Choosing between GKE, Cloud Run, and Compute Engine
Three genuinely different workload shapes point to three different platforms — and Meridian's own three-way split proves the decision table rather than being arbitrary.
Speaker notes
- Stateless HTTP with spiky traffic and no special runtime needs points to Cloud Run; event-driven processing points to Cloud Run functions plus Eventarc; a workload needing sidecars, custom schedulers, or complex multi-container orchestration points to GKE, since those Kubernetes primitives don't exist on Cloud Run at all; a steady-state predictable batch or ingestion workload points to Compute Engine, especially combined with Spot capacity.
- Tie to the running example directly: shipment-api (spiky, customer-facing HTTP) runs on Cloud Run, route-optimizer (needs closer runtime control as ML dependencies grow) runs on GKE, and the GPS-ingestion fleet (steady, interruption-tolerant) runs on Compute Engine — three platforms because the workload shapes are genuinely different, not an inconsistent architecture.
- The worked cost comparison confirms the crossover point: GKE Autopilot wins below roughly 60-70% sustained utilization, GKE Standard wins above it, and Cloud Run wins for a genuinely spiky, mostly-idle profile where per-request billing beats paying for any always-on baseline beyond the minimum needed to avoid cold starts.
Deck map
01
GCP foundations in one line
02
How the ACE exam maps to this course
03
GCP's geography and the project as the unit of isolation
04
Organization, folders, and projects
05
Org policies and how inheritance works
06
Labels, network tags, and resource manager tags
07
Billing accounts, budgets, and cost control
08
gcloud CLI, Cloud Shell, and client libraries
09
Terraform on GCP and the end of Deployment Manager
10
Gemini CLI, Cloud Assist, and Application Design Center
11
Principals, roles, bindings, and policies
12
Primitive, predefined, custom roles, and IAM conditions
13
Service accounts, keys, and impersonation
14
Workload Identity Federation
15
Break-glass access and IAM auditing
16
Choosing a machine family: E2, N4, C4
17
Disks, OS Login, and VM Manager
18
Spot VMs and managed instance groups
19
Autoscaling policies, health checks, GPUs and TPUs
20
GKE Autopilot vs Standard vs the 2026 hybrid option
21
Node pools and pod autoscaling
22
Cloud Run revisions, traffic splitting, and functions
23
Choosing between GKE, Cloud Run, and Compute Engine
24
Cloud Storage classes and lifecycle management
25
Choosing a managed database
26
The managed database lineup
27
Connection pooling, read replicas, and Pub/Sub
28
Backup, regional failover, and CMEK
29
VPC networks, subnets, and Shared VPC
30
Firewall rules, tags, and Cloud NAT
31
Load balancers, Cloud DNS, and Cloud CDN
32
VPN, Interconnect, and private access
33
How a request actually reaches shipment-api
34
Cloud Monitoring: metrics, dashboards, alerts
35
Cloud Logging: router, buckets, and audit logs
36
Trace, Profiler, Error Reporting, and Managed Prometheus
37
How the five Cloud Operations products fit together
38
Readiness checklist