In Cloud Computing This Week [May 8th 2020]

Hello cloud land,  like always, we've read the news, so you don't have to.  

Here's this week's round up of everything that's happening in cloud computing this week. 

There's not a huge amount going on this week, with a general feeling that parts of the market are treading water while CV19 plays out, however cloud spend continues to rise as organisations scale their distributed workforce capabilities and online retailers enjoy some of their best weeks on record.   

Did you check out our recent blog post on places to source cloud training courses for free or mostly free?  You can find it here:  https://www.hava.io/blog/best-free-aws-gcp-and-azure-training-in-2020

Enjoy.

 

General Availability of UltraWarm for AWS ElasticSearch   

This week AWS announced the general availability of UltraWarm for Amazon Elasticsearch Service.

This new low-cost storage tier provides fast, interactive analytics on up to three petabytes of log data at one-tenth of the cost of the current Amazon Elasticsearch Service storage tier.

UltraWarm, complements the existing Amazon Elasticsearch Service hot storage tier by providing less expensive storage for older and less-frequently accessed data while still ensuring that snappy, interactive experience that Amazon Elasticsearch Service customers have come to expect. Amazon Elasticsearch Service stores data in Amazon S3 while using custom, highly-optimized nodes, purpose-built on the AWS Nitro System, to cache, pre-fetch, and query that data.

There are many use cases for the Amazon Elasticsearch Service, from building a search system for your website, storing, and analyzing data from application or infrastructure logs. AWS think this new storage tier will work particularly well for customers that have large volumes of log data.

https://aws.amazon.com/blogs/aws/general-availability-of-ultrawarm-for-amazon-elasticsearch-service/

 

Building a Continuous Integration Workflow with Step Functions and AWS CodeBuild

Automating your software build is an important step to adopt DevOps best practices. To help you with that, AWS built AWS CodeBuild, a fully managed continuous integration service that compiles source code, runs tests, and produces packages that are ready for deployment, and AWS CodePipeline, a fully managed continuous delivery service to automate your release pipelines.

However, there are so many possible customizations in AWS customers’ build processes, and they have seen developers spend time in creating their own custom workflows to coordinate the different activities required by their software build. For example, you may want to run, or not, some tests, or skip static analysis of your code when you need to deploy a quick fix. Depending on the results of your unit tests, you may want to take different actions, or be notified via SNS.

To simplify complex use cases that cannot be easily implemented with CodePipeline, AWS launched a new AWS Step Functions service integration with CodeBuild. Now, during the execution of a state machine, you can start or stop a build, get build report summaries, and delete past build executions records.

https://aws.amazon.com/blogs/aws/new-building-a-continuous-integration-workflow-with-step-functions-and-aws-codebuild/

Easy Access to stream analytics with SQL, real-time AI & more.

During times of challenge and uncertainty, businesses across the world must think creatively and do more with less in order to maintain reliable and effective systems for customers in need. In terms of data analytics, it’s important to find ways for bootstrapped engineering and ops teams working in unique circumstances to maintain necessary levels of productivity. Balancing the development of modern, high-value streaming pipelines with maintaining and optimizing cost-saving batch workflows is an important goal for a lot of teams. Google Cloud, launched new capabilities to help developers and ops teams easily access stream analytics.

Highlights across these launches include:  

• Streaming pipelines developed directly within the BigQuery web UI with general availability of Dataflow SQL

• Dataflow integrations with AI Platform allow for simple development of advanced analytics use cases

• Enhanced monitoring capabilities with observability dashboards

Built on the autoscaling infrastructure of Pub/Sub, Dataflow, and BigQuery, Google Cloud’s streaming platform provisions the resources that engineering and operations teams need to ingest, process, and analyze fluctuating volumes of real-time data to get real-time business insights. GCP are honored that The Forrester Wave™: Streaming Analytics, Q3 2019 report named Google Cloud a Leader in the space. These launches build on and strengthen the capabilities that drove that recognition.

https://cloud.google.com/blog/products/data-analytics/easy-access-stream-analytics-sql-real-time-ai-and-more

New Zealand gets its own Microsoft Cloud region

Microsoft plans to open its first data centre region in New Zealand, hailing it as a first step toward providing local access to enterprise-grade cloud services there.

