The 3-Week Schedule for AWS Certified CloudOps Engineer - Associate

 

The 3-Week Schedule for AWS Certified CloudOps Engineer - Associate 


Week 1 — Monitoring and Reliability (44% of the exam)

Day 1 — CloudWatch fundamentals Metrics, namespaces, dimensions, statistics vs. percentiles. Default EC2 metrics vs. what needs the CloudWatch agent (memory and disk usage are not default — this shows up constantly). Custom metrics, resolution, retention.

Day 2 — Logs and audit trail CloudWatch Logs, log groups, retention settings, metric filters, subscription filters, Logs Insights query syntax. CloudTrail: management vs. data events, organization trails, log file validation. Know when the answer is CloudTrail vs. CloudWatch Logs vs. VPC Flow Logs.

Day 3 — Alarms and auto-remediation Alarm states, missing-data treatment, composite alarms. EventBridge rules and targets. SNS. Then the remediation side: Systems Manager Automation runbooks, Lambda targets, EC2 recovery actions. This is where domain 1 gets scenario-heavy.

Day 4 — Auto Scaling and load balancing Launch templates vs. launch configs, target tracking vs. step vs. scheduled scaling, cooldowns, lifecycle hooks, warm pools. ALB vs. NLB vs. GWLB, target groups, health check tuning, stickiness, cross-zone balancing.

Day 5 — High availability Multi-AZ vs. multi-Region. RDS Multi-AZ vs. read replicas (different purposes — the exam checks that you know which). Aurora failover. S3 Cross-Region Replication. Route 53 health checks and failover routing.

Day 6 — Backup and recovery AWS Backup plans and vaults, EBS snapshots and the incremental model, AMI lifecycle, Data Lifecycle Manager. RTO/RPO and matching the four DR strategies to them. S3 versioning, lifecycle policies, Object Lock.

Day 7 — Consolidate No new material. 50–60 practice questions on domains 1 and 2 only, then re-read the docs for everything you got wrong.

Week 2 — Automation, Security, Networking (56%)

Day 8 — CloudFormation Template anatomy, intrinsic functions (Ref, GetAtt, Sub, FindInMap), parameters and mappings, conditions. Then the operational parts the exam loves: change sets, drift detection, DeletionPolicy, UpdateReplacePolicy, nested stacks, StackSets across accounts and Regions, and which update types cause replacement.

Day 9 — Systems Manager The single densest service on this exam. Parameter Store (Standard vs. Advanced, SecureString), Session Manager and why it beats bastion hosts, Patch Manager and patch baselines, Run Command, State Manager, Automation runbooks, Inventory. Know the SSM Agent prerequisites and the IAM instance profile it needs.

Day 10 — Deployment and containers Rolling, blue/green, canary, immutable. Elastic Beanstalk deployment policies. Then the SOA-C03 additions: ECR basics, EKS operational concepts, and where CDK and Terraform fit relative to CloudFormation.

Day 11 — IAM Policy evaluation logic and explicit deny. Identity vs. resource policies. Roles and cross-account access. Permission boundaries. SCPs and how they interact with IAM policies. IAM Identity Center. Practise reading a policy document and saying exactly what it allows.

Day 12 — Security services and cost KMS key types, rotation, grants. Secrets Manager vs. Parameter Store. GuardDuty, AWS Config with conformance packs and remediation, Inspector, Security Hub, Trusted Advisor — know which one answers which question. Then cost: Cost Explorer, Budgets, Savings Plans vs. Reserved Instances, S3 storage classes and Intelligent-Tiering, Compute Optimizer.

Day 13 — VPC Subnets and route tables, IGW vs. NAT Gateway, Security Groups vs. NACLs (stateful vs. stateless — reliably tested), VPC endpoints gateway vs. interface, peering and its limits, Transit Gateway, VPC Flow Logs and reading a rejected-traffic line. Expect multi-step troubleshooting scenarios here.

Day 14 — DNS and edge, then consolidate Route 53 routing policies — simple, weighted, latency, failover, geolocation, geoproximity, multivalue — and alias vs. CNAME. CloudFront behaviours, OAC, cache invalidation. Finish with 50–60 questions across domains 3, 4 and 5.

