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

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

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

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

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

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

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

— seb

Amazon Neptune is a fully managed graph database service that makes it easy to build and run applications that work with highly connected datasets. With Neptune, you can use open and popular graph query languages to execute powerful queries that are easy to write and perform well on connected data. You can use Neptune for graph use cases such as recommendation engines, fraud detection, knowledge graphs, drug discovery, and network security.

Neptune has always been fully managed and handles time-consuming tasks such as provisioning, patching, backup, recovery, failure detection and repair. However, managing database capacity for optimal cost and performance requires you to monitor and reconfigure capacity as workload characteristics change. Also, many applications have variable or unpredictable workloads where the volume and complexity of database queries can change significantly. For example, a knowledge graph application for social media may see a sudden spike in queries due to sudden popularity.

Introducing Amazon Neptune Serverless
Today, we’re making that easier with the launch of Amazon Neptune Serverless. Neptune Serverless scales automatically as your queries and your workloads change, adjusting capacity in fine-grained increments to provide just the right amount of database resources that your application needs. In this way, you pay only for the capacity you use. You can use Neptune Serverless for development, test, and production workloads and optimize your database costs compared to provisioning for peak capacity.

With Neptune Serverless you can quickly and cost-effectively deploy graphs for your modern applications. You can start with a small graph, and as your workload grows, Neptune Serverless will automatically and seamlessly scale your graph databases to provide the performance you need. You no longer need to manage database capacity and you can now run graph applications without the risk of higher costs from over-provisioning or insufficient capacity from under-provisioning.

With Neptune Serverless, you can continue to use the same query languages (Apache TinkerPop Gremlin, openCypher, and RDF/SPARQL) and features (such as snapshots, streams, high availability, and database cloning) already available in Neptune.

Let’s see how this works in practice.

Creating an Amazon Neptune Serverless Database
In the Neptune console, I choose Databases in the navigation pane and then Create database. For Engine type, I select Serverless and enter my-database as the DB cluster identifier.

I can now configure the range of capacity, expressed in Neptune capacity units (NCUs), that Neptune Serverless can use based on my workload. I can now choose a template that will configure some of the next options for me. I choose the Production template that by default creates a read replica in a different Availability Zone. The Development and Testing template would optimize my costs by not having a read replica and giving access to DB instances that provide burstable capacity.

For Connectivity, I use my default VPC and its default security group.

Finally, I choose Create database. After a few minutes, the database is ready to use. In the list of databases, I choose the DB identifier to get the Writer and Reader endpoints that I am going to use later to access the database.

Using Amazon Neptune Serverless
There is no difference in the way you use Neptune Serverless compared to a provisioned Neptune database. I can use any of the query languages supported by Neptune. For this walkthrough, I choose to use openCypher, a declarative query language for property graphs originally developed by Neo4j that was open-sourced in 2015 and contributed to the openCypher project.

To connect to the database, I start an Amazon Linux Amazon Elastic Compute Cloud (Amazon EC2) instance in the same AWS Region and associate the default security group and a second security group that gives me SSH access.

With a property graph I can represent connected data. In this case, I want to create a simple graph that shows how some AWS services are part of a service category and implement common enterprise integration patterns.

I use curl to access the Writer openCypher HTTPS endpoint and create a few nodes that represent patterns, services, and service categories. The following commands are split into multiple lines in order to improve readability.

