which S3 buckets should be included in a sensitive data-discovery job. When a job runs, Macie identifies the S3 buckets that match your criteria, and automatically adds or removes them from the job’s scope. Before this feature, once a job was configured, it was immutable. Now, for example, you can create a policy where if a bucket becomes public in the future, it’s automatically added to the scan, and similarly, if a bucket is no longer public, it will no longer be included in the daily scan.

Originally Macie included all managed data identifiers available for all scans. However, customers wanted more surgical search criteria. For example, they didn’t want to be informed if there were exposed data types in a particular environment. In September 2021, Macie launched the ability to enable/disable managed data identifiers. This allows you to customize the data types you deem sensitive and would like Macie to alert on, in accordance with your organization’s data governance and privacy needs.

Amazon Detective

Amazon Detective is a service to analyze and visualize security findings and related data to rapidly get to the root cause of potential security issues. In January 2021, Amazon Detective added a convenient, time-saving integration that allows you to start security incident investigation workflows directly from the GuardDuty console. This new hyperlink pivot in the GuardDuty console takes findings directly from the GuardDuty console into the Detective console. Another time-saving capability added was the IP address drill down functionality. This new capability can be useful to security forensic teams performing incident investigations, because it helps quickly determine the communications that took place from an EC2 instance under investigation before, during, and after an event.

In December 2021, Detective added support for AWS Organizations to simplify management for security operations and investigations across all existing and future accounts in an organization. This launch allows new and existing Detective customers to onboard and centrally manage the Detective graph database for up to 1,200 AWS accounts.

AWS Key Management Service

In June 2021, AWS Key Management Service (AWS KMS) introduced multi-Region keys, a capability that lets you replicate keys from one AWS Region into another. With multi-Region keys, you can more easily move encrypted data between Regions without having to decrypt and re-encrypt with different keys for each Region. Multi-Region keys are supported for client-side encryption using direct AWS KMS API calls, or in a simplified manner with the AWS Encryption SDK and Amazon DynamoDB Encryption Client.

AWS Secrets Manager

Last year was a busy year for AWS Secrets Manager, with four feature launches to make it easier to manage secrets at scale, not just for client applications, but also for platforms. In March 2021, Secrets Manager launched multi-Region secrets to automatically replicate secrets for multi-Region workloads. Also in March, Secrets Manager added three new rules to AWS Config, to help administrators verify that secrets in Secrets Manager are configured according to organizational requirements. Then in April 2021, Secrets Manager added a CSI driver plug-in, to make it easy to consume secrets from Amazon EKS by using Kubernetes’s standard Secrets Store interface. In November, Secrets Manager introduced a higher secret limit of 500,000 per account to simplify secrets management for independent software vendors (ISVs) that rely on unique secrets for a large number of end customers. Although launched in January 2022, it’s also worth mentioning Secrets Manager’s release of rotation windows to align automatic rotation of secrets with application maintenance windows.

Amazon CodeGuru and Secrets Manager

In November 2021, AWS announced a new secrets detector feature in Amazon CodeGuru that searches your codebase for hardcoded secrets. Amazon CodeGuru is a developer tool powered by machine learning that provides intelligent recommendations to detect security vulnerabilities, improve code quality, and identify an application’s most expensive lines of code.

This new feature can pinpoint locations in your code with usernames and passwords; database connection strings, tokens, and API keys from AWS; and other service providers. When a secret is found in your code, CodeGuru Reviewer provides an actionable recommendation that links to AWS Secrets Manager, where developers can secure the secret with a point-and-click experience.

Looking ahead for 2022

AWS will continue to deliver experiences in 2022 that meet administrators where they govern, developers where they code, and applications where they run. A lot of customers are moving to container and serverless workloads; you can expect to see more work on this in 2022. You can also expect to see more work around integrations, like CodeGuru Secrets Detector identifying plaintext secrets in code (as noted previously).

To stay up-to-date in the year ahead on the latest product and feature launches and security use cases, be sure to read the Security service launch announcements. Additionally, stay tuned to the AWS Security Blog for Part 2 of this blog series, which will provide an overview of some of the important 2021 launches that security professionals should be aware of across all AWS services.

If you’re looking for more opportunities to learn about AWS security services, check out AWS re:Inforce, the AWS conference focused on cloud security, identity, privacy, and compliance, which will take place June 28-29 in Houston, Texas.