Week 3 — Mocks and repair

No new content this week. The whole point is finding your gaps while there's still time to close them.

Day 15 — Mock exam 1. Full 130 minutes, timed, no pausing, no looking anything up. Score it and note the per-domain breakdown.

Day 16 — Review every single wrong answer. Not just the right option — why each distractor is wrong. For anything you don't fully follow, read the actual AWS documentation page. Slower than it sounds; budget the full two hours.

Day 17 — Mock exam 2.

Day 18 — Review, then drill your weakest domain. By now a pattern is obvious. Mine was CloudFormation update behaviour and Route 53 routing policies.

Day 19 — Mock exam 3. You want to be consistently above 80% here. The real exam pass mark is 72%, but mock scores tend to run a little optimistic relative to it.

Day 20 — Read the official exam guide task statements end to end. Every bullet AWS lists is fair game. Anything you can't explain in a sentence, go look up. Flashcards for service limits and defaults.

Day 21 — Light review and stop. Skim your notes, confirm your Pearson VUE booking and ID, and finish early. Cramming the night before buys nothing on a scenario exam.

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How to Fix Kubernetes CrashLoopBackOff


If your Pod is stuck in CrashLoopBackOff, it means Kubernetes is repeatedly starting the container, but the container keeps crashing. After a few failed restarts, Kubernetes applies a backoff delay and shows the status CrashLoopBackOff.

In this guide, you’ll learn the exact commands to debug CrashLoopBackOff and the 7 most common real-world causes with fixes.

  1. What is CrashLoopBackOff in Kubernetes?

  2. Quick Commands to Debug CrashLoopBackOff

  3. Fix #1: Application is crashing on startup

  4. Fix #2: Wrong command or entrypoint

  5. Fix #3: Missing environment variables / secrets

  6. Fix #4: Liveness probe killing the pod

  7. Fix #5: Image issues or wrong architecture

  8. Fix #6: OOMKilled (memory limit exceeded)

  9. Fix #7: Volume mount or permission issues

  10. Best Practices to Prevent CrashLoopBackOff

1) What is CrashLoopBackOff in Kubernetes?

CrashLoopBackOff is not the error itself.
It is Kubernetes telling you:

“Your container keeps crashing. I will restart it, but with increasing delay.”

So your real job is to find why the container exits.

2) Quick Commands to Debug CrashLoopBackOff

Step 1: Check pod status

kubectl get pods -n <namespace>

Step 2: Describe the pod (most important)

kubectl describe pod <pod-name> -n <namespace>

Look at:

  • Events section

  • Container restart count

  • Probe failures

  • OOMKilled

Step 3: Check logs

kubectl logs <pod-name> -n <namespace>

If the pod restarted, check previous container logs:

kubectl logs <pod-name> -n <namespace> --previous

Step 4: Check container exit code

kubectl get pod <pod-name> -n <namespace> -o jsonpath='{.status.containerStatuses[*].state.terminated.exitCode}'

3) Fix #1: Application is Crashing on Startup

Symptoms

  • Logs show stack trace

  • Exit code is often 1

  • Pod restarts continuously

Fix

Check the logs:

kubectl logs <pod-name> -n <namespace> --previous

Then fix the app issue:

  • missing config file

  • invalid config format

  • app cannot connect to DB

  • missing dependency

4) Fix #2: Wrong Command or Entrypoint

This is extremely common in Docker + Kubernetes.

Symptoms

Logs show:

  • exec format error

  • command not found

  • container exits instantly

Check your deployment YAML

kubectl get deploy <deploy-name> -n <namespace> -o yaml

Look for:

command: ["..."]
args: ["..."]

Fix

  • Remove incorrect command/args

  • Ensure the binary exists in image

  • Verify Dockerfile ENTRYPOINT and CMD

5) Fix #3: Missing Environment Variables / Secrets

Symptoms

Logs show:

  • ENV VAR not set

  • unable to load config

  • permission denied to secret

Check env vars

kubectl describe pod <pod-name> -n <namespace>

Fix

If using secret:

kubectl get secret -n <namespace>
kubectl describe secret <secret-name> -n <namespace>

Also confirm secret is referenced correctly:

envFrom:
  - secretRef:
      name: my-secret

6) Fix #4: Liveness Probe Killing the Pod

Many people confuse probe failure with “app crash”.

