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

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AWS Weekly Roundup – AWS Dedicated Zones, Events and More – August 28, 2023

This week, I will meet our customers and partners at the AWS Summit Mexico. If you are around, please come say hi at the community lounge and at the F1 Game Day where I will spend most of my time. I would love to discuss your developer experience on AWS and listen to your stories about building on AWS.

Last Week’s Launches
I am amazed at how quickly service teams are deploying services to the new il-central-1 Region, aka AWS Israel (Tel-Aviv) Region. I counted no fewer than 25 new service announcements since we opened the Region on August 1, including ten just for last week!

In addition to these developments in the new Region, here are some launches that got my attention during the previous week.

AWS Dedicated Local Zones – Just like Local Zones, Dedicated Local Zones are a type of AWS infrastructure that is fully managed by AWS. Unlike Local Zones, they are built for exclusive use by you or your community and placed in a location or data center specified by you to help comply with regulatory requirements. I think about them as a portion of AWS infrastructure dedicated to my exclusive usage.

Enhanced search on AWS re:Post – AWS re:Post is a cloud knowledge service. The enhanced search experience helps you locate answers and discover articles more quickly. Search results are now presenting a consolidated view of all AWS knowledge on re:Post. The view shows AWS Knowledge Center articles, question and answers, and community articles that are relevant to the user’s search query.

Amazon QuickSight supports scheduled programmatic export to Microsoft Excel – Amazon QuickSight now supports scheduled generation of Excel workbooks by selecting multiple tables and pivot table visuals from any sheet of a dashboard. Snapshot Export APIs will now also support programmatic export to Excel format, in addition to Paginated PDF and CSV.

Amazon WorkSpaces announced a new client to support Ubuntu 20.04 and 22.04 – The new client, powered by WorkSpaces Streaming Protocol (WSP), improves the remote desktop experience by offering enhanced web conferencing functionality, better multi-monitor support, and a more user-friendly interface. To get started, simply download the new Linux client versions from Amazon WorkSpaces client download website.

Amazon Sagemaker CPU/GPU profiler – We launched the preview of Amazon SageMaker Profiler, an advanced observability tool for large deep learning workloads. With this new capability, you are able to access granular compute hardware-related profiling insights for optimizing model training performance.

Amazon Sagemaker rolling deployments strategy – You can now update your Amazon SageMaker Endpoints using a rolling deployment strategy. Rolling deployment makes it easier for you to update fully-scaled endpoints that are deployed on hundreds of popular accelerated compute instances.

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:

On-demand Container Loading in AWS Lambda – This one is not new from this week, but I spotted it while I was taking a few days of holidays. Marc Brooker and team were awarded Best Paper by USENIX Association for On-demand Container Loading in AWS Lambda (pdf). They explained in detail the challenges of loading (huge) container images in AWS Lambda. A must-read if you’re curious how Lambda functions work behind the scenes (pdf).

The Official AWS Podcast – Listen each week for updates on the latest AWS news and deep dives into exciting use cases. There are also official AWS podcasts in several languages. Check out the ones in French, German, Italian, and Spanish.

AWS Open Source News and Updates – This is a 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 Hybrid Cloud & Edge Day (August 30) – Join a free-to-attend one-day virtual event to hear the latest hybrid cloud and edge computing trends, emerging technologies, and learn best practices from AWS leaders, customers, and industry analysts. To learn more, see the detail agenda and register now.

AWS Global Summits – The 2023 AWS Summits season is almost ending with the last two in-person events in Mexico City (August 30) and Johannesburg (September 26).

AWS re:Invent – But don’t worry because re:Invent season (November 27–December 1) is coming closer. Join us to hear the latest from AWS, learn from experts, and connect with the global cloud community. Registration is now open.

AWS Community Days – Join a community-led conference run by AWS user group leaders in your region: Aotearoa (September 6), Lebanon (September 9), Munich (September 14), Argentina (September 16), Spain (September 23), and Chile (September 30). Visit the landing page to check out all the upcoming AWS Community Days.

