Post Syndicated from Patrick Kennedy original https://www.servethehome.com/the-end-of-another-sth-era-the-austin-texas-studio-is-in-shambles/
Today marks the end of another STH era as the Austin Texas studio went from production to shambles, to boxes en route to a better future
The post The End of Another STH Era The Austin Texas Studio is in Shambles appeared first on ServeTheHome.
Post Syndicated from Donnie Prakoso original https://aws.amazon.com/blogs/aws/aws-weekly-roundup-amazon-ec2-m2-pro-mac-amazon-coretto-21-amazon-cloudwatch-synthetics-and-more-sept-25-2023/
This week, I’m in Jakarta to support AWS User Group Indonesia and AWS Cloud Day Indonesia. Yesterday, I attended a community event – a collaboration between AWS User Group Indonesia and Hacktiv8 with “Innovating Yourself as Early-Stage Developers” as the main theme. We had a blast and I had a wonderful time connecting with speakers and developers.
Next up, AWS Cloud Day Indonesia. I’ll be at the Developer Lounge, come and say hi!
Last Week’s Launches
Here are some of the launches that caught my attention last week:
Add Your Swift Packages to AWS CodeArtifact – In this article, Seb describes how Swift developers who write code for Apple platforms (iOS, iPadOS, macOS, tvOS, watchOS, visionOS or Swift) applications running on the server side can use AWS CodeArtifact to securely store and retrieve their package dependencies. What I really like is how developers can still use standard developer tools, such as Xcode, xcodebuild, and the Swift Package Manager (the swift package command) to interact with AWS CodeArtifact and facilitate integration into the development workflow.
Amazon EC2 M2 Pro Mac Instances Built on Apple Silicon M2 Pro Mac Mini Computers – Channy wrote how developers can use Amazon EC2 M2 Pro Mac to run memory intensive builds and test workloads, modernize their CI/CD and accelerate their product time to market. With 2x RAM, 1.5x CPU cores, and more than 2x GPU cores compared to EC2 M1 Mac instances, Apple developers can now run more tests in parallel using multiple Xcode simulators.
Synthetics Python runtime version 2.0 for Amazon CloudWatch Synthetics – With Amazon CloudWatch Synthetics, you can continually verify your customer experience and discover issues before your customers do by creating canaries. Canaries are configurable scripts that run on a schedule, to monitor your endpoints and APIs. In this announcement, you can use Synthetics Python runtime version syn-python-selenium-2.0 to create canaries.
Amazon QuickSight adds new layout and sparkline to KPI visual – Effortlessly design visually appealing KPIs on Amazon Quicksight with these new updates. Quicksight introduces a range of enhancements with user-friendly experience, including templated KPI layouts, support for sparklines, improvements in conditional formatting, and a revamped format pane.
Amazon Location Services announces a price reduction of up to 75 percent for tracking and geofencing – Amazon Location Service just announced a four-tiered pricing model for tracking and geofencing to help you scale and cost-effectively run your operations and business. If you use geofencing, you might see your bill decrease by 20 percent to 70 percent, and tracking by up to 75 percent.
Amazon Corretto 21 is now generally available – Happy news for Java developers. Amazon Coretto 21 with long term support (LTS) is generally available for Linux, Windows and macOS.
AWS App Runner launches improvements for Auto-Scaling configuration management – Now you can use new APIs and parameters for AWS App Runner service to manage your App Runner services and define your auto-scaling configuration (ASC). For example, setting default ASC, update existing ASC and list all App Runner services that are using an ASC resource.
Amazon SNS message data protection with redaction or masking – With Amazon SNS, now you can discover and protect certain types of personally identifiable information (PII) and protected health information (PHI). You can define your data protection policies and SNS will scan messages in real-time for sensitive data.
Upcoming AWS and Community Events
Check your calendars and sign up for these AWS events:
And let’s learn from our fellow builders and join AWS Community Days:
Visit the landing page to check out all the upcoming AWS Community Days.
Happy building!
— Donnie
This post is part of our Weekly Roundup series. Check back each week for a quick roundup of interesting news and announcements from AWS!
Post Syndicated from Channy Yun original https://aws.amazon.com/blogs/aws/new-amazon-ec2-m2-pro-mac-instances-built-on-apple-silicon-m2-pro-mac-mini-computers/
Today, we are announcing the general availability of Amazon EC2 M2 Pro Mac instances. These instances deliver up to 35 percent faster performance over the existing M1 Mac instances when building and testing applications for Apple platforms.
New EC2 M2 Pro Mac instances are powered by Apple M2 Pro Mac Mini computers featuring 12 core CPU, 19 core GPU, 32 GiB of memory, and 16 core Apple Neural Engine and uniquely enabled by the AWS Nitro System through high-speed Thunderbolt connections, offering these Mac mini computers as fully integrated and managed compute instances with up to 10 Gbps of Amazon VPC network bandwidth and up to 8 Gbps of Amazon EBS storage bandwidth. EC2 M2 Pro Mac instances support macOS Ventura (version 13.2 or later) as AMIs.
A Story of EC2 Mac Instances
When Jeff Barr first introduced Amazon EC2 Mac Instances in 2020, customers were surprised to be able to run macOS on Amazon EC2 to build, test, package, and sign applications developed with Xcode applications for the Apple platform, including macOS, iOS, iPadOS, tvOS, and watchOS.
In his keynote in AWS re:Invent 2020, Peter DeSantis revealed the secret to build EC2 Mac instances powered by the AWS Nitro System, which makes it possible to offer Apple Mac mini computers as fully integrated and managed compute instances with Amazon VPC networking and Amazon EBS storage, just like any other EC2 instances.
“We did not need to make any changes to the Mac hardware. We simply connected a Nitro controller via the Mac’s Thunderbolt connection. When you launch a Mac instance, your Mac-compatible Amazon Machine Image (AMI) runs directly on the Mac Mini, with no hypervisor. The Nitro controller sets up the instance and provides secure access to the network and any storage attached. And that Mac Mini can now natively use any AWS service.”
In July 2022, we introduced Amazon EC2 M1 Mac Instances built around the Apple-designed M1 System on Chip (SoC). Developers building for iPhone, iPad, Apple Watch, and Apple TV applications can choose either x86-based EC2 Mac instances or Arm-based EC2 M1 instances. If you want to re-architect your apps to natively support Macs with Apple Silicon using EC2 M1 instances, you can build and test your apps to deliver up to 60 percent better price performance over the EC2 Mac instances for iPhone and Mac app build workloads with all the benefits of AWS.
Many customers take advantage of EC2 Mac instances to deliver a complete end-to-end build pipeline on macOS on AWS. With EC2 Mac instances, they can scale their iOS build fleet; easily use custom macOS environments with AMIs; and debug any build or test failures with fully reproducible macOS environments.
Customers have reported up to 4x reduction in build times, up to 3x increase in parallel builds, up to 80 percent reduction in machine-related build failures, and up to 50 percent reduction in fleet size. They can continue to prioritize their time on innovating products and features while reducing the tedious effort required to manage on-premises macOS infrastructure.
To accelerate this innovation, EC2 Mac instances recently began to support replacing root volumes on a running EC2 Mac instance, enabling you to restore the root volume of an EC2 Mac instance to its initial launch state or to a specific snapshot, without requiring you to stop or terminate the instance.
You can also use in-place operating system updates from within the guest environment on EC2 M1 Mac instances to a specific or latest macOS version, including the beta version, by registering your instances with the Apple Developer Program. Developers can now integrate the latest macOS features into their applications and test existing applications for compatibility before public macOS releases.
Getting Started with EC2 M2 Pro Instances
As with other EC2 Mac instances, EC2 M2 Pro Mac instances also support Dedicated Host tenancy with a minimum host allocation duration of 24 hours to align with macOS licensing.
To get started, you should allocate a Mac-dedicated host, a physical server fully dedicated for your own use in your AWS account. After the host is allocated, you can launch, stop, and start your own macOS environment as one instance on that host for one dedicated host.
After the host is allocated, you can start an EC2 Mac instance on it. The procedure is no different from starting any EC2 instance type. Choose your macOS AMI version and select the mac2-m2pro.metal instance type in the Application and OS Images section.
In the Advanced details section, select Dedicated host in Tenancy and a dedicated host you just created in Tenancy host ID.
When you use EC2 Mac instances for the first time, you can use SSH to connect to the newly launched instance as usual or enable Apple Remote Desktop and start a VNC session to the EC2 instance. To learn more, see Sebastien’s series of articles to launch and connect your Mac instance.
When you no longer need the Mac dedicated host, you can terminate your running Mac instance and release the underlying host. Note again that after being allocated, a Mac dedicated host can only be released after 24 hours to align with Apple’s macOS licensing.
Now Available
Amazon EC2 M2 Pro Mac instances are available in the US West (Oregon) and US East (Ohio) AWS Regions, with additional regions coming soon.
