As organizations adopt Kubernetes for container orchestration, a common question arises: should I have multiple Kubernetes clusters or just one? There are valid arguments on both sides of this debate. In this comprehensive guide, we’ll explore the pros and cons of single vs multiple Kubernetes clusters and provide best practices for cluster architecture.
The Case for a Single Kubernetes Cluster
Having a single Kubernetes cluster keeps things simple. With one cluster, you only have one set of control plane components to manage like the API server, scheduler, and controllers. Upgrades and maintenance are straightforward as there is only one cluster to patch and update. Policies for security, resource quotas, and access control are defined once and apply to the whole cluster.
A single cluster is easier to monitor as logs, metrics, and events are centralized. And without cross-cluster communication to worry about, networking is simpler. The cluster network provides connectivity for all pods across all nodes.
There is also lower overhead from an infrastructure perspective. You only need one set of masters, etcd nodes, and networking infrastructure for the cluster. And development teams share this common pool of resources which can improve utilization compared to sparse multi-cluster deployments.
When a Single Cluster Works Best
Here are some scenarios where a single Kubernetes cluster makes the most sense:
- You have one application or a small number of related applications with similar scale and availability needs.
- You want maximum utilization of resources across teams and applications.
- Your applications have loose coupling and low risk from co-deployment.
- Centralized management and monitoring is preferred over isolation.
Reasons for Multiple Kubernetes Clusters
While a single cluster keeps things simple, there are many good reasons to have multiple Kubernetes clusters. Let’s look at some of the benefits of this multi-cluster approach.
Isolation
The strongest argument for multiple clusters is isolation. When clusters are separated, applications are insulated from “noisy neighbors”. The resource contention, security breaches, and failed deployments of one application cannot impact unrelated applications in other clusters.
Development teams each get their own cluster sandbox. They gain autonomy to deploy and manage services without stepping on each other’s toes. Separate clusters also provide clean separation for different environments like development, testing, and production.
Customization
With multiple clusters, each one can be tailored to specific application needs. Cluster settings like Kubernetes version, extensions, CNI networking, and machine types can vary. Critical applications might run on a cluster with premium VMs and maxed out resource requests. Experimental applications could run on a low-cost cluster. Per-cluster customization provides tuning for specific apps.
Scale
Kubernetes scale limits are per cluster. To scale beyond the node count or pod capacity of a single cluster, you can deploy additional independent clusters. Large organizations with thousands of applications may require multiple clusters just to handle the volume. And huge applications with thousands of pods may need to shard across clusters for scale.
Availability
Clusters can provide high availability through replication. If you run a cluster per availability zone in a region, you are resilient to zone failure. Critical applications can spread across clustered data centers for geographic redundancy. And multi-master Kubernetes clusters provide local failover.
Cost
Carefully tuned clusters allow efficient use of cloud resources. Separating development, test, and production clusters allows lower cost options like spot VMs for non-production. And clusters can be scaled down during off hours to save on costs. Scaling clusters up and down based on resource needs can provide major cost savings.
When Multiple Clusters Work Best
Here are some key scenarios where multiple Kubernetes clusters shine:
- Isolation is critical between applications and teams.
- Applications have diverse scales, availability, and resources needs.
- Maximizing cloud cost efficiency is a priority.
- You are operating at Kubernetes scale limits.
- Regulatory compliance requires separation.
How Many Clusters Should I Have?
So when architecting Kubernetes infrastructure, how many clusters should you have? Here are some guidelines on striking the right balance:
- Default to a single cluster for simplicity unless you have a specific need.
- Isolate prod, test, and dev environments into separate clusters.
- Create clusters by team or major application to limit interference.
- Plan for 3-5 clusters to cover most simple use cases.
- For large enterprises, target 10-20 clusters.
- Limit cluster sprawl – it quickly becomes unmanageable.
The growth over time may look like:
| Stage | # of Clusters |
|---|---|
| Getting Started | 1 |
| Simple Growth | 3-5 |
| Divisional Expansion | 10-15 |
| Enterprise Scale | 15-25 |
The number of clusters depends heavily on organizational and application diversity. Plan clusters around security boundaries, teams, environments, regions, and scale needs.
Architectural Best Practices
If embracing multiple clusters, there are some key architectural best practices to follow:
Network Interconnectivity
Clusters must have efficient network connectivity between them. Container networking architectures like Calico provide optimized routing across clusters. A well-architected Kubernetes network is critical for multi-cluster.
Cluster Federation
The Kubernetes Cluster Federation project can synchronize resources across clusters. This includes namespaces, RBAC policies, services, and deployments. Federated clusters can provide unified management and monitoring.
Centralized Identity
Use a central identity provider like Active Directory, LDAP, or OAuth to authenticate users across all clusters. Single sign-on and centralized account management improves security.
Hybrid Cloud Portability
Design application deployments to be portable across on-prem and public cloud Kubernetes. Open service catalog and storage interfaces smooth porting of apps between clusters.
Consistent Tooling
Manage all clusters through consistent tooling for deployment, monitoring, logs, and troubleshooting. Kubernetes-native tools like Helm and Prometheus work seamlessly across clusters.
Automation
Automate cluster creation, upgrading, scaling, and tear down. Infrastructure-as-code approaches allow programmatically managing clusters.
Managing Multiple Clusters
Operating multiple Kubernetes clusters does increase operational complexity. Here are some techniques to manage multi-cluster environments:
Centralized Control Plane
For maximum manageability, use a centralized control plane to administer all clusters. Popular options include Red Hat OpenShift, VMware Tanzu, and Amazon EKS Anywhere. These consolidate the functionality of managing individual control planes.
Consistency Across Clusters
Strive for uniformity in cluster configurations, Kubernetes versions, extensions, authentication, and tooling. Consistency reduces complexity.
Cluster Templates
Define common cluster templates with infrastructure-as-code tooling like Terraform or Ansible. Stamp out consistent preset clusters for things like dev, test, and production.
Declarative Infrastructure
Adopt a declarative approach to cluster management. Declare the desired cluster state in Git rather than procedural scripts. A desired state framework like Terraform or Pulumi can then realize clusters.
Policy Conformance
Use a policy engine like Gatekeeper or Kyverno to define mandatory policies for security, cost, and compliance. Automatically enforce policies across all clusters.
GitOps
Use GitOps techniques to automate application deployment, configuration, and lifecycle management across clusters from Git. A Git centric workflow aids cluster management.
Observability
Collect logs, metrics, and traces from all clusters into a central observability platform. Correlate insights across clusters for streamlined monitoring.
Multi-Cluster Management Tools
Here are some key Kubernetes tools for simplifying multi-cluster management:
| Tool | Description |
|---|---|
| Red Hat Advanced Cluster Management | Govern and manage Kubernetes clusters across regions, zones, and clouds. |
| VMware Tanzu Mission Control | Centralized management and observability for Tanzu Kubernetes clusters. |
| Rancher | Enterprise Kubernetes management for deploying and operating clusters. |
| Amazon EKS Anywhere | Amazon EKS control plane to manage clusters across on-prem and cloud. |
| GitOps Tools (Flux, Argo CD) | Declarative Git-based cluster and app management. |
These platforms provide consolidated visibility, access control, monitoring, and automation across multiple Kubernetes clusters.
Conclusion
In summary, while a single Kubernetes cluster is simplest, many scenarios demand multiple clusters. Separate clusters provide isolation, customization, scalability, availability, and cost efficiencies. But beware of cluster sprawl. Archtecturally connect clusters, centralize identity, enable portability, use consistent tooling, and automate management. The right multi-cluster foundation unlocks the true power of Kubernetes.
