DevOps Bootcamp · Lesson

Resource Requests and Limits

Define CPU and memory requests and limits for Pods to ensure efficient resource allocation and prevent resource starvation.

Resource Requests and Limits is a free DevOps Bootcamp lesson on CoddyKit — lesson 1 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the DevOps Bootcamp learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.

Resource Needs in Kubernetes

Just like any application, your Pods need resources to run. Kubernetes helps manage these resources efficiently using Resource Requests and Resource Limits.

These settings tell Kubernetes how much CPU and memory your Pods need and how much they are allowed to use, ensuring fair resource distribution.

CPU Requests: Guaranteeing CPU

A CPU Request tells Kubernetes the minimum amount of CPU your Pod needs to run comfortably. It's a guarantee!

Kubernetes uses requests to schedule Pods on nodes with enough available resources.
If a node doesn't have enough CPU for the request, the Pod won't be scheduled there.
This helps prevent resource starvation for your critical applications.

CPU Units & Request Example

CPU is measured in 'cores' or 'millicores' (m). 1000m equals 1 CPU core. So, 500m is half a core.

Here's how to request 0.5 CPU cores in a Pod definition:

apiVersion: v1
kind: Pod
metadata:
  name: cpu-request-pod
spec:
  containers:
  - name: my-container
    image: nginx
    resources:
      requests:
        cpu: "500m"

CPU Limits: Preventing Overuse

A CPU Limit sets the maximum amount of CPU a Pod can use. It's a cap.

If a Pod tries to use more CPU than its limit, Kubernetes will throttle it.
This means the Pod's CPU usage will be restricted, preventing it from hogging resources from other Pods on the same node.

CPU Limit in Action

Here's an example of setting a CPU limit. If this Pod tries to use more than 1 CPU core, it will be throttled, meaning its performance will be constrained.

apiVersion: v1
kind: Pod
metadata:
  name: cpu-limit-pod
spec:
  containers:
  - name: my-container
    image: nginx
    resources:
      limits:
        cpu: "1"

Memory Requests: Guaranteed RAM

Similar to CPU, a Memory Request specifies the minimum amount of RAM your Pod needs to operate.

Kubernetes uses this to find a node with enough free memory for your Pod.
If a node runs out of memory, Pods without requests are often the first to be terminated (evicted) to free up space.

Memory Units & Request Example

Memory is measured in bytes. Common units are Mi (mebibytes) and Gi (gibibytes).

100Mi is 100 mebibytes. Here's how to request 256 MiB of memory:

apiVersion: v1
kind: Pod
metadata:
  name: mem-request-pod
spec:
  containers:
  - name: my-container
    image: nginx
    resources:
      requests:
        memory: "256Mi"

Memory Limits: Avoiding OOM

A Memory Limit defines the maximum memory a Pod can consume.

If a Pod exceeds its memory limit, it will be immediately terminated by the operating system with an 'Out Of Memory' (OOM) error. This is often seen as 'OOMKilled'.
This prevents a single runaway Pod from consuming all node memory and crashing the entire node.

Memory Limit in Action

This Pod has a memory limit of 512 MiB. If it tries to use more, it will be terminated (OOMKilled) to protect other workloads and the node.

apiVersion: v1
kind: Pod
metadata:
  name: mem-limit-pod
spec:
  containers:
  - name: my-container
    image: nginx
    resources:
      limits:
        memory: "512Mi"

Best Practices: Requests & Limits

It's a best practice to define both requests and limits for all your Pods. This provides stability and predictability for your cluster.

Requests ensure your Pods get minimum resources for scheduling.
Limits prevent resource starvation for other Pods and the node itself.

Here's a complete example:

apiVersion: v1
kind: Pod
metadata:
  name: full-resource-pod
spec:
  containers:
  - name: my-app
    image: my-registry/my-app:1.0
    resources:
      requests:
        cpu: "200m"
        memory: "128Mi"
      limits:
        cpu: "500m"
        memory: "256Mi"

Resource Check

You have a Pod defined with a CPU request of 200m and a CPU limit of 1 (which is 1000m).

What happens if this Pod tries to use 1.5 CPU cores?

Recap: Resource Management

In this lesson, we learned about Resource Requests and Resource Limits in Kubernetes.

Requests (CPU & Memory) guarantee minimum resources for Pod scheduling.
Limits (CPU & Memory) cap maximum usage to prevent resource contention.
Exceeding CPU limits leads to throttling; exceeding memory limits leads to termination (OOMKilled).
Always define both requests and limits for stable and predictable application performance!

Frequently asked questions

Is the “Resource Requests and Limits” lesson free?

Yes — the full text of “Resource Requests and Limits” is free to read here on the web, and the DevOps Bootcamp course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the DevOps Bootcamp course, upgrade to CoddyKit PRO.

What will I learn in “Resource Requests and Limits”?

Define CPU and memory requests and limits for Pods to ensure efficient resource allocation and prevent resource starvation. You practise DevOps Bootcamp with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.

Do I need any experience to start DevOps Bootcamp?

No prior experience is required. DevOps Bootcamp on CoddyKit is structured for beginners through advanced learners; this is — lesson 1 of 4, so you can start here or from the beginning and move at your own pace.

How long does the “Resource Requests and Limits” lesson take?

Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.

Can I write and run code in this DevOps Bootcamp lesson?

Yes. Every DevOps Bootcamp lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.

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