Understanding Kubernetes: Part 22 Kubernetes Resource Requests & Limits
Last updated
Last updated
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In Kubernetes, resource requests and limits define how much CPU and memory a container can use. This ensures fair resource allocation among workloads and prevents any single pod from consuming excessive resources, which could impact other applications running in the cluster.
Requests: The minimum amount of CPU/memory guaranteed to a container. The scheduler uses this value to place the pod on a suitable node.
Limits: The maximum amount of CPU/memory a container can use. If a container exceeds this, Kubernetes restricts it (for CPU) or terminates it (for memory).
For example:
If you have a microservice that processes user requests, you can set CPU and memory requests to ensure it has enough resources to function and limits to prevent it from consuming excessive resources during traffic spikes.
✅ Efficient Resource Management: Prevents resource hogging and ensures optimal cluster utilization. ✅ Better Performance: Guarantees that critical applications always have the required resources. ✅ Avoids OOM (Out of Memory) Kills: Helps prevent crashes due to excessive memory usage. ✅ Fair Scheduling: Ensures the Kubernetes scheduler places workloads appropriately based on available resources.
As a Senior DevOps Engineer, I ensured all Kubernetes deployments had proper resource requests and limits to avoid performance degradation. For example, in a high-traffic Node.js API, I set:
Requests: Ensured the service always had enough resources to handle base traffic.
Limits: Prevented excessive resource usage, ensuring stability during peak loads.
Monitoring: Used Prometheus + Grafana to fine-tune limits based on actual usage.
requests.memory: “256Mi” → The container is guaranteed 256MiB of memory.
requests.cpu: “250m” → The container is guaranteed 0.25 vCPU.
limits.memory: “512Mi” → The container cannot exceed 512MiB of memory.
limits.cpu: “500m” → The container cannot exceed 0.5 vCPU.
This setup ensures optimal performance while preventing excessive resource usage.
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