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aws-pro

AWS guidance — core services, IAM least privilege, networking, cost control, and production architecture patterns.

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Overview

AWS is the broadest cloud platform — 200+ services, with a core set (EC2, S3, RDS, IAM, VPC, Lambda, CloudFront, Route53, EKS/ECS) covering most architectures. Its breadth is the challenge: there are five ways to do everything, pricing is complex, and IAM misconfigurations are the leading cause of cloud incidents.

The disciplines that matter: IAM least privilege, VPC networking fundamentals, choosing the right compute/storage per workload, and cost awareness from day one. This skill covers the core services, the security baseline, and architecture patterns that work — plus the cost traps to avoid.

When to use

  • Designing architecture on AWS (choosing services).
  • Setting up IAM (users, roles, policies, least privilege).
  • Building VPC networking (subnets, routing, security groups).
  • Choosing compute (EC2, Lambda, ECS, EKS, Fargate).
  • Controlling AWS costs (finding waste, budgets, alerts).
  • Securing an AWS account (baseline, auditing, incident response).
  • Preparing for production (multi-AZ, backups, DR).

Core concepts

  • IAM: least privilege, always. Roles for workloads (never long-lived access keys for apps), policies scoped to specific actions and resources, no * on production policies. IAM Access Analyzer finds unused permissions; credential reports find stale keys.
  • VPC fundamentals. Your private network: public subnets (load balancers, NAT) + private subnets (apps, databases) across 2-3 AZs; route tables, internet gateway, NAT gateway. Security groups (stateful instance firewalls) + NACLs (stateless subnet firewalls) — security groups do most of the work.
  • Compute choices. EC2 (control, steady workloads), Lambda (event-driven, spiky, short tasks), ECS/Fargate (containers without managing servers), EKS (Kubernetes when you need it). Match the abstraction to the team's operational capacity — EKS without K8s expertise is pain.
  • S3. Object storage for everything static: versioning on, encryption on, block public access on (use CloudFront OAC for public content), lifecycle policies to Glacier for old data. S3 is also the Terraform-state, backup, and log-archive default.
  • RDS/Aurora. Managed Postgres/MySQL: Multi-AZ for HA, read replicas for scale, automated backups + point-in-time recovery, Performance Insights for query tuning. Never run production databases on EC2 unless you have a very good reason.
  • CloudFront + Route53. CDN for global latency and caching; Route53 for DNS with health-checked routing. CloudFront in front of S3/ALB is the standard public-web pattern.
  • Lambda well. Small functions, right-sized memory (CPU scales with memory), VPC only when needed (it adds cold-start latency), reserved concurrency to bound blast radius, DLQs for async failures.
  • SQS/SNS/EventBridge. Queues (SQS) for decoupling, topics (SNS) for fan-out, EventBridge for event routing between services. Prefer managed messaging over self-hosted brokers unless you need the protocol.
  • CloudWatch. Metrics, logs, alarms — the default observability. Structured JSON logs, metric filters, composite alarms; but know its costs (custom metrics, log ingestion) and supplement with purpose-built tools at scale.
  • Organizations and accounts. Multi-account strategy (prod/staging/dev, security, logging) with SCPs for guardrails. One account for everything is how incidents become company-wide.
  • Pricing model. On-demand vs reserved/savings plans (steady workloads), spot (interruptible batch), graviton (ARM — cheaper and faster for many workloads). Right-size before committing to reservations.
  • Backups and DR. AWS Backup for centralized policies; cross-region replication for S3 and RDS snapshots; define RTO/RPO per workload and test restores — untested backups are rumors.
  • Tagging. Cost allocation tags (team, environment, service) enforced by policy — without tags, cost attribution is impossible.
  • Security baseline. CloudTrail on (all regions, log file validation), GuardDuty for threat detection, Security Hub for posture, Config for compliance rules. Enable these before you need them.
  • Secrets Manager / Parameter Store. Never env-var secrets into containers or bake them into AMIs; fetch at runtime with IAM-scoped access and rotation.
  • VPC endpoints. PrivateLink endpoints for S3, DynamoDB, and other AWS services — keeps traffic off the internet and avoids NAT data-processing charges.
  • Auto Scaling done right. Target-tracking policies on meaningful metrics (request count per target, custom app metrics) — not just CPU; warm pools for spiky workloads.

