Running Ollama on OCI Container Instances - Private LLM API in 5 Minutes, No Kubernetes
Article summary
Quick briefing — cleaned from the original RSS feed
A colleague asked me to set up a private LLM endpoint their team could use for code review suggestions. Requirements: OpenAI-compatible API, runs inside our cloud (no data leaving the tenancy), and "I don't want to learn Kubernetes." That last requirement ruled out OKE. And honestly, for a single-model inference endpoint serving 10 people, Kubernetes is overkill anyway. I had Ollama running on an OCI Container Instance with a GPU in about 5 minutes. Here's the whole thing. Why Ollama Instead of…
1Key Takeaways
- A colleague asked me to set up a private LLM endpoint their team could use for code review suggestions.
- Requirements: OpenAI-compatible API, runs inside our cloud (no data leaving the tenancy), and "I don't want to learn Kubernetes." That last requirement ruled out OKE.
- And honestly, for a single-model inference endpoint serving 10 people, Kubernetes is overkill anyway.
- I had Ollama running on an OCI Container Instance with a GPU in about 5 minutes.
2AIWedia Score
8.3/10
High relevance — worth your attention today
Based on source trust, recency, category impact, and story depth.
3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — AI reports that a colleague asked me to set up a private LLM endpoint their team could use for code review suggestions.
Explore related
Browse toolsCoding AI news
Explore curated coding ai tools on AIWedia — compare, rank, and launch from our directory.
Full story on DEV — AI
Read full articleHeadlines aggregated via RSS for discovery on AIWedia. Original content © DEV — AI. We link to the source and do not republish full articles.