FeaturedEntry 007
Running LLMs on GKE: what breaks before you find the Inference Gateway
When someone first asks to run an LLM on Kubernetes, the instinct is reasonable: it's a containerised workload, it exposes an HTTP API, it needs to scale. Deploy it like anything else — a `Deployment`, a `Service`, maybe an `HPA` on CPU. That instinct gets you surprisingly far. Until it doesn't
Read EntryRecent Entries
Chronological archive| No. | Date | Title | Time |
|---|---|---|---|
| 006 | 06/10/2024 | Platform Engineering: Building the Right Abstractions | 3 min read |
| 005 | 05/01/2024 | Data Pipelines on Kubernetes: Lessons from Airflow to Argo | 3 min read |
| 004 | 03/20/2024 | Progressive Delivery with Argo Rollouts | 3 min read |
| 003 | 03/05/2024 | LLMOps in Production: What Nobody Tells You | 3 min read |
| 002 | 02/08/2024 | Writing Production-Grade Kubernetes Operators | 3 min read |
| 001 | 01/15/2024 | GitOps at Scale: Managing 50 Clusters with Flux | 3 min read |
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