In Cloud Computing This Week [May 6th 2022]

Amazon SageMaker Canvas is a visual point-and-click interface that enables business analysts to generate accurate ML predictions on their own — without requiring any machine learning experience or having to write a single line of code. SageMaker Canvas makes it easy to access and combine data from a variety of sources, automatically clean data and apply a variety of data adjustments, and build ML models to generate accurate predictions with a few clicks.

This week, Amazon SageMaker Canvas announced new data preparation features that make it easier to manage, explore, and modify datasets before building ML models. Key features include:

•  Filtering rows to explore and modify datasets: You can now preview and remove rows with missing values and outliers. You can also specify additional conditions to preview and remove rows from your dataset. For example, for numeric data types, you can specify conditions such as greater than, less than, equal to, in between and more. The list of supported conditions vary by data type and are documented here
• Expanded timestamp formats and transforms to extract date, time: You can now extract date and time information from the timestamp column and create new columns. This makes it easy to prepare and transform your time series data and add the transform to your model recipe with just a few clicks. Additionally, SageMaker Canvas now supports multiple timestamp formats making it easy to work with timeseries data for forecasting problems. For a full list of timestamp formats and date, time extraction capabilities, please see here

In addition to the above listed data preparation and transformation features, you can now rename datasets and columns for ease of use. Other usability updates include improved user facing messages with recommended actions, and visibility into dataset cell count before building an ML model.

Amazon Interactive Video Service (Amazon IVS) announces its first points of presence (PoPs) in Argentina and Chile located in Buenos Aires and Santiago. The new edge locations will enable streamers and viewers based in Argentina and Chile to enjoy lower latency, better video quality, and increased capacity.

Alongside the new Buenos Aires and Santiago edge locations, AWS have updated pricing to include Argentina and Chile into a new South America region that also includes Brazil. To learn more about Amazon IVS pricing, including pricing for Argentina and Chile, visit the pricing page.

The new Amazon ElastiCache console provides you with an intuitive way to manage ElastiCache resources with simpler navigation and richer contextual information. The new console provides a more consistent look and feel with other AWS service consoles.

The new ElastiCache dashboard provides an overview of most important actions, resources and information. AWS restructured and simplified the cluster creation experience for ElastiCache for Redis and ElastiCache for Memcached. The new console also helps you perform tasks faster by providing you with contextual information and help panels. AWS have also redesigned the user and user group management pages with new controls, making interaction much more intuitive.

AWS Lambda customers can now enable functions to access Amazon Elastic File System (Amazon EFS) in the Asia Pacific (Jakarta) Region. With AWS Lambda support for Amazon EFS, customers can easily share data across function invocations, read large reference data files, and write function output to a persistent and shared data store.

Customers can use AWS Lambda with Amazon EFS to build data-intensive applications, load larger libraries and models, process larger amounts of data in a highly distributed manner, and share data across functions, containers, and instances. AWS Lambda will automatically mount the file system and provide a local path to read and write data at low latency.

AWS Service Catalog Provisioning constructs for the AWS Cloud Development Kit (AWS CDK) are now available for builders to create application infrastructure in code that provisions cloud resources from their approved Service Catalog products. Service Catalog builders can now create their AWS CDK applications with approved constructs in familiar programming languages like Typescript and Python directly in their Integrated Development Environment. Using cdk-import, builders can access a library of Provisioning constructs in their local development environment for the AWS Service Catalog products they have access to provision which automatically include the governance that their administrators have configured.

Following inline guidance in their local development environment and automatically generated comments within their locally-installed constructs, builders can model complex application infrastructure that meets enterprise requirements with a few lines of code in a few minutes. When deploying CDK applications that contain one or more Provisioning constructs, AWS Service Catalog creates provisioned products reflective of those constructs and their configurations.

AWS Certificate Manager (ACM) Private Certificate Authority (CA) is now available in the Asia Pacific (Jakarta) Region. This regional expansion extends the availability of ACM Private CA across the globe, increasing the number of regions to 24. The Jakarta Region supports CAs with the private key stored in a FIPS 140-2 level 2 HSM. To learn more about the key storage certification level see the AWS Private CA Documentation.

ACM Private CA is a managed private CA service that helps you easily and securely manage the lifecycle of your private certificates. ACM Private CA provides you a highly-available private CA service without the upfront investment and ongoing maintenance costs of operating your own private CA. ACM Private CA extends ACM’s certificate management capabilities to private certificates, enabling you to manage public and private certificates centrally.

Amazon Relational Database Service (Amazon RDS) for PostgreSQL announces support for PostgreSQL 14 with three levels of cascaded read replicas, 5 replicas per instance, supporting a maximum of up to 155 read replicas per source instance. You can now create Single-AZ or Multi-AZ cascaded read replica DB instances in same region or any one cross region from another read replica instance, enabling you to build a more robust disaster recovery architecture.

