How do you document a data platform migration for future teams?

To document a data platform migration for future teams, capture three things: what the system looked like before, what decisions were made during the migration and why, and what the new system requires to operate. Good migration documentation is not a narrative of what happened – it is a reference that lets someone who was not in the room understand the architecture, reproduce the environment, and troubleshoot without hunting down the people who ran the project.

The quality of that documentation determines whether your migration creates institutional knowledge or just institutional debt. Teams working with Kubernetes-native platforms face some specific documentation challenges around operator configuration and declarative state – and how you handle those challenges shapes whether the documentation is actually useful to the next engineer who inherits the system.

What should a data platform migration document include?

A data platform migration document should include a pre-migration architecture snapshot, a record of architectural decisions with their rationale, a post-migration system description, operational runbooks, a dependency map, and a known issues log. Together, these give future teams both the context and the practical information they need to work with the system confidently.

Think of the document as answering two distinct questions: “What did we do and why?” and “How does this thing work now?” Many teams write only one or the other. The first without the second leaves future engineers with history but no operational guide. The second without the first leaves them unable to understand why the system is structured the way it is – which makes every change a guessing game.

At minimum, include:

Pre-migration state: data sources, existing tooling, known pain points, and why the migration was initiated
Decision log: key architectural choices, the options considered, and the reasoning behind what was selected
Post-migration architecture: component inventory, data flows, integration points, and environment configuration
Operational runbooks: step-by-step procedures for common operational tasks
Dependency map: upstream and downstream systems affected by the migration
Known issues and workarounds: anything that did not go as planned and how it was resolved or mitigated

The known issues section is the one most teams skip. It is also the one future engineers will find most useful at 2am.

How do you capture architectural decisions during a migration?

Architectural decisions during a migration are best captured using Architecture Decision Records (ADRs) – short, structured documents that record a single decision, the context that drove it, the options considered, and the outcome. Writing ADRs as decisions are made, rather than retrospectively, produces far more accurate and useful documentation.

The ADR format works well because it forces specificity. Instead of a vague note that says “we chose Trino for querying,” an ADR explains that Trino was selected over an alternative because it supports federated queries across object storage and relational sources, fits the existing Kubernetes deployment model, and has an active open-source community. That context matters when someone revisits the decision two years later.

Practically, this means someone needs to own the habit of writing ADRs in real time. Migrations move fast and decisions compound. If you wait until the migration is complete to document decisions, you will reconstruct them from memory – and memory is unreliable about the options that were rejected.

Store ADRs in version control alongside your infrastructure code. This keeps decisions traceable to the state of the system at the time they were made, and it means the documentation lives where engineers already work.

What’s the difference between runbooks and migration documentation?

Runbooks are operational procedures for recurring tasks – how to restart a service, rotate credentials, scale a cluster, or respond to an alert. Migration documentation is a historical and architectural record of how the system came to be. They serve different audiences at different moments: runbooks are for the engineer on call; migration documentation is for the engineer trying to understand the system.

Conflating the two is a common mistake. Teams sometimes produce a single “migration document” that mixes architectural rationale with step-by-step procedures, making it too long to use as a quick operational reference and too shallow to serve as a real architectural record.

Keep them separate but connected. Your migration documentation should reference the runbooks that apply to the new system. Your runbooks should include a brief note on the context they operate in – which component, which environment, which version – so they stay accurate as the system evolves.

One practical rule: if a procedure needs to be repeated, it belongs in a runbook. If something happened once and explains why the system is the way it is, it belongs in migration documentation.

How do you document a Kubernetes-native data platform migration?

Documenting a Kubernetes-native data platform migration requires capturing the declarative configuration state – the YAML manifests, Helm values, or operator custom resources that define the system – alongside the architectural decisions that shaped them. Because Kubernetes systems are defined as code, the configuration files themselves are primary documentation, but they need context to be useful.

Raw YAML without explanation is not documentation. A manifest that defines a Kafka cluster tells you the current state; it does not tell you why the replication factor is set to three, why a specific storage class was chosen, or what the resource limits are based on. That context needs to live somewhere explicit.