CDK Day (September 29) – A community-led fully virtual event with tracks in English and Spanish about CDK and related projects. Learn more at the website.

That’s all for this week. Check back next Monday for another Week in Review!

This post is part of our Week in Review series. Check back each week for a quick roundup of interesting news and announcements from AWS!

-- seb

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AWS Weekly Roundup – AWS AppSync, AWS CodePipeline, Events and More – August 21, 2023

In a few days, I will board a plane towards the south. My tour around Latin America starts. But I won’t be alone in this adventure, you can find some other News Blog authors, like Jeff or Seb, speaking at AWS Community Days and local events in Peru, Argentina, Chile, and Uruguay. If you see us, come and say hi. We would love to meet you.

Last Week’s Launches
Here are some launches that got my attention during the previous week.

AWS AppSync now supports JavaScript for all resolvers in GraphQL APIs – Last year, we announced that AppSync now supports JavaScript pipeline resolvers. And starting last week, developers can use JavaScript to write unit resolvers, pipeline resolvers, and AppSync functions that are run on the AppSync Javascript runtime.

AWS CodePipeline now supports GitLab – Now you can use your GitLab.com source repository to build, test, and deploy code changes using AWS CodePipeline, in addition to other providers like AWS CodeCommit, Bitbucket, GitHub.com, and GitHub Enterprise Server.

Amazon CloudWatch Agent adds support for OpenTelemetry traces and AWS X-Ray – With the new version of the agent you are now able to collect metrics, logs, and traces with a single agent, not only for CloudWatch but also for OpenTelemetry and AWS X-Ray. Simplifying the installation, configuration, and management of telemetry collection.

New instance types: Amazon EC2 M7a and Amazon EC2 Hpc7a – The new Amazon EC2 M7a is a general purpose instance type powered by 4^th Gen AMD EPYC processor. In the announcement blog, you can find all the specifics for this instance type. The new Amazon EC2 Hpc7a instances are also powered by 4^th Gen AMD EPYC processors. These instance types are optimized for high performance computing and Channy Yun wrote a blog post describing the different characteristics of the Amazon EC2 Hpc7a instance type.

AWS DeepRacer Educator Playbooks – Last week we introduced the AWS DeepRacer educator playblooks, these are a tool for educators to integrate foundational machine learning (ML) curriculum and labs into their classrooms. Educators can use these playbooks to easily upskill students in the basics of ML with autonomous vehicles.

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:

Guide for using AWS Lambda to process Apache Kafka Streams – Julian Wood just published the most complete guide you can find on how to use Lambda with Apache Kafka. If you are an Amazon Kinesis user, don’t worry. We’ve got you covered with this video series where you will find similar topics.

The Official AWS Podcast – Listen each week for updates on the latest AWS news and deep dives into exciting use cases. There are also official AWS podcasts in several languages. Check out the ones in French, German, Italian, and Spanish.

AWS Open-Source News and Updates – This is a 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 Hybrid Cloud & Edge Day (August 30) – Join a free-to-attend one-day virtual event to hear the latest hybrid cloud and edge computing trends, emerging technologies, and learn best practices from AWS leaders, customers, and industry analysts. To learn more, see the detail agenda and register now.

AWS Global Summits – The 2023 AWS Summits season is almost ending with the last two in-person events in Mexico City (August 30) and Johannesburg (September 26).

AWS re:Invent (November 27–December 1) – But don’t worry because re:Invent season is coming closer. Join us to hear the latest from AWS, learn from experts, and connect with the global cloud community. Registration is now open.

AWS Community Days – Join a community-led conference run by AWS user group leaders in your region:Taiwan (August 26), Aotearoa (September 6), Lebanon (September 9), Munich (September 14), Argentina (September 16), Spain (September 23), and Chile (September 30). Check all the upcoming AWS Community Days here.

CDK Day (September 29) – A community-led fully virtual event with tracks in English and in Spanish about CDK and related projects. Learn more in the website.

That’s all for this week. Check back next Monday for another Week in Review!

This post is part of our Week in Review series. Check back each week for a quick roundup of interesting news and announcements from AWS!

