Building apps in containers capitalizes on dependencies and similar configurations within a business work cluster to streamline the development, implementation, and troubleshooting processes. Kubernetes is open-source software that enables IT professionals to develop and manage those containers to scale, saving time and money. Within Kubernetes, going with a single work cluster for a business or multiple work clusters is one of the first questions installers must answer. As part of the multiple work clusters equation, developers must also decide if a hosted Kubernetes platform is appropriate for a bird’s eye view of the system.
Understanding how single and multiple Kubernetes clusters work can help decision-makers choose the best alignment for their company’s needs.
Kubernetes Clusters Basics
When multiple containers begin using applications, maintaining them becomes more and more difficult. Kubernetes Cluster helps manage work clusters of containers and schedules based on available resources and container resources requirements. Each container is part of a Kubernetes’ “pod,” or work cluster. Each work cluster has three principal planes:
Control plane
This plane is the nerve center of any Kubernetes work cluster and consists of the API Server, Scheduler, and Controller manager.
Data plane
The Data Plane is the storage part of the Kubernetes work cluster. It stores the work cluster configurations and other data to help manage the work cluster.
Worker plane
The worker plane runs a workload based on the configurations stored in the Data Plane and sent to the API server in the Control Plane. Each of these planes works together to help manage a Kubernetes work cluster. Each work cluster can exist singularly, across multiple cloud virtual machines or as the “brain” of a data center.
Single Kubernetes cluster
A single Kubernetes work cluster is one set of those three planes. Using a single work cluster makes it easier to authenticate users and implement upgrades or patches. It also creates a cleaner work cluster and node management environment and makes application deployment more manageable.
Security is the only drawback to a singular work cluster. Developers must put controls in place to keep workloads separate from each other. With a multiple work cluster alignment, that need is still acute but spans across multiple work clusters rather than having several distinct work clusters with their own security needs.
Single pod scalability
Regardless of how work clusters are treated, there are three Kubernetes scaling methods.
- Horizontal: Scales how many pods based on utilization metrics
- Vertical: Scales the resources needed to manage apps (CPU allotment, memory, etc.)
- Work cluster: Scales by increasing or decreasing the number of nodes in a working cluster
With single work cluster configurations, scaling works to the point of diminishing returns, which usually happens when demand exceeds available resources.
Single pod security
Running apps over a single work cluster possesses some inherent risks. The more nodes in a working cluster, the greater the chances of misconfigurations factoring into work cluster management. Greater resources utilization also runs the risk of application runtime conflicts.
To address these concerns, the development of pod and network security policies is critical. Another approach is to enable RBAC to manage user permissions better.
Single work cluster resilience
A single Kubernetes work cluster runs a higher risk of app-specific failure. This increased risk is because more resources are used from the same source instead of spreading over several work clusters.
This vulnerability can affect operations by losing underlying hosts, bad configurations applied to work cluster resources, and upgrade and plug-in failures. These failures can disable a work cluster and render it useless until the issue resolves.
Single work cluster cost
If your decision to go with a single work cluster or multiple work clusters is financially based, a single work cluster alignment costs less. The savings add up because of less time required to set up the work clusters and fewer licensing and maintenance costs.
Multiple clusters
This model creates the ability to isolate needs based on the work cluster in question. Developers have the freedom to move within work clusters, and resources management becomes broader with more available resources within each pod of work clusters. The downside to multiple work clusters is that consistency in alignment in user authentication and authorization is more complex. That complexity also applies to updating Kubernetes versions, developing policies, granting permissions, and authenticating user identification.
An easy way to envision the challenge is to think of a middle school class trip. Managing a trip of five students is more accessible than trying to control a crowd of twenty students.
Ease of management is apparent, although every student on the trip has identical needs and challenges. In this comparison, a single school grade of students represents one work cluster while the multiple work clusters represent several grades.
Multiple cluster scalability
Multiple work clusters scale the same way as single work clusters (horizontal, vertical, by work cluster), but workloads pull resources across pods. Pooled resources allow more nodes in a pod without sacrificing resource access. Additionally, because app or system problems are the same regardless of where each starts, the availability of resources increases by multiple work cluster volumes.
In the case of multiple work clusters, it is advisable to host the Kubernetes environment via a trusted Kubernetes platform. The hosted environment ensures common issues get addressed quickly. It also allows the hosted business to benefit from institutional knowledge derived by the management company on previous implementations.
Multiple cluster security
Running workloads over multiple work clusters reduces the ability of one user to impact an entire work cluster. Additionally, assigning apps or environments to specific work clusters hampers apps from causing conflicts with each other.
Multiple cluster resilience
The distributed architecture of a multiple work cluster arrangement spreads work across many sites while not affecting system availability. If things go wrong, full recovery is much more likely because data resides in multiple locations versus just one work cluster. Additionally, problems are confined to a single work cluster while recovery actions pull from many work clusters.
Multiple cluster cost
A multiple work cluster alignment will cost more than a single work cluster alignment. However, that cost equation does not consider ROI, saved costs by reduced downtime, more straightforward implementation, etc.
Final thoughts
A single work cluster works well with a limited number of nodes, budget constraints, or when a business has no plans for any massive expansion. A multiple work cluster alignment works well in larger organizations where workload management and resources drive many actions and activities.
Also read: How does the Customer Data Platform relate to the Business Data?
