AWS Maintenance Best Practices for Startups

I've set up hundreds of AWS accounts for clients over the years. Here's your essential checklist when starting a new AWS account: 1. Delete default VPC, create a custom one 2. Set up budget alerts 3. Enable CloudTrail logs 4. Configure strong password policy 5. Enforce MFA for all users 6. Enable AWS Resource Explorer 7. Set up IAM roles and least privilege access 8. Enable AWS Security Hub for centralized security management 9. Implement tagging strategy for cost allocation 10. Enable AWS Organizations for multi-account strategy These steps establish a robust foundation for security, cost management, compliance, and scalability. Pro tip: Automate this process with Infrastructure as Code (IaC) tools like AWS CloudFormation, AWS CDK or Terraform. It ensures consistency and saves time on future setups. Which of these do you prioritize? Any crucial steps I missed? Share your thoughts!

Most startup DevOps engineers don’t fail because they lack skills. They fail because they start with the wrong priorities. Your first 30 days will quietly decide how painful (or smooth) the next 3 years will be. And yet most people jump straight into building features. Bad move. Here’s what actually matters first: DAY 1–3: Lock Things Down ➝ Enable MFA on the root account (non-negotiable) ➝ Create an IAM admin user, stop using root like a regular account ➝ Turn on CloudTrail in all regions (not just default) ➝ Set billing alerts (50%, 80%, 100%) Miss this stage, and you’re one mistake away from chaos. DAY 4–7: Build the Right Structure ➝ Set up AWS Organizations (yes, even if you’re “small”) ➝ Separate accounts: dev, staging, production ➝ Configure remote Terraform state (S3 + DynamoDB locking) ➝ Add git-secrets pre-commit hooks to every repo This is where you decide if your system will scale or fight you later. WEEK 2: Infrastructure as Code ➝ Define VPC, IAM, security groups in Terraform ➝ Stop clicking around the console ➝ If it’s not in code, it doesn’t truly exist Manual setups feel fast until they break. WEEK 3-4: CI/CD ➝ Build pipelines before product features ➝ Lint ➝ Test ➝ Security Scan ➝ Build ➝ Deploy ➝ Every commit to main should be deployable If deployments are painful now, they’ll become a nightmare later. Most engineers ignore this. Six months later, they’re rebuilding everything from scratch. Not because they’re bad engineers. Because they skipped the foundation. If you’re the first DevOps hire in a startup, this phase isn’t optional. It’s the job. #FirstDevOpsHire #StartupDevOps #DevOpsJourney

I have used this method on 100+ projects, Now, I am giving it here for free. Battle-tested playbook I’ve used with 100+ teams from startups to enterprise to reduce the AWS bill by 30% No fluff. No fancy dashboards. Just what actually works. Day 1–2: Cost Explorer + Tagging Audit → Open [AWS Cost Explorer] → Enable hourly + resource-level granularity → Filter by service, then by linked accounts → Identify top 3 spend categories (e.g., EC2, S3, Data Transfer) Now tag everything: - `Project` - `Owner` - `Environment` (dev/stage/prod) - `CostCenter` (if needed) Why? Untagged = invisible = unaccountable. Without tags, you’re flying blind. Pro tip: Use AWS Resource Groups to group untagged items. Day 3–4: Right-size Your Compute → Use AWS Compute Optimizer → Check EC2 instances with <20% CPU and Memory over 7–30 days → Consider: - Downgrading (e.g., m5 → t3) - Switching to **Graviton** (ARM-based, 20–40% cheaper) - Moving to **Fargate or Lambda** if infra is idle often Also review: - RDS instances: auto-pause in dev - ECS services: scale down unused services Why? Compute is often 60–70% of your bill. Fix this first. Day 5: Delete Zombie Infra → Use [Trusted Advisor] + [AWS Config] to find: - Orphaned EBS volumes (attached to terminated EC2s) - Idle Load Balancers (no traffic for 14+ days) - Old RDS snapshots (more than 7–14 days old) - Elastic IPs not attached to running instances - Unused S3 buckets storing logs from years ago Set deletion policies where safe. For dev resources, enforce auto-termination tags. Why? These don’t show up in dashboards But quietly drain your budget. Day 6: Set Storage Lifecycle Policies → For S3 buckets: - Archive logs after 30 days (Glacier or Deep Archive) - Delete test files after 90 days - Enable versioning cleanup → For EBS volumes: - Schedule snapshot pruning - Auto-delete unused volumes post-instance termination Why? Storage rarely gets optimized until it explodes. But small tweaks = big gains over time. Day 7: Set Budgets + Alerts → Go to [AWS Budgets] → Create: - Overall budget (with 80%, 90%, 100% thresholds) - Service-specific budgets (e.g., EC2, S3) - Linked account budgets if using Organizations → Set alerts via email or Slack (SNS integration) → Bonus: Add alerts for sudden cost spikes using anomaly detection Why? No alert = no awareness = no action. What happens after 7 days? You’ve got: ✅ Visibility ✅ Ownership ✅ Quick wins ✅ A repeatable process And most teams save 25–40% in the first month alone. We do this for AWS customers all the time. Want me to run this playbook for your infrastructure? DM me “audit” and I’ll spend 30 mins on your AWS account for free. Let’s make your cloud cost-efficient, not chaotic.