curl https://<my-writer-endpoint>:8182/openCypher 
-d "query=CREATE (mq:Pattern {name: 'Message Queue'}),
(pubSub:Pattern {name: 'Pub/Sub'}),
(eventBus:Pattern {name: 'Event Bus'}),
(workflow:Pattern {name: 'WorkFlow'}),
(applicationIntegration:ServiceCategory {name: 'Application Integration'}),
(sqs:Service {name: 'Amazon SQS'}), (sns:Service {name: 'Amazon SNS'}),
(eventBridge:Service {name: 'Amazon EventBridge'}), (stepFunctions:Service {name: 'AWS StepFunctions'}),
(sqs)-[:IMPLEMENT]->(mq), (sns)-[:IMPLEMENT]->(pubSub),
(eventBridge)-[:IMPLEMENT]->(eventBus),
(stepFunctions)-[:IMPLEMENT]->(workflow),
(applicationIntegration)-[:CONTAIN]->(sqs),
(applicationIntegration)-[:CONTAIN]->(sns),
(applicationIntegration)-[:CONTAIN]->(eventBridge),
(applicationIntegration)-[:CONTAIN]->(stepFunctions);"

This is a visual representation of the nodes and their relationships for the graph created by the previous command. The type (such as Service or Pattern) and properties (such as name) are shown inside each node. The arrows represent the relationships (such as CONTAIN or IMPLEMENT) between the nodes.

Now, I query the database to get some insights. To query the database, I can use either a Writer or a Reader endpoint. First, I want to know the name of the service implementing the “Message Queue” pattern. Note how the syntax of openCypher resembles that of SQL with MATCH instead of SELECT.

curl https://<my-endpoint>:8182/openCypher 
-d "query=MATCH (s:Service)-[:IMPLEMENT]->(p:Pattern {name: 'Message Queue'}) RETURN s.name;"

{
  "results" : [ {
    "s.name" : "Amazon SQS"
  } ]
}

I use the following query to see how many services are in the “Application Integration” category. This time, I use the WHERE clause to filter results.

curl https://<my-endpoint>:8182/openCypher 
-d "query=MATCH (c:ServiceCategory)-[:CONTAIN]->(s:Service) WHERE c.name='Application Integration' RETURN count(s);"

{
  "results" : [ {
    "count(s)" : 4
  } ]
}

There are many options now that I have this graph database up and running. I can add more data (services, categories, patterns) and more relationships between the nodes. I can focus on my application and let Neptune Serverless manage capacity and infrastructure for me.

Availability and Pricing
Amazon Neptune Serverless is available today in the following AWS Regions: US East (Ohio, N. Virginia), US West (N. California, Oregon), Asia Pacific (Tokyo), and Europe (Ireland, London).

With Neptune Serverless, you only pay for what you use. The database capacity is adjusted to provide the right amount of resources you need in terms of Neptune capacity units (NCUs). Each NCU is a combination of approximately 2 gibibytes (GiB) of memory with corresponding CPU and networking. The use of NCUs is billed per second. For more information, see the Neptune pricing page.

Having a serverless graph database opens many new possibilities. To learn more, see the Neptune Serverless documentation. Let us know what you build with this new capability!

Simplify the way you work with highly connected data using Neptune Serverless.

— Danilo

Last week, we announced plans to launch the AWS Asia Pacific (Bangkok) Region, which will become our third AWS Region in Southeast Asia. This Region will have three Availability Zones and will give AWS customers in Thailand the ability to run workloads and store data that must remain in-country.

In the Works – AWS Region in Thailand
With this big news, AWS announced a 190 billion baht (US 5 billion dollars) investment to drive Thailand’s digital future over the next 15 years. It includes capital expenditures on the construction of data centers, operational expenses related to ongoing utilities and facility costs, and the purchase of goods and services from Regional businesses.

Since we first opened an office in Bangkok in 2015, AWS has launched 10 Amazon CloudFront edge locations, a highly secure and programmable content delivery network (CDN) in Bangkok. In 2020, we launched AWS Outposts, a family of fully managed solutions delivering AWS infrastructure and services to virtually any on-premises or edge location for a truly consistent hybrid experience in Thailand. This year, we also plan the upcoming launch of an AWS Local Zone in Bangkok, which will enable customers to deliver applications that require single-digit millisecond latency to end users in Thailand.

Photo courtesy of Conor McNamara, Managing Director, ASEAN at AWS

The new AWS Region in Thailand is also part of our broader, multifaceted investment in the country, covering our local team, partners, skills, and the localization of services, including Amazon Transcribe, Amazon Translate, and Amazon Connect.

