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Showing content from http://cloud.google.com/kubernetes-engine/fleet-management/docs/multi-cluster-use-cases below:

Multi-cluster use cases | Fleet management

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While it is generally a best practice to use as few clusters as possible, organizations choose to deploy multiple clusters to achieve their technical and business objectives for a variety of reasons. At a minimum, most organizations separate their non-production from their production services by placing them in different clusters. In more complex scenarios, organizations might choose multiple clusters to separate services across tiers, locales, teams, or infrastructure providers.

Most reasons for adopting multiple clusters fall into three categories of requirements:

We look at these in more detail in the following sections.

In many cases, organizations need to balance several of these requirements simultaneously. As you think about your own organization, remember that our general recommendation is to use as few clusters as possible. Determine which of the multi-cluster needs are the highest priority for your organization and cannot be compromised, and then make appropriate tradeoffs to create a multi-cluster architecture.

If you find your organization considering a cluster per service-model or a cluster-per-team mode, you might want to consider the management burden imposed on the operators of such a system. Fleets and the Google Cloud components and features that support them strive to make managing multiple clusters as easy as possible, but there is always some additional management complexity with more clusters.

Isolation

In this context, isolation refers to separation of the control plane and/or data plane, both of which can be achieved by running multiple clusters. However, depending on implementation, this separation likely also extends to data plane isolation. Isolation usually comes up when considering the following:

Location Scale

Because GKE can scale clusters to more than 5000 nodes, these limits rarely become a reason to operate multiple clusters. Before a cluster reaches scalability limits, organizations often decide to distribute services across multiple clusters. For clusters that do reach scalability limits, running an application across multiple clusters can ease some challenges, but with the added complexity of managing multiple clusters.

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.

Last updated 2025-08-07 UTC.

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