To learn more or get started, see Amazon EC2 Mac Instances or visit the EC2 Mac documentation. You can send feedback to AWS re:Post for EC2 or through your usual AWS Support contacts.
— Channy
Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/new-nvme-reservations-for-amazon-elastic-block-store-io2-volumes/
Amazon Elastic Block Store (Amazon EBS) io2 and io2 Block Express volumes now support storage fencing using NVMe reservations. As I learned while writing this post, storage fencing is used to regulate access to storage for a compute or database cluster, ensuring that just one host in the cluster has permission to write to the volume at any given time. For example, you can set up SQL Server Failover Cluster Instances (FCI) and get higher application availability within a single Availability Zone without the need for database replication.
As a quick refresher, io2 Block Express volumes are designed to meet the needs of the most demanding I/O-intensive applications running on Nitro-based Amazon Elastic Compute Cloud (Amazon EC2) instances. Volumes can be as big as 64 TiB, and deliver SAN-like performance with up to 256,000 IOPS/volume and 4,000 MB/second of throughput, all with 99.999% durability and sub-millisecond latency. The volumes support other advanced EBS features including encryption and Multi-Attach, and can be reprovisioned online without downtime. To learn more, you can read Amazon EBS io2 Block Express Volumes with Amazon EC2 R5b Instances Are Now Generally Available.
Using Reservations
To make use of reservations, you simply create an io2 volume with Multi-Attach enabled, and then attach it to one or more Nitro-based EC2 instances (see Provisioned IOPS Volumes for a full list of supported instance types):
If you have existing io2 Block Express volumes, you can enable reservations by detaching the volumes from all of the EC2 instances, and then reattaching them. Reservations will be enabled as soon as you make the first attachment. If you are running Windows Server using AMIs data-stamped 2023.08 or earlier you will need to install the aws_multi_attach driver as described in AWS NVMe Drivers for Windows Instances.
Things to Know
Here are a couple of things to keep in mind regarding NVMe reservations:
Operating System Support – You can use NVMe reservations with Windows Server (2012 R2 and above, 2016, 2019, and 2022), SUSE SLES 12 SP3 and above, RHEL 8.3 and above, and Amazon Linux 2 & later (read NVMe reservations to learn more).
Cluster and Volume Managers – Windows Server Failover Clustering is supported; we are currently working to qualify other cluster and volume managers.
Charges – There are no additional charges for this feature. Each reservation counts as an I/O operation.
— Jeff;
Post Syndicated from Patrick Kennedy original https://www.servethehome.com/intel-announces-288-e-core-sierra-forest-variant-at-innovation-2023/
At Intel Innovation 2023 Intel formally disclosed that it will have a 288 core Sierra Forest Xeon with all E-cores for cloud-native servers
The post Intel Announces 288 E-Core Sierra Forest Variant at Innovation 2023 appeared first on ServeTheHome.
Post Syndicated from Danilo Poccia original https://aws.amazon.com/blogs/aws/aws-weekly-roundup-c7i-instances-knowledge-base-for-amazon-bedrock-and-more-sept-18-2023/
While daylight is getting shorter in the Northern hemisphere, we’ve got two new EC2 instance types optimized for compute and memory and many new capabilities for other services. Last week there was also the EMEA AWS Heroes Summit in Munich, an amazing day full of insights and passion. Here’s a nice picture of the participants!
Last Week’s Launches
Here are some of the launches that caught my attention last week:
C7i Instances – Powered by custom 4th Generation Intel Xeon Scalable processors (code-named Sapphire Rapids) and available only on AWS, these compute-optimized instances offer up to 15 percent better performance over comparable x86-based Intel processors used by other cloud providers. A great choice for all compute-intensive workloads, such as batch processing, distributed analytics, high performance computing (HPC), ad serving, highly scalable multiplayer gaming, and video encoding, C7i instances deliver up to 15 percent better price performance versus C6i instances.
| vCPUs |
Memory (GiB) |
Network Bandwidth |
EBS Bandwidth |
|
| c7i.large | 2 | 4 | Up to 12.5 Gbps | Up to 10 Gbps |
| c7i.xlarge | 4 | 8 | Up to 12.5 Gbps | Up to 10 Gbps |
| c7i.2xlarge | 8 | 16 | Up to 12.5 Gbps | Up to 10 Gbps |
| c7i.4xlarge | 16 | 32 | Up to 12.5 Gbps | Up to 10 Gbps |
| c7i.8xlarge | 32 | 64 | 12.5 Gbps | 10 Gbps |
| c7i.12xlarge | 48 | 96 | 18.75 Gbps | 15 Gbps |
| c7i.16xlarge | 64 | 128 | 25 Gbps | 20 Gbps |
| c7i.24xlarge | 96 | 192 | 37.5 Gbps | 30 Gbps |
| c7i.48xlarge | 192 | 384 | 50 Gbps | 40 Gbps |
| c7i.metal-24xl* | 96 | 192 | 37.5 Gbps | 30 Gbps |
| c7i.metal-48xl* | 192 | 384 | 50 Gbps | 40 Gbps |
*Bare metal instances are coming soon.
To facilitate efficient offload and acceleration of data operations and optimize performance for workloads, C7i instances support built-in Intel accelerators such as Data Streaming Accelerator (DSA), In-Memory Analytics Accelerator (IAA), QuickAssist Technology (QAT), and the new Intel Advanced Matrix Extensions (AMX) that accelerate matrix multiplication operations for applications such as CPU-based ML.
EC2 R7a Instances – Powered by 4th Gen AMD EPYC processors (code-named Genoa) with a maximum frequency of 3.7 GHz, these memory optimized instances deliver up to 50 percent higher performance compared to R6a instances and are ideal for high performance, memory-intensive workloads such as SQL and NoSQL databases, distributed web scale in-memory caches, in-memory databases, real-time big data analytics, and Electronic Design Automation (EDA) applications. Read more in Channy’s blog post.
Knowledge Base for Amazon Bedrock (Preview) – To deliver more relevant and contextual responses, Bedrock can now manage both the ingestion workflow and runtime orchestration to connect your organization’s private data sources to foundation models (FMs) and enable retrieval augmented generation (RAG) for your generative AI applications. To store data, you can choose from a range of vector databases including the vector engine for Amazon OpenSearch Serverless, Pinecone, and Redis Enterprise Cloud. Read more in Antje’s blog post.
High Query Rates with Amazon OpenSearch Serverless Extends Auto-Scaling – You can now rely on OpenSearch Serverless to help manage unpredictable surges in your search and query traffic and efficiently handle tens of thousands of query transactions per minute.
Amazon EMR on EKS – You can now improve resource utilization and simplify infrastructure management by using EMR to run Apache Flink (Public Preview) on the same Amazon EKS cluster as your other applications. Also, to provide a secure, stable, high-performance environment with the latest enhancements such as kernel, toolchain, glibc, and openssl, you can now use Amazon Linux 2023 as the operating system together with Java 17 as Java runtime to run your workloads with Amazon EMR on EKS.
Amazon Connect – Amazon Connect Cases now supports uploading attachments to a case, enabling agents to have the information they need at their fingertips in order to resolve cases, and displaying the author name for comments that are written on cases, to more easily track who contributed to the resolution of the case and collaborate more effectively. To receive near real-time stream of contact (voice calls, chat, and task) events (for example, call is queued) in a contact center, you can now subscribe to the new Contact Data Updated event.
Custom Notifications for AWS Chatbot – This lets you include additional information, such as number of orders or current throttling limits, when monitoring the health and performance of your AWS applications in Microsoft Teams and Slack channels.
AWS IAM Identity Center Session Duration Increased Up to 90 Days – You now have more flexibility based on your security context and desired end-user experience. Previously, the maximum duration was 7 days. The default session duration continues to be 8 hours and existing customer-configured session limits will remain unchanged.
Full Support of GraphQL APIs in Amplify Studio – You can now generate forms connected to your API, manage records in your API with Data Manager, and create data-bound Figma to React components for GraphQL APIs created with Amplify Studio or Amplify CLI. Previously, these data-powered features were only available when using Amplify DataStore.
Nested Filtering for AWS AppSync WebSockets-Based Subscriptions – You now have additional control over how data should be published out to connected clients by using filtering rules that allow you to target specific sub-items within the published data. Read more in this blog post.
API Gateway Console Refresh – There are usability improvements to REST and WebSocket API workflows (now visually aligned with the console experience of HTTP APIs) and dark mode support. Accessibility enhancements also help to better integrate with assistive technology.
Override Retention Capability for AWS Supply Chain – Manual forecast adjustments made by a demand planner are now automatically saved and reapplied from one planning cycle to the next.
Other AWS News
Serverless Development on AWS – AWS Hero Sheen Brisals and his colleague Luke Hedger revealed that they are sharing their expertise with a book that helps build enterprise-scale serverless solutions on AWS. The book outlines the adoption requirements in terms of people, mindset, and workloads, and details architectural patterns, security, and data best practices for building serverless applications.
