“AWS feels like a supermarket. Azure feels like enterprise paperwork.
GCP feels like... an engineer built it.”
If you’ve ever opened the GCP console and thought:
- “This looks clean. but different”
- “Why is everything so data centric?”
- “Why do Kubernetes and BigQuery feel native here?”
This blog is for you.
Let’s demystify Google Cloud Platform, how it works, why it exists, and why engineers quietly love it.
What is Google Cloud Platform (GCP)?
Google Cloud Platform is Google’s public cloud offering. the same backbone that powers:
- Google Search
- YouTube
- Gmail
- Google Maps
- Android ecosystem
Unlike other clouds that adapted to scale later, Google was born at planetary scale.
That DNA matters.
GCP’s Philosophy (This Is the Big Difference)
Most clouds say:
“Here’s infrastructure. You manage it.”
GCP says:
“Here’s a distributed system. Don’t worry about servers.”
Core ideas:
- Containers first
- Data everywhere
- Managed > Manual
- SRE > SysAdmin
Google doesn’t want you babysitting servers.
They want you shipping systems.
How GCP Is Structured
1. Global Infrastructure
- Regions → Zones
- Private global fiber network
- Same network Google uses internally
Your VM in Mumbai talks to BigQuery in the US without touching public internet
2. Core Layers
Think in layers, not services.
| Layer | Purpose |
|---|---|
| Compute | Run code |
| Storage | Store data |
| Networking | Connect everything |
| Data | Analyze everything |
| DevOps | Build & deploy |
| Security | Protect by default |
3. Compute: Where Your Code Runs
Compute Engine (GCE)
- Virtual machines
- Custom machine types
- Per-second billing
Google Kubernetes Engine (GKE)
- Kubernetes created by Google
- Industry gold standard
- Auto-scaling, auto-repair, auto peace :)
Cloud Run (Serverless)
- Deploy a container
- Zero infrastructure thinking
- Scales from 0 → millions
If AWS is EC2-first, GCP is Kubernetes first.
Storage & Databases (Google Loves Data)
Cloud Storage
- Object storage
- Simple, fast, global
- Ideal for logs, backups, media
BigQuery - The Star🌟
- Serverless data warehouse
- Query TBs in seconds
- SQL without infra pain
BigQuery feels like cheating, and that’s the point.
Cloud Spanner
- Globally consistent SQL database
- Horizontal scaling
- Used by Google internally
Data Engineering & Streaming (GCP’s Superpower)
🔸 Pub/Sub
- Global messaging system
- Event-driven architectures
- Handles insane throughput
🔸 Dataflow (Apache Beam)
- Unified batch + streaming
- Managed Flink-like pipelines
- No cluster management
If you’re a data engineer, GCP feels like home.
DevOps on GCP (Clean & Opinionated)
🔹 Cloud Build
- Serverless CI/CD
- YAML pipelines
- GitHub / GitLab friendly
🔹 Artifact Registry
- Docker, Maven, npm, Python
- One registry to rule them all
🔹 Cloud Operations (Stackdriver)
- Logs
- Metrics
- Traces
- Alerts
Logging on GCP is ridiculously good.
Security: Quietly Excellent
- IAM is resource centric
- Default encryption everywhere
- Zero Trust mindset
- VPC Service Controls
You don’t add security later, it’s baked in.
GCP vs AWS vs Azure (Quick Reality Check)
| Area | GCP | AWS | Azure |
|---|---|---|---|
| Kubernetes | Best | Good | Good |
| Data & Analytics | Best | Good | Average |
| UI Simplicity | Clean | Cluttered | Corporate |
| Enterprise Legacy | Meh | Good | Best |
| Learning Curve | Moderate | Steep | Moderate |
Who Should Choose GCP?
Choose GCP if you are:
- A DevOps / SRE
- A Data Engineer
- A Java + Beam + Flink developer
- Building event-driven systems
- Tired of managing servers
Avoid GCP if:
- You need legacy enterprise tooling
- You want every service under the sun (AWS wins here)
Why Engineers Fall in Love with GCP
- Kubernetes just works
- BigQuery changes how you think about data
- Clean console
- Less ops, more engineering
- Google grade infrastructure
GCP doesn’t scream.
It delivers quietly.
Final Thoughts
AWS teaches you cloud.
Azure teaches you enterprise.
GCP teaches you distributed systems.
If you truly want to understand how modern systems are built, GCP is not optional — it’s essential.
Hope you like this introductory post on GCP.
If you want next part, Please let me know in the comments.
- Building a Production-Grade Java App on GCP
- GCP Data Engineering Pipeline (Beam + Dataflow + BigQuery)
- AWS vs GCP Architecture War Stories
- How Google Runs SRE Internally
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