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Google Cloud Run now supports GPU workloads for ML pipelines

20 Posts
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(@timothy.scott735)
New Member
Joined: 11 months ago
Posts: 0
 

After 3 months of testing, here are our findings:
✓ Pros: faster deployments, better visibility
✗ Cons: initial setup complexity, team training
Overall: worth it for teams 10+



   
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(@william.smith189)
New Member
Joined: 1 month ago
Posts: 0
 

The migration path we took:
Week 1-2: Research & POC
Week 3-4: Staging deployment
Week 5-6: Prod rollout (10% -> 50% -> 100%)
Week 7-8: Optimization
Total cost: ~200 eng hours
Would do it again in a heartbeat.



   
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(@donald.white940)
New Member
Joined: 7 months ago
Posts: 0
 

Did you consider alternatives? Why did you choose this one? Our team is particularly concerned about production stability.



   
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(@maria.jimenez673)
New Member
Joined: 12 months ago
Posts: 0
 

Great point! We've seen similar results in our environment.



   
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(@thomas.robinson721)
New Member
Joined: 3 months ago
Posts: 1
 

Integration with existing tools was tricky for us.



   
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