More posts from AWS blogs – Here are a few posts from some of the other AWS and cloud blogs that I follow:
Upcoming AWS Events
Check your calendars and sign up for these AWS events:
AWS On Tour, Sept. 18-Oct. 6 – The AWS Developer Relations team is boarding a bus and traveling across European cities (London, Paris, Brussels, Amsterdam, Frankfurt, Zurich, Milan, Lyon, and Barcelona) to share their experiences and help you improve productivity.
AWS Global Summits, Sept. 26 – The last in-person AWS Summit of the year will be held in Johannesburg on Sept. 26.
CDK Day, Sept. 29 – Learn more at the website about this community-led fully virtual event with tracks in English and Spanish about CDK and related projects.
AWS re:Invent, Nov. 27-Dec. 1 – Browsing the session catalog is a nice way to start planning your re:Invent. Join us to hear the latest from AWS, learn from experts, and connect with the global cloud community.
AWS Community Days – Join a community-led conference run by AWS user group leaders in your region: Netherlands (Sept. 20), Spain (Sept. 23), Zimbabwe (Sept. 30), Peru (Sept. 30), Chile (Sept. 30), and Bulgaria (Oct. 7). Visit the landing page to check out all the upcoming AWS Community Days.
You can browse all upcoming AWS-led in-person and virtual events, and developer-focused events such as AWS DevDay.
— Danilo
This post is part of our Weekly Roundup series. Check back each week for a quick roundup of interesting news and announcements from AWS!
Post Syndicated from Channy Yun original https://aws.amazon.com/blogs/aws/new-amazon-ec2-r7a-instances-powered-by-4th-gen-amd-epyc-processors-for-memory-optimized-workloads/
We launched the memory optimized Amazon EC2 R6a instances in July 2022 powered by 3rd Gen AMD EPYC (Milan) processors, running at frequencies up to 3.6 GHz. Many customers who run workloads that are dependent on x86 instructions, such as SAP, are looking for ways to optimize their cloud utilization. They’re taking advantage of the compute choice that EC2 offers.
Today, we’re announcing the general availability of new memory optimized Amazon EC2 R7a instances powered by 4th Gen AMD EPYC (Genoa) processors with a maximum frequency of 3.7 GHz, which offer up to 50 percent higher performance compared to the previous generation instances. You can use this increased performance to process data faster, consolidate workloads, and lower the cost of ownership.
R7a instances also support AVX-512, Vector Neural Network Instructions (VNNI), and brain floating point (bfloat16). These instances feature Double Data Rate 5 (DDR5) memory, which enables high-speed access to data in-memory, and deliver 2.25 times more memory bandwidth compared to R6a instances for lower latency. Moreover, these instances support always-on memory encryption using AMD secure memory encryption (SME).
These instances are SAP-certified and ideal for high performance, memory-intensive workloads, such as SQL and NoSQL databases, distributed web scale in-memory caches, in-memory databases, real-time big data analytics, and Electronic Design Automation (EDA) applications.
R7a instances feature sizes of up to 192 vCPUs with 1536 GiB RAM. Here are the detailed specs:
| Name | vCPUs | Memory (GiB) | Network Bandwidth (Gbps) | EBS Bandwidth (Gbps) |
| r7a.medium | 1 | 8 | Up to 12.5 | Up to 10 |
| r7a.large | 2 | 16 | Up to 12.5 | Up to 10 |
| r7a.xlarge | 4 | 32 | Up to 12.5 | Up to 10 |
| r7a.2xlarge | 8 | 64 | Up to 12.5 | Up to 10 |
| r7a.4xlarge | 16 | 128 | Up to 12.5 | Up to 10 |
| r7a.8xlarge | 32 | 256 | 12.5 | 10 |
| r7a.12xlarge | 48 | 384 | 18.75 | 15 |
| r7a.16xlarge | 64 | 512 | 25 | 20 |
| r7a.24xlarge | 96 | 768 | 37.5 | 30 |
| r7a.32xlarge | 128 | 1024 | 50 | 40 |
| r7a.48xlarge | 192 | 1536 | 50 | 40 |
R7a instances have up to 50 Gbps enhanced networking and 40 Gbps EBS bandwidth, which is similar to R6a instances. You have a new medium instance size, which you can use to right-size your workloads more accurately, offering 1 vCPUs, 8 GiB. Additionally, with R7a instances you can attach up to 128 EBS volumes to an instance compared to up to 28 EBS volume attachments with R6a instances. R7a instances support AES-256 compared to AES-128 in R6a instances for enhanced security.
R7a instances are built on the AWS Nitro System and support Elastic Fabric Adapter (EFA) for workloads that benefit from lower network latency and highly scalable inter-node communication, such as high-performance computing and video processing.
Now Available
Amazon EC2 R7a instances are now available in AWS Regions: US East (Ohio), US East (N. Virginia), US West (Oregon), and EU (Ireland). As usual with Amazon EC2, you only pay for what you use. For more information, see the Amazon EC2 pricing page.
To learn more, visit the EC2 R7a instances page, and AWS/AMD partner page. You can send feedback to [email protected], AWS re:Post for EC2, or through your usual AWS Support contacts.
— Channy
Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/aws-weekly-roundup-r7iz-instances-amazon-connect-cloudwatch-logs-and-lots-more-sept-11-2023/
Looks like it is my turn once again to write the AWS Weekly Roundup. I wrote and published the first one on April 16, 2012 — just 4,165 short day ago!
Last Week’s Launches
Here are some of the launches that caught my eye last week:
R7iz Instances – Optimized for high CPU performance and designed for your memory-intensive workloads, these instances are powered by the fastest 4th Generation Intel Xeon Scalable-based (Sapphire Rapids) instances in the cloud. They are available in eight sizes, with 2 to 128 vCPUs and 16 to 1024 GiB of memory, along with generous allocations of network and EBS bandwidth:
| vCPUs |
Memory (GiB) |
Network Bandwidth |
EBS Bandwidth |
|
| r7iz.large | 2 | 16 | Up to 12.5 Gbps | Up to 10 Gbps |
| r7iz.xlarge | 4 | 32 | Up to 12.5 Gbps | Up to 10 Gbps |
| r7iz.2xlarge | 8 | 64 | Up to 12.5 Gbps | Up to 10 Gbps |
| r7iz.4xlarge | 16 | 128 | Up to 12.5 Gbps | Up to 10 Gbps |
| r7iz.8xlarge | 32 | 256 | 12.5 Gbps | 10 Gbps |
| r7iz.12xlarge | 48 | 384 | 25 Gbps | 19 Gbps |
| r7iz.16xlarge | 64 | 512 | 25 Gbps | 20 Gbps |
| r7iz.32xlarge | 128 | 1024 | 50 Gbps | 40 Gbps |
As Veliswa shared in her post, the R7iz instances also include four built-in accelerators, and are available in two AWS regions.
Amazon Connect APIs for View Resources – A new set of View APIs allows you to programmatically create and manage the view resources (UI templates) used in the step-by-step guides that are displayed in the agent’s UI.
Daily Disbursements to Marketplace Sellers – Sellers can now set disbursement preferences and opt-in to receiving outstanding balances on a daily basis for increased flexibility, including the ability to match payments to existing accounting processes.
Enhanced Error Handling for AWS Step Functions – You can now construct detailed error messages in Step Functions Fail states, and you can set a maximum limit on retry intervals.
Amazon CloudWatch Logs RegEx Filtering – You can now use regular expressions in your Amazon CloudWatch Logs filter patterns. You can, for example, define a single filter that matches multiple IP subnets or HTTP status codes instead of having to use multiple filters, as was previously the case. Each filter pattern can have up to two regular expression patterns.
Amazon SageMaker – There’s a new (and quick) Studio setup experience, support for Multi Model Endpoints for PyTorch, and the ability to use SageMaker’s geospatial capabilities on GPU-based instances when using Notebooks.
X in Y – We launched existing services and instance types in new regions:
Other AWS News
Here are some other AWS updates and news:
AWS Fundamentals – The second edition of this awesome book, AWS for the Real World, Not for Certifications, is now available. In addition to more than 400 pages that cover 16 vital AWS services, each chapter includes a detailed and attractive infographic. Here’s a small-scale sample:
More posts from AWS blogs – Here are a few posts from some of the other AWS and cloud blogs that I follow:
Upcoming AWS Events
Check your calendars and sign up for these AWS events:
AWS End User Computing Innovation Day, Sept. 13 – The one-day virtual event is designed to help IT teams tasked with providing the tools employees need to do their jobs, especially in today’s challenging times. Learn more.
AWS Global Summits, Sept. 26 – The last in-person AWS Summit will be held in Johannesburg on Sept. 26th. You can also watch on-demand videos of the latest Summit events such as Berlin, Bogotá, Paris, Seoul, Sydney, Tel Aviv, and Washington DC in the AWS YouTube channels.
