Google Cloud Engineering & Architecture Bootcamp Certificate
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Bootcamp Mastery Certificate B35
Primary spine: freeCodeCamp / Andrew Brown Google Cloud Associate Cloud Engineer 2025, deepened with the 15+ hour Professional Cloud Architect course and an official Google Cloud reliable-application architecture bridge. Build from resource hierarchy, IAM, compute, storage and networking into GKE, serverless, IaC, observability, resilience and cost-aware architecture.
Benchmark: freeCodeCamp publishes the Andrew Brown Google Cloud Associate Cloud Engineer and Professional Cloud Architect courses as free public videos, and Google Cloud publishes the reliable application platform session publicly. Zuyini curates the videos and applies an independent build-and-proof rubric; this is not a Google-issued certification or endorsement.
Core Video Sequence
01 — 2025 Google Cloud engineer foundation - complete spine
02 — Resource hierarchy, IAM + identity boundaries
03 — Serverless + application deployment choices
04 — Cloud storage + managed data foundations
05 — Compute Engine deployment + operations
06 — GKE deployment + container operations
07 — VPC networking + hybrid connectivity
08 — Infrastructure as Code + day-2 operations
09 — Professional cloud architecture deep dive
10 — Reliable multi-region application platform
Build-Along Checkpoints
- Checkpoint 1: Create a budgeted GCP sandbox with organization/project conventions, IAM groups/service accounts, MFA expectations, labels and billing alerts; document trust boundaries and least privilege.
- Checkpoint 2: Design a VPC with subnets, firewall rules, Cloud NAT or controlled egress, private service access where needed and an explicit ingress path; prove connectivity and denied paths.
- Checkpoint 3: Deploy one containerized workload on Cloud Run or GKE and one VM-based workload on Compute Engine; compare scaling, operational burden, latency and cost tradeoffs.
- Checkpoint 4: Add Cloud Storage plus one managed database appropriate to the workload; configure lifecycle/backup behavior, encryption/IAM and a recovery test.
- Checkpoint 5: Codify the core environment with Terraform or another IaC path; make a controlled change, detect drift and show repeatable create/update/destroy behavior in a non-production environment.
- Checkpoint 6: Instrument Cloud Monitoring/Logging, define user-centered SLOs and alerts, inject a zonal/service failure or dependency outage, recover safely and complete a Well-Architected-style review.
7-Day Independent Capstone
- Day 1: Set workload SLOs, data sensitivity and cost ceiling; create project hierarchy, IAM/service accounts, budgets and audit baseline.
- Day 2: Build VPC, subnets, routes/firewalls and ingress/egress; validate connectivity and publish architecture/trust-boundary diagram.
- Day 3: Deploy on Cloud Run/GKE/Compute Engine; add load balancing/autoscaling and capture health, scale and latency evidence.
- Day 4: Add Cloud Storage plus managed data; configure backup/lifecycle, IAM/encryption and perform a restore with RPO/RTO notes.
- Day 5: Move core environment to IaC; use reviewed version control and demonstrate idempotent deployment, drift and reversible change.
- Day 6: Add logs, metrics, traces/SLOs and alerts; inject a dependency failure and show detection, diagnosis, mitigation and recovery.
- Day 7: Publish repo, ADR, IaC, dashboards, recovery proof, cost estimate, security notes, demo and operations runbook.
Google Cloud - Build, Govern, Observe & Recover
Operate a Google Cloud workload end to end rather than memorizing product names. Completion requires identity and network boundaries, multiple runtime/data choices, repeatable IaC, observability, SLOs, a controlled failure drill, recovery evidence and explicit cost/reliability tradeoffs.
Proof Rubric — What Must Be Shown
- IDENTITY: IAM/service accounts + least-privilege evidence
- NETWORK: VPC, routing, firewall + controlled connectivity
- COMPUTE: Runtime choice, scaling + availability proof
- DATA: Storage/database, protection + recovery evidence
- IAC: Versioned, repeatable infrastructure + drift control
- OBSERVABILITY: Logs/metrics/SLOs + actionable alerting
- RELIABILITY: Failure injection, recovery + graceful degradation
- ECONOMICS: Cost estimate + architecture tradeoff rationale