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Kubernetes v1.15 introduces alpha support for volume cloning. This feature allows you to create new volumes using the contents of existing volumes in the user’s namespace using the Kubernetes API. Many storage systems provide the ability to create a “clone” of a volume. A clone is a duplicate of an existing volume that is its own unique volume on the system, but the data on the source is duplicated to the destination (clone).

CustomResourceDefinitions were introduced roughly two years ago as the primary way to extend the Kubernetes API with custom resources. From the beginning they stored arbitrary JSON data, with the exception that kind, apiVersion and metadata had to follow the Kubernetes API conventions. In Kubernetes 1.8 CRDs gained the ability to define an optional OpenAPI v3 based validation schema. By the nature of OpenAPI specifications though—only describing what must be there, not what shouldn’t, and by being potentially incomplete specifications—the Kubernetes API server never knew the complete structure of CustomResource instances.

We’re pleased to announce the delivery of Kubernetes 1.15, our second release of 2019! Kubernetes 1.15 consists of 25 enhancements: 2 moving to stable, 13 in beta, and 10 in alpha. The main themes of this release are: Continuous ImprovementProject sustainability is not just about features. Many SIGs have been working on improving test coverage, ensuring the basics stay reliable, and stability of the core feature set and working on maturing existing features and cleaning up the backlog.

What are Golden signals metrics? How do you monitor golden signals in Kubernetes applications? Golden signals can help to detect issues of a microservices application. These signals are a reduced set of metrics that offer a wide view of a service from a user or consumer perspective, so you can detect potential problems that might be directly affecting the behaviour of the application. Golden signals can help to detect issues of a microservices application.

Litmus is an open source chaos engineering framework for Kubernetes environments running stateful applications. Created by MayaData, Litmus enables users to run test suites, capture logs, generate rep The book Mastering Collaboration by Gretchen Anderson provides techniques and exercises that can be used to improve collaboration in teams and between teams and their environment. It explores topics like enlisting people, teamworking, trust, and respect, generating ideas collectively, decision making, and transparent communication.

The Datawire team and I have returned home from an awesome time last week where we attended KubeCon and CloudNativeCon in Barcelona. Together, we were part of six talks at KubeCon, staffed a packed booth with amazing T-shirts (if I do say so myself!), spoke to dozens of community members, and attended some fantastic talks. As there was so much goodness on offer at KubeCon EU, I’ve tried to summarise some of my key observations in this blog post.

Kubernetes is a very popular container orchestration framework. I’ll show you how to get Symmetric-DS working on a single Kubernetes instance. Source: crunchydata.com

Kubernetes’ increased adoption is showcased by a number of influential companies which have integrated the technology into their services. Let us take a look at how some of the biggest companies of our time are successfully using Kubernetes. The Docker adoption is still growing exponentially, more and more companies have started using it in Production. It is important to use an orchestration platform to scale & manage your containers. Imagine a situation where you have been using Docker for a little while, and have deployed on a few different servers.

If you’ve ever worked with your hands, you know that you can’t do the job right without the right tools. That adage carries over quite well to software development as well. The right tools can make the difference between success or failure, regardless of the underlying technology. In the Kubernetes ecosystem, more and more tools are being introduced as folks find ways to solve a common problem. This article looks are four of those tools.

Backups can capture subsets of the cluster’s resources, filtering by namespace, resource type, and/or label selector, providing a high degree of flexibility around what’s backed up and restored. Users of managed Kubernetes offerings often do not have access to the underlying etcd database, so direct backups/restores of it are not possible. Resources exposed through aggregated API servers can easily be backed up and restored even if they’re stored in a separate etcd database.