— Marcia

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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

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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

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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 ec2-amd-customer-feedback@amazon.com, AWS re:Post for EC2, or through your usual AWS Support contacts.

— Channy

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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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Welcome to AWS Storage Day 2023

Welcome to the fifth annual AWS Storage Day! This virtual event is happening today starting at 9:00 AM Pacific Time (12:00 PM Eastern Time) and is available for you to watch on the AWS On Air Twitch channel. The first AWS Storage Day was hosted in 2019, and this event has grown into an innovation day that we look forward to delivering to you every year. In last year’s Storage Day post, I wrote about the constant innovations in AWS Storage aimed at helping you put your data to work while keeping it secure and protected. This year, Storage Day is focused on storage for AI/ML, data protection and resiliency, and the benefits of moving to the cloud.

AWS Storage Day Key Themes
When it comes to storage for AI/ML, data volumes are increasing at an unprecedented rate, exploding from terabytes to petabytes and even to exabytes. With a modern data architecture on AWS, you can rapidly build scalable data lakes, use a broad and deep collection of purpose-built data services, scale your systems at a low cost without compromising performance, share data across organizational boundaries, and manage compliance, security, and governance, allowing you to make decisions with speed and agility at scale.
To train machine learning models and build Generative AI applications, you must have the right data strategy in place. So, I’m happy to see that, among the list of sessions to look forward to at the live event, the Optimize generative AI and ML with AWS Infrastructure session will discuss how you can transform your data into meaningful insights.

Whether you’re just getting started with the cloud, planning to migrate applications to AWS, or already building applications on AWS, we have resources to help you protect your data and meet your business continuity objectives. Our data protection and resiliency features and solutions can help you meet your business continuity goals and deliver disaster recovery during data loss events, across recovery point and time objectives (RPO and RTO). With the unprecedented data growth happening in the world today, determining where your data is stored, how it’s secured, and who has access to it is a higher priority than ever. Be sure to join the Protect data in AWS amid a rapidly evolving cyber landscape session to learn more.

When moving data to the cloud, you need to understand where you’re moving it for different use cases, the types of data you’re moving, and the network resources available, among other considerations. There are many reasons to move to the cloud, recently, Enterprise Strategy Group (ESG) validated that organizations reduced compute, networking, and storage costs by up to 66 percent by migrating on-premises workloads to AWS Cloud infrastructure. ESG confirmed that migrating on-premises workloads to AWS provides organizations with reduced costs, increased performance, improved operational efficiency, faster time to value, and improved business agility.
We have a number of sessions that discuss how to move to the cloud, based on your use case. I’m most looking forward to the Hybrid cloud storage and edge compute: AWS, where you need it session, which will discuss considerations for workloads that can’t fully move to the cloud.

Tune in to learn from experts about new announcements, leadership insights, and educational content related to the broad portfolio of AWS Storage services and features that address all these themes and more. Today, we have announcements related to Amazon Simple Storage Service (Amazon S3), Amazon FSx for Lustre, Amazon FSx for Windows File Server, Amazon Elastic File System (Amazon EFS), Amazon FSx for OpenZFS, and more.

Let’s get into it.

15 Years of Amazon EBS
Not long ago, I was reading Jeff Barr’s post titled 15 Years of AWS Blogging! In this post, Jeff mentioned a few posts he wrote for the earliest AWS services and features. Amazon Elastic Block Store (Amazon EBS) is on this list as a service that simplifies the use of Amazon EC2.

Well, it’s been 15 years since the launch of Amazon EBS was announced, and today we celebrate 15 years of this service. If you were one of the original users who put Amazon EBS to good use and provided us with the very helpful feedback that helped us invent and simplify, iterate and improve, I’m sure you can’t believe how time flies. Today, Amazon EBS handles more than 100 trillion I/O operations daily, and over 390 million EBS volumes are created every day.

If you’re new to Amazon EBS, join us for a fireside chat with Matt Garman, Senior Vice President, Sales, Marketing, and Global Services at AWS, and learn the strategy and customer challenges behind the launch of the service in 2008. You’ll also hear from long-term EBS customer, Stripe, about its growth with EBS since Stripe was launched 12 years ago.

