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In a previous post, we saw how to leverage Istio Multicluster to deploy an application (bookinfo) on multiple Red Hat OpenShift clusters and apply mesh policies on all of the deployed services. We also saw that the deployment process was relatively complex. In this post we are going to see how Federation V2 can help simplify the process of deploying an application to multiple clusters. Federation V2, as the name suggests, is the evolution of the Kubernetes Federation initiative, after the project was rebooted around the beginning of 2018.

Running production quality databases in Kubernetes can be quite a hassle. But KubeDB promises to solve all your problems. Let’s have a quick look at this framework. You can count on KubeDB to solve your problems when running production quality databases in Kubernetes. KubeDB is a framework for writing operators for any database that support certain requirements. Namely: Create a database declaratively using CRD. Take one-off backups or period backups to various cloud stores, eg,S3, GCS, etc.

I started to compile a list of public failure/horror stories related to Kubernetes. It should make it easier for people tasked with operations to find outage reports to learn from. Since we started with Kubernetes at Zalando in 2016, we collected many internal postmortems. Docker bugs (daemon unresponsive, process stuck in pipe wait, ..) were a major pain point in the beginning, but Docker itself has become more mature and did not bite us recently.

If you’ve been following the evolution of the Kubernetes templates for Jaeger, you might have noticed an important change recently: the Jaeger Agent is not being deployed as a DaemonSet anymore. Instead, instructions are now being provided on how to deploy it as a “Sidecar”. The Agent component was developed to act as a “buffer” between the tracer and the collector. This buffer should sit very close to the tracer, usually on localhost.

At Namely we’ve been running with Istio for a year now. Yes, that’s pretty much when it first came out. We had a major performance regression with a Kubernetes cluster, we wanted distributed tracing, and used Istio to bootstrap Jaeger to investigate. We immediately saw the potential of a service mesh as it relates to our infrastructure and decided to make an investment in the tool. It hasn’t always been the smoothest ride, but we have learned a ton about how it works and how to operate it.

PostgreSQL is a very popular open source relational database. It’s been in active development for over 30 years and has achieved a very high level of reliability and performance, as well as a very robust feature set. If your applications make use of PostgreSQL, you’ll now be able to use Crossplane to deploy both your application and its PostgreSQL database to many of the major cloud providers as well on on-premises.

The term “garbage collection” often refers to a memory management technique in computer programs where a garbage collector reclaims memory from objects that have gone out of scope or are no longer used. Interestingly, there is a garbage collector in Kubernetes which helps cleaning up Kubernetes objects that have gone out of scope. Source: medium.com

Kubernetes is a Container Orchestration Engine designed to host containerized applications on a set of nodes, commonly referred to as a cluster. Using a systems modeling approach, this series aims to advance the understanding of Kubernetes and its underlying concepts. The Kubernetes Scheduler is a core component of Kubernetes: After a user or a controller creates a Pod, the Kubernetes Scheduler, monitoring the Object Store for unassigned Pods, will assign the Pod to a Node.

Reddit’s engineering team and product complexity has seen significant growth over the last three years. Facilitating that growth has taken a lot of behind-the-scenes evolution of Reddit’s backend infrastructure. One major component has been adopting a service-oriented architecture, and a significant facet of that has been evolving service-to-service discovery and communication. As the number of services has grown, so has the complexity in how they interact with each other and legacy systems.

Containerization is now officially mainstream. A quarter of Datadog’s total customer base has adopted Docker and other container technologies, and half of the companies with more than 1,000 hosts have done so. As containers take a more prominent place in the infrastructure landscape, we see our customers adding automation and orchestration to help manage their fleets of ephemeral containers. Across all infrastructure environments, our data shows increased usage of container orchestration technologies such as Kubernetes and Amazon Elastic Container Service (ECS).