“This significant investment in New Zealand’s digital infrastructure is a testament to the remarkable spirit of New Zealand’s innovation and reflects how we’re pushing the boundaries of what is possible as a nation,” Vanessa Sorenson, general manager of Microsoft New Zealand, said in a statement.

https://www.crn.com.au/news/new-zealand-gets-its-own-microsoft-cloud-region-547862

 

Windows Server containers on GKE now generally available.

As organizations look to modernize their Windows Server applications to achieve improved scalability and smoother operations, migrating them into Windows containers has become a leading solution. And orchestrating these containers with Kubernetes has become the industry norm, just as it has with Linux. 

GCP launched the preview of Windows Server container support in Google Kubernetes Engine (GKE) earlier this year, and today, it’s generally available for production use. Running your Windows apps in containers on Kubernetes can provide significant cost savings, as well as improved reliability, scalability, and security—things that are especially important in times of uncertainty. 

Since GCP launched the preview, many customers have kicked the tires on GCP Windows Server containers. Thanks to their feedback, GCP have added features like support for private clusters and regional clusters, choice of Long-Term Servicing Channel (LTSC) and Semi-Annual Channel (SAC) versions, integration with Active Directory using group Managed Service Account (gMSA) and much more. 

This release also includes integration with the Google Cloud Console to simplify creating new GKE clusters or updating existing clusters with Windows Server node pools.

https://cloud.google.com/blog/products/containers-kubernetes/windows-server-containers-on-gke-now-ga

Microsoft announces next evolution of Azure VMware Solution 

Azure were excited to announce the preview of the next generation of Azure VMware Solution, designed, built, and supported by Microsoft and endorsed by VMware.

With the current economic environment, many organizations face new challenges to find rapid and cost-effective solutions that enable business stability, continuity, and resiliency. The new Azure VMware Solution empowers customers to seamlessly extend or completely migrate their existing on-premises VMware applications to Azure without the cost, effort, or risk of re-architecting applications or retooling operations.

This helps Microsoft customers gain cloud efficiency and enables them to innovate at their own pace with Azure services across security, data, and artificial intelligence, as well as unified management capabilities. Customers can also save money with Windows Server and SQL Server workloads running on Azure VMware by taking advantage of Azure Hybrid Benefits.

https://azure.microsoft.com/en-us/blog/microsoft-announces-next-evolution-of-azure-vmware-solution/

Manage and find data with Blob Index for Azure Storage (preview) 

Blob Index—a managed secondary index, allowing you to store multi-dimensional object attributes to describe your data objects for Azure Blob storage—is now available in preview. Built on top of blob storage, Blob Index offers consistent reliability, availability, and performance for all your workloads. Blob Index provides native object management and filtering capabilities, which allows you to categorize and find data based on attribute tags set on the data.

Manage and find data with Blob Index

As datasets get larger, finding specific related objects in a sea of data can be difficult and frustrating. Previously, Azure clients used the ListBlobs API to retrieve 5000 lexicographical records at a time, parse through the list, and repeat until you found the blobs you wanted. Some users also resorted to managing a separate lookup table to find specific objects. These separate tables can get out-of-sync—increasing cost, complexity, and frustration. Azure note that customers should not have to worry about data organization or index table management, and instead focus on building powerful applications to grow their business.

Blob Index alleviates the data management and querying problem with support for all blob types (Block Blob, Append Blob, and Page Blob). Blob Index is exposed through a familiar blob storage endpoint and APIs, allowing you to easily store and access both your data and classification indices on the same service to reduce application complexity.

https://azure.microsoft.com/en-us/blog/manage-and-find-data-with-blob-index-for-azure-storage-now-in-preview/