Practical workflow

  1. Set up the account foundation. Organizations with separate accounts (prod/staging/dev/security), CloudTrail everywhere, GuardDuty + Security Hub enabled, IAM Identity Center for human access (no IAM users for people).
  2. Build the VPC. Public/private subnets across 3 AZs, NAT gateways (or NAT instances for dev cost savings), security groups with least-privilege rules, VPC flow logs for debugging.
    # sketch: public ALB -> private app -> private RDS, 3 AZs
    module "vpc" {
      source = "terraform-aws-modules/vpc/aws"
      azs = ["us-east-1a", "us-east-1b", "us-east-1c"]
      public_subnets = ["10.0.1.0/24", "10.0.2.0/24", "10.0.3.0/24"]
      private_subnets = ["10.0.11.0/24", "10.0.12.0/24", "10.0.13.0/24"]
    }
    
  3. Lock down IAM. Roles per workload with scoped policies; no static keys for apps (IRSA for EKS, instance profiles for EC2, OIDC for CI); MFA for humans; regular access reviews.
  4. Choose compute per workload. Steady API → ECS/Fargate or EC2 ASG; spiky events → Lambda; need K8s → EKS; batch → spot fleets. Right-size with Compute Optimizer, prefer Graviton.
  5. Put data on managed services. RDS Multi-AZ with automated backups, ElastiCache for Redis, S3 with versioning + lifecycle. Test restore procedures quarterly.
  6. Front with CloudFront + WAF. CDN caching, TLS, WAF rules for common attacks; Route53 health checks with failover routing for multi-region.
    • Cache static aggressively, dynamic selectively; invalidate deliberately — invalidations cost and signal a design smell if constant.
  7. Observe and alarm. CloudWatch dashboards for golden signals; alarms on error rates, latency, and saturation; structured logs with correlation IDs; trace with X-Ray or OpenTelemetry.
  8. Control costs. Budgets with alerts, Cost Explorer reviews, kill idle resources (unattached EBS, old snapshots, idle NAT/LBs), S3 lifecycle policies, compute savings plans after right-sizing.

Common pitfalls

  • AdministratorAccess everywhere — wildcard IAM is the #1 cloud security failure; least privilege from the start.
  • Long-lived access keys — leaked in repos and logs; roles + OIDC, rotate what remains.
  • Single AZ deployments — one AZ failure = outage; multi-AZ for everything production.
  • Public S3 buckets — data exposure; block public access, serve via CloudFront OAC.
  • Unencrypted everything — EBS, RDS, S3 without encryption; enable by default (it's free).
  • No CloudTrail — flying blind after an incident; enable in all regions with log validation.
  • Oversized instances — paying for idle CPU; right-size, then commit to savings plans.
  • Idle resource sprawl — unattached volumes, old AMIs/snapshots, forgotten load balancers; audit regularly.
  • NAT gateway cost surprise — per-GB data processing charges; budget for it or architect around it.
  • Lambda in VPC by default — cold-start latency and ENI management for no benefit; only when accessing VPC resources.
  • No backups tested — snapshots exist but restores never tried; test quarterly.
  • One account for everything — blast radius of a compromise; multi-account with SCPs.
  • Ignoring GuardDuty findings — threat detection enabled but unmonitored; findings need a response runbook.
  • Secrets in user-data / env vars — visible in console and snapshots; use Secrets Manager with runtime retrieval.
  • Default VPC for production — the default VPC's flat open design; build purpose-specific VPCs instead.
  • Cross-AZ data transfer blindness — chatty cross-AZ traffic racking up charges; keep data-local where possible.

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