Starting with Amazon RDS for PostgreSQL 14.1 and higher, read intensive workloads such as data analytics can now benefit from up to 155 cascaded read replicas that offer up to 30 times higher read capacity versus previous versions of PostgreSQL, thereby reducing the load on source instance. You can now also pre-create read replicas for your selected disaster recovery target read replica and utilize read scaling immediately after promoting the target. The cascaded read replicas also come with the option to enable automated backup that allows for a quicker promotion of read replica to source instance since only incremental snapshot is required for the promoted read replica. See Working with PostgreSQL read replicas in Amazon RDS to learn more about cascaded read replicas on RDS PostgreSQL.

Now you can use the AWS Serverless Application Model (AWS SAM) CLI to enable AWS X-Ray tracing in your AWS SAM templates automatically, without manually authoring your AWS SAM templates. This makes it easier to centrally manage AWS X-Ray tracing across your Lambda functions in your serverless application.

The AWS SAM CLI is a developer tool that makes it easier to initialize, build, package, test on local and cloud, and deploy serverless applications. AWS X-Ray helps you analyze and debug your distributed applications, such as those built using a microservices architecture. AWS X-Ray provides an end-to-end view of requests as they travel through your application, making it easier to monitor and troubleshoot complex serverless architectures. Enabling tracing through the AWS SAM CLI reduces the complexity of setting up tracing on each of your Lambda functions.

AWS Trusted Advisor adds 4 checks automatically ingested from AWS Compute Optimizer. AWS Trusted Advisor provides recommendations that help you follow AWS best practices. Trusted Advisor evaluates your account by using checks to identify opportunities for you to improve security and performance, reduce costs, and monitor service quotas. This week, AWS Compute Optimizer checks are available in the Business Support, Enterprise Support On-Ramp, and Enterprise Support plans. The new checks are:

• Amazon EBS over-provisioned volumes
• Amazon EBS under-provisioned volumes
• AWS Lambda over-provisioned functions for memory size
• AWS Lambda under-provisioned functions for memory size

These checks are available to view in the AWS Trusted Advisor Console and accessible via the AWS Support API. Customers of Trusted Advisor will be directed to Compute Optimizer for deeper investigations and advanced actions.

AWS RoboMaker, a service that makes it easy to simulate robotics applications at scale, is now available in the in the AWS GovCloud (US-West) Region. Support in the GovCloud Region allows U.S. government agencies and contractors to run sensitive simulation workloads in AWS RoboMaker by addressing their specific regulatory and compliance requirements.

AWS RoboMaker provides a robotics simulation service to enable robotics developers to run, scale, and automate simulation without managing any infrastructure. To get started, one can explore the RoboMaker webpage.

Amazon Managed Service for Prometheus is now available in Europe (London) Region. Amazon Managed Service for Prometheus is a fully managed Prometheus-compatible monitoring service that makes it easy to monitor and alarm on operational metrics at scale. Prometheus is a popular Cloud Native Computing Foundation open-source project for monitoring and alerting that is optimized for container environments.

Amazon Managed Service for Prometheus is now generally available in the following regions: US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Europe (Frankfurt), Europe (Ireland), Europe (Stockholm), and Europe (London) Regions.

This week Amazon Kinesis Video Streams announces new APIs and SDKs to help you extract images from your video streams. This fully-managed capability allows customers to request images via API calls or configure automatic image generation based on metadata tags in ingested video. 

AWS customers can use this new functionality to generate images for playback applications such as thumbnails or enhanced timeline scrubbing. They can also generate images for Machine Learning pipelines, including Amazon Sagemaker, Amazon Rekognition, or custom solutions. 

Amazon Elastic Kubernetes Service (Amazon EKS) now allows you to see all standard Kubernetes API resource types running on your Amazon EKS cluster using the AWS Management Console. This makes it easy to visualize and troubleshoot your Kubernetes applications using Amazon EKS.

Amazon EKS is a fully managed Kubernetes service. Until now, the Amazon EKS console only supported viewing workload specific resources, such as deployments, jobs and DaemonSets running in your cluster. You needed to install and run additional tools to view, understand, and troubleshoot any other Kubernetes resource type.

The updated Amazon EKS console now includes all standard Kubernetes API resource types such as service resources, configuration and storage resources, authorization resources, policy resources and more. You can easily filter your Kubernetes resources by a specific namespace and search by property values, making it quick and easy to find objects, all within a single consistent experience in the console.

In the latest release of the AWS AppConfig Lambda Extension, there is support for Arm/Graviton2 processors. Using AWS AppConfig, a feature of AWS Systems Manager, customers can easily create feature flags or other dynamic/runtime configuration and safely deploy updates. The AWS AppConfig Lambda Extension allows customers to access this feature flag and dynamic configuration data in Lambda functions.

