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A few weeks ago we discussed the way that we integrated Kubernetes federation v2 into Pipeline, and took a deep dive into how it works. This is the next post in our federation multi cloud/cluster series, in which we’ll dig into some real world use cases involving one of Kubefed’s most interesting features: Replica Scheduling Preference.

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One of the key features of our container management platform, Pipeline, and our CNCF certified Kubernetes distribution, PKE, is their ability to seamlessly form and run federated clusters across multi- and hybrid-cloud environments. While users of the Pipeline platform often have different requirements depending on whether they take a single or multi-cloud approach, they’re usually built around two key features: Multi-cloud application management Backyards, an Istio-based automated service mesh for multi- and hybrid-clouds Today, we’re happy to announce that we’ve added support for Kubernetes federation v2, which is being made available as a beta feature in the Pipeline platform.
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Service mesh probably needs no introduction. But, just to recap, let’s define it as a highly configurable, dedicated and low‑latency infrastructure layer designed to handle and provide reliable service-to-service communication, implemented as lightweight network proxies deployed alongside application code. Typical examples of mesh services are service discovery, load balancing, encryption, observability (metrics and traces) and security (authn and authz). Circuit breakers, service versioning, and canary releases are frequent use cases, all of which are part of any modern cloud-native microservice architecture.
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Hybrid- and multi-cloud are quickly becoming the new norm for enterprises, just as service mesh is becoming essential to the cloud native computing environment. From the very beginning, the Pipeline platform has supported multiple cloud providers and wiring them together at multiple levels (cluster, deployments and services) was always one of the primary goals. We supported setting up multi-cluster service meshes from the first release of our open source Istio operator.
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Last week we released our open source Istio operator designed to help ease the sometimes difficult task of managing Istio. One of the main feature of the operator is its ability to manage a single mesh multi-cluster Istio. Multi cluster scenarios Typical multi-cluster-based patterns are single mesh - combining multiple clusters into one unit managed by one Istio control plane - and mesh federation, wherein multiple clusters act as individual management domains and the service exposure between those domains is done selectively.
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