CDK Day, Sept. 29 – A community-led fully virtual event with tracks in English and Spanish about CDK and related projects. Learn more at the website.
AWS re:Invent, Nov. 27-Dec. 1 – 
Ready to start planning your re:Invent? Browse the session catalog now. Join us to hear the latest from AWS, learn from experts, and connect with the global cloud community.
AWS Community Days, multiple dates 
– Join a community-led conference run by AWS user group leaders in your region: Munich (Sept. 14), Argentina (Sept. 16), Spain (Sept. 23), Peru (Sept. 30), and Chile (Sept. 30). Visit the landing page to check out all the upcoming AWS Community Days.
You can browse all upcoming AWS-led in-person and virtual events, and developer-focused events such as AWS DevDay.
— Jeff;
This post is part of our Weekly Roundup series. Check back each week for a quick roundup of interesting news and announcements from AWS!
Post Syndicated from Taylor Jacobsen original https://aws.amazon.com/blogs/aws/the-newest-aws-heroes-are-here-september-2023/
Each quarter, the AWS Heroes program recognizes technical enthusiasts who lift up the greater AWS community through various approaches. While these inspirational individuals are driven to knowledge share, they sometimes discover novel and fun ways of using technology, such as leveraging LEDs to create a magical display of holiday lights. Many are also contributing heavily in their local communities by leading user groups, bootcamps, and workshops, speaking at conferences to share solutions, and beyond.
Without further ado, we’re eager to introduce the latest cohort of Heroes to the world—let’s give them a grand welcome!
Community Hero Alex Lau is a Lead Instructor of Tecky Academy with a focus on full stack, mobile apps, and AWS technologies. Enthusiastic about teaching and sharing, Alex has been an active leader in the Hong Kong developer community since 2015. He has organized annual hackathons and founded a coding bootcamp, growing the community to over 1,000 members. Earlier this year, he took the stage at the AWS Summit Hong Kong to introduce the cutting edge of AWS technologies, and also led a session during the Hong Kong AWS GenAI Solution Day.
DevTools Hero Brian H. Hough is the founder of the Tech Stack Playbook®, a software engineering firm serving enterprise and startup clients, and a media brand with over 10k+ followers. His talks, presentations, and work have been featured by AWS, freeCodeCamp, MongoDB, and NASA. Brian has also served as a mentor for AWS’ All Builders Welcome Grant Program and other tech communities, as he enjoys lifting up the voices of builders and empowering everyone to build the future they want to see in the world. In addition, he has spoken about full-stack development, microservices, MLOps, and Infrastructure as Code at conferences including, AWS re:Invent, AWS Summit New York, Geekle’s Worldwide Software Architecture Summit, DataSaturday, and more.
Community Hero Dheeraj Choudhary is a lead engineer focused on the AWS cloud and the DevOps domain with over 10+ years of IT experience. He specializes in DevOps and build and release engineering, and software configuration management. As an AWS User Group Pune leader, he is passionate about co-organizing physical meetups and AWS Community Days. Additionally, Dheeraj is an active international speaker at AWS community events, and conducts guest lectures and workshops on AWS cloud computing at colleges and universities in Pune.
Serverless Hero Evandro Pires is a CTO who started programming when he was 12 years old. His background is in technology and entrepreneurship, and he has led important projects in internet and mobile banking, and AI and low code for SaaS solutions. Since 2020, Evandro founded and hosts a podcast dedicated to serverless called, “Sem Servidor.” Evandro is also the organizer of the first ServerlessDays in LATAM.
Community Hero Kazuki Miura is a senior engineer at Hokkaido Television Broadcasting Co., Ltd. (HTB). He is involved in the development and operation of the company’s video on demand service and e-commerce service. Kazuki continues to share his knowledge gained through the development of web services widely with the Japanese AWS User Group (JAWS-UG).
Community Hero Linda Mohamed has been navigating the tech landscape for over a decade. She is currently at EBCONT where her primary focus and specialization is in cloud technologies, IT process optimization, and agile methodologies. Linda also holds the title of Chairperson for the AWS Community DACH Support Association, and is an active member of a funding advisory board. When she is not guiding companies on their cloud journey, she is diving into AI/ML services and technologies, and sharing her insights at AWS community events and other tech platforms.
DevTools Hero Monica Colangelo is a principal cloud architect with 15-years in the IT industry. Her experience spans across operations, infrastructure, and notably, DevOps. Automation and operational excellence have always been central to her work, guiding her approach and solutions. Monica is also a regular speaker at tech conferences, sharing her expertise and insights. Furthermore, she is an advocate for diversity and emphasizes the need for a stronger representation of women in the tech sector.
Community Hero Nick Triantafillou is a cloud engineer, educator, User Group founder, and Christmas Light enthusiast. He was one of the original course instructors at the cloud education startup A Cloud Guru, having taught over 1 million students the fundamentals of AWS, and produced the world’s first AWS Certified DevOps Engineer course. He is also the founder of his local Wollongong AWS User Group, co-founder of the Sydney Serverless Meetup, and has assisted in the planning and operation of both the ServerlessConf and ServerlessDays ANZ conferences. He currently runs “NickExplainsAWS,” where he is attempting to make a video about every single AWS service on TikTok and YouTube. In addition, every December Nick brings traffic to a standstill by installing over 75,000 LEDs on his house for his serverless, AWS powered light show spectacular.
If you’d like to learn more about the new Heroes or connect with a Hero near you, please visit the AWS Heroes website or browse the AWS Heroes Content Library.
— Taylor
Post Syndicated from Irshad Buchh original https://aws.amazon.com/blogs/aws/aws-end-user-computing-innovation-day-2023-architecting-end-user-computing-for-change-and-agility/
Join us on Wednesday, September 13, for a free-to-attend online event, AWS End User Computing Innovation Day 2023. AWS will stream the event simultaneously across multiple platforms, including LinkedIn Live, Twitter, YouTube, and Twitch.
Adapting to a complex landscape shaped by return-to-office mandates, pressure to migrate out of self-operated data centers, escalating security concerns, scarcity of in-house IT expertise, and constant focus on controlling expenses creates numerous challenges for IT teams responsible for providing the tools employees need to do their jobs.
AWS End User Computing Innovation Day 2023 is a one-day, free virtual event designed to dissect these very challenges. Join us as we delve into how AWS End User Computing (EUC) services can be harnessed to navigate this transformative era. Discover how to construct a remarkably agile and secure foundation poised to support the immediate and future requirements of remote and hybrid workforces.
During this event, you will have the opportunity to hear directly from senior leaders at AWS. Here are some of the highlights you can expect from this event.
Keynote – Muneer Mirza, General Manager of AWS End User Computing, will kick off with a keynote session. Muneer will explore an array of strategic approaches primed to maximize agility and foster seamless adaptation to change.
Browser-based workload security – Brett Taylor, General Manager of Amazon WorkSpaces Web, will discuss ways to secure web-based applications using Amazon WorkSpaces Web, so you can strengthen your security and compliance posture.
You can add an event reminder to your calendar by registering on the event page.
See you there.
— Irshad
Post Syndicated from Channy Yun original https://aws.amazon.com/blogs/aws/aws-weekly-roundup-farewell-ec2-classic-ebs-at-15-years-and-more-sept-4-2023/
Last week, there was some great reading about Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Elastic Block Store (Amazon EBS) written by AWS tech leaders.
Dr. Werner Vogels wrote Farewell EC2-Classic, it’s been swell, celebrating the 17 years of loyal duty of the original version that started what we now know as cloud computing. You can read how it made the process of acquiring compute resources simple, even though the stack running behind the scenes was incredibly complex.
We have come a long way since 2006, and we’re not done innovating for our customers. As celebrated in this year’s AWS Storage Day, Amazon EBS was launched 15 years ago this month. James Hamilton, SVP and distinguished engineer at Amazon, wrote Amazon EBS at 15 Years, about how the service has evolved to handle over 100 trillion I/O operations a day, and transfers over 13 exabytes of data daily.
As Dr. Werner said in his piece, “it’s a reminder that building evolvable systems is a strategy, and revisiting your architectures with an open mind is a must.” Our innovation efforts driven by customer feedback continue today, and this week is no different.
Last Week’s Launches
Here are some launches that got my attention:
Renaming Amazon Kinesis Data Analytics to Amazon Managed Service for Apache Flink – You can now use Amazon Managed Service for Apache Flink, a fully managed and serverless service for you to build and run real-time streaming applications using Apache Flink. All your existing running applications in Kinesis Data Analytics will work as-is, without any changes. To learn more, see my blog post.
Extended Support for Amazon Aurora and Amazon RDS – You can now get more time for support, up to three years, for Amazon Aurora and Amazon RDS database instances running MySQL 5.7, PostgreSQL 11, and higher major versions. This e will allow you time to upgrade to a new major version to help you meet your business requirements even after the community ends support for these versions.
