Cloud Technology

How do I choose between Google Kubernetes Engine and Cloud Run for a new microservices project?

S Asked by Sarah Jenkins · 12-05-2023
0 upvotes 15,762 views 0 comments
The question

I am currently planning a migration for our legacy on-premises API suite to Google Cloud. I am torn between using GKE for the full orchestration control and Cloud Run for the serverless simplicity. My team is small, but we expect high traffic volatility. Which one offers better long-term scalability and ease of maintenance for a DevOps team of three? 

3 answers

0
JE
Answered on 15-05-2023

If your team is small, I highly recommend starting with Cloud Run. It abstracts away the cluster management, which can be a significant overhead in GKE. Cloud Run’s scale-to-zero feature is a lifesaver for cost management during low-traffic periods, whereas GKE nodes incur costs even when idle unless you use GKE Autopilot. However, if you require specific networking protocols beyond HTTP/gRPC or need deep hardware customization (like GPUs), GKE is the way to go. For 90% of standard web APIs, the operational simplicity of serverless will let your three-person team focus on code rather than infrastructure. 

0
RO
Answered on 18-05-2024

Have you looked into GKE Autopilot as a middle ground between the two? It offers the power of Kubernetes without the manual node management. 

DA 19-05-2024

Robert, Autopilot is great, but it still requires managing K8s manifests and CRDs. For a team of three, even "managed" Kubernetes can feel like a lot compared to the simple container-to-URL workflow of Cloud Run. If they don't need complex service meshes like Istio right away, Cloud Run reduces the "cognitive load" significantly.

0
LI
Answered on 20-05-2024

Cloud Run is definitely the SEO-friendly choice for speed-to-market. It integrates natively with Cloud Build for a seamless CI/CD pipeline, which is perfect for small teams. 

SA 21-05-2024

I agree with Linda. We moved our staging environment to Cloud Run last year and the deployment velocity doubled because we stopped fighting with YAML configurations.

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