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Step 08 of 8 Ongoing — especially the first 6 months post-migration· advanced

Step 8: Optimize and Stabilize

Tune performance, rationalize cost, build operational maturity, refine patterns. The migration is over — the platform owns the work now.

What you're doing in this step

Profile and tune hot pipelines. Right-size compute (Synapse Spark pools, Fabric capacity). Move cold data to cheaper storage tiers. Establish runbooks, on-call rotation, SLO tracking, postmortem culture. Refactor the rushed migration code. Update the shared library based on patterns that emerged. Hand the platform off from migration team to ops team.

Recommended prompts

Use one of these to do the work in your IDE

Open the template to read it in full. Click Copy prompt to grab it (with your stack values pre-filled where they apply) — then paste into Claude Code, Cursor, or wherever you build.

Primary recommendation 5 min setup

Performance Profiler Skill

Claude Code skill that diagnoses performance issues — slow queries, slow renders, memory leaks — with measurement-first methodology.

claude-code
View skill
Skill· Skill 5 min setup

Documentation Skill

Claude Code skill that generates README, API docs, JSDoc, ADRs, and other docs that match the project's existing voice and depth.

Use this when: Driving the post-migration retrospective and the optimization roadmap

claude-code
View skill
Skill· Skill 5 min setup

Code Reviewer Skill

Claude Code skill that performs comprehensive code review on PRs and diffs, prioritized by severity with concrete fixes.

Use this when: Auditing migration-era code for the rushed-but-shipped parts that need cleanup

claude-code
View skill
Template· Template 20 min initial assembly + ongoing additions

Regression Test Bed — Master Suite

Assemble per-program / per-component test cases into a single master regression suite — coverage summary, critical path, domain sections, end-to-end scenarios, run instructions.

Use this when: Standing up a permanent regression bed for the new platform

View template
Recommended skills

Drop these into Claude Code for this phase

Skills auto-trigger on the right kind of request. Install once; they apply to every prompt that fits.

Skill· Skill 5 min setup

Performance Profiler Skill

Claude Code skill that diagnoses performance issues — slow queries, slow renders, memory leaks — with measurement-first methodology.

claude-code
View skill
Skill· Skill 5 min setup

Documentation Skill

Claude Code skill that generates README, API docs, JSDoc, ADRs, and other docs that match the project's existing voice and depth.

claude-code
View skill
Skill· Skill 5 min setup

Code Reviewer Skill

Claude Code skill that performs comprehensive code review on PRs and diffs, prioritized by severity with concrete fixes.

claude-code
View skill
Recommended MCP configs

Wire these tools into Claude Code first

MCP servers give Claude Code direct access to external systems (Jira, browsers, databases). Configure once.

MCP config· MCP config 10 min setup

Azure DevOps MCP for Evoke

Pre-configured Azure DevOps MCP server for Claude Code — work items, repos, PRs, and pipelines from chat.

claude-codemcp
View config
MCP config· MCP config 10 min setup

GitHub MCP for Evoke

Pre-configured GitHub MCP server for Claude Code — issues, PRs, code search, and Actions from chat.

claude-codemcp
View config
MCP config· MCP config 10 min setup

Postgres MCP for Evoke

Pre-configured Postgres MCP server for Claude Code — schema inspection and read-only queries to make database work safer and faster.

claude-codemcppostgres
View config
When you're done

Verify these in your own work before moving on

This is a checklist for you to mentally tick off in your repo and IDE — the site doesn't track it, you do.

  • Cost outcomes verified vs business case
  • Performance acceptable on critical paths
  • DQ trend improving
  • Operational runbooks complete
  • Team transitioned from "migration mode" to "platform ops mode"
Common pitfalls

What goes wrong at this step

  • Skipping optimization — code shipped during migration is rushed; tech debt persists
  • No retrospective — lessons not captured
  • Treating optimization as one-shot — it's continuous
  • No transition plan from project to ops — project team disbands; nobody owns the platform
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