Couchbase operator automates database scaling in Kubernetes


Couchbase extends the operator, which was created to provide a document database of the same name, to a Kubernetes cluster so that IT teams can check logs using fluent bit and support autoscaling. We have secured a level of performance.

Couchbase Autonomous Operator (CAO) version 2.2 for Kubernetes IT teams can individually scale the storage without having to restart their Kubernetes cluster. The team can also change the settings used to identify and authenticate the remote cluster.

This update gives IT teams more control over upgrades, more customizable server groups, tighter integration with Prometheus and Kubernetes resources based on policies defined by IT teams. You can assign it automatically.

Couchbase Product Management Director Anil Kumar said last year that Couchbase has expanded to employ a single Kubernetes operator who provides both the database and a variety of complementary third-party tools such as Prometheus and Istio monitoring software. And now you can manage it. Service network ..

Kumar also said that CAO 2.2 improves integration with HelmCharts for IT teams who prefer to use the tool rather than the operator.

Finally, Couchbase has improved both the security and the backup and recovery tools that come with the database.

Operators was originally developed by CoreOS and has evolved into a class of tools that give the average IT administrator better access to the Kubernetes environment. Most vendors today have provided operators that make it easy to deploy and update both the offering and the Kubernetes cluster in which they are deployed. Couchbase is now expanding this concept to include all the tools that IT teams need to provide.

Some IT organizations go one step further with the operator concept by creating their own instances of the operator. This allows you to manage specific applications and associated infrastructure that you want to deploy in addition to your Kubernetes cluster fleet.

In any case, the Kubernetes environment is more accessible to the average IT team. In an ideal world, every IT organization has a small team of Site Reliability Engineers (SREs) who can automate the management of their Kubernetes environment on a large scale. However, SREs are difficult to find and relatively expensive to rent. Operators enable the average IT administrator to perform certain tasks alone or in collaboration with SREs.

As more data is stored in Kubernetes clusters, it becomes increasingly important to find a way to balance these capabilities. Many IT teams still prefer to run stateless applications on Kubernetes clusters that store data outside of the cluster but access databases on Kubernetes clusters to integrate compute management. I’m starting to deploy a stateful application that has to be. And storage.

Of course, most IT teams will find that they are managing a combination of stateless and stateful applications that run on many Kubernetes clusters. The first step in bringing some order into this potential disruption is to decide which combination of operators can be relied on to streamline the management process.

Couchbase operator automates database scaling in Kubernetes

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