Enhanced Starter Template for AWS Step Functions Workflow Studio – You can now use starter templates to streamline the process of creating and prototyping workflows swiftly, plus a new code mode, which enables builders to move easily between design and code authoring views. With the improved authoring experience in Workflow Studio, you can seamlessly alternate between a drag-and-drop visual builder experience or the new code editor so that you can pick your preferred tool to accelerate development.
To learn more, see Enhancing Workflow Studio with new features for streamlined authoring in the AWS Compute Blog.
Email Delivery History for Every Email in Amazon SES – You can now troubleshoot individual email delivery problems, confirm delivery of critical messages, and identify engaged recipients on a granular, single email basis. Email senders can investigate trends in delivery performance and see delivery and engagement status for each email sent using Amazon SES Virtual Deliverability Manager.
Response Streaming through Amazon SageMaker Real-time Inference – You can now continuously stream inference responses back to the client to help you build interactive experiences for various generative AI applications such as chatbots, virtual assistants, and music generators.
For more details on how to use response streaming along with examples, see Invoke to Stream an Inference Response and How containers should respond in the AWS documentation, and Elevating the generative AI experience: Introducing streaming support in Amazon SageMaker hosting in the AWS Machine Learning Blog.
For a full list of AWS announcements, be sure to keep an eye on the What’s New at AWS page.
Other AWS News
Some other updates and news that you might have missed:
AI & Sports: How AWS & the NFL are Changing the Game – Over the last 5 years, AWS has partnered with the National Football League (NFL), helping fans better understand the game, helping broadcasters tell better stories, and helping teams use data to improve operations and player safety. Watch AWS CEO, Adam Selipsky, former NFL All-Pro Larry Fitzgerald, and the NFL Network’s Cynthia Frelund during their earlier livestream discussing the intersection of artificial intelligence and machine learning in sports.
Amazon Bedrock Story from Amazon Science – This is a good article explaining the benefits of using Amazon Bedrock to build and scale generative AI applications with leading foundation models, including Amazon’s Titan FMs, which focus on responsible AI to avoid toxic content.
Amazon EC2 Flexibility Score – This is an open source tool developed by AWS to assess any configuration used to launch instances through an Auto Scaling Group (ASG) against the recommended EC2 best practices. It converts the best practice adoption into a “flexibility score” that can be used to identify, improve, and monitor the configurations.
To learn more open-source news and updates, see this newsletter curated by my colleague Ricardo to bring you the latest open source projects, posts, events, and more.
Upcoming AWS Events
Check your calendars and sign up for these AWS events:
AWS re:Invent – Ready to start planning your re:Invent? Browse the session catalog now. Join us to hear the latest from AWS, learn from experts, and connect with the global cloud community.
AWS Global Summits
– The last in-person AWS Summit will be held in Johannesburg on Sept. 26.
AWS Community Days – Join a community-led conference run by AWS user group leaders in your region: Aotearoa (Sept. 6), Lebanon (Sept. 9), Munich (Sept. 14), Argentina (Sept. 16), Spain (Sept. 23), and Chile (Sept. 30). Visit the landing page to check out all the upcoming AWS Community Days.
CDK Day – A community-led fully virtual event on Sept. 29 with tracks in English and Spanish about CDK and related projects. Learn more at the website.
You can browse all upcoming AWS-led in-person and virtual events, and developer-focused events such as AWS DevDay.
— Channy
This post is part of our Weekly Roundup series. Check back each week for a quick roundup of interesting news and announcements from AWS!
Post Syndicated from Channy Yun original https://aws.amazon.com/blogs/aws/announcing-amazon-managed-service-for-apache-flink-renamed-from-amazon-kinesis-data-analytics/
Today we are announcing the rename of Amazon Kinesis Data Analytics to Amazon Managed Service for Apache Flink, a fully managed and serverless service for you to build and run real-time streaming applications using Apache Flink.
We continue to deliver the same experience in your Flink applications without any impact on ongoing operations, developments, or business use cases. All your existing running applications in Kinesis Data Analytics will work as is without any changes.
Many customers use Apache Flink for data processing, including support for diverse use cases with a vibrant open-source community. While Apache Flink applications are robust and popular, they can be difficult to manage because they require scaling and coordination of parallel compute or container resources. With the explosion of data volumes, data types, and data sources, customers need an easier way to access, process, secure, and analyze their data to gain faster and deeper insights without compromising on performance and costs.
Using Amazon Managed Service for Apache Flink, you can set up and integrate data sources or destinations with minimal code, process data continuously with sub-second latencies from hundreds of data sources like Amazon Kinesis Data Streams and Amazon Managed Streaming for Apache Kafka (Amazon MSK), and respond to events in real-time. You can also analyze streaming data interactively with notebooks in just a few clicks with Amazon Managed Service for Apache Flink Studio with built-in visualizations powered by Apache Zeppelin.
With Amazon Managed Service for Apache Flink, you can deploy secure, compliant, and highly available applications. There are no servers and clusters to manage, no compute and storage infrastructure to set up, and you only pay for the resources your applications consume.
A History to Support Apache Flink
Since we launched Amazon Kinesis Data Analytics based on a proprietary SQL engine in 2016, we learned that SQL alone was not sufficient to provide the capabilities that customers needed for efficient stateful stream processing. So, we started investing in Apache Flink, a popular open-source framework and engine for processing real-time data streams.
In 2018, we provided support for Amazon Kinesis Data Analytics for Java as a programmable option for customers to build streaming applications using Apache Flink libraries and choose their own integrated development environment (IDE) to build their applications. In 2020, we repositioned Amazon Kinesis Data Analytics for Java to Amazon Kinesis Data Analytics for Apache Flink to emphasize our continued support for Apache Flink. In 2021, we launched Kinesis Data Analytics Studio (now, Amazon Managed Service for Apache Flink Studio) with a simple, familiar notebook interface for rapid development powered by Apache Zeppelin and using Apache Flink as the processing engine.
Since 2019, we have worked more closely with the Apache Flink community, increasing code contributions in the area of AWS connectors for Apache Flink such as those for Kinesis Data Streams and Kinesis Data Firehose, as well as sponsoring annual Flink Forward events. Recently, we contributed Async Sink to the Flink 1.15 release, which improved cloud interoperability and added more sink connectors and formats, among other updates.
Beyond connectors, we continue to work with the Flink community to contribute availability improvements and deployment options. To learn more, see Making it Easier to Build Connectors with Apache Flink: Introducing the Async Sink in the AWS Open Source Blog.
New Features in Amazon Managed Service for Apache Flink
As I mentioned, you can continue to run your existing Flink applications in Kinesis Data Analytics (now Amazon Managed Apache Flink) without making any changes. I want to let you know about a part of the service along with the console change and new feature, a blueprint where you create an end-to-end data pipeline with just one click.
First, you can use the new console of Amazon Managed Service for Apache Flink directly under the Analytics section in AWS. To get started, you can easily create Streaming applications or Studio notebooks in the new console, with the same experience as before.
To create a streaming application in the new console, choose Create from scratch or Use a blueprint. With a new blueprint option, you can create and set up all the resources that you need to get started in a single step using AWS CloudFormation.
The blueprint is a curated collection of Apache Flink applications. The first of these has demo data being read from a Kinesis Data Stream and written to an Amazon Simple Storage Service (Amazon S3) bucket.
After creating the demo application, you can configure, run, and open the Apache Flink dashboard to monitor your Flink application’s health with the same experiences as before. You can change a code sample in the GitHub repository to perform different operations using the Flink libraries in your own local development environment.
Blueprints are designed to be extensible, and you can leverage them to create more complex applications to solve your business challenges based on Amazon Managed Service for Apache Flink. Learn more about how to use Apache Flink libraries in the AWS documentation.
You can also use a blueprint to create your Studio notebook using Apache Zeppelin as a new setup option. With this new blueprint option, you can also create and set up all the resources that you need to get started in a single step using AWS CloudFormation.
This blueprint includes Apache Flink applications with demo data being sent to an Amazon MSK topic and read in Managed Service for Apache Flink. With an Apache Zeppelin notebook, you can view, query, and analyze your streaming data. Deploying the blueprint and setting up the Studio notebook takes about ten minutes. Go get a cup of coffee while we set it up!
After creating the new Studio notebook, you can open an Apache Zeppelin notebook to run SQL queries in your note with the same experiences as before. You can view a code sample in the GitHub repository to learn more about how to use Apache Flink libraries.
You can run more SQL queries on this demo data such as user-defined functions, tumbling and hopping windows, Top-N queries, and delivering data to an S3 bucket for streaming.
You can also use Java, Python, or Scala to power up your SQL queries and deploy your note as a continuously running application, as shown in the blog posts, how to use the Studio notebook and query your Amazon MSK topics.