Documenting operator configuration

If you are using Kubernetes operators to manage data services, document the custom resource definitions (CRDs) you are using and the non-default values you have set. Operators often expose a large configuration surface, and future teams need to know which settings were deliberately chosen versus left at defaults.

For each major component, include a short explanation of the configuration choices that deviate from defaults. This does not need to be exhaustive – focus on the decisions that would be non-obvious to someone reading the manifest cold.

Capturing environment and dependency state

Kubernetes-native migrations often involve multiple environments – development, staging, production – with configuration differences between them. Document these differences explicitly. A future engineer should be able to tell at a glance what changes between environments and why.

Also document external dependencies: storage backends, identity providers, secret management systems, network policies, and any cloud-provider-specific integrations. These are often the first things that break when a system is reproduced in a new environment, and they are rarely captured in the manifests themselves.

Who is responsible for writing migration documentation?

Responsibility for migration documentation should sit with the engineers who made the architectural decisions – not with a technical writer working from interviews after the fact. This does not mean every engineer writes full prose documentation; it means the people with direct knowledge own the accuracy of what is recorded, even if someone else helps with structure and clarity.

In practice, assigning a documentation owner at the start of the migration works better than treating documentation as a post-migration task. The documentation owner does not need to write everything themselves – their job is to make sure decisions are recorded as they happen, that runbooks are drafted before the system goes live, and that the post-migration architecture description reflects reality rather than the original plan.

If your team uses a pull request workflow for infrastructure changes, documentation updates can be required as part of the PR process. This makes documentation a condition of the work being done, rather than a separate task that competes with other priorities.

One honest note: documentation quality tends to reflect team culture more than process. If senior engineers treat documentation as optional, junior engineers will follow that lead. If the people who made the decisions write the ADRs, the rest of the team takes the practice seriously.

How do you keep migration documentation useful over time?

Migration documentation stays useful over time when it is treated as a living artifact that is updated alongside the system, stored in version control, and reviewed periodically against the actual state of the platform. Documentation that is written once and never touched becomes a liability – it misleads rather than informs.

The most effective approach is to tie documentation updates to system changes. If a configuration change goes through a pull request, the PR should include a documentation update if the change affects architecture, operational procedures, or decision rationale. This keeps documentation in sync with reality without requiring a separate documentation sprint.

Schedule a lightweight documentation review every six months or after any significant system change. The goal is not a full rewrite – it is to identify sections that no longer reflect the system and either update them or mark them as superseded. Outdated documentation that is clearly labeled as outdated is less dangerous than outdated documentation presented as current.

Finally, make documentation discoverable. A well-written migration document that lives in an obscure wiki folder no one knows about has the same practical value as no documentation at all. Store it where engineers already look – in the repository, in the team’s primary knowledge base, or linked from the service’s README.

How Stackable helps with data platform migration documentation

The SDP is built around a declarative, infrastructure-as-code model, which means the configuration of your data platform – every operator, every service, every integration – is expressed as Kubernetes custom resources stored in version control. That gives you a traceable, reproducible record of system state as a direct output of how the platform works, not as an extra documentation task.

Specifically, the SDP supports migration documentation through:

Declarative configuration as documentation: Custom resources for components like the Stackable Operator for Apache Kafka® define service configuration explicitly and version-controllably, so the state of the system is always readable from the manifests
Modular architecture: Because the SDP is composable, you can document each component independently and add or remove components without rewriting the full architecture description
Cloud-agnostic deployment: The same configuration runs on-premises, in any cloud, or in hybrid environments – reducing the number of environment-specific documentation variants you need to maintain
Open-source transparency: Every operator and integration is open source, so documentation can link directly to upstream Apache project documentation and community resources rather than relying on proprietary knowledge bases
stackablectl: The CLI tool supports reproducible deployments from configuration files, which can serve as executable documentation for environment setup procedures

If you are planning a migration to the SDP or want to understand how the platform’s architecture maps to your documentation requirements, talk to the Stackable team directly – or explore the Stackable Data Platform to see how the components fit together.

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