Here's a round up of all things AWS, Azure, GCP and Hava for the week ending Friday 11th December 2020. It's been steady as she goes at Hava with the team winding up some Azure Network Diagrams planning ahead of the break.
Amazon EC2 announces Spot Blueprints, an infrastructure code template generator to get started with EC2 Spot Instances
Spot Blueprints is an infrastructure code template generator that makes it easy to start using Spot Instances. It saves time in learning to use Spot and to start leveraging the steep savings and scale that Spot offers for interruptible workloads. You can use Spot Blueprints for the most popular services used with Spot Instances, including Amazon EC2 Auto Scaling, Amazon EMR, AWS Batch, and Amazon Elastic Kubernetes Service (Amazon EKS).
Amazon Aurora with PostgreSQL compatibility can now make calls to AWS Lambda functions. AWS Lambda lets you run code without provisioning or managing servers, and without worrying about scalability.
On December 11, 2020 AWS launched the AWS Toolkit for AWS Cloud9, enabling users of the browser-based IDE to easily manage core AWS services through the graphical user interface. A key component of the AWS Toolkit is the Resource Explorer – a view that allows you to navigate and interact with your AWS resources such as AWS Lambda, Amazon API Gateway, AWS CloudFormation, Amazon S3, and more. Cloud9 will continue to increase support for other AWS resource types through the Toolkit.
Following the announcement of updates to the PostgreSQL database by the open source community, AWS have updated Amazon Aurora with PostgreSQL compatibility to support PostgreSQL versions 11.9, 10.14, and 9.6.19. These releases contain bug fixes and improvements by the PostgreSQL community.
Customers can now create HTTP APIs that route requests to the new AWS Step Functions Synchronous Express Workflows.
AWS Graviton2-based database instances are now available in preview for Amazon Aurora with PostgreSQL compatibility and Amazon Aurora with MySQL compatibility. Graviton2 instances are already generally available for Amazon RDS for MySQL, Amazon RDS for PostgreSQL, and Amazon RDS for MariaDB.
Amplify CLI helps front-end web & mobile developers provision APIs and host websites. With today’s Amplify CLI release, you gain the ability to deploy the GraphQL & REST APIs and host websites using AWS Fargate in addition to existing AppSync, API Gateway and Amplify console options. Just run the “amplify configure project” command and enable the “container-based deployments” option.
VPC Reachability Analyzer is a new feature that enables you to perform connectivity testing between resources in your virtual private clouds (VPC). With Reachability Analyzer, you can quickly troubleshoot connectivity issues caused by misconfiguration, and proactively verify that your configuration matches your network connectivity intent.
Amazon Kendra is a highly accurate and easy to use intelligent search service powered by machine learning. Starting today, AWS customers can use custom synonyms with Amazon Kendra to improve the accuracy of their search results.
Amazon EC2 now provides additional network performance metrics to help customers gain more insights into instance network performance. Five new metrics provide customers visibility when their instances exceed network allowances defined by AWS. This visibility helps you proactively resolve application performance issues and right size your instance fleets based on your desired network performance.
Amazon Redshift RA3 with managed storage is the the latest generation node type and allows you to scale compute and storage independently. Today, we're announcing RA3.xlplus - the third and smallest member of the RA3 node-family. RA3 allows you to size your cluster based primarily on your compute needs. With the introduction of RA3.xlplus, you now have even more compute sizing options to choose from to address a broader set of workload requirements.
Amazon Redshift, the most widely used cloud data warehouse, now enables a secure and easy way to share live data across Amazon Redshift clusters. Data sharing enables instant, granular, and high-performance data access across Amazon Redshift clusters without the need to copy or move data. Data Sharing provides live access to the data so that your users always see most up-to-date and consistent information as it is updated in the data warehouse.
Amazon Redshift, a fully-managed cloud data warehouse, announces preview of native support for JSON and semi-structured data. It is based on the new data type ‘SUPER’ that allows you to store the semi-structured data in Redshift tables. Redshift also adds support for the PartiQL query language to seamlessly query and process the semi-structured data. This functionality enables you to achieve advanced analytics that combine the classic structured SQL data (such as strings, numerics, and timestamps) with the semi-structured SUPER data with superior performance, flexibility, and ease-of-use.
AWS Global Accelerator announces custom routing accelerator, a new type of accelerator that allows you to use your own application logic to route user traffic to a specific Amazon EC2 destination, while still leveraging the benefits of Global Accelerator.
