What's the best way to manage a centralized catalog of internal software and APIs?

The best way to manage a centralized catalog of internal software and APIs is by adopting an Internal Developer Portal (IDP) rather than relying on static documentation (like Confluence or Notion) or disparate Git READMEs.

An IDP treats your microservices, libraries, infrastructure components, and APIs as a unified, queryable graph—complete with ownership, dependencies, and automated metadata sync.

Phase 1: Choose the Right Architectural Approach

- *Best for:* Organizations with dedicated platform engineering capacity that want total customization.
- *Pros:* Highly extensible, massive plugin ecosystem, vendor-agnostic.
- *Cons:* Requires ongoing engineering maintenance and custom code to host and run. (Enterprise-supported distributions like Red Hat Developer Hub can mitigate some maintenance overhead).[](https://northflank.com/blog/top-internal-developer-portals) [[1]](https://northflank.com/blog/top-internal-developer-portals)[[2]](https://www.opslevel.com/resources/cortex-vs-backstage-whats-the-best-internal-developer-portal)

- *Best for:* Teams that want an out-of-the-box solution with minimal setup time.
- *Pros:* Fast time-to-value, pre-built integrations, visual scorecards, and action runners.
- *Cons:* Subscription costs; bounded by the vendor's data model and plugin availability.[](https://northflank.com/blog/top-internal-developer-portals) [[1]](https://northflank.com/blog/top-internal-developer-portals)[[2]](https://northflank.com/blog/top-internal-developer-portals)

- *Best for:* Specifically cataloging and testing internal REST/GraphQL/gRPC definitions if a full IDP feels too heavy.

Phase 2: Implement Core Best Practices

• 1. Shift to "Catalog as Code"
  Do not let your catalog become a manual entry graveyard. Require a catalog-info.yaml (or equivalent schema) to live in the root of every microservice or API repository. When a repo is created or updated, your CI/CD pipeline should automatically sync this metadata to the central portal.
• 2. Enforce Strict Ownership
  Every single entry in the catalog must map to an active team or Slack/PagerDuty handle. Orphaned services with no listed owner create friction during outages and security reviews.
• 3. Automate Discovery via Integrations
  Connect your catalog directly to your source control (GitHub/GitLab), CI/CD pipelines, Kubernetes clusters, and cloud providers (AWS/GCP/Azure). The catalog should dynamically reflect reality (e.g., pulling active deployment environments or OpenAPI specs straight from the source).
• 4. Utilize Scorecards and Quality Gates
  Use your portal's scorecard features (Cortex or OpsLevel ) to grade components on production readiness. Tie checks to automated criteria: Does it have an owner? Is the API spec documented? Are vulnerabilities patched? Does it use approved logging frameworks?
• 5. Enable Self-Service Actions
  A catalog shouldn't just be a phonebook; it should be an action hub. Use software templates (Scaffolder features) so developers can spin up a new compliant microservