Federated Kubernetes Operator for Disaster Resilience
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Solution Overview
Problem
Kubernetes clusters configured as a single point of failure lead to significant delays and potential data loss during disaster recovery, as recreating the cluster from backups can be time-consuming and may result in loss of metadata and customer systems.
Innovation Solution
Implementing a federated operator architecture that separates custom resources between an orchestration cluster and a worker cluster, using a Kubernetes API proxy server for communication and decoupling the control plane, allowing for rapid recreation of the worker cluster without requiring human intervention or cluster state backups.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single Kubernetes cluster is used, then device complexity is reduced, but reliability deteriorates due to single point of failure
Solution Approach 1:
The system divides the Kubernetes cluster into two separate clusters: an orchestration cluster that maintains control plane components and custom resources, and a worker cluster that runs workload pods. This segmentation allows the worker cluster to be rapidly recreated after disaster without affecting the orchestration cluster, thereby improving reliability while managing complexity through clear functional separation.
Solution Approach 2:
The control plane components (API server, etcd, scheduler, controller manager) are extracted from the worker cluster and placed in a separate orchestration cluster. This extraction creates a single point of control that can survive worker cluster failures, improving reliability while the simplified worker cluster can be quickly rebuilt.
2Reliability
If cluster state backups are used for disaster recovery, then reliability improves, but loss of time increases due to considerable recreation delay
Solution Approach 1:
The orchestration cluster maintains custom resources (CustomResourceDefinitions, ClusterRoles, ServiceAccounts, ConfigMaps) in advance that define the desired state of the worker cluster. When disaster strikes, these pre-configured resources enable rapid recreation of the worker cluster without needing to restore from backups, significantly reducing recovery time while maintaining reliability.
Solution Approach 2:
Instead of backing up and restoring entire cluster states, the system uses lightweight custom resources that can be quickly copied and applied to recreate the worker cluster. This copying approach is much faster than traditional backup restoration while ensuring reliability through the orchestration cluster's persistent storage of resource definitions.
3Reliability
If a federated operator architecture is implemented, then reliability improves through rapid recovery, but device complexity increases due to multi-cluster setup
Solution Approach 1:
The orchestration cluster acts as an intermediary that manages the worker cluster through custom resources and operators. This intermediary pattern simplifies the complexity by providing a single point of management while enabling disaster resilience - the operator in the orchestration cluster automatically manages worker cluster recreation, hiding the complexity from users.
Solution Approach 2:
The worker cluster is designed to be self-service capable, automatically recreating itself when it detects it has been deleted or becomes unhealthy. The custom resources in the orchestration cluster trigger automatic recreation workflows, eliminating the need for manual intervention and reducing operational complexity despite the federated architecture.
4Reliability
If custom resources are separated between clusters, then reliability improves through decoupling, but loss of information increases due to communication overhead
Solution Approach 1:
The custom resources in the orchestration cluster serve multiple functions: they define the desired state of the worker cluster, act as control signals for automatic recreation, and maintain metadata about customer systems. This multi-functionality reduces information loss by consolidating control and metadata management in a single location that survives disasters.
Solution Approach 2:
The operator continuously monitors the worker cluster's health and compares its state against the desired state defined in custom resources. When discrepancies are detected (such as cluster deletion), the operator provides feedback and automatically triggers recreation. This feedback mechanism ensures minimal information loss by continuously synchronizing the actual cluster state with the desired state stored in the orchestration cluster.
Data Source
AI summary
Disclosed herein are system, method, and computer program product embodiments for disaster resilience of applications managed by Kubernetes operators. An embodiment operates by creating an orchestration and worker cluster, where the worker cluster is coupled to the orchestration cluster by a proxy server. Custom resources are deployed to the orchestration cluster and custom resource controllers are deployed to the worker cluster. The proxy server federates these custom resources between the orchestration cluster and the worker cluster. During disasters, the worker cluster is recreated and reconciled to prevent loss of the federated cluster.