To learn more blueprint samples, see GitHub repositories such as reading from MSK Serverless and writing to Amazon S3, reading from MSK Serverless and writing to MSK Serverless, and reading from MSK Serverless and writing to Amazon S3.
Now Available
You can now use Amazon Managed Service for Apache Flink, renamed from Amazon Kinesis Data Analytics. All your existing running applications in Kinesis Data Analytics will work as is without any changes.
To learn more, visit the new product page and developer guide. You can send feedback to AWS re:Post for Amazon Managed Service for Apache Flink, or through your usual AWS Support contacts.
— Channy
Post Syndicated from Patrick Kennedy original https://www.servethehome.com/intel-shows-8-core-528-thread-processor-with-silicon-photonics/
Intel showed an 8 core CPU with 66 hardware threads per core for 528 threads and it even included silicon photonics networking
The post Intel Shows 8 Core 528 Thread Processor with Silicon Photonics appeared first on ServeTheHome.
Post Syndicated from Channy Yun original https://aws.amazon.com/blogs/aws/new-amazon-ec2-hpc7a-instances-powered-by-4th-gen-amd-epyc-processors-optimized-for-high-performance-computing/
In January 2022, we launched Amazon EC2 Hpc6a instances for customers to efficiently run their compute-bound high performance computing (HPC) workloads on AWS with up to 65 percent better price performance over comparable x86-based compute-optimized instances.
As their jobs grow more complex, customers have asked for more cores with more compute performance and more memory and network performance to reduce the time to complete jobs. Additionally, as customers look to bring more of their HPC workloads to EC2, they have asked how we can make it easier to distribute processes to make the best use of memory and network bandwidth, to align with their workload requirements.
Today, we are announcing the general availability of Amazon EC2 Hpc7a instances, the next generation of instance types that are purpose-built for tightly coupled HPC workloads. Hpc7a instances powered by the 4th Gen AMD EPYC processors (Genoa) deliver up to 2.5 times better performance compared to Hpc6a instances. These instances offer 300 Gbps Elastic Fabric Adapter (EFA) bandwidth powered by the AWS Nitro System, for fast and low-latency internode communications.
Hpc7a instances feature Double Data Rate 5 (DDR5) memory, which provides 50 percent higher memory bandwidth compared to DDR4 memory to enable high-speed access to data in memory. These instances are ideal for compute-intensive, latency-sensitive workloads such as computational fluid dynamics (CFD) and numerical weather prediction (NWP).
If you are running on Hpc6a, you can use Hpc7a instances and take advantage of the 2 times higher core density, 2.1 times higher effective memory bandwidth, and 3 times higher network bandwidth to lower the time needed to complete jobs compared to Hpc6a instances.
Here’s a quick infographic that shows you how the Hpc7a instances and the 4th Gen AMD EPYC processor (Genoa) compare to the previous instances and processor:
Hpc7a instances feature sizes of up to 192 cores of the AMD EPYC processors CPUs with 768 GiB RAM. Here are the detailed specs:
| Instance Name | CPUs | RAM (Gib) |
EFA Network Bandwidth (Gbps) |
Attached Storage |
| Hpc7a.12xlarge | 24 | 768 | Up to 300 | EBS Only |
| Hpc7a.24xlarge | 48 | 768 | Up to 300 | EBS Only |
| Hpc7a.48xlarge | 96 | 768 | Up to 300 | EBS Only |
| Hpc7a.96xlarge | 192 | 768 | Up to 300 | EBS Only |
These instances provide higher compute, memory, and network performance to run the most compute-intensive workloads, such as CFD, weather forecasting, molecular dynamics, and computational chemistry on AWS.
Similar to EC2 Hpc7g instances released a month earlier, we are offering smaller instance sizes that makes it easier for customers to pick a smaller number of CPU cores to activate while keeping all other resources constant based on their workload requirements. For HPC workloads, common scenarios include providing more memory bandwidth per core for CFD workloads, allocating fewer cores in license-bound scenarios, and supporting more memory per core. To learn more, see Instance sizes in the Amazon EC2 Hpc7 family – a different experience in the AWS HPC Blog.
As with Hpc6a instances, you can use the Hpc7a instance to run your largest and most complex HPC simulations on EC2 and optimize for cost and performance. You can also use the new Hpc7a instances with AWS Batch and AWS ParallelCluster to simplify workload submission and cluster creation. You can also use Amazon FSx for Lustre for submillisecond latencies and up to hundreds of gigabytes per second of throughput for storage.
To achieve the best performance for HPC workloads, these instances have Simultaneous Multithreading (SMT) disabled, they’re available in a single Availability Zone, and they have limited external network and EBS bandwidth.
Now Available
Amazon EC2 Hpc7a instances are available today in three AWS Regions: US East (Ohio), EU (Ireland), and US GovCloud for purchase in On-Demand, Reserved Instances, and Savings Plans. For more information, see the Amazon EC2 pricing page.
To learn more, visit our Hpc7a instances page and get in touch with our HPC team, AWS re:Post for EC2, or through your usual AWS Support contacts.
— Channy
Post Syndicated from Channy Yun original https://aws.amazon.com/blogs/aws/join-aws-hybrid-cloud-edge-day-to-learn-how-to-deploy-your-applications-in-the-everywhere-cloud/
In his keynote of AWS re:Invent 2021, Dr. Werner Vogels shared the insight of how “the everywhere cloud” is bringing AWS to new locales through AWS hardware and services and spotlighted it as one of his tech predictions for 2022 and beyond in his blog post.
“What we will see in 2022, and even more so in the years to come, is the cloud accelerating beyond the traditional centralized infrastructure model and into unexpected environments where specialized technology is needed. The cloud will be in your car, your tea kettle, and your TV. The cloud will be in everything from trucks driving down the road, to the ships and planes that transport goods. The cloud will be globally distributed, and connected to almost any digital device or system on Earth, and even in space.”
AWS provides a truly consistent and secure experience to build and run applications across the continuum of environments where customers operate—from the cloud to large metro areas, 5G networks, on-premises locations, and to mobile and Internet of Things (IoT) devices.
To learn more, join us for AWS Hybrid Cloud & Edge Day, a free-to-attend one-day virtual event on August 30, 2023, starting at 10:00 AM PDT (1:00 PM ET). We will stream the event simultaneously across multiple platforms, including LinkedIn Live, Twitter, YouTube, and Twitch.
You can hear from AWS leaders and industry analysts on the latest hybrid cloud and edge computing trends and emerging technologies and learn best practices for using AWS hybrid cloud and edge services across the cloud continuum. Also, learn from our customers on data strategies and key use cases and gain a deeper understanding of AWS hybrid cloud and edge services and new features and benefits.
Here are some of the highlights you can expect from this event:
Leadership session – To kick off the day, we have a leadership session featuring Jan Hofmeyr, vice president of EC2 Edge, sharing insights into how customers are building high-performance, intelligent applications with recently announced AWS hybrid cloud, edge, and IoT capabilities. Elias Khnaser, chief of research at EK Media Group, will join Jan to discuss the global, business, and economic trends impacting hybrid cloud and edge computing and discuss the customer requirements and use cases.
Cloud-closer sessions – We’ll discuss how AWS is bringing the cloud closer to metro areas and telco networks. Services such as AWS Local Zones, AWS Outposts family, and AWS Wavelength bring the power of cloud compute and storage to the edge of 5G networks, unlocking more performant mobile experiences. We’ll highlight new and innovative use cases, including Norton LifeLock, Electronic Arts, and Epic Games, who have taken advantage of the operational consistency between AWS Regions and the edge. Also you can learn how to deploy in hybrid cloud scenarios in on-premises locations, such as examples from MindBody and ElToro through Onica, and more customer cases.
On-premises sessions – Learn about our options to bring AWS Cloud to your data centers and on-premises locations for a truly consistent experience across your environments. We will review real-world examples of how AWS hybrid and edge services enable local processing of data for faster response time and faster decision-making. Also, we will share how Toyota takes advantage of hybrid options from Amazon ECS and Amazon EKS to use familiar management tools across your environments to successfully modernize your applications. You can learn how to meet your on-premises regulatory requirements and real-world scenarios effectively in critical aspects of digital sovereignty and data residency.
Rugged edge sessions – You will learn about AWS services to support rugged, mobile, and disconnected edge, such as AWS Snow Family to enable organizations to deploy compute workloads in locations with denied, disrupted, intermittent, and limited (DDIL) connectivity. Learn how DDR.Live deployed their own 4G/LTE or 5G private network using AWS Private 5G for live events in the place with limited wireless connection. We will discuss the top use cases, such as deploying a pre-trained object detection model and architecting applications at the edge. Finally, we will discuss the benefits and requirements of operating at the edge with Holger Mueller, vice president and principal analyst, Constellation Research, Inc.
IoT panel discussion – We will discuss from panelist of AWS IoT customers and industry experts on their innovation journey. Join us to see how EuroTech brought to market a set of devices and services that improve operational efficiencies with connectivity at the edge. You’ll also hear how Wallbox, an Electric Vehicle charging company, reduced their operational costs and scaled efficiently with AWS IoT services.