We are excited to announce the availability of Amazon EC2 G4ad instances that provide the best price performance for graphics intensive applications in the cloud. G4ad instances are powered by AMD Radeon Pro V520 GPUs and second-generation AMD EPYC processors, and provide up to 45% better price performance over G4dn instances for graphics intensive applications such as virtual workstations, game streaming, and graphics rendering.
Amazon Redshift, the most widely used data warehouse, now offers the ability to move an Amazon Redshift cluster to another AWS Availability Zone (AZ). The cluster relocation feature moves a cluster to another AZ in one step without requiring application changes. You can invoke the relocation function in cases where resource constraints in a given AZ are disrupting cluster operations such as the ability to resume or resize a cluster. This feature is available for use on clusters leveraging the RA3 instance family and is offered at no additional cost.
Amazon Redshift, the most widely used cloud data warehouse, announces general availability of Automatic Table Optimization, a new self-tuning capability that optimizes the physical design of tables by automatically setting sort and distribution keys to improve query speed. You can use Automatic Table Optimization to get started with Amazon Redshift easily or optimize production workloads by decreasing the administrative effort required to get the best possible performance.
Amazon CodeGuru Profiler now profiles your application’s memory, giving you a consolidated view of the heap. The heap summary shows all objects allocated on the heap during a given time frame. For each object (e.g. String, int, char[], custom types, etc.) you can see a summed-up size and number of objects. These metrics are also presented in a time series so you can see how the object size or count changes over time.
Amazon Kendra is a highly accurate and easy to use intelligent search service powered by machine learning. Starting today, AWS customers can automatically index and search content that is contained in Google Drive repositories using Amazon Kendra's new built-in Google Drive connector.
AWS Audit Manager is a new service that helps you continuously audit your AWS usage to simplify how you assess risk and compliance with regulations and industry standards. Audit Manager automates evidence collection to make it easier to assess whether your policies, procedures, and activities, also known as controls, are operating effectively. When it is time for an audit, AWS Audit Manager helps you manage stakeholder reviews of your controls and enables you to build audit-ready reports with much less manual effort and in less time.
Amazon Kendra is a highly accurate and easy to use intelligent search service powered by machine learning. Starting today, customers can centralize content from over 40+ data sources and make it discoverable, with the launch of the Amazon Kendra connector library.
Amazon Braket now supports PennyLane, an open source software framework for hybrid quantum computing. Pennylane provides interfaces to common machine learning libraries, including PyTorch and TensorFlow, so you can train quantum circuits in the same way you would train a neural network. The integration with Amazon Braket allows you to test and fine-tune algorithms faster and at a larger scale on scalable and fully managed simulators and run them on your choice of quantum computing hardware.
Amazon Elastic Container Registry (Amazon ECR) now supports cross region replication of images in private repositories, enabling developers to easily copy container images across multiple AWS accounts and regions with a single push to a source repository. Storing images in-region to your infrastructure helps applications start up faster as image download time is reduced due to lower latency, and removes cross region downloads that helps with region isolation. Geographically dispersed images also helps you meet backup and disaster recovery requirements for your application. By creating a simple way to reliably replicate images across regions, Amazon ECR now makes it even easier to run highly available applications in AWS.
Amazon Redshift ML makes it possible for data warehouse users such as data analysts, database developers, and data scientists to create, train, and deploy machine learning (ML) models using familiar SQL commands. Amazon Redshift is the most widely used cloud data warehouse and, with Amazon Redshift ML, you can now leverage Amazon SageMaker, a fully managed machine learning service, using SQL and without moving your data or learning new skills.
Amazon Kendra is a highly accurate and easy to use intelligent search service powered by machine learning. Starting today, Amazon Kendra will use incremental learning to continuously optimize search results based on end-user search patterns and feedback.
AWS were excited to announce Amazon SageMaker Pipelines, a new capability of Amazon SageMaker to build, manage, automate, and scale end to end machine learning workflows. SageMaker Pipelines brings automation and orchestration to ML workflows, enabling you to accelerate machine learning projects and scale up to thousands of models in production.
Azure Synapse brings together data integration, enterprise data warehousing, and big data analytics—at cloud scale. The unification of these workloads enables organizations to massively reduce their end-to-end development time and accelerate time to insight. It now also provides both no-code and code-first experiences for critical tasks such as data ingestion, preparation, and transformation.
UPComing Events:
Azure Virtual Events
Microsoft have a full schedule of Virtual Events
A full list including session times and details are here : https://azure.microsoft.com/en-us/community/events/
AWS Events:
AWS events are pretty fluid at the moment, with most in-person events being cancelled or postponed. There are a number that have been taken online and full details can be found here: https://aws.amazon.com/events/
Thanks for reading again this week, we hope you found something useful.
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