If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, contact AWS Support.

Want more AWS Security news? Follow us on Twitter.

Author

Ryan Holland

Ryan is a Senior Manager with GuardDuty Security Response. His team is responsible for ensuring GuardDuty provides the best security value to customers, including threat intelligence, behavioral analytics, and finding quality.

Author

Marta Taggart

Marta is a Seattle-native and Senior Product Marketing Manager in AWS Security Product Marketing, where she focuses on data protection services. Outside of work you’ll find her trying to convince Jack, her rescue dog, not to chase squirrels and crows (with limited success).

2021 AWS security-focused workshops

Post Syndicated from Temi Adebambo original https://aws.amazon.com/blogs/security/2021-aws-security-focused-workshops/

Every year, Amazon Web Services (AWS) looks to help our customers gain more experience and knowledge of our services through hands-on workshops. In 2021, we unfortunately couldn’t connect with you in person as much as we would have liked, so we wanted to create and share new ways to learn and build on AWS. We built and published several security-focused workshops that help you learn how to use or configure new services and features securely. Workshops are hands-on learning modules designed to teach or introduce practical skills, techniques, or concepts you can use to solve business problems.

In this blog post, we highlight the newest AWS security-focused workshops below. There are also several other workshops that were developed before 2021; you can find them on AWS Workshops, AWS Security Workshops, and AWS Samples. Here’s the list:

Data Protection and Privacy

Workshop Title

Abstract

Data discovery and classification with Amazon Macie

In this workshop, get familiar with Amazon Macie and learn to scan and classify data in your Amazon Simple Storage Service (Amazon S3) buckets. Work with Macie (data classification) and AWS Security Hub (centralized security view) to see how data in your environment is stored, and to understand any changes in S3 bucket policies that may affect your security posture. Learn to create a custom data identifier and to create and scope data discovery and classification jobs in Macie. Finally, use Macie to filter and investigate the results from the scans you create.

Scaling your encryption at rest capabilities with AWS KMS

AWS makes it easy to protect your data with encryption. This hands-on workshop provides an opportunity to dive deep into encryption at rest options with AWS. Learn AWS server-side encryption with AWS Key Management Service (AWS KMS) for services such as Amazon S3, Amazon Elastic Block Store (Amazon EBS), and Amazon Relational Database Service (Amazon RDS). Also, learn best practices for using AWS KMS across multiple accounts and Regions and how to scale while optimizing for performance.

Store, retrieve, and manage sensitive credentials in AWS Secrets Manager

In this workshop, learn how to integrate AWS Secrets Manager in your development platform, backed by serverless applications. Work through a sample application, and use Secrets Manager to retrieve credentials as well as work with attribute-based access control using tags. Also, learn how to monitor the compliance of secrets and implement incident response workflows that will rotate the secret, restore the resource policy, alert the SOC, and deny access to the offender.

Building and operating a Private Certificate Authority on AWS

This workshop covers private certificate management on AWS, employing the concepts of least privilege, separation of duties, monitoring, and automation. Participants learn operational aspects of creating a complete certificate authority (CA) hierarchy, building a simple web application, and issuing private certificates. It also covers how job functions—including CA administrators, application developers, and security administrators—can follow the principle of least privilege to perform various functions associated with certificate management. Finally, learn about IoT certificates, code-signing, and certificate templates to enable all your use cases.

Amazon S3 security and access settings and controls

Amazon S3 provides many security and access settings to help you secure your data, controls that ensure that those settings remain in place, and features to help you audit those settings and controls. This workshop walks you through these Amazon S3 capabilities and scenarios, to help you apply them for different security requirements.

Redact data as needed using Amazon S3 Object Lambda

Amazon S3 Object Lambda works with your existing applications, and allows you to add your own code using AWS Lambda functions to automatically process and transform data from Amazon S3 before returning it to an application. This enables different views of the same object depending on user identity, such as restricting access to confidential information, or disallowing access to personally identifiable information (PII) data. In this workshop, learn how to use Amazon S3 Object Lambda to modify objects during GET requests, so you no longer need to store multiple views of the same document.

