GPU providers

Important Developer Trends for December 2021 (View Older or Newer)

Reconstructed with current taxonomy

Rank	Trend	Score	Change	Components	Recent scores
#1	Kubernetes Kubernetes is durable core infrastructure for deploying, scaling, and operating GPU-backed workloads, especially training and inference services.	69.1	—	Strategic 80 Adoption 20 · Attention 100 · Momentum 43	72 · 70 · 70 · 69
#2	Developer Experience Developer experience directly influences adoption, retention, and workload expansion for GPU providers by reducing friction in provisioning, deployment, observability, and cost management.	61.5	+4	Strategic 74 Adoption 20 · Attention 63 · Momentum 75	61 · 63 · 56 · 62
#3	Serverless Serverless execution is materially relevant to GPU providers because it reduces operational overhead and enables elastic, usage-based AI inference and application deployment.	59.7	-1	Strategic 64 Adoption 20 · Attention 100 · Momentum 45	70 · 49 · 66 · 60
#4	Platform Engineering Platform engineering directly shapes how organizations provision, govern, and operationalize GPU capacity through self-service developer workflows.	56.2	—	Strategic 63 Adoption 20 · Attention 63 · Momentum 100	40 · 40 · 40 · 56
#5	LLM LLMs are a primary workload for GPU providers, driving demand for training, fine-tuning, inference, model hosting, and high-performance cluster capacity.	51.0	-2	Strategic 85 Adoption 0 · Attention 0 · Momentum 0	51 · 54 · 66 · 51

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