Infrastructure

Infrastructure Management

Framework for managing infrastructure as code, deployments, and disaster recovery.

Infrastructure as Code (IaC) Best Practices

Principles

• Version control everything — All infrastructure configs in Git
• Idempotent — Running same config multiple times produces same result
• Modular — Reusable modules for common patterns
• Documented — README for each module, inline comments for complex logic
• Tested — Validate configs before applying (terraform validate, linting)

Workflow

1. Plan — Review changes, estimate impact
2. Validate — Run validation/linting
3. Review — Code review for infrastructure changes
4. Apply — Deploy in stages (dev → staging → prod)
5. Verify — Confirm changes work as expected
6. Document — Update architecture docs

Change Management

• Small changes: Direct PR, single reviewer
• Medium changes: PR with 2 reviewers, staging test
• Large changes: RFC, architecture review, staged rollout

Deployment Strategies

Blue-Green Deployment

• Two identical environments: Blue (current), Green (new)
• Switch traffic from Blue to Green instantly
• Rollback: Switch back to Blue if issues
• Pros: Zero downtime, instant rollback
• Cons: Requires 2x capacity during deployment

Canary Deployment

• Gradual rollout: 5% → 25% → 50% → 100%
• Monitor metrics at each stage
• Rollback: Stop rollout if metrics degrade
• Pros: Risk mitigation, gradual validation
• Cons: Slower deployment, requires monitoring

Rolling Deployment

• Update instances one at a time
• Maintains capacity during rollout
• Rollback: Stop rollout, revert remaining instances
• Pros: No capacity overhead
• Cons: Partial version running, slower rollback

Feature Flags

• Toggle features without deployment
• Gradual rollout: Enable for % of users
• Instant rollback: Disable flag
• A/B testing: Compare feature variants

Disaster Recovery Planning

RTO/RPO Definitions

• RTO (Recovery Time Objective): Max acceptable downtime
• RPO (Recovery Point Objective): Max acceptable data loss

Disaster Recovery Template

# Disaster Recovery Plan: {Service/Component}

## RTO/RPO Targets
- **RTO**: {Time} (e.g., 1 hour)
- **RPO**: {Time} (e.g., 15 minutes)

## Failure Scenarios

### Scenario: {Failure Type}
- **Likelihood**: {High/Medium/Low}
- **Impact**: {Description}
- **Detection**: {How to detect}
- **Recovery Steps**:
  1. {Step 1}
  2. {Step 2}
  3. {Step 3}
- **Verification**: {How to verify recovery}
- **Prevention**: {How to prevent}

### Scenario: {Another Failure}
{Repeat structure}

## Backup Strategy
- **Frequency**: {Daily/Hourly/Continuous}
- **Retention**: {Duration}
- **Location**: {Primary/Secondary regions}
- **Verification**: {How backups are tested}

## Recovery Procedures
- **Failover**: {Steps to failover}
- **Failback**: {Steps to failback}
- **Data Restore**: {Steps to restore from backup}

Change Management Checklist

Before making infrastructure changes:

• Impact assessment — What services/components affected?
• Rollback plan — How to revert if issues?
• Testing — Tested in dev/staging?
• Documentation — Runbook updated?
• Communication — Stakeholders notified?
• Monitoring — Alerts configured for new components?
• Backup — Backup/restore tested?
• Approval — Required approvals obtained?

Scaling Playbook

Horizontal Scaling (Scale Out)

When to use:

• Stateless services
• Need to handle more load
• Want redundancy

How:

• Add more instances
• Load balancer distributes traffic
• Auto-scaling based on metrics

Metrics to monitor:

• CPU utilization
• Request rate
• Queue depth

Vertical Scaling (Scale Up)

When to use:

• Stateful services (databases)
• Single-instance bottlenecks
• Memory/CPU limits reached

How:

• Increase instance size
• More CPU, memory, disk
• May require downtime

Metrics to monitor:

• CPU utilization
• Memory usage
• Disk I/O

Auto-Scaling Configuration

Scale-up triggers:

• CPU > 70% for 5 minutes
• Memory > 80% for 5 minutes
• Request rate > threshold
• Queue depth > threshold

Scale-down triggers:

• CPU < 30% for 15 minutes
• Request rate < threshold
• Ensure minimum instances maintained

Best practices:

• Set min/max instance limits
• Use multiple metrics (not just CPU)
• Scale up faster than scale down
• Test auto-scaling in staging

Infrastructure Review Checklist

• Security: Secrets managed, access controls, encryption
• Reliability: Redundancy, failover, backups
• Performance: Capacity planning, scaling configured
• Cost: Right-sized instances, reserved instances, unused resources
• Observability: Monitoring, logging, alerting configured
• Documentation: Architecture docs, runbooks updated
• Compliance: Meets regulatory requirements
• Disaster recovery: DR plan tested, RTO/RPO met