Amazon EBS has continuously improved its scalability and performance to support more customer workloads as the direct storage attachment for Amazon EC2 instances. With the launch of Amazon EC2 M7i instances, powered by custom 4th Generation Intel Xeon Scalable processors, on August 2, you can attach up to 128 Amazon EBS volumes, an increase from 28 on a previous generation M6i instance. The higher number of volume attachments means you can increase storage density per instance and improve resource utilization, reducing total compute cost.

You can host up to 127 containers per instance for larger database applications and scale them more cost effectively before needing to provision more instances and only pay for resources you need. With a higher number of volume attachments, you can fully utilize the memory and vCPU available on these powerful M7i instances as your database storage footprint grows. EBS is also increasing the number of multi-volume snapshots you can create, for up to 128 EBS volumes attached to an instance, enabling you to create crash-consistent backups of all volumes attached to an instance.

Join the 15 years of innovations with Amazon EBS session for a discussion about how the original vision for Amazon EBS has evolved to meet your growing demands for cloud infrastructure.

Mountpoint for Amazon S3
Now generally available, Mountpoint for Amazon S3 is a new open source file client that delivers high throughput access, lowering compute costs for data lakes on Amazon S3. Mountpoint for Amazon S3 is a file client that translates local file system API calls to S3 object API calls. Using Mountpoint for Amazon S3, you can mount an Amazon S3 bucket as a local file system on your compute instance, to access your objects through a file interface with the elastic storage and throughput of Amazon S3. Mountpoint for Amazon S3 supports sequential and random read operations on existing files, and sequential write operations for creating new files.

The Deep dive and demo of Mountpoint for Amazon S3 session demonstrates how to use the file client to access objects in Amazon S3 using file APIs, making it easier to store data at scale and maximize the value of your data with analytics and machine learning workloads. Read this blog post to learn more about Mountpoint for Amazon S3 and how to get started, including a demo.

Put Cold Storage to Work Faster with Amazon S3 Glacier Flexible Retrieval
Amazon S3 Glacier Flexible Retrieval improves data restore time by up to 85 percent, at no additional cost. Faster data restores automatically apply to the Standard retrieval tier when using Amazon S3 Batch Operations. These restores begin to return objects within minutes, so you can process restored data faster. Processing restored data in parallel with ongoing restores helps you accelerate data workflows and quickly respond to business needs. Now, whether you’re transcoding media, restoring operational backups, training machine learning models, or analyzing historical data, you can speed up your data restores from archive.

Coupled with the S3 Glacier improvements to restore throughput by up to 10 times for millions of objects announced in 2022, S3 Glacier data restores of all sizes now benefit from both faster starts and shorter completion times.

Join the Maximize the value of cold data with Amazon S3 Glacier session to learn how Amazon S3 Glacier is helping organizations of all sizes and from all industries transform their data archiving to unlock business value, increase agility, and save on storage costs. Read this blog post to learn more about the Amazon S3 Glacier Flexible Retrieval performance improvements and follow step-by-step guidance on how to get started with faster standard retrievals from S3 Glacier Flexible Retrieval.

Supporting a Broad Spectrum of File Workloads
To serve a broad spectrum of use cases that rely on file systems, we offer a portfolio of file system services, each targeting a different set of needs. Amazon EFS is a serverless file system built to deliver an elastic experience for sharing data across compute resources. Amazon FSx makes it easier and cost-effective for you to launch, run, and scale feature-rich, high-performance file systems in the cloud, enabling you to move to the cloud with no changes to your code, processes, or how you manage your data.

Power ML research and big data analytics with Amazon EFS
Amazon EFS offers serverless and fully scalable file storage, designed for high scalability in both storage capacity and throughput performance. Just last week, we announced enhanced support for faster read and write IOPS, making it easier to power more demanding workloads. We’ve improved the performance capabilities of Amazon EFS by adding support for up to 55,000 read IOPS and up to 25,000 write IOPS per file system. These performance enhancements help you to run more demanding workflows, such as machine learning (ML) research with KubeFlow, financial simulations with IBM Symphony, and big data processing with Domino Data Lab, Hadoop, and Spark.

