Migrate To Msk

Migrating to MSK Express

Overview

This skill helps customers migrate self-managed Apache Kafka workloads to Amazon MSK Express. It provides three phases — Discovery, Assessment, and an optional Simulation — that can be run end-to-end or individually depending on the customer's needs.

Scope

This skill covers migrations from self-managed Apache Kafka (on-premises, EC2, Docker, Kubernetes, or other non-MSK deployments) to MSK Express. Migrations from MSK Standard (Provisioned) to MSK Express are out of scope.

Prerequisites

The AWS MCP server is recommended for documentation lookups and informational questions, but is not required. The assessment scripts are pure file processors with no AWS API calls.

Intent Routing

Route the customer's request based on their intent:

1. Open/exploratory question ("How do I migrate to MSK?")

Explain what this skill offers:

This skill helps you migrate to MSK Express in three phases: Phase 1 — Discovery: Inventory your source Kafka cluster — brokers, topics, partition counts, configs, authentication, and workload metrics — plus two target decisions that drive cost: consumer rack affinity and any negotiated AWS pricing. I can discover this from IaC files (Terraform, CDK, Docker Compose, Kubernetes manifests), provide commands for you to run on your cluster, or you can provide the information manually. Output: migrate-to-msk-skill-artifacts/<cluster_name>/cluster-config.json. Phase 2 — Assessment: Validate your cluster against MSK Express across 5 compatibility pillars (topology, Kafka version, configs, auth, quotas) and produce a target Express specification using the managing-amazon-msk Skill's pricing logic. I'll flag what Express will refuse vs what Express will silently convert. Outputs: compatibility.<cluster_name>.json, the pricing results in Markdown msk_sizing_pricing.md, and msk-sizing-inputs.<cluster_name>.json. Phase 3 — Simulation: Spin up an MSK Express cluster with load-testing infrastructure to see how Express performs on your own workload, then run a vended test (End-to-End Latency or Broker Restart Under Load) and review the results on a CloudWatch dashboard. Data replication: For migrating data to your Express cluster, you can use MSK Replicator. I can provide guidance on setup and configuration. Where would you like to start? I can begin with discovery if you point me to your infrastructure code or describe your cluster, or jump to assessment if you already have a cluster-config.json file, or go straight to simulation if you already know your target Express configuration.

Guardrails for this overview response:

• This response is an overview and a routing question only. Do NOT begin, simulate, or pre-empt any phase.
• Do NOT produce or estimate assessment output here — no verdicts, pillar findings, compatibility conclusions, broker counts, instance recommendations, or cost figures. Those values exist only after you run the Phase 2 scripts against a real cluster-config.json.
• Do NOT open, read, or summarize the internals of compatibility.py, simulation_load_test_config.py, or the reference files to explain how a phase works. Describe the phases at the level shown above; do not walk the customer through the implementation.
• When the customer chooses a phase, run that phase's scripts or flow to produce real results. Always operate the skill to answer — never answer from having read its source. For the exact commands, see "Running the assessment" in references/assessment-compatibility.md for Phase 2, and references/simulation.md for Phase 3.

2. Discovery intent (DEFAULT when IaC files are provided)

If the customer provides a directory path, IaC files, or says "here's our infra" — this is discovery intent. Run ONLY Phase 1 (Discovery). Do NOT run assessment, do NOT suggest migration steps, do NOT mention blockers or compatibility. Produce the migrate-to-msk-skill-artifacts/<cluster_name>/cluster-config.json file and stop.

3. Assessment intent

Customer explicitly asks to assess or has a migrate-to-msk-skill-artifacts/<cluster_name>/cluster-config.json file already produced. Run Phase 2 (Assessment) only.

4. Simulation intent

Customer wants to test MSK Express with their workload. They can provide cluster sizing directly (instance type, broker count, Kafka version) or reference an earlier assessment. Proceed directly to Phase 3 — Simulation. An assessment is helpful but not required — the simulation asks for sizing inputs directly.

5. Informational questions

Customer asks about Express capabilities, constraints, configuration differences, authentication support, pricing, or compaction behavior without providing cluster-specific data. Use AWS documentation tools (aws___search_documentation, aws___read_documentation) if available to look up the answer from MSK Express documentation. If MCP tools are not available, reference the MSK Express documentation and answer based on knowledge of AWS MSK.

6. Migration strategy questions

Customer asks about MSK Replicator compatibility, version upgrade paths, MirrorMaker 2, or migration strategies. MSK Replicator is the native AWS-supported solution for data replication and works for both MSK-to-MSK and non-MSK-to-MSK migrations. Use AWS documentation tools (aws___search_documentation, aws___read_documentation) if available to retrieve current requirements and supported configurations. If MCP tools are not available, reference the MSK Replicator documentation and answer based on knowledge of AWS MSK.

Phase 1 — Discovery

Purpose: Inventory the source cluster to build a migration profile.

Input: One of:

• A directory path containing IaC files (CDK, CloudFormation, Docker Compose, Kubernetes manifests, Terraform)
• Output from Kafka CLI commands the customer runs on their cluster
• Manual information provided by the customer in conversation

Output: migrate-to-msk-skill-artifacts/<cluster_name>/cluster-config.json — saved to the working directory.

Discovery rules

• Before doing ANYTHING else in discovery, you MUST read references/discovery.md in full. It defines the input methods, the REQUIRED response template, the forbidden content, and the cluster-config.json schema. Do NOT respond until you have read it, and follow its template EXACTLY.
• ALWAYS save migrate-to-msk-skill-artifacts/<cluster_name>/cluster-config.json in the working directory.
• Do NOT proceed to Phase 2 without explicit customer confirmation.

Phase 2 — Assessment

Purpose: Assess the cluster against MSK Express requirements and produce a target Express specification (instance type, broker count, monthly cost projection).

Input: migrate-to-msk-skill-artifacts/<cluster_name>/cluster-config.json from Phase 1.

Outputs:

• migrate-to-msk-skill-artifacts/<cluster_name>/compatibility.<cluster_name>.json — five-pillar verdict.
• migrate-to-msk-skill-artifacts/<cluster_name>/msk_sizing_pricing.md — the managing-amazon-msk Skill's pricing report with broker count and cost recommendations.
• migrate-to-msk-skill-artifacts/<cluster_name>/msk-sizing-inputs.<cluster_name>.json — a record of the six input values for sizing logic.

Assessment has two independent halves; run them in either order, and a failure in one does not block the other:

• Compatibility — scripts/compatibility.py, a pure file processor (no live AWS API calls) run via uv run with PEP 723 inline dependencies. It validates the source across five pillars — topology, Kafka version, configs, auth, and