Many Thailand customers have chosen AWS to run their workloads to accelerate innovation, increase agility, and drive cost savings, such as 2C2P, CP All Plc., Digital Economy Promotion Agency, Energy Response Co. Ltd. (ENRES), PTT Global Public Company Limited (PTT), Siam Cement Group (SCG), Sukhothai Thammathirat Open University, The Stock Exchange of Thailand, Papyrus Studio, and more.

For example, Dr. Werner Vogels, CTO of Amazon.com, introduced the story of Papyrus Studio, a large film studio and one of the first customers in Thailand.

“Customer stories like Papyrus Studio inspire us at AWS. The cloud can allow a small company to rapidly scale and compete globally. It also provides new opportunities to create, innovate, and identify business opportunities that just aren’t possible with conventional infrastructure.”

For more information on how to enable AWS and get support in Thailand, contact our AWS Thailand team.

Last Week’s Launches
My favorite news of last week was to launch dark mode as a beta feature in the AWS Management Console. In Unified Settings, you can choose between three settings for visual mode: Browser default, Light, and Dark. Browser default applies the default dark or light setting of the browser, dark applies the new built-in dark mode, and light maintains the current look and feel of the AWS console. Choose your favorite!

Here are some launches that caught my eye for web, mobile, and IoT application developers:

New AWS Amplify Library for Swift – We announce the general availability of Amplify Library for Swift (previously Amplify iOS). Developers can use Amplify Library for Swift via the Swift Package Manager to build apps for iOS and macOS (currently in beta) platforms with Auth, Storage, Geo, and more features.

The Amplify Library for Swift is open source on GitHub, and we deeply appreciate the feedback we have gotten from the community. To learn more, see Introducing the AWS Amplify Library for Swift in the AWS Front-End Web & Mobile Blog or Amplify Library for Swift documentation.

New Amazon IVS Chat SDKs – Amazon Interactive Video Service (Amazon IVS) now provides SDKs for stream chat with support for web, Android, and iOS. The Amazon IVS stream chat SDKs support common functions for chat room resource management, sending and receiving messages, and managing chat room participants.

Amazon IVS is a managed, live-video streaming service using the broadcast SDKs or standard streaming software such as Open Broadcaster Software (OBS). The service provides cross-platform player SDKs for playback of Amazon IVS streams you need to make low-latency live video available to any viewer around the world. Also, it offers Chat Client Messaging SDK. For more information, see Getting Started with Amazon IVS Chat in the AWS documentation.

New AWS Parameters and Secrets Lambda Extension – This is new extension for AWS Lambda developers to retrieve parameters from AWS Systems Manager Parameter Store and secrets from AWS Secrets Manager. Lambda function developers can leverage this extension to improve their application performance as it decreases the latency and the cost of retrieving parameters and secrets.

Previously, you had to initialize either the core library of a service or the entire service SDK inside a Lambda function for retrieving secrets and parameters. Now you can simply use the extension. To learn more, see AWS Systems Manager Parameter Store documentation and AWS Secrets Manager documentation.

New FreeRTOS Long Term Support Version – We announce the second release of FreeRTOS Long Term Support (LTS) – FreeRTOS 202210.00 LTS. FreeRTOS LTS offers a more stable foundation than standard releases as manufacturers deploy and later update devices in the field. This release includes new and upgraded libraries such as AWS IoT Fleet Provisioning, Cellular LTE-M Interface, coreMQTT, and FreeRTOS-Plus-TCP.

All libraries included in this FreeRTOS LTS version will receive security and critical bug fixes until October 2024. With an LTS release, you can continue to maintain your existing FreeRTOS code base and avoid any potential disruptions resulting from FreeRTOS version upgrades. To learn more, see the FreeRTOS announcement.