Multicloud sessions – AWS has the tools to help you run and support your multicloud operations in the areas of governance, ops management, observability, and more. We will discuss common challenges in hybrid and multicloud environments and how AWS helps you manage, operate, and automate your processes. We’ll also talk about how Rackspace used AWS Systems Manager for instance patching across hybrid and multicloud environments, automating their infrastructure management across cloud providers.
This event is for any customer and builder who is eager to learn more about hybrid cloud, edge computing, IoT, networking, content delivery, and 5G. We’ll cover how you can support applications that need to remain on premises or at the edge due to low latency, local data processing, or data residency requirements.
To learn more details, see the event schedule, and register for AWS Hybrid Cloud & Edge Day, go to the event page.
— Channy
Post Syndicated from Patrick Kennedy original https://www.servethehome.com/intel-terminates-the-tower-acquisition/
Intel announced that it is paying a $353M termination fee after failing to secure regulatory approval for its Tower Semiconductor acquisition
The post Intel Terminates the Tower Acquisition appeared first on ServeTheHome.
Post Syndicated from Channy Yun original https://aws.amazon.com/blogs/aws/new-amazon-ec2-m7a-general-purpose-instances-powered-by-4th-gen-amd-epyc-processors/
In November 2021, we launched Amazon EC2 M6a instances, powered by 3rd Gen AMD EPYC (Milan) processors, running at frequencies up to 3.6 GHz, which offer you up to 35 percent improvement in price performance compared to M5a instances. Many customers who run workloads that are dependent on x86 instructions, such as SAP, are looking for ways to optimize their cloud utilization. They’re taking advantage of the compute choice that EC2 offers.
Today, we’re announcing the general availability of new, general purpose Amazon EC2 M7a instances, powered by the 4th Gen AMD EPYC (Genoa) processors with a maximum frequency of 3.7 GHz, which offer up to 50 percent higher performance compared to M6a instances. This increased performance gives you the ability to process data faster, consolidate workloads, and lower the cost of ownership.
M7a instances support AVX-512, Vector Neural Network Instructions (VNNI) and brain floating point (bfloat16). These instances feature Double Data Rate 5 (DDR5) memory, which enable high-speed access to data in-memory, and deliver 2.25 times more memory bandwidth compared to M6a instances for lower latency.
M7a instances are SAP-certified and ideal for applications that benefit from high performance and high throughput, such as financial applications, application servers, simulation modeling, gaming, mid-size data stores, application development environments, and caching fleets.
M7a instances feature sizes of up to 192 vCPUs with 768 GiB RAM. Here are the detailed specs:
| Name | vCPUs | Memory (GiB) | Network Bandwidth (Gbps) | EBS Bandwidth (Gbps) |
| m7a.medium | 1 | 4 | Up to 12.5 | Up to 10 |
| m7a.large | 2 | 8 | Up to 12.5 | Up to 10 |
| m7a.xlarge | 4 | 16 | Up to 12.5 | Up to 10 |
| m7a.2xlarge | 8 | 32 | Up to 12.5 | Up to 10 |
| m7a.4xlarge | 16 | 64 | Up to 12.5 | Up to 10 |
| m7a.8xlarge | 32 | 128 | 12.5 | 10 |
| m7a.12xlarge | 48 | 192 | 18.75 | 15 |
| m7a.16xlarge | 64 | 256 | 25 | 20 |
| m7a.24xlarge | 96 | 384 | 37.5 | 30 |
| m7a.32xlarge | 128 | 512 | 50 | 40 |
| m7a.48xlarge | 192 | 768 | 50 | 40 |
| m7a.metal-48xl | 192 | 768 | 50 | 40 |
M7a instances have up to 50 Gbps enhanced networking and 40 Gbps EBS bandwidth, which is similar to M6a instances. But you have a new medium instance size, which enables you to right-size your workloads more accurately, offering 1 vCPUs, 4 GiB, and the largest size offering 192 vCPUs, 768 GiB.
The new instances are built on the AWS Nitro System, a collection of building blocks that offloads many of the traditional virtualization functions to dedicated hardware for high performance, high availability, and highly secure cloud instances.
Now Available
Amazon EC2 M7a instances are now available today in AWS Regions: US East (Ohio), US East (N. Virginia), US West (Oregon), and EU (Ireland). As usual with Amazon EC2, you only pay for what you use. For more information, see the Amazon EC2 pricing page.
To learn more, visit the EC2 M7a instance and AWS/AMD partner page. You can send feedback to [email protected], AWS re:Post for EC2, or through your usual AWS Support contacts.
— Channy
Post Syndicated from Antje Barth original https://aws.amazon.com/blogs/aws/aws-weekly-roundup-amazon-mwaa-emr-studio-generative-ai-and-more-august-14-2023/
While I enjoyed a few days off in California to get a dose of vitamin sea, a lot has happened in the AWS universe. Let’s take a look together!
Last Week’s Launches
Here are some launches that got my attention:
Amazon MWAA now supports Apache Airflow version 2.6 – Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is a managed orchestration service for Apache Airflow that you can use to set up and operate end-to-end data pipelines in the cloud. Apache Airflow version 2.6 introduces important security updates and bug fixes that enhance the security and reliability of your workflows. If you’re currently running Apache Airflow version 2.x, you can now seamlessly upgrade to version 2.6.3. Check out this AWS Big Data Blog post to learn more.
Amazon EMR Studio adds support for AWS Lake Formation fine-grained access control – Amazon EMR Studio is a web-based integrated development environment (IDE) for fully managed Jupyter notebooks that run on Amazon EMR clusters. When you connect to EMR clusters from EMR Studio workspaces, you can now choose the AWS Identity and Access Management (IAM) role that you want to connect with. Apache Spark interactive notebooks will access only the data and resources permitted by policies attached to this runtime IAM role. When data is accessed from data lakes managed with AWS Lake Formation, you can enforce table and column-level access using policies attached to this runtime role. For more details, have a look at the Amazon EMR documentation.
AWS Security Hub launches 12 new security controls – AWS Security Hub is a cloud security posture management (CSPM) service that performs security best practice checks, aggregates alerts, and enables automated remediation. With the newly released controls, Security Hub now supports three additional AWS services: Amazon Athena, Amazon DocumentDB (with MongoDB compatibility), and Amazon Neptune. Security Hub has also added an additional control against Amazon Relational Database Service (Amazon RDS). AWS Security Hub now offers 276 controls. You can find more information in the AWS Security Hub documentation.
Additional AWS services available in the AWS Israel (Tel Aviv) Region – The AWS Israel (Tel Aviv) Region opened on August 1, 2023. This past week, AWS Service Catalog, Amazon SageMaker, Amazon EFS, and Amazon Kinesis Data Analytics were added to the list of available services in the Israel (Tel Aviv) Region. Check the AWS Regional Services List for the most up-to-date availability information.
For a full list of AWS announcements, be sure to keep an eye on the What’s New at AWS page.
Other AWS News
Here are some additional blog posts and news items that you might find interesting:
AWS recognized as a Leader in 2023 Gartner Magic Quadrant for Contact Center as a Service with Amazon Connect – AWS was named a Leader for the first time since Amazon Connect, our flexible, AI-powered cloud contact center, was launched in 2017. Read the full story here.
Generate creative advertising using generative AI – This AWS Machine Learning Blog post shows how to generate captivating and innovative advertisements at scale using generative AI. It discusses the technique of inpainting and how to seamlessly create image backgrounds, visually stunning and engaging content, and reducing unwanted image artifacts.
AWS open-source news and updates – My colleague Ricardo writes this weekly open-source newsletter in which he highlights new open-source projects, tools, and demos from the AWS Community.
Upcoming AWS Events
Check your calendars and sign up for these AWS events:
Build On Generative AI – Your favorite weekly Twitch show about all things generative AI is back for season 2 today! Every Monday, 9:00 US PT, my colleagues Emily and Darko look at new technical and scientific patterns on AWS, inviting guest speakers to demo their work and show us how they built something new to improve the state of generative AI.
In today’s episode, Emily and Darko discussed the latest models LlaMa-2 and Falcon, and explored them in retrieval-augmented generation design patterns. You can watch the video here. Check out show notes and the full list of episodes on community.aws.
AWS NLP Conference 2023 – Join this in-person event on September 13–14 in London to hear about the latest trends, ground-breaking research, and innovative applications that leverage natural language processing (NLP) capabilities on AWS. This year, the conference will primarily focus on large language models (LLMs), as they form the backbone of many generative AI applications and use cases. Register here.
AWS Global Summits – The 2023 AWS Summits season is almost coming to an end with the last two in-person events in Mexico City (August 30) and Johannesburg (September 26).
