Cloud Engineer Roadmap

How to start, what to learn, and the resources to help you build real-world cloud skills

Author

Vishakha Sadhwani
June 19, 2025

Hi Inner Circle,

Welcome back!

Today we are going to dive into the cloud engineer's step-by-step roadmap.

This role goes beyond simply learning tools – it's about understanding how all the components work together to design, build, and deploy effective cloud systems. It's a journey of continuous learning, but with a structured approach, you can master the skills needed to thrive.

Here’s a simple breakdown of the key areas you should focus on, along with resources to help you get started:

1/ Core Service Models: IaaS, PaaS, SaaS

↳ Why it exists: These are the basic building blocks of cloud computing — each one shifts responsibility between you and the cloud provider.

↳ Why it's needed: Knowing the difference helps you choose the right approach for any application or project.

  • IaaS: Provides virtual machines, storage, networking and infrastructure components — you control the operating system (OS) and app stack

  • PaaS: Manages infrastructure for you — focus on writing and deploying code

  • SaaS: Ready-to-use software — no infrastructure or deployment effort needed

2/ Compute & Storage: VMs, Containers, Serverless + Storage Types

↳ Why it exists: Cloud needs compute power to run apps and storage + databases to hold data — each option supports an operation.

↳ Why it's needed: Choosing the right combination affects scalability, cost, and performance.

  • VMs: Full control over OS and dependencies — great for traditional apps

  • Containers: Lightweight and portable — ideal for microservices

  • Serverless: Event-driven, scales automatically — ideal for short-lived tasks

  • Storage: Understand when to use object (S3, GCS), block (Volumes), or file storage (EFS)

  • Databases: Store and query data efficiently — choose SQL for structured data and relationships, NoSQL for flexible schema and scalability, and Data Warehouses for analytics

3/ Networking & Delivery: VPCs, Subnets, VPNs, API Gateway, CDN

↳ Why it exists: Apps need to talk to each other and to users — securely and quickly.

↳ Why it's needed: Cloud networks control access, isolate traffic, and deliver content globally.

  • VPCs, Subnets: Create isolated, private networks

  • VPN/Direct Connect: Secure cloud-on-premise connectivity

  • API Gateway: Route and secure service requests

  • CDN: Cache and speed up content delivery

  • Load Balancers: Distribute traffic across servers

🔗 Cisco Networking Academy
🔗 Review cloud specific networking docs such as : AWS VPC Docs, GCP VPC
🔗 What is a CDN

4/ Security & Compliance: IAM, Encryption, Compliance

↳ Why it exists: The cloud is shared — security controls are needed to protect data and access.

↳ Why it's needed: Misconfigurations are a leading cause of breaches. Policies help enforce rules.

  • IAM: Manage who can access what

  • Encryption: Protect data in transit and at rest

  • Compliance: Align with legal/regulatory standards like GDPR, HIPAA

  • Security Groups/NACLs: Control traffic in and out

5/ Architecture & Design: Scalability, Resilience, Microservices

↳ Why it exists: Systems must adapt to change — scale under load, stay online during failure.

↳ Why it's needed: Bad design = downtime, high costs, poor performance.

  • High Availability & DR: Build for failure, recover quickly

  • Microservices: Break large apps into smaller, manageable pieces

  • Event-Driven Design: Trigger actions automatically based on events

  • Well-Architected Frameworks: Design checklists from top cloud providers

🔗 Microservices.io
🔗 Well Architected Frameworks (AWS, GCP, Azure )

6/ DevOps & Automation: Terraform, Git, CI/CD

↳ Why it exists: Manual setups don’t scale — automation ensures consistency and speed.

↳ Why it's needed: Infrastructure and deployment should be repeatable and trackable.

7/ Observability: Logging, Monitoring, Tracing

↳ Why it exists: You can’t fix what you can’t see — visibility is critical for reliability.

↳ Why it's needed: Logs and metrics help detect problems before users do.

  • Logging: Capture app and system behavior

  • Monitoring: Get alerts on performance and availability

  • Tracing: Track requests across services

  • Analytics: Spot trends, predict issues

8/ Data & Analytics: Pipelines, Warehousing, Kafka, BigQuery

↳ Why it exists: Cloud enables storing and processing large volumes of data efficiently.

↳ Why it's needed: Structured pipelines and tools ensure data can be used for insight and action.

  • ETL Tools: Move and transform data (Glue, Dataflow)

  • Warehouses: Centralized storage for analytics (BigQuery, Snowflake)

  • Streaming: Handle real-time data (Kafka, Pub/Sub)

  • Lakehouse: Blend flexibility of lakes with structure of warehouses

9/ AI & ML in the Cloud: SageMaker, Vertex AI, MLOps

↳ Why it exists: Cloud platforms offer tools to build, train, and deploy ML models without setting up complex infra.

↳ Why it's needed: Simplifies experimentation, scaling, and maintenance of ML workflows.

  • Managed ML Services: Train and deploy faster

  • Prebuilt APIs: Add vision, speech, and text features without custom models

  • MLOps: Automate ML model lifecycle


    🔗 MLOps Community GitHub

10/ Cost Optimization: Auto-scaling, Right-sizing, Spot Instances

↳ Why it exists: Cloud is pay-as-you-go — cost efficiency is built into the model.

↳ Why it's needed: Without tracking and tuning, costs can spike unexpectedly.

  • Auto-scaling: Use resources only when needed

  • Right-sizing: Match instance type to actual usage

  • Spot/Reserved Instances: Lower costs for flexible or steady workloads

  • Cost Monitoring: Stay ahead of budget overruns

🔗 Cost Optimization (AWS, GCP, Azure)
🔗 Cloud Cost Optimization – YouTube

11/ Governance & Strategy: Tagging, Policies, Multi-cloud

↳ Why it exists: Cloud environments grow fast — governance keeps things clean and compliant.

↳ Why it's needed: Policies help manage risk, cost, and complexity at scale.

  • Tagging: Track and organize resources

  • Policies: Enforce security and usage rules

  • Multi-cloud: Avoid vendor lock-in or meet regional requirements

  • Business Alignment: Ensure cloud supports org goals

You already know about the free resources now:

Now what’s next?

Cloud engineering is about putting the right pieces together — securely, efficiently, and thoughtfully.

From hybrid infra to open-source tools, this field keeps evolving. Start where you are, and layer your skills over time.

See you next week!