Using Graviton2 processors for your Lambda functions may result in an up-to 34% better price/performance. If you use that processor in AWS Lambda, you can now use the AWS AppConfig Lambda Extension as well.

Amazon Managed Blockchain (AMB) announces general availability of Goerli Testnet (Goerli), a proof-of-authority test network for Ethereum. As a fully managed service, AMB's support of Goerli provides customers a stable testing environment for their distributed applications ahead of Ethereum’s upcoming consensus upgrade (The Merge), without having to manage complicated blockchain infrastructure.

With this launch, AMB customers can more easily provision Goerli nodes in minutes and connect to the public Ethereum test network (testnet). With AMB, customers get encryption at rest and transport, secure access to the network via standard open-source Ethereum APIs, fast and reliable synchronization to the Goerli, and durable elastic storage for ledger data. AMB monitors node health, replaces unhealthy nodes, and automates Goerli software upgrades, improving the availability of customers’ Goerli’s infrastructure. In addition to testing their DeFi applications, customers building analytical products such as smart contract monitoring tools and fraud detection software can also benefit from this scalable, highly available, and fully managed Goerli service. Once customers are ready for production launch, they can transition to Ethereum mainnet on AMB.

Amazon Relational Database Service (Amazon RDS) on AWS Outposts now supports manual and automatic storage scaling. AWS Outposts is a fully managed service that extends AWS infrastructure, AWS services, APIs, and tools to virtually any datacenter, co-location space, or on-premises facility for a truly consistent hybrid experience. With Amazon RDS on AWS Outposts, you can deploy managed DB instances in your on-premises environments.

Storage autoscaling provides dynamic scaling of your database storage based on your application’s needs. You can now turn on storage autoscaling when you create or modify Amazon RDS on Outposts DB instances by selecting a checkbox to "Enable storage autoscaling" and specifying the maximum database storage size.

Amazon Relational Database Service (Amazon RDS) now offers customers the option to use Internet Protocol version 6 (IPv6) addresses in their Virtual Private Cloud (VPC) on new and existing RDS instances. Customers moving to IPv6 can simplify their network stack by running their databases on a network that supports both IPv4 and IPv6.

The continued growth of the Internet is exhausting available Internet Protocol version 4 (IPv4) addresses. IPv6 increases the number of available addresses several fold and customers no longer need to manage overlapping address spaces in their VPCs. Customers can standardize their applications on the new version of Internet Protocol by moving to IPv6 with a few clicks in the AWS Management Console.

Amazon CodeGuru Reviewer is a developer tool that leverages automated reasoning and machine learning to detect potential code defects that are difficult to find and offers suggestions for improvements. This week, AWS announced the support of file/folder suppression for Amazon CodeGuru Reviewer, a new feature that allows customer to prevent CodeGuru Reviewer from surfacing findings on certain parts of their codebase.

Previously, every full repository analysis performed by CodeGuru Reviewer would scan every file/folder within a customer’s repository. Now, with the launch of CodeGuru Reviewer’s file/folder suppression, customers can specify the files and/or folders they want to be suppressed from their full repository scans. Findings can be suppressed files or folders during incremental scans (i.e. scans initiated by a pull request) as well. Customers are not charged for the lines of code within suppressed files or folders. This new feature helps customers prevent CodeGuru Reviewer from generating unwanted findings on certain files, like test files, autogenerated files, or files that have not been recently updated.

Amazon Elastic Kubernetes Service (EKS) customers can now create and manage clusters in the AWS Asia Pacific (Jakarta) Region.

Amazon EKS is a managed Kubernetes service that makes it easy for you to run Kubernetes on AWS without needing to install, operate, and maintain your own Kubernetes control plane or worker nodes. Amazon EKS is certified Kubernetes conformant, so existing applications running on upstream Kubernetes are compatible with Amazon EKS. You can also easily migrate any standard Kubernetes application to EKS without needing to refactor your code.

Support for europe-west9 (Paris).

New maintenance versions are now available through self-service maintenance. See the maintenance changelog to learn more about these new maintenance versions.

Config Controller is now supported in region europe-north1 and australia-southeast1

Added --use-private-endpoint flag to gcloud anthos config controller create to restrict access to the master's private endpoint IP of a config controller instance. Available in gcloud 378.0.0 (release note).

Added gcloud anthos config controller get-config-connector-identity which prints the default Config Connector identity, to allow easier subsequent permission grant. Available in gcloud 383.0.0 (release notes)

Let gcloud anthos config controller create prints the default Config Connector identity, to allow easier subsequent permission grant. Available in gcloud 383.0.0 (release notes)