You can now benefit from even more features and functionality in Elastic Cloud. In case you missed it, we’ve added powerful tools to simplify and automate operations. We’ve added support for more regions. And we’ve even added new ways to pay for, and understand your bill for Elastic Cloud. With a cup of tea and five minutes, we’ll recap them for you.

Ocean by Spot is a fully managed solution for your Kubernetes and/or AWS ECS data plane, with the goal of delivering a serverless container experience for application developers. With that in mind, we are excited to announce that users can now import AWS Auto Scaling Groups (ASGs) into Ocean via the Spot Console.

It has arrived! Azure Red Hat OpenShift 4 is here and generally available; now, how do you add even more granular security and faster time to repair (MTTR) for your teams? Sysdig, that’s how!

One of the benefits of Serverless architectures is the possibility of scaling applications without worrying about load balancers and clusters of servers. While services like AWS Lambda hold their promises on this area, there are usually misconceptions about how they work. It is common for developers to assume that Lambda functions can scale infinitely, at any speed, in any circumstances. Reality is quite different from that.

Over the past decade, organizations have been moving to a hybrid cloud model. A hybrid cloud is a form of cloud computing where applications are deployed on a combination of public clouds and private infrastructure. With a hybrid cloud, organizations can choose the most optimal deployment strategy for their applications while maintaining control over certain aspects, such as running user-facing services from a public cloud while storing sensitive data on-premise.

Ocean by Spot’s right-sizing feature helps cloud users optimize their workload resource utilization while reducing unnecessary infrastructure costs. Ocean continuously monitors Kubernetes workloads’ CPU and Memory usage, providing sizing recommendations for deployments based on the delta between the workload’s request and utilization.

Virtual machines (VMs) are one of the on-demand, scalable computing resources that Microsoft Azure offers. They enable streamlined allocation of resources in backup, disaster recovery, and deployment environments. A VM is typically chosen when you need more control over your computing environment. However, Azure VMs come with the challenge of simultaneously monitoring them across multiple environments when the VMs are spread unevenly, with some being overutilized and others underutilized.

Organizations around the world are increasingly relying on the cloud to capitalize on its speed, ease of management and scalability, and the business value it provides to transform and grow their business. It’s an ever-growing market that is currently estimated at 266.4 billion dollars—a whopping 982.9 percent increase in growth compared to a decade ago when it was worth a little over 24.6 billion dollars.

Today, the AWS Lambda platform has added a new arrow to its quiver – the ability to integrate with Amazon Elastic File System (EFS) natively. Until now, a Lambda function was limited to 512MB of /tmp directory storage. While this is sufficient for most use cases, it’s often prohibitive for use cases such as Machine Learning, as Tensorflow models are often GBs in size and cannot fit into the limited /tmp storage.

Chaos Engineering was conceived as a direct response to the complexity and nondeterministic nature of cloud-based applications. Thoughtful fault injection closes the gap between traditional testing methodologies and modern approaches to software engineering like microservices, continuous delivery, and DevOps.