GPU providers

Important Developer Trends for April 2022 (View Older or Newer)

Reconstructed with current taxonomy

Rank	Trend	Score	Change	Components	Recent scores
#1	Serverless Serverless execution is materially relevant to GPU providers because it reduces operational overhead and enables elastic, usage-based AI inference and application deployment.	70.4	+4	Strategic 64 Adoption 60 · Attention 100 · Momentum 100	70 · 49 · 66 · 60 · 38 · 66 · 50 · 70
#2	Kubernetes Kubernetes is durable core infrastructure for deploying, scaling, and operating GPU-backed workloads, especially training and inference services.	69.2	-1	Strategic 80 Adoption 20 · Attention 100 · Momentum 44	72 · 70 · 70 · 69 · 69 · 71 · 69 · 69
#3	Platform Engineering Platform engineering directly shapes how organizations provision, govern, and operationalize GPU capacity through self-service developer workflows.	56.8	—	Strategic 63 Adoption 20 · Attention 67 · Momentum 100	40 · 40 · 40 · 56 · 38 · 40 · 40 · 57
#4	Developer Experience Developer experience directly influences adoption, retention, and workload expansion for GPU providers by reducing friction in provisioning, deployment, observability, and cost management.	55.2	-1	Strategic 74 Adoption 20 · Attention 33 · Momentum 37	61 · 63 · 56 · 62 · 44 · 62 · 57 · 55
#5	Secrets Management Secrets management is a durable security and operational requirement for GPU platforms, protecting API keys, credentials, model access tokens, and infrastructure configuration.	54.8	—	Strategic 68 Adoption 20 · Attention 33 · Momentum 100	43 · 43 · 43 · 43 · 43 · 43 · 43 · 55

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