Join the Build and run analytics and SaaS applications at scale session to hear how recent Amazon EFS performance improvements can help power more workloads.

File release on Amazon FSx for Lustre
File release for Amazon FSx for Lustre helps users manage their high-performance Lustre file system and save costs by giving them the ability to move cold data to Amazon S3. File release extends FSx for Lustre’s S3 integration by releasing file data that is synchronized with S3 from Lustre. You can release data from your FSx for Lustre file system by running or scheduling release data repository tasks, which enable you to specify criteria for which files to release. Use file release to tier colder data to Amazon S3 and let users and applications continue to write new data to FSx for Lustre. If needed, you can quickly and easily retrieve released file data and access files that have been released because the file metadata for released files stays on your FSx for Lustre file system.

Join the Run compute-heavy workloads at cloud scale session to learn more about file release for Amazon FSx for Lustre.

Multi-AZ file systems on Amazon FSx for OpenZFS
You can now use a multi-AZ deployment option when creating file systems on Amazon FSx for OpenZFS, making it easier to deploy file storage that spans multiple AWS Availability Zones to provide multi-AZ resilience for business-critical workloads. With this launch, you can take advantage of the power, agility, and simplicity of Amazon FSx for OpenZFS for a broader set of workloads, including business-critical workloads like database, line-of-business, and web-serving applications that require highly available shared storage that spans multiple AZs.

The new multi-AZ file systems are designed to deliver high levels of performance to serve a broad variety of workloads, including performance-intensive workloads such as financial services analytics, media and entertainment workflows, semiconductor chip design, and game development and streaming, up to 21 GB per second of throughput and over 1 million IOPS for frequently accessed cached data, and up to 10 GB per second and 350,000 IOPS for data accessed from persistent disk storage.

Join the Migrate NAS to AWS to reduce TCO and gain agility session to learn more about multi-AZs with Amazon FSx for OpenZFS.

New, Higher Throughput Capacity Levels on Amazon FSx for Windows File Server
Performance improvements for Amazon FSx for Windows File Server help you accelerate time-to-results for performance-intensive workloads such as SQL Server databases, media processing, cloud video editing, and virtual desktop infrastructure (VDI).

We’re adding four new, higher throughput capacity levels to increase the maximum I/O available up to 12 GB per second from the previous I/O of 2 GB per second. These throughput improvements come with correspondingly higher levels of disk IOPS, designed to deliver an increase up to 350,000 IOPS.

In addition, by using FSx for Windows File Server, you can provision IOPS higher than the default 3 IOPS per GiB for your SSD file system. This allows you to scale SSD IOPS independently from storage capacity, allowing you to optimize costs for performance-sensitive workloads.

Join the Migrate NAS to AWS to reduce TCO and gain agility session to learn more about the performance improvements for Amazon FSx for Windows File Server.

Logically Air-Gapped Vault for AWS Backup
AWS Backup is a fully managed, policy-based data protection solution that enables customers to centralize and automate backup restores across 19 AWS services (spanning compute, storage, and databases) and third-party applications such as VMware Cloud on AWS and on-premises, as well as SAP HANA on Amazon EC2.

Today, we’re announcing the preview of logically air-gapped vault as a new type of AWS Backup Vault that acts as an additional layer of protection to mitigate against malware events. With logically air-gapped vault, customers can recover their application data through a different trusted account.

Join the Deep dive on data recovery for ransomware events session to learn more about logically air-gapped vault for AWS Backup.

Copy Data to and from Other Clouds with AWS DataSync
AWS DataSync is an online data movement and discovery service that simplifies data migration and helps you quickly, easily, and securely transfer your file or object data to, from, and between AWS storage services. In addition to support of data migration to and from AWS storage services, DataSync supports copying to and from other clouds such as Google Cloud Storage, Azure Files, and Azure Blob Storage. Using DataSync, you can move your object data at scale between Amazon S3 compatible storage on other clouds and AWS storage services such as Amazon S3. We’re now expanding the support of DataSync for copying data to and from other clouds to include DigitalOcean Spaces, Wasabi Cloud Storage, Backblaze B2 Cloud Storage, Cloudflare R2 Storage, and Oracle Cloud Storage.

