Understanding Kubernetes: Part 25 Affinity and Anti-Affinity
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Last updated
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Node Affinity is a rule that ensures Pods are scheduled on specific nodes based on defined labels.
Pod Affinity ensures that Pods are scheduled close to other Pods based on label selectors.
Pod Anti-Affinity prevents Pods from being scheduled on the same nodes or within a failure domain.
Affinity and Anti-Affinity are useful in various scenarios:
Ensuring that workloads requiring SSD storage run on nodes labeled with storage=ssd
.
Running GPU-intensive workloads on nodes labeled gpu=true
.
Ensuring that microservices communicate efficiently by scheduling them on the same node.
Keeping interdependent applications (e.g., frontend and backend) close together to reduce latency.
Distributing replicas of an application across multiple nodes for high availability.
Ensuring that critical workloads are not placed on the same node to prevent single points of failure.
Node Affinity rules are defined in the Pod specification under affinity.nodeAffinity
.
This ensures that the Pod is scheduled only on nodes labeled storage=ssd
.
Pod Affinity rules are defined under affinity.podAffinity
.
This ensures that the Pod is scheduled on the same node as other Pods labeled app=frontend
.
Pod Anti-Affinity is defined under affinity.podAntiAffinity
.
This ensures that backend
Pods are scheduled on different nodes to improve reliability.
As a Senior DevOps Engineer, I leveraged Affinity and Anti-Affinity for:
Optimizing Microservice Deployments: Ensured interdependent services were scheduled on the same node to reduce latency.
High Availability Strategies: Used Anti-Affinity to distribute replicas across nodes to prevent single points of failure.
Performance Tuning: Enforced Node Affinity rules to assign workloads to high-memory nodes for better performance.
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