Here is some news on performance improvement and increasing capacity:

Up to 10X Improving Amazon Aurora Snapshot Exporting Speed – Amazon Aurora MySQL-Compatible Edition for MySQL 5.7 and 8.0 now speed up to 10x faster snapshot exports to Amazon S3. The performance improvement is automatically applied to all types of database snapshot exports, including manual snapshots, automated system snapshots, and snapshots created by the AWS Backup service. For more information, see Exporting DB cluster snapshot data to Amazon S3 in the Amazon Aurora documentation.

3X Increasing Amazon RDS Read Capacity – Amazon Relational Database Service (RDS) for MySQL, MariaDB, and PostgreSQL now supports 15 read replicas per instance, including up to 5 cross-Region read replicas, delivering up to 3x the previous read capacity. For more information, see Working with read replicas in the Amazon RDS documentation.

2X Increasing AWS Snowball Edge Compute Capacity – The AWS Snowball Edge Compute Optimized device doubled the compute capacity up to 104 vCPUs, doubled the memory capacity up to 416GB RAM, and is now fully SSD with 28TB NVMe storage. The updated device is ideal when you need dense compute resources to run complex workloads such as machine learning inference or video analytics at the rugged, mobile edge such as trucks, aircraft or ships.  You can get started by ordering a Snowball Edge device on the AWS Snow Family console.

2X Increasing Amazon SQS FIFO Default Quota – Amazon Simple Queue Service (SQS) announces the increase of default quota up to 6,000 transactions per second per API action. It is double the previous 3,000 throughput quota for a high throughput mode for FIFO (first in, first out) queues in all AWS Regions where Amazon SQS FIFO queue is available. For a detailed breakdown of default throughput quotas per Region, see Quotas related to messages in the Amazon SQS documentation.

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 other news items that you may find interesting:

22 New or Updated Open Datasets on AWS – We released 22 new or updated datasets, including Amazonia-1 imagery, Bitcoin and Ethereum data, and elevation data over the Arctic and Antarctica. The full list of publicly available datasets is on the Registry of Open Data on AWS and is now also discoverable on AWS Data Exchange.

Sustainability with AWS Partners (ft. AWS On Air) – This episode covers a broad discipline of environmental, social, and governance (ESG) issues across all regions, organization types, and industries. AWS Sustainability & Climate Tech provides a comprehensive portfolio of AWS Partner solutions built on AWS that address climate change events and the United Nation’s Sustainable Development Goals (SDG).

AWS Open Source News and Updates #131 – This newsletter covers latest open-source projects such as Amazon EMR Toolkit for VS Code, a VS Code Extension to make it easier to develop Spark jobs on EMR and AWS CDK For Discourse, sample codes that demonstrates how to create a full environment for Discourse, etc. Remember to check out the Open source at AWS keep up to date with all our activity in open source by following us on @AWSOpen.

Upcoming AWS Events
Check your calendars and sign up for these AWS events:

AWS re:Invent 2022 Attendee Guide – Browse re:Invent 2022 attendee guides, curated by AWS Heroes, AWS industry teams, and AWS Partners. Each guide contains recommended sessions, tips and tricks for building your agenda, and other useful resources. Also, seat reservations for all sessions are now open for all re:Invent attendees. You can still register for AWS re:Invent either offline or online.

AWS AI/ML Innovation Day on October 25 – Join us for this year’s AWS AI/ML Innovation Day, where you’ll hear from Bratin Saha and other leaders in the field about the great strides AI/ML has made in the past and the promises awaiting us in the future.

AWS Container Day at Kubecon 2022 on October 25–28 – Come join us at KubeCon + CloudNativeCon North America 2022, where we’ll be hosting AWS Container Day Featuring Kubernetes on October 25 and educational sessions at our booth on October 26–28. Throughout the event, our sessions focus on security, cost optimization, GitOps/multi-cluster management, hybrid and edge compute, and more.

You can browse all upcoming in-person, and virtual events.

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

— Channy

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!