microservice guide implementation checklist
microservice guide is central to this topic. microservice guide strategy improves planning and delivery. Teams that standardize microservice guide reduce rework and increase reliability.
This microservice guide guide covers practical execution, governance, and rollout. Strong microservice guide execution helps teams ship faster with fewer regressions.
Read our internal reference and official documentation for deeper patterns.
microservice implementation checklist
microservice is central to this topic. microservice strategy improves planning and delivery. Teams that standardize microservice reduce rework and increase reliability.
This microservice guide covers practical execution, governance, and rollout. Strong microservice execution helps teams ship faster with fewer regressions.
Read our internal reference and official documentation for deeper patterns.
If you work at a company running more than a handful of services, you already know the problem. Someone joins the team and asks “which services does the checkout flow depend on?” Nobody has a current answer. The architecture diagram on the wiki was accurate in 2022. The tech lead gives a verbal walkthrough from memory, probably missing two things. Two weeks later, the new engineer makes a change that breaks a service nobody mentioned.
This is not a people problem. It is a tooling problem. Architecture documentation rots the moment it is written because it lives outside the codebase. The services keep evolving; the diagram does not.
Service Map solves this by making the source of truth a set of YAML files that live in your repository alongside your code. From those files, it generates an interactive, filterable, always-current dependency graph that any engineer can open in a browser, explore, and share with a link. No backend required. No SaaS subscription. No data ever leaving your infrastructure.
What Service Map Does
Service Map is a self-hosted visualization tool that reads YAML service definitions and renders them as an interactive graph. Each node in the graph is a service. Edges represent dependencies. The graph is live — filter it, focus on a subset, hover over a node to trace its entire upstream and downstream chain, and copy a shareable URL that encodes everything about the current view.
The output is a static web application: HTML, CSS, and JavaScript files that you deploy to any static host. GitHub Pages, Netlify, Vercel, an S3 bucket behind CloudFront, your internal nginx — it does not matter. If it can serve files, it can host Service Map. Zero ongoing infrastructure cost.
You define services in YAML. The format is straightforward:
id: payment-service
name: Payment Service
area: Payments
kind: api
status: active
tech: [Node.js, PostgreSQL]
owner: payments-team
depends_on:
- target: user-service
- target: fraud-detection
- target: stripe
kind: externalThat is the entire definition for a service. Add one file per service to the data/services/ directory, run the build, and deploy. The graph updates to include the new service and its declared dependencies.
The Four Features That Make It Useful Day-to-Day
Filter and Focus Mode
A dependency graph with 40 services is noise if you only care about the payment domain. The filter sidebar lets you narrow the view by product area, service status, technology stack, and team ownership simultaneously. Non-matching services dim out but stay in the layout, giving you spatial context.
When you need to go further, Focus Mode re-runs the layout with only the matching services. Isolated nodes — services with no edges to anything in the filtered set — are excluded. What remains is a clean subgraph of exactly the services relevant to your current question.
Hover Tracing
Hover over any node and Service Map highlights the complete connected chain: every service that feeds into it (upstream) and every service it feeds into (downstream), following the graph in both directions through multiple hops. Everything outside that chain dims. This is the feature that makes impact analysis fast. “If I change the user service, what else is affected?” Hover over it and you have the answer in under a second.
Shareable URLs
Every state of the map — which filters are active, which service is selected, what the search query is — is encoded in the URL. Share a link in Slack and your colleague opens exactly the same view you are looking at. No screenshots, no “let me walk you through how to get there.” Paste the URL. Done.
Automatic Layout
You do not position nodes manually. The layout engine (ELK — Eclipse Layout Kernel) calculates positions automatically using a layered algorithm that respects dependency direction. Services that depend on nothing sit at one end; services that everything depends on sit at the other. The result is a readable graph without any manual arrangement work.
Who It Is For
Service Map is built for engineering teams. The specific personas that get the most value from it are slightly different, so it is worth addressing each one directly.
Engineers Onboarding to a New Codebase
The first week on a new team is spent building a mental model of the system. Service Map compresses that process. Instead of reading READMEs and asking questions to reconstruct the dependency graph in your head, you open the map and have it in front of you. Filter to your team’s area. Hover over the services you have been assigned to. See what they depend on. See what depends on them. The spatial representation sticks in a way that text descriptions do not.
Engineers Planning a Change
Before touching a service, you want to know the blast radius. Hover tracing shows you every downstream consumer that might be affected by a change to the service you are about to modify. This is especially valuable for shared infrastructure services — databases, auth services, internal SDKs — where the dependency graph is deep and not obvious from the code alone.
Architects and Tech Leads
Architecture documentation that is maintained as Confluence pages or draw.io diagrams drifts from reality within weeks. When the YAML files are treated as code and reviewed in pull requests, the map stays current automatically. Architects can use the live graph as a stakeholder communication tool — share a URL instead of a screenshot, and stakeholders see the actual current state rather than a snapshot that may already be outdated.
Engineering Managers and Staff Engineers
Service ownership tracking becomes trivial when every service has an owner field in its YAML. Filter by team to see everything a given team is responsible for. Use the status field (active, deprecated, planned) to track migrations in progress — filter to deprecated services and see what still depends on them, giving you a clear picture of remaining migration work.
The Self-Hosted Advantage
Most architecture visualization tools are SaaS. They charge per seat, require your service data to live on their servers, and add another vendor relationship to manage. When a team of 20 engineers needs access to the map, that is 20 seats at whatever the per-seat rate is. The tools that are good enough to be useful are typically not cheap.
Service Map is a one-time purchase at 99 EUR. You get the full source code. You deploy it yourself. Your service data stays in your infrastructure — it never leaves. There is no per-seat model because the deployment is a static site: anyone with the URL can view it, anyone with repository access can edit it. One license, unlimited internal use.
The self-hosted model also means you control the update cadence. You get one year of updates via git pull. After that, you keep the version you have and it keeps working. There is no “your plan has been discontinued” or “this feature is now Enterprise-only.”
Deployment in Practice
Getting Service Map running takes under 15 minutes for a team that already has Node.js and pnpm installed.
- Clone or download the repository into your project.
- Add your service YAML files to
data/services/, one file per service. - Run the build:
pnpm install && pnpm build - Deploy the
dist/directory to your static host of choice.
