Post Syndicated from Elise Chahine original https://aws.amazon.com/blogs/architecture/author-spotlight-vittorio-denti-machine-learning-engineer-at-amazon/

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

I’m Vittorio, and I work as a Machine Learning Engineer at Amazon. My journey in the engineering world began when I started studying Computer Engineering at Politecnico di Milano during my bachelor’s degree. It continued during the master’s degree, when I started focusing on data and artificial intelligence. During my master’s, I spent one year in Stockholm, at the KTH Royal Institute of Technology, where I studied machine learning and deep learning. I joined Amazon Web Services (AWS) in 2020 through Tech U, a graduate program for technical roles in AWS, where I started working in the area of cloud architecture. During my time in AWS, I have had the opportunity to become familiar with software architectures, the AWS cloud, and develop system design skills for distributed systems.

At AWS, I was able to grow from a technical standpoint by learning new technologies and architectural patterns for distributed systems. I’ve also had the opportunity to grow my personal perspective. I found amazing mentors: people with years of experience that were always available to talk with me, compare ideas, and explain complex topics. When I was studying at university, I developed a vertical set of technical skills, which I’m still using every day at work, and I’m now able to boost those skills by taking advantage of the pragmatism and mindset acquired through mentoring.

With AWS, I was mainly working on cloud architectures for customers but also on internal projects and blog posts. I had the opportunity to support customers in designing their machine learning architectures for model training and for serving real-time traffic, as well as working on different challenges like query optimization for databases or asynchronous communication patterns for microservices. This breadth of scenarios was fundamental to build horizontal skills outside of the machine learning domain and learning how to navigate unexplored areas.

At the end of 2022, I moved from AWS to Amazon, where I started working as a Machine Learning Engineer on Amazon Sponsored Display, a self-service solution from Amazon Ads. In this new role, I work as an engineer developing and productionizing some of the machine learning algorithms used in advertising. I really like this role because there are many opportunities to explore and build. Also, working on a product and understanding the long-term impact of architectural and engineering decisions is extremely valuable to grow as a professional.

By working at Amazon’s scale, there are many factors to consider before coming up with a solution. All of this is an amazing opportunity to learn more, experiment, and satisfy my curiosity. As you have understood by now, I always like facing new challenges, pushing myself out of the comfort zone, and being able to learn about new areas and technologies.

Some of my favorite moments so far are related to public and internal conferences that I have attended both with AWS and Amazon. In 2021, I had the opportunity to go to re:Invent 2021 in Las Vegas—the annual AWS cloud conference. In 2023, I went to Madrid for DevCon, the internal engineering conference for Amazon employees. These experiences have been extremely valuable to discover more about new technical content as well as for networking and learning from peers.

Vittorio (on the right) with his colleague Darren (on the left) at re:Invent 2021, supporting AWS Game Day

What’s on my mind

Machine learning is a growing area: it’s still fairly new and there is a lot of innovation happening. Engineers work to find the “optimal” way for running machine learning in production and balance all the different trade-offs that consistently arise. Machine learning engineering faces the complexities of software engineering and adds extra challenges deriving from working with data and models. It’s not only about developing software! We also have to work to explore, monitor, and (in some cases) build datasets and training models, plus productionize them. There are two main entities to consider (datasets and models) that do not usually appear in software engineering, and this brings extra complexity.

Some stimulating challenges are about increasing model performance without impacting latency, working with unbalanced datasets, and detecting model or data drift automatically and solving for it. This is just a set of fascinating engineering areas to explore for machine learning. While for some of these problems, the industry already has some answers or directions, the question is: how can we do this at scale and create mature and reliable solutions? In the next few years I would like to answer these questions. For instance, car manufacturers have well-established supply chains and mature manufacturing processes. To the best of my knowledge, we don’t have something comparable in the area of machine learning engineering… yet! We have a set of excellent artisans working at scale, good processes to ensure quality (like code reviews and testing), but the risk of failures or inefficiencies is still high because of the stochastic nature of the domain.

Other topics I’m passionate about are machine learning science and software architecture. I like reading research papers, understanding the latest innovations, and learn not only from their contributions, but also from the processes that the authors followed to achieve those results. There are many opportunities to transfer knowledge from other domains to machine learning engineering, and I’m always inquiring to learn more about science and engineering to run the latest innovations in production.

Favorite blog posts and resources

Design a data mesh with event streaming for real-time recommendations on AWS

Data architectures were mainly designed around technologies rather than business domains in the past. This changed in 2019, when Zhamak Dehghani introduced the data mesh. Data mesh is an application of the Domain-Driven-Design (DDD) principles to data architectures: data is organized into data domains, and the data is the product that the team owns and offers for consumption.

Designing a data architecture for working with machine learning at scale requires careful thought. You may have different data sources, consumers, and data coming from different areas of the organization. Also, your organization may grow and evolve throughout time, so you may have some domains coming up and others disappearing. In 2022, I published an AWS Big Data blog on designing a data mesh architecture with event streaming for machine learning.

In the blog, we design a data mesh with event streaming for a scenario that requires real-time music recommendations on AWS. Because ML applications may have multiple types of input data, we propose a solution that works both for data at rest as well as real-time streaming.

The complete data mesh with event-streaming architecture uses two different data planes: one is dedicated for sharing data at rest (blue), the other one is for data in motion (red)

The Let’s Architect! series on the Architecture Blog

Let’s Architect! is an editorial initiative that publishes a bi-weekly post on a specific topic since January 2022. Some of the most recent topics include event-driven architectures, microservices, data mesh and machine learning. We gather four or five different AWS content pieces that provide a perspective on why that content is relevant. Content can be an AWS blog post, a whitepaper, any hands-on workshop with architectural patterns, or a video. We focus on architectural content that can be valuable for software architects as well as software engineers willing to learn more about system design and distributed systems.

This is not only a way to learn and stay familiar with different technical areas but also to contribute and share resources with the community. The initiative has had a strong influence, and we now have customers and even many of our colleagues waiting for the upcoming posts. I have been working on this initiative with Luca Mezzalira, Zamira Jaupaj, Federica Ciuffo and Laura Hyatt, and with the support of the AWS Architecture Blog.

The Let’s Architect! series

Amazon Builder’s Library

One of most inspiring resources to learn from is the Amazon Builder’s Library. Its mission is to share with customers our experience of building secure and highly available services, and successful durable businesses, at Amazon and AWS.

I think it’s extremely valuable because we can learn directly from the Amazon’s experience of running distributed systems at scale. It’s not only about the content itself or how they solved a specific challenge, but also about learning how they were able to formalize a problem and the journey that they followed to achieve the solution. Also, if you wonder how some AWS services are designed under the hood… you can learn about typical patterns used to implement them by navigating through the resources in the library.

What you’ll find on the Amazon Builder’s Library

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

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

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.

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

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

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

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!

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.