Your container might be running, but Kubernetes kills it due to liveness probe failures.

Symptoms

Events show:

  • Liveness probe failed

  • Readiness probe failed

Check pod events

kubectl describe pod <pod-name> -n <namespace>

Fix

  • Increase initialDelaySeconds

  • Increase timeoutSeconds

  • Fix health endpoint

Example:

livenessProbe:
  httpGet:
    path: /health
    port: 8080
  initialDelaySeconds: 30
  periodSeconds: 10
  timeoutSeconds: 5

7) Fix #5: Image Issues or Wrong Architecture

Symptoms

  • exec format error

  • Works on local, fails in cluster

  • Image pulled successfully but crashes instantly

Fix

Check node architecture:

kubectl get nodes -o wide

If your nodes are amd64 but image is arm64, container will fail.

Solution:

  • Build multi-arch image

  • Or build image for correct architecture

8) Fix #6: OOMKilled (Memory Limit Exceeded)

This is one of the most common reasons in production.

Symptoms

  • Exit code often 137

  • Pod restarts

  • Events show OOMKilled

Check pod status

kubectl describe pod <pod-name> -n <namespace>

Fix

Increase memory limit:

resources:
  requests:
    memory: "256Mi"
  limits:
    memory: "512Mi"

Or optimize application memory usage.

9) Fix #7: Volume Mount or Permission Issues

Symptoms

  • container crashes when writing to a directory

  • logs show permission denied

  • errors related to volume mount paths

Check volume mount in YAML

kubectl get pod <pod-name> -n <namespace> -o yaml

Fix

  • Ensure mountPath is correct

  • Use correct securityContext

  • If using non-root container, fix permissions

Example:

securityContext:
  runAsUser: 1000
  fsGroup: 1000

10) Best Practices to Prevent CrashLoopBackOff

✅ Always use readiness + liveness probes correctly
✅ Add proper resource requests/limits
✅ Validate config before deploy
✅ Use structured logs
✅ Use kubectl logs --previous during debugging
✅ Add alerting for restart count

11) FAQ

Q1. How long does CrashLoopBackOff last?

It continues until:

  • the pod becomes healthy

  • or you delete/scale down deployment

Q2. How do I stop CrashLoopBackOff immediately?

Scale deployment to 0:

kubectl scale deploy <deploy-name> -n <namespace> --replicas=0

Q3. What is the fastest way to debug?

Run:

kubectl describe pod <pod-name> -n <namespace>
kubectl logs <pod-name> -n <namespace> --previous

Conclusion

CrashLoopBackOff is common in Kubernetes, but it is always solvable if you debug systematically.

Start with:

  • kubectl describe pod

  • kubectl logs --previous

  • Events + exit codes

Then apply the fix based on the root cause.

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Kubernetes for Begineers [PDF Notes]

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10 Books Every DevOps Engineer Should Read

Introduction:

DevOps is a set of practices that combines software development (Dev) and IT operations (Ops) to shorten the systems development life cycle and provide continuous delivery with high quality. DevOps engineers are responsible for implementing and maintaining these practices.

There are many great books available on DevOps. Here are 10 of the best books that every DevOps engineer should read:

  1. The DevOps Handbook: How to Create World-Class Agility, Reliability, and Security in Technology Organizations by Gene Kim, Jez Humble, Patrick Debois, John Allspaw, and John Willis. This book is considered to be the "DevOps bible" and is a comprehensive guide to the principles and practices of DevOps.
  2. The Phoenix Project: A Novel about IT, DevOps, and Helping Your Business Win by Gene Kim, Kevin Behr, and George Spafford. This book is a fictional story that illustrates the benefits of DevOps through the eyes of a fictional IT manager.
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Cloud & DevOPS Material

DevOps material for interview

https://drive.google.com/drive/folders/1fBSPB2qZNzxvnhfiwMb9sfwdoJfgfALF?usp=sharing

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Kubernetes Workloads (Deployments, Jobs, CronJobs, etc.)

 

Deployments

In Kubernetes, Deployments provides updates for pod and replica sets. It is basically a tool to manage how the pod will behave inside the cluster.

Once we declare the desired state in the YAML file, the deployment controller makes sure the actual state to desired

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