Join the Identify and accelerate data migrations at scale session to learn more about this expanded support for DataSync.

Join Us Online
Join us today for the AWS Storage Day virtual event on the AWS On Air channel on Twitch. The event will be live starting at 9:00 AM Pacific Time (12:00 PM Eastern Time) on August 9. All sessions will be available on demand approximately two days after Storage Day.

We look forward to seeing you on Twitch!

– Veliswa 

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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:

$ wget https://s3.amazonaws.com/mountpoint-s3-release/latest/x86_64/mount-s3.rpm
$ sudo yum install ./mount-s3.rpm

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:

$ mkdir wsdot-ferry
$  mount-s3 wsdot-ferry wsdot-ferry

I can traverse the mount point and inspect the bucket:

$ cd wsdot-ferry
$ ls -l | head -10
total 0
drwxr-xr-x 2 jeff jeff 0 Aug  7 23:07 2020_12_30
drwxr-xr-x 2 jeff jeff 0 Aug  7 23:07 2020_12_31
drwxr-xr-x 2 jeff jeff 0 Aug  7 23:07 2021_01_01
drwxr-xr-x 2 jeff jeff 0 Aug  7 23:07 2021_01_02
drwxr-xr-x 2 jeff jeff 0 Aug  7 23:07 2021_01_03
drwxr-xr-x 2 jeff jeff 0 Aug  7 23:07 2021_01_04
drwxr-xr-x 2 jeff jeff 0 Aug  7 23:07 2021_01_05
drwxr-xr-x 2 jeff jeff 0 Aug  7 23:07 2021_01_06
drwxr-xr-x 2 jeff jeff 0 Aug  7 23:07 2021_01_07
$
$  cd 2020_12_30
$ ls -l
total 0
drwxr-xr-x 2 jeff jeff 0 Aug  7 23:07 fauntleroy_holding
drwxr-xr-x 2 jeff jeff 0 Aug  7 23:07 fauntleroy_way
drwxr-xr-x 2 jeff jeff 0 Aug  7 23:07 lincoln
drwxr-xr-x 2 jeff jeff 0 Aug  7 23:07 trenton
drwxr-xr-x 2 jeff jeff 0 Aug  7 23:07 vashon_112_north
drwxr-xr-x 2 jeff jeff 0 Aug  7 23:07 vashon_112_south
drwxr-xr-x 2 jeff jeff 0 Aug  7 23:07 vashon_bunker_north
drwxr-xr-x 2 jeff jeff 0 Aug  7 23:07 vashon_bunker_south
drwxr-xr-x 2 jeff jeff 0 Aug  7 23:07 vashon_holding
$
$ cd fauntleroy_holding
$  ls -l | head -10
total 2680
-rw-r--r-- 1 jeff jeff  19337 Feb 10  2021 17-12-01.jpg
-rw-r--r-- 1 jeff jeff  19380 Feb 10  2021 17-15-01.jpg
-rw-r--r-- 1 jeff jeff  19080 Feb 10  2021 17-18-01.jpg
-rw-r--r-- 1 jeff jeff  17700 Feb 10  2021 17-21-01.jpg
-rw-r--r-- 1 jeff jeff  17016 Feb 10  2021 17-24-01.jpg
-rw-r--r-- 1 jeff jeff  16638 Feb 10  2021 17-27-01.jpg
-rw-r--r-- 1 jeff jeff  16713 Feb 10  2021 17-30-01.jpg
-rw-r--r-- 1 jeff jeff  16647 Feb 10  2021 17-33-02.jpg
-rw-r--r-- 1 jeff jeff  16750 Feb 10  2021 17-36-01.jpg
$

I can create my animation with a single command:

$ ffmpeg -framerate 10 -pattern_type glob -i "*.jpg" ferry.gif

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;

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