Google Cloud & the Three-Cloud Head-to-Head
Third cloud, then the numbers: cost, cold start, GPU availability, and pain.
# what you build
The finale. You will deploy the platform a third time on Google Cloud, then put all three side by side with real measurements — monthly cost at identical load, cold start, GPU availability and how long each one took to set up. It ends with DNS-level failover, so one cloud having a bad day stops being your problem.
What you end up with
handles after this
~50,000, on any of three clouds
what it costs to run
the full comparison
What you will be able to do
- Deploy the same platform on GKE, and see where Google's Kubernetes differs
- Benchmark all three clouds at identical load, with numbers you can defend
- Compare GPU availability, quotas and real hourly cost across providers
- Fail over between clouds with DNS health checks
- Choose a cloud for a given workload, and be able to explain the choice
The build, step by step
These are the chapters of the video, in order.
- 1Deploy on Google CloudGKE Autopilot and Cloud Run — the least config of the three, and where its limits are.
- 2Run the same benchmarkIdentical load against all three, measuring latency, throughput and cost.
- 3Build the comparisonOne table: cost, cold start, GPU access, setup time, and honest verdicts.
- 4Fail over between cloudsDNS health checks that route around a cloud having an outage.
The stack
- GKE
- Cloud Run
- DNS failover
- Terraform
# before this one
This project continues the system built in 08 · Port the Whole Platform to Azure. You can start here, but the repo assumes the previous rung exists.
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