Kubernetes Multi-cluster Part 1: Defining Goals and Responsibilities

Lukas Gentele
Elly Obare
9 min read

#Kubernetes Multi-Cluster Series

Developers who work in fast-paced environments face the risk of infrastructure sprawl in their VMs or servers. Even with the rise in containerized deployments on Kubernetes and other platforms, admins still must determine how to efficiently manage hundreds and thousands of clusters for various projects.

Common concerns for an organization’s project deployments include how to run multiple workloads and whether a cluster is large enough to handle the work.

A Kubernetes multi-cluster setup can solve these problems. Multi-cluster architecture is a strategy for spinning up several clusters to achieve better isolation, availability, and scalability. In this type of implementation, an application’s infrastructure is distributed and maintained across multiple clusters. Because this strategy can also make cluster management more difficult, it needs to be handled properly.

This article will give you an introduction to Kubernetes multi-cluster deployments.

#What Is a Kubernetes Multi-Cluster Setup?

Kubernetes works with clusters to efficiently run and manage workloads.

In Kubernetes multi-cluster orchestration, platforms such as managed services help you to run workloads across multiple clusters and environments. The multiple clusters can be configured within a single physical host, within multiple hosts in the same data center, or even in a single cloud provider across different regions. This allows you to provision your workloads in several clusters, rather than just one.

This type of deployment enables more scalability, availability, and isolation for your workloads and environments. It also enables you to better coordinate the planning, delivery, and management of these environments.

A key feature of multi-cluster Kubernetes architecture is that each cluster is highly independent, managing its internal state for maximum resource provisioning and service configuration.

#Why Use a Kubernetes Multi-Cluster Setup?

There are multiple use cases for a multi-cluster deployment. You can use it to deploy workloads spanning multiple regions for increased availability, eliminate cloud blast radius, prevent compliance issues, and enforce security around your clusters and tenants.

As your environment grows, so do the potential issues you need to solve in order to align your cluster maintenance with your business needs. Using a Kubernetes multi-cluster setup can help with the following concerns.

#Cluster Discovery and Tenant Isolation

It is common for projects to exist in dev, staging, and production environments. To achieve this kind of isolation, you require multiple Kubernetes environments.

Conventionally, using namespaces would be enough for discovery and isolation in a single cluster, but Kubernetes isn’t a direct multitenant system. Namespaces are also not great for isolation since any compromise in the namespace means that your cluster is also compromised. Additionally, badly configured applications in a namespace can consume more resources than expected, which impacts other applications in the cluster.

Kubernetes multi-cluster environments enable you to isolate users and projects by cluster, simplifying the process.


Architecting multi-cluster workloads minimizes the downtime issues common within a single cluster, because you can freely transfer the workloads to other running clusters.

#Multi-Cluster, Multitenancy, or a Mix?

Kubernetes is a complex, high-level platform that offers multiple options for your deployments: single server, multitenant, or multi-cluster.

Multitenancy means a cluster is shared among several workloads, or tenants. Multiple users share the same cluster resources and control plane. Multitenant clusters require fair allocation of resources to the tenants as well as isolation of tenants from each other, in order to minimize the effects of a faulty tenant on other tenants and the overall cluster.

A multi-cluster setup, on the other hand, involves several clusters deployed across one or many data centers. This type of deployment can be used to separate development and production. It improves availability and enhances security around workloads.

The best choice for your organization depends on factors that include the technical expertise of your team, your infrastructure availability, and your budget. Many organizations separate their critical production services from non-critical services by placing them in separate tenants across tiers, teams, locations, or infrastructure providers. Projects that are time- and resource-dependent (where resources are spun up and down on the go) are, however, suitable for multi-cluster architecture.

#When to Use a Multi-Cluster Setup

To decide whether your projects would function best in a multi-cluster deployment, you first need to define your goals.

You should know the challenges you are trying to solve and how transitioning to a multi-cluster setup would help your organization. Projects that are performance-dependent with workloads that are sensitive to factors like latency can take advantage of the high availability and isolation available in multi-cluster setups. In other words, you can run workloads with intensive computations that don’t need to share resources.

You’ll need to collect workload data and other feedback from your various teams before making a decision. You should assess your teams’ expertise: are they well-versed in provisioning single clusters, even before transitioning to multi-clusters? You’ll also need to evaluate your business model and how such an infrastructure transition could affect your users or customers.

The following are some of the advantages of transitioning to a Kubernetes multi-cluster setup.

#Tenant Isolation

You might want to establish order while accommodating your development teams. The multi-cluster architecture allows workload isolation. For example, you could spin up separate clusters for staging and production.

With multiple clusters, any tenant configuration changes affect only that specific cluster. This way, cluster admins can easily identify issues, run new feature experiments, and carry out workload shifts without troubling other tenants and clusters.

#No Single Point of Failure

Running a single cluster can expose your project to a single point of failure, in which one malfunctioning component can bring down an entire system. Using a multi-cluster environment enables you to shift your workloads between clusters so that your projects continue to function if one cluster is down or even disappears entirely.

#No Vendor Lock-In

There are multiple third-party cloud vendors available with varying resource offerings. Because of evolving resource pricing and models, organizations change their usage models over time as well. A Kubernetes multi-cluster setup ensures your workloads are cloud-agnostic so that you can safely use multiple vendors or move workloads from one cloud to another.

#Regulatory Compliance

Using cloud infrastructure means that your workloads can run anywhere. However, organizations located in or doing business with certain regions need to ensure they follow local regulations around how data is handled. Such regulations include the EU’s GDPR and the California Consumer Privacy Act.

If you use a multi-cluster architecture, you can run clusters for different locations that follow the needed regulations without sacrificing the flexibility of your cloud-native applications.

#When Can Shared Clusters Save Costs?

With a shared cluster, multiple users can access a cluster’s resources at the same time. A shared cluster can help optimize costs and reduce overhead in the following situations:

  • Isolation isn’t needed: While there are namespaces and other solutions for isolation, many tenants on a shared cluster can be trusted to work harmoniously. In this situation, soft multitenancy is enough and an organization doesn’t need to create a single cluster for any tenant or workload.
  • Developers are new to Kubernetes: An experienced cluster-admin can manage a shared cluster from a central point when the dev team isn’t well versed in managing Kubernetes clusters. This enables the organization to skip the costs of managing several clusters.

#Ownership of Clusters

As the size and number of clusters increase, so does the complexity of owning and managing them. The solution is to implement best practices for cluster governance.

Teams can provision multiple smaller clusters from a single centralized management plane to more easily track all clusters, providing greater observability. This centralized management also provides better alerting, capacity control, cost reduction, and logging.

#Using a Multi-Cloud Deployment

In a multi-cloud deployment, computing workloads are distributed across several cloud providers. This can help organizations to improve security, follow compliance requirements, and cut costs, among other advantages.

Cutting costs, though, depends on an organization’s goal. If the organization wants to scale across several regions to increase availability, then it may incur higher costs. However, if the goal for using a multi-cluster approach is to use less expensive services from different Kubernetes providers based on workloads, then the organization can save on costs.

More organizations now architect their Kubernetes clusters on the infrastructure of major cloud vendors. Using a multi-cloud deployment can also work well for multi-cluster deployments. For instance, businesses can deploy Kubernetes clusters to spread across several public and even hybrid clouds.

This type of deployment can add complexity to your environment, but a multi-cloud option also offers multiple benefits depending on the needs of your organization.

#How Can You Operate Clusters across Clouds?

If you deploy clusters at scale across clouds, you need automation. Automation enables you to manage clusters more easily and provides better consistency and tracking. It also allows you to apply your configurations to as many clusters as necessary.

If you operate your clusters through Kubernetes managed services, your platform can manage everything for you so that your team can focus on crafting the best configurations for your workloads. This approach makes it simpler to manage dozens of clusters and boosts security by minimizing the risk of manual configuration mistakes.

#Leveraging Loft for Multi-Cluster Deployments

There are multiple tools available that you can use to configure and manage your Kubernetes multi-cluster environments. One such tool is Loft. The control plane offers managed self-service functionalities so that you can optimize your Kubernetes use. Loft features self-service environment provisioning, secure Kubernetes multitenancy, and enterprise-grade access control.

Loft provides virtual clusters for tenant workloads, which allows teams to decouple tenants and apply specific configurations to the deployments. Virtual clusters also run your tenants with separate control planes so that any upgrade can be achieved independently.

Admins can install Loft to create namespaces and multiple virtual clusters on demand for seamless multitenancy.


The Kubernetes multi-cluster approach, in defining separate workloads and tenants, can provide high availability and higher levels of isolation between tenants while customizing maintenance lifecycles for various workloads.

There are multiple benefits to embracing this architecture. The complexity of Kubernetes environments does present challenges, but setting clear goals and objectives for deploying your clusters can help you wade through the hurdles as your organization makes the transition.

Ultimately, multi-cluster environments are a good choice for organizations that are building highly distributed systems but need better control over their infrastructure.

Photo by K8 on Unsplash

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