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Free tutorial · 24 lessons

Cloud Computing Tutorial

Cloud computing for engineers, AWS first with Azure and Google Cloud equivalents: regions and zones, shared responsibility, pricing, IAM and policies, encryption, VMs, containers, serverless, object storage, databases, messaging, monitoring, cost management, disaster recovery and well-architected design. Every example is Python you can run in the browser.

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Cloud Basics

  1. Cloud Computing Introduction — What cloud computing is, the service models (IaaS, PaaS, SaaS, serverless), and how AWS, Azure and Google Cloud compare.
  2. Regions and Availability Zones — How cloud infrastructure is organised into regions and availability zones, and how to use them for availability and latency.
  3. The Shared Responsibility Model — What the cloud provider secures and what remains your job, for IaaS, PaaS and serverless.
  4. Cloud Pricing Models — On-demand, reserved capacity and savings plans, spot instances and free tiers, and how to estimate a monthly bill.
  5. Cloud Computing History & Milestones — How Amazon, Microsoft and Google turned their infrastructure into public clouds, the launches that defined each era from S3 and EC2 to serverless, Kubernetes and AI accelerators, and how the three providers compare today.

Identity and Security

  1. Identity and Access Management (IAM) — Users, groups, roles and policies on AWS, and how Azure (Entra ID and RBAC) and Google Cloud IAM model the same ideas.
  2. How Policies Are Evaluated — Explicit deny, allow and implicit deny: how AWS evaluates IAM policies, conditions, and organisation guardrails.
  3. Least Privilege and Temporary Credentials — Grant only what's needed, use roles and federation instead of keys, and find unused permissions.
  4. Encryption and Key Management — Encryption at rest and in transit, managed key services (KMS, Key Vault, Cloud KMS), and envelope encryption.
  5. A Cloud Security Baseline — The guardrails every cloud account needs from day one: audit logs, threat detection, MFA, guardrails and secure defaults.

Compute

  1. Virtual Machines and Auto Scaling — Choose instance types, use machine images, and scale fleets of VMs automatically with auto scaling groups.
  2. Containers in the Cloud — Run containers on ECS, Fargate, EKS, Azure Container Apps, AKS, Cloud Run and GKE, and choose between them.
  3. Serverless Functions — How Lambda, Azure Functions and Cloud Run functions work: events, scaling, cold starts, limits and pricing.
  4. Load Balancing and Scaling Patterns — Put load balancers in front of fleets, scale stateless tiers horizontally, and protect stateful tiers.

Storage and Databases

  1. Object Storage (S3, Blob, Cloud Storage) — Store files in buckets: keys, storage classes, lifecycle rules, versioning, presigned URLs and keeping buckets private.
  2. Block and File Storage — Disks for VMs (EBS, Managed Disks, Persistent Disk), shared file systems (EFS, Azure Files, Filestore) and snapshots.
  3. Managed Relational Databases — RDS, Aurora, Azure SQL and Cloud SQL: what managed means, Multi-AZ, read replicas, backups, and choosing an engine.
  4. NoSQL Databases — Key-value and document databases (DynamoDB, Cosmos DB, Firestore, Bigtable): partition keys, access patterns and hot partitions.

Integration and Operations

  1. Queues, Topics and Events — Decouple services with queues (SQS, Service Bus, Pub/Sub), publish/subscribe topics and event buses, and handle retries safely.
  2. Monitoring and Logging in the Cloud — CloudWatch, Azure Monitor and Google Cloud Observability: metrics, logs, alarms, dashboards and tracing for cloud workloads.
  3. Cost Management (FinOps) — See where money goes with tags and cost allocation, set budgets and anomaly alerts, and find the usual savings.
  4. Reliability and Disaster Recovery — RTO and RPO, the four disaster-recovery strategies from backup-and-restore to multi-site, and testing restores.
  5. Well-Architected Design — The well-architected frameworks from AWS, Azure and Google Cloud, and how to use their pillars to review a design.
  6. Cloud Next Steps — What to learn next: the Cloud Engineering in Production course, networking, Terraform, certifications and quizzes.

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