AWS Community Days – Join a community-led conference run by AWS user group leaders in your region: West Africa (August 19), Taiwan (August 26), Aotearoa (September 6), Lebanon (September 9), and Munich (September 14).
AWS re:Invent (November 27 – December 1) – Join us to hear the latest from AWS, learn from experts, and connect with the global cloud community. Registration is now open.
You can browse all upcoming in-person and virtual events.
That’s all for this week. Check back next Monday for another Weekly Roundup!
— Antje
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Post Syndicated from Veliswa Boya original https://aws.amazon.com/blogs/aws/new-file-release-for-amazon-fsx-for-lustre/
Amazon FSx for Lustre provides fully managed shared storage with the scalability and high performance of the open-source Lustre file systems to support your Linux-based workloads. FSx for Lustre is for workloads where storage speed and throughput matter. This is because FSx for Lustre helps you avoid storage bottlenecks, increase utilization of compute resources, and decrease time to value for workloads that include artificial intelligence (AI) and machine learning (ML), high performance computing (HPC), financial modeling, and media processing. FSx for Lustre integrates natively with Amazon Simple Storage Service (Amazon S3), synchronizing changes in both directions with automatic import and export, so that you can access your Amazon S3 data lakes through a high-performance POSIX-compliant file system on demand.
Today, I’m excited to announce file release for FSx for Lustre. This feature helps you manage your data lifecycle by releasing file data that has been synchronized with Amazon S3. File release frees up storage space so that you can continue writing new data to the file system while retaining on-demand access to released files through the FSx for Lustre lazy loading from Amazon S3. You specify a directory to release from, and optionally a minimum amount of time since last access, so that only data from the specified directory, and the minimum amount of time since last access (if specified), is released. File release helps you with data lifecycle management by moving colder file data to S3 enabling you to take advantage of S3 tiering.
File release tasks are initiated using the AWS Management Console, or by making an API call using the AWS CLI, AWS SDK, or Amazon EventBridge Scheduler to schedule release tasks at regular intervals. You can choose to receive completion reports at the end of your release task if so desired.
Initiating a Release Task
As an example, let’s look at how to use the console to initiate a release task. To specify criteria for files to release (for example, directories or time since last access), we define release data repository tasks (DRTs). DRTs release all files that are synchronized with Amazon S3 and that meet the specified criteria. It’s worth noting that release DRTs are processed in sequence. This means that if you submit a release DRT while another DRT (for example, import or export) is in progress, the release DRT will be queued but not processed until after the import or export DRT has completed.
Note: For the data repository association to work, automatic backups for the file system must be disabled (use the Backups tab to do this). Secondly, ensure that the file system and the associated S3 bucket are in the same AWS Region.
I already have an FSx for Lustre file system my-fsx-test.
I create a data repository association, which is a link between a directory on the file system and an S3 bucket or prefix.
I specify the name of the S3 bucket or an S3 prefix to be associated with the file system.
After the data repository association has been created, I select Create release task.
The release task will release directories or files that you want to release based on your specific criteria (again, important to remember that these files or directories must be synchronized with an S3 bucket in order for the release to work). If you specified the minimum last access for release (in addition to the directory), files that have not been accessed more recently than that will be released.
In my example, I chose to Disable completion reports. However, if you choose to Enable completion reports, the release task will produce a report at the end of the release task.
Files that have been released can still be accessed using existing FSx for Lustre functionality to automatically retrieve data from Amazon S3 back to the file system on demand. This is because, although released, their metadata stays on the file system.
File release won’t automatically prevent your file system from becoming full. It remains important to ensure that you don’t write more data than the available storage capacity before you run the next release task.
Now Available
File release on FSx for Lustre is available today in all AWS Regions where FSx for Lustre is supported, on all new or existing S3-linked file systems running Lustre version 2.12 or later. With file release on FSx for Lustre, there is no additional cost. However, if you release files that you later access again from the file system, you will incur normal Amazon S3 request and data retrieval costs where applicable when those files are read back into the file system.
To learn more, visit the Amazon FSx for Lustre Page, and please send feedback to AWS re:Post for Amazon FSx for Lustre or through your usual AWS support contacts.
– Veliswa
Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/mountpoint-for-amazon-s3-generally-available-and-ready-for-production-workloads/
Mountpoint for Amazon S3 is an open source file client that makes it easy for your file-aware Linux applications to connect directly to Amazon Simple Storage Service (Amazon S3) buckets. Announced earlier this year as an alpha release, it is now generally available and ready for production use on your large-scale read-heavy applications: data lakes, machine learning training, image rendering, autonomous vehicle simulation, ETL, and more. It supports file-based workloads that perform sequential and random reads, sequential (append only) writes, and that don’t need full POSIX semantics.
Why Files?
Many AWS customers use the S3 APIs and the AWS SDKs to build applications that can list, access, and process the contents of an S3 bucket. However, many customers have existing applications, commands, tools, and workflows that know how to access files in UNIX style: reading directories, opening & reading existing files, and creating & writing new ones. These customers have asked us for an official, enterprise-ready client that supports performant access to S3 at scale. After speaking with these customers and asking lots of questions, we learned that performance and stability were their primary concerns, and that POSIX compliance was not a necessity.
When I first wrote about Amazon S3 back in 2006 I was very clear that it was intended to be used as an object store, not as a file system. While you would not want use the Mountpoint / S3 combo to store your Git repositories or the like, using it in conjunction with tools that can read and write files, while taking advantage of S3’s scale and durability, makes sense in many situations.
All About Mountpoint
Mountpoint is conceptually very simple. You create a mount point and mount an Amazon S3 bucket (or a path within a bucket) at the mount point, and then access the bucket using shell commands (ls, cat, dd, find, and so forth), library functions (open, close, read, write, creat, opendir, and so forth) or equivalent commands and functions as supported in the tools and languages that you already use.
Under the covers, the Linux Virtual Filesystem (VFS) translates these operations into calls to Mountpoint, which in turns translates them into calls to S3: LIST, GET, PUT, and so forth. Mountpoint strives to make good use of network bandwidth, increasing throughput and allowing you to reduce your compute costs by getting more work done in less time.
Mountpoint can be used from an Amazon Elastic Compute Cloud (Amazon EC2) instance, or within an Amazon Elastic Container Service (Amazon ECS) or Amazon Elastic Kubernetes Service (EKS) container. It can also be installed on your existing on-premises systems, with access to S3 either directly or over an AWS Direct Connect connection via AWS PrivateLink for Amazon S3.
Installing and Using Mountpoint for Amazon S3
Mountpoint is available in RPM format and can easily be installed on an EC2 instance running Amazon Linux. I simply fetch the RPM and install it using yum:
For the last couple of years I have been regularly fetching images from several of the Washington State Ferry webcams and storing them in my wsdot-ferry bucket:
I collect these images in order to track the comings and goings of the ferries, with a goal of analyzing them at some point to find the best times to ride. My goal today is to create a movie that combines an entire day’s worth of images into a nice time lapse. I start by creating a mount point and mounting the bucket:
I can traverse the mount point and inspect the bucket:
I can create my animation with a single command:
And here’s what I get:
As you can see, I used Mountpoint to access the existing image files and to write the newly created animation back to S3. While this is a fairly simple demo, it does show how you can use your existing tools and skills to process objects in an S3 bucket. Given that I have collected several million images over the years, being able to process them without explicitly syncing them to my local file system is a big win.
Mountpoint for Amazon S3 Facts
Here are a couple of things to keep in mind when using Mountpoint:
Pricing – There are no new charges for the use of Mountpoint; you pay only for the underlying S3 operations. You can also use Mountpoint to access requester-pays buckets.
Performance – Mountpoint is able to take advantage of the elastic throughput offered by S3, including data transfer at up to 100 Gb/second between each EC2 instance and S3.
Credentials – Mountpoint accesses your S3 buckets using the AWS credentials that are in effect when you mount the bucket. See the CONFIGURATION doc for more information on credentials, bucket configuration, use of requester pays, some tips for the use of S3 Object Lambda, and more.
Operations & Semantics – Mountpoint supports basic file operations, and can read files up to 5 TB in size. It can list and read existing files, and it can create new ones. It cannot modify existing files or delete directories, and it does not support symbolic links or file locking (if you need POSIX semantics, take a look at Amazon FSx for Lustre). For more information about the supported operations and their interpretation, read the SEMANTICS document.
Storage Classes – You can use Mountpoint to access S3 objects in all storage classes except S3 Glacier Flexible Retrieval, S3 Glacier Deep Archive, S3 Intelligent-Tiering Archive Access Tier, and S3 Intelligent-Tiering Deep Archive Access Tier.
Open Source – Mountpoint is open source and has a public roadmap. Your contributions are welcome; be sure to read our Contributing Guidelines and our Code of Conduct first.
Hop On
As you can see, Mountpoint is really cool and I am guessing that you are going to find some awesome ways to put it to use in your applications. Check it out and let me know what you think!
— Jeff;