Using AWS Nitro Enclaves to process highly sensitive data

In this hands-on workshop, learn how to use AWS Nitro Enclaves to isolate highly-sensitive data from your users, applications, and third-party libraries on your Amazon Elastic Compute Cloud (Amazon EC2) instances. Explore AWS Nitro Enclaves, discuss common use cases, and build and run your own enclave. During this workshop, learn about enclave isolation, cryptographic attestation, enclave image files, local Vsock communication channels, common debugging scenarios, and the enclave lifecycle.

Ransomware prevention strategies in Amazon S3

Learn how to use the protective, detective and monitoring controls in AWS to protect your data in S3 from ransomware threats. Set up Amazon GuardDuty for S3 and AWS Identity and Access Management (IAM) Access Analyzer, and learn to read and respond to findings and create IAM invariants. Create a tiered storage approach to backup and recovery, and learn to use Amazon S3 Object Lock, versioning, and replication to provide immutable storage and protect against accidental or malicious deletion.

Governance, Risk, and Compliance

Operating securely in a multi-account environment

Operating multiple AWS accounts under an organization is how many users consume AWS Cloud services. In this workshop, learn how to build foundational security monitoring in multi-account environments. Walk through an initial setup of AWS Security Hub for centralized aggregation of findings across your AWS Organizations organization. Additionally, learn how to centralize Amazon GuardDuty findings, Amazon Detective functions, AWS Identity and Access Management (IAM) Access Analyzer findings (if available), AWS Config rule evaluations, and AWS CloudTrail logs into the central security monitoring account (security tools account). Finally, implement a service control policy (SCP) that denies the ability to disable these security controls.

Building remediation workflows to simplify compliance

Automation and simplification are key to managing compliance at scale. Remediation is one of the essential elements of simplifying and managing risk. In this workshop, see how to build a remediation workflow using AWS Config and AWS Systems Manager automation. Learn how this workflow can be deployed at scale and monitored with AWS Security Hub to oversee the entire organization and how to use AWS Audit Manager to easily access evidence of risk management.

Identity and Access Management

Integrating IAM Access Analyzer into a CI/CD pipeline

Want to analyze Identity and Access Management (IAM) policies at scale? Want to help your developers write secure IAM policies? This workshop provides you the hands-on opportunity to run IAM Access Analyzer policy validation on your AWS CloudFormation templates in a continuous integration/continuous deployment (CI/CD) pipeline.

Data perimeter workshop

In this workshop, learn how to create a data perimeter by building controls that allow access to data only from expected network locations and by trusted identities. The workshop consists of five modules, each designed to illustrate a different Identity and Access Management (IAM) or network control. Learn where and how to implement the appropriate controls based on different risk scenarios. Discover how to implement these controls as service control policies, identity- and resource-based policies, and Amazon Virtual Private Cloud (Amazon VPC) endpoint policies.

Network and Infrastructure Security

Build a Zero Trust architecture for service-to-service workloads on AWS

In this workshop, get hands-on experience implementing a Zero Trust architecture for service-to-service workloads on AWS. Learn how to use services such as Amazon API Gateway and Virtual Private Cloud (Amazon VPC) endpoints to integrate network and identity controls while using Amazon GuardDuty, Lambda, and Amazon DynamoDB to take advantage of native service controls. Learn how these services allow you to authorize specific flows between components to reduce lateral network mobility risk and improve the overall security posture of your workload.

Securing deployment of third-party ML models

Enterprise users adopting machine learning (ML) on AWS often look for prescriptive guidance on implementing security best practices, establishing governance, securing their ML models, and meeting compliance standards. Building a repeatable solution provides users with standardization and governance over what gets provisioned in their AWS account. In this workshop, learn steps you can take to secure third-party ML model deployments. We provide cloud infrastructure-as-code templates to automate the setup of a hardened Amazon SageMaker environment. These templates include private networking, VPC endpoints, end-to-end encryption, logging and monitoring, and enhanced governance and access controls through AWS Service Catalog.

Building Prowler into a QuickSight-powered AWS security dashboard

In this workshop, get hands-on experience with Prowler, AWS Security Hub, and Amazon QuickSight by building a custom security dashboard for the AWS environment. Using a multi-account deployment of Prowler integrated into Security Hub, learn to identify and analyze Prowler findings and integrate QuickSight to visualize the information. Discover how to get the most from QuickSight and Prowler with automatically created datasets.

Threat Detection and Incident Response

Integration, prioritization, and response with AWS Security Hub

This workshop is designed to get you familiar with AWS Security Hub, so you can better understand how to use it in your own AWS environment. This workshop has two sections. The first section demonstrates the features and functions of AWS Security Hub. The second section shows you how to use AWS Security Hub to import findings from different data sources, analyze findings so you can prioritize response work, and implement responses to findings to help improve your security posture.

Building an AWS incident response plan using Jupyter notebooks

This workshop guides you through building an incident response plan for your AWS environment using Jupyter notebooks. Walk through an easy-to-follow sample incident, using building blocks as a ready-to-use playbook in a Jupyter notebook. Then, follow simple steps to add additional programmatic and documented steps to your incident response plan.

Scaling threat detection and response on AWS

In this hands-on workshop, learn about several AWS services involved in threat detection and response as you walk through real-world threat scenarios. Learn about the threat detection capabilities of Amazon GuardDuty, Amazon Macie, and AWS Security Hub and the available response options. For each hands-on scenario, review methods to detect and respond to threats using the following services: AWS CloudTrail, Virtual Private Cloud (Amazon VPC) Flow Logs, Amazon CloudWatch Events, AWS Lambda, Amazon Inspector, Amazon GuardDuty, and AWS Security Hub.

Building incident response playbooks for AWS

In this workshop, learn how to develop incident response playbooks. Explore the incident response lifecycle, including preparation, detection and analysis, containment, eradication and recovery, and post-incident activity. To get the most out of this workshop, you should have advanced experience with AWS services and responsibilities aligned with incident response frameworks such as NIST SP 800-61 R2.

This list is representative of the security workshops created in 2021 to help customers on their journey in AWS. If you’d like to find more workshops, please go to AWS Workshops and select Security in the top navigation bar, or you can also check out AWS Security Workshops for a subset of workshops curated by AWS Security Specialists. We hope you enjoy these workshops!

 
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Author

Temi Adebambo

Temi leads the Security and Network Solutions Architecture team at AWS. His team is focused on working with customers on cloud migration and modernization, cybersecurity strategy, architecture best practices, and innovation in the cloud. Before AWS, he spent over 14 years as a consultant, advising CISOs and security leaders.

Scaling Ad Verification with Machine Learning and AWS Inferentia

Post Syndicated from Julien Simon original https://aws.amazon.com/blogs/aws/scaling-ad-verification-with-machine-learning-and-aws-inferentia/

Amazon Advertising helps companies build their brand and connect with shoppers, through ads shown both within and beyond Amazon’s store, including websites, apps, and streaming TV content in more than 15 countries. Businesses or brands of all sizes including registered sellers, vendors, book vendors, Kindle Direct Publishing (KDP) authors, app developers, and agencies on Amazon marketplaces can upload their own ad creatives, which can include images, video, audio, and of course products sold on Amazon. To promote an accurate, safe, and pleasant shopping experience, these ads must comply with content guidelines.

Here’s a simple example. Can you figure out why two of the following ads would not be compliant?

Amazon Ads

The ad in the center doesn’t feature the product in context. It also shows the same product multiple times. The ad on the right looks much better, but it contains text, which is not allowed for this ad format.

New ad creatives come in many sizes, shapes, and languages, and at very large scale. Assuming it would even be possible, verifying them manually would be a complex, slow, and error-prone process. Machine learning (ML) to the rescue!

Using Machine Learning to Verify Ad Creatives
Each ad must be evaluated against many rules, which no single model could reasonably learn. In fact, it takes many models to check ad properties, for example:

  • Media-specific models that analyze images, video, audio, and text that describe the advertised products.
  • Content-specific models that detect headlines, text, backgrounds, and objects.
  • Language-specific models that validate syntax and grammar, and flag unapproved language.

Some of these capabilities are readily available in AWS AI services. For example, Amazon Advertising teams use Amazon Rekognition to extract metadata information from images and videos.

Other capabilities require custom models trained on in-house datasets. For this purpose, Amazon teams labeled large ad datasets with Amazon SageMaker Ground Truth, using a combination of manual labeling, and automatic labeling with active learning. Using these datasets, teams then used Amazon SageMaker to train models, and deploy them automatically on real-time prediction endpoints with the AWS Cloud Development Kit (AWS CDK) and Amazon SageMaker Pipelines.

When a business uploads a new ad, relevant models are invoked simultaneously to process specific ad components, extract signals, and output a quality score. All scores are then consolidated, and sent to a final model that predicts whether the ad should be manually reviewed.

Thanks to this process, most new ads can be verified and published automatically, which means businesses can quickly promote their brand and products, and Amazon can maintain a high-quality shopping experience.

However, faced with a growing number of more complex models, Amazon Advertising teams started to look for a solution that could increase prediction throughput while reducing costs. They found it in AWS Inferentia.

What is AWS Inferentia?
Available in Amazon EC2 Inf1 instances, AWS Inferentia is a custom chip built by AWS to accelerate ML inference workloads, and optimize their cost. Each AWS Inferentia chip contains four NeuronCores. Each NeuronCore implements a high-performance systolic array matrix multiply engine, which massively speeds up typical deep learning operations such as convolution and transformers. NeuronCores are also equipped with a large on-chip cache, which helps to cut down on external memory accesses, reduce latency, and increase throughput.

Thanks to AWS Neuron, a software development kit for ML inference, AWS Inferentia can be used natively from ML frameworks like TensorFlow, PyTorch, and Apache MXNet. It consists of a compiler, runtime, and profiling tools that enable you to run high-performance and low latency inference. For many trained models, compilation is a one-liner with the Neuron SDK, not requiring any additional application code changes. The result is a high performance inference deployment, that can easily scale while keeping costs under control. You’ll find many examples in the Neuron documentation. Alternatively, thanks to Amazon SageMaker Neo, you can also compile models directly in SageMaker.

Scaling Ad Verification with AWS Inferentia
Amazon Advertising teams started compiling their models for Inferentia, and deploying them on SageMaker endpoints powered by Inf1 instances. They compared the Inf1 endpoints to the GPU endpoints they had been using so far. They found that large deep learning models like BERT run more effectively on Inferentia, which decreases latency by 30%, and reduces costs by 71%. A few months ago, ML teams working on Amazon Alexa came to the same conclusions.

What about prediction quality? GPU models are typically trained with single-precision floating-point data (FP32). Inferentia uses the shorter FP16, BF16, and INT8 data types, which can create slight differences in predicted output. Running both GPU and Inferentia models in parallel, teams analyzed probability distributions, tweaked prediction thresholds for their Inferentia models, and made sure that these models would predict ads just like GPU models did. You can learn more about these techniques in the Performance Tuning section of the documentation.

With these final adjustments out of the way, the Amazon Advertising teams started phasing out GPU models. All text data is now predicted on Inferentia, and the migration of computer vision pipelines is in progress.

AWS Customers Are Successful with AWS Inferentia
In addition to Amazon teams, customers also report very nice results on scaling and optimizing their ML workloads with Inferentia.

Binghui Ouyang, Senior Data Scientist at Autodesk: “Autodesk is advancing the cognitive technology of our AI-powered virtual assistant, Autodesk Virtual Agent (AVA) by using Inferentia. AVA answers over 100,000 customer questions per month by applying natural language understanding (NLU) and deep learning techniques to extract the context, intent, and meaning behind inquiries. Piloting Inferentia, we are able to obtain a 4.9x higher throughput over G4dn for our NLU models, and look forward to running more workloads on the Inferentia-based Inf1 instances.”

Paul Fryzel, Principal Engineer, AI Infrastructure at Condé Nast: “Condé Nast’s global portfolio encompasses over 20 leading media brands, including Wired, Vogue, and Vanity Fair. Within a few weeks, our team was able to integrate our recommendation engine with AWS Inferentia chips. This union enables multiple runtime optimizations for state-of-the-art natural language models on SageMaker’s Inf1 instances. As a result, we observed a 72% reduction in cost than the previously deployed GPU instances.”

Getting Started
You can get started with Inferentia and Inf1 instances today, either on Amazon SageMaker or with the Neuron SDK. This self-paced workshop walks you through both options.

Give it a try, and let us know what you think. As always, we look forward to your feedback. You can send it through your usual AWS Support contacts, post it on the AWS Forum for SageMaker, or on the Neuron SDK Github repository.

– Julien