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docs: add MLOps-with-coding-agents how-to#246

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typhoonzero merged 1 commit into
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docs/mlops-with-coding-agents
May 29, 2026
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docs: add MLOps-with-coding-agents how-to#246
typhoonzero merged 1 commit into
docs/coding-agents-onprem-llmfrom
docs/mlops-with-coding-agents

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Summary

Follow-on to #245. Adds a second how-to: Run MLOps with Coding Agents and On-Premise LLMs under model_inference/inference_service/how_to. Stacked on the PR1 branch — once #245 lands, GitHub will auto-retarget this PR to master.

The doc focuses on four agent-driven MLOps workflows on Alauda AI:

  • Manage InferenceService / LLMInferenceService — agent loop (draft → server-side dry-run → apply → poll → smoke-test), with concrete starter prompts.
  • Configure Envoy AI Gateway — auth and rate limits via AIGatewayRoute, AIServiceBackend, BackendSecurityPolicy, SecurityPolicy, and BackendTrafficPolicy; links to the existing intro/install docs.
  • Tune service performance to fit hardware — explicit five-step agent-driven loop (SLOs → benchmark → one-change-at-a-time → measure → stop on SLO or ceiling); cross-links to the prior doc's tuning section instead of duplicating it.
  • Plan fine-tuning and generate reports — a tool-selection table (Notebook / Training Hub / Kubeflow Trainer v2 / LLM Compressor) and two ready-to-commit markdown templates: a pre-run plan and a post-run report, both designed to be filled in by the agent from live cluster data.

Also includes a "daily MLOps loop" walk-through, guardrails (read-only first, --dry-run=server, one change per iteration, never fabricate metrics, no hosted-provider fallback), and a References section.

The amended PR1 commit adds a \{#best-practices} anchor to the prior doc so this doc's deep links resolve under doom lint.

Test plan

  • doom lint passes on the new file (0 errors, 0 warnings)
  • Pre-commit yarn lint passes
  • All internal cross-links (./*.mdx, ../../../envoy_ai_gateway/*, ../../../kubeflow/how_to/*, ../../../workbench/how_to/*, ../../../llm-compressor/how_to/*, ../../../infrastructure_management/hardware_profile/*) resolve to files that exist on the stacked base
  • Reviewer: verify rendered page and the two markdown templates render cleanly inside fenced code blocks

🤖 Generated with Claude Code

Follow-on to the on-prem coding agent guide. Covers four agent-driven
MLOps workflows: managing InferenceService and LLMInferenceService
resources, configuring authentication and rate limiting on Envoy AI
Gateway, an iterative agent-driven performance tuning loop, and reusable
templates for fine-tuning plans and post-run reports. Links to the
existing fine-tuning paths (Workbench Notebook, Training Hub, Kubeflow
Trainer v2, LLM Compressor) and to the Envoy AI Gateway install doc.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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coderabbitai Bot commented May 29, 2026

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@typhoonzero typhoonzero merged commit 914aa53 into docs/coding-agents-onprem-llm May 29, 2026
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@typhoonzero typhoonzero deleted the docs/mlops-with-coding-agents branch May 29, 2026 04:04
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Superseded — both docs are now in #245. Closing.

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