Develop and maintain Infrastructure as Code using Terraform, Ansible, and cloud-native IaC tools

 

1) “Develop and maintain Infrastructure as Code using Terraform, Ansible, and cloud-native IaC tools.”

What it means (in simple words)

Instead of clicking in cloud portals, you define infrastructure in code and deploy it consistently:

• Terraform → provisions cloud resources (VPC/VNet, subnets, EKS/AKS, IAM, RDS, etc.)

• Ansible → configures servers/apps after provisioning (packages, config files, users, services)

• Cloud-native IaC → AWS CloudFormation, Azure Bicep/ARM, GCP Deployment Manager (or Pulumi)

Why it’s helpful in development

• Repeatable environments: Dev/Test/Prod become identical (less “works on my machine”)

• Faster onboarding: New env in minutes

• Safer changes: PR review + plan output

• Audit trail: Git history shows who changed infra and why

• Disaster recovery: You can recreate infra from code

How to implement (real-world approach)

A. Terraform structure (common enterprise pattern)

• Create modules: network, eks/aks, rds, iam, monitoring

• Separate environments using workspaces or folders:

  • environments/dev, environments/stage, environments/prod

• Use remote state:

  • S3 + DynamoDB lock (AWS) / Azure Storage + locking / GCS (GCP)

B. Terraform workflow

1. Dev opens PR with Terraform changes

2. CI runs:

   • terraform fmt (format)

   • terraform validate

   • tflint (lint)

   • checkov/tfsec (security scans)

   • terraform plan and posts output to PR

3. After approval:

   • terraform apply runs via pipeline (not a laptop)

C. Where Ansible fits
Use Ansible when you have:

• VMs, legacy apps, OS-level configs

• Need to install agents (Datadog, Splunk), configure Nginx, patching, hardening
  Implementation:

• Terraform creates the VM + network + security groups

• Ansible configures the VM (idempotent playbooks)

• Use Ansible Vault/Secrets manager for credentials

✅ Rule of thumb: Terraform creates infrastructure; Ansible configures software and OS.

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2) “Implement HA/DR strategies, load balancing, and hybrid networking solutions.”

What it means

You design systems that:

• Stay up when components fail (HA: High Availability)

• Recover from disasters (DR: Disaster Recovery)

• Distribute traffic safely (load balancing)

• Connect on-prem + cloud securely (hybrid networking)

Why it’s helpful in development

• Your app won’t go down during deployments, node failures, AZ outages

• You meet enterprise requirements (uptime/SLA)

• You avoid “big bang outages” by designing for failure

How to implement HA (practical patterns)

Compute HA

• Run services across multiple Availability Zones

• Kubernetes:

  • replicas across AZs

  • PodDisruptionBudgets

  • readiness/liveness probes

  • autoscaling (HPA + Cluster Autoscaler)

Database HA

• Managed DB Multi-AZ (RDS Multi-AZ / Azure SQL HA / Cloud SQL HA)

• Read replicas for scaling reads

• Backup + point-in-time recovery

Load Balancing

• L7 LB (HTTP/HTTPS): Ingress controller / ALB / App Gateway

• L4 LB (TCP): NLB / Azure Load Balancer
  Implement:

• TLS termination

• health checks

• weighted routing / blue-green / canary (advanced)

How to implement DR (real DR)

Define:

• RPO (how much data loss is acceptable)

• RTO (how fast must you recover)

Common DR strategies:

• Backup & Restore (cheap, slower RTO)

• Pilot Light (core running, scale on disaster)

• Warm Standby (smaller version running)

• Active-Active (best RTO, complex & expensive)

Implementation checklist:

• Automated backups + tested restores

• Infrastructure reproducible with IaC

• Replicated data (cross-region where required)

• Runbooks + game days (DR drills)

Hybrid networking (on-prem + cloud)

Typical solutions:

• Site-to-Site VPN (quick, cheaper)

• Dedicated private link: AWS Direct Connect / Azure ExpressRoute (more stable)

• DNS strategy: split-horizon DNS, private endpoints

• Routing: BGP, route tables, NAT, firewall rules

• Security: least privilege, segmentation, inspection (firewalls), zero trust

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3) “Integrate monitoring, SLOs, and quality gates into CI/CD pipelines for resilient delivery.”

What it means

You don’t just deploy fast — you deploy safely:

• Monitoring tells you if systems are healthy

• SLOs define reliability targets

• Quality gates block bad changes before production

Why it’s helpful

• Stops broken builds and insecure deployments early

• Prevents outages by using measurable “go/no-go” checks

• Makes release quality consistent across teams

How to implement Monitoring (standard stack)

• Metrics: Prometheus / CloudWatch / Azure Monitor

• Logs: ELK / Loki / Splunk

• Traces: OpenTelemetry + Jaeger/Tempo

• Alerts: PagerDuty / Opsgenie / Teams/Slack

Minimum monitoring baseline:

• Golden signals: latency, traffic, errors, saturation

• Dashboards per service + per dependency

• Alerting tied to customer impact (not noisy)

What are SLOs (in practical terms)

• SLA = promise to customer (contract)

• SLO = internal target (engineering goal)
  Example:

• SLO: 99.9% successful requests per 30 days

• Error budget = allowed failure (0.1%) → guides release speed

How to integrate “quality gates” in CI/CD

Think of gates as checkpoints:

CI gates (before merge)

• Unit tests + coverage threshold

• Linting + formatting

• SAST (code security)

• Dependency scan (SCA)

• IaC scan (tfsec/checkov)

• Container scan (Trivy)

• Policy-as-code (OPA/Conftest)

CD gates (before production)

• Manual approval for prod (optional)

• Smoke tests on staging

• Deployment strategy checks:

  • canary/blue-green

  • automatic rollback if health degrades

• SLO-based gate:

  • “If error rate > X% or latency > Yms → block / rollback”

Post-deploy gates (progressive delivery)

• Argo Rollouts / Flagger

• Metrics analysis during rollout

• Automated rollback on bad metrics

✅ The “resilient delivery” part comes from progressive rollouts + SLO-based automated rollback.