These are the fundamental building blocks that enable the Controller Manager to automatically maintain and reconcile the desired state of a Kubernetes cluster:

• Node Controller: Monitors the health and status of cluster nodes. When a node becomes unreachable or fails, this component updates node condition and triggers pod rescheduling or resource cleanup as necessary.
• Replication Controller: Ensures the specified number of pod replicas are running at all times. If pods are missing or extra, this controller creates or removes pods to match the intended state.
• Endpoints Controller: Populates endpoint objects with IP addresses of the relevant pods, providing up-to-date service discovery so that traffic is routed correctly inside the cluster.
• Service Account Controller: Automatically creates default service accounts and associated secrets for API access within new namespaces, supporting pod authentication.
• Namespace Controller: Manages the lifecycle of namespaces, handling deletion processes and ensuring resources within a deleting namespace are also removed.
• Job Controller: Watches for job objects and manages the execution of pods until job completion, handling restarts and clean-up in line with job specifications.

The Controller Manager runs several controller loops, each responsible for managing a specific aspect of the cluster’s state:

• Node Controller: Oversees node health by detecting when nodes become unreachable or unhealthy, then manages pod eviction or resource cleanup as needed.
• Replication Controller: Maintains the defined number of pod replicas for replication controllers, ensuring availability and scalability of applications.
• Endpoints Controller: Updates endpoint objects with the IP addresses of active pods to ensure proper routing for services within the cluster.
• Service Account Controller: Automatically creates default service accounts and secrets for namespaces, facilitating pod interaction with the Kubernetes API.
• Namespace Controller: Manages namespaces by cleaning up and deleting resources when namespaces are removed, maintaining cluster organization.
• Job Controller: Monitors job objects to ensure pods run to completion, managing restarts and cleanup required for batch or parallel task execution.

The architecture of the Kubernetes Controller Manager is designed to ensure reliable, continuous operation and cluster consistency:

• Single Binary Process: Runs as a single process called kube-controller-manager, which manages multiple controller loops in parallel.
• Control Loops: Each controller functions as a loop that continuously watches the Kubernetes API server for changes and updates, then acts to move the cluster towards the desired state.
• Leader Election Support: In highly available clusters, multiple controller manager instances can run at once, but only one becomes active through leader election. This prevents conflicting updates and ensures smooth failover.
• API Server Integration: Communicates directly with the Kubernetes API server to read cluster state and submit any necessary changes, such as creating, deleting, or updating resources.
• Modular Controllers: Each built-in controller manages a specific resource (such as pods, nodes, jobs, or endpoints) and can be enabled or disabled using configuration flags.
• Deployment: Deployed as a static pod or a system process on control-plane nodes, ensuring it is always available to perform reconciliation tasks.

The deployment and configuration of the Kubernetes Controller Manager ensure cluster reliability and correct operation, adapting to various environments and needs:

• Deployment Methods: The controller manager is typically deployed as a static pod on control-plane nodes or as a managed system service. This approach guarantees the process is always up and running, even during reboots or upgrades.
• Configuration via Flags: Command-line arguments control aspects such as which controllers are enabled or disabled, connectivity to the API server, cloud integration settings, and security options.
• Controller Selection: Use the --controllers flag to include or exclude specific controllers, allowing customization based on the cluster’s requirements.
• Leader Election: Enable leader election with dedicated flags to support high availability when multiple controller manager instances are running.
• Security Settings: Adjust TLS settings, CA bundles, and authentication parameters to uphold cluster integrity and protect communications.
• Resource Management: Tune resource limits and operational parameters to optimize controller performance for varying cluster sizes and workloads.

Effective operation of the Controller Manager involves monitoring, availability, and troubleshooting practices to maintain cluster stability:

• High Availability: Run multiple instances of the controller manager with leader election enabled to ensure continuous operation and automatic failover in case of an instance failure.
• Monitoring and Metrics: Expose and collect metrics via integrated endpoints for monitoring controller health, performance, and reconciliation rates, enabling proactive issue detection.
• Logging: Regularly review logs generated by the controller manager to identify errors, warnings, or anomalies that might indicate problems in resource reconciliation or controller loops.
• Resource Limits: Configure CPU and memory limits appropriately to prevent resource exhaustion, especially in large or heavily loaded clusters.
• Controller Configuration: Customize enabled controllers and tuning parameters based on workload characteristics to balance performance and resource usage.
• Troubleshooting: Investigate failed or slow reconciliation cycles by inspecting controller manager logs and reviewing the state of affected resources using Kubernetes tools.

This example demonstrates the step-by-step operation of a controller, specifically the Replication Controller, as it manages pod replica counts to maintain the desired state:

1. Observe Desired State: The controller detects that a user has defined a replication controller manifest specifying three replicas should exist.
2. Watch Actual State: Periodically checks the Kubernetes API server to see how many pods are currently running that match the desired specification.
3. Detect Discrepancy: Notices only one pod is running, which is less than the specified three replicas.
4. Take Action: Initiates pod creation requests to the API server until the running pods total three, reconciling the difference.
5. Continuous Loop: Repeats this observation and correction process continually, ensuring that any pod failures or deletions are quickly remedied to maintain the specified replica count.

This process illustrates how controllers automatically keep the actual cluster state in sync with what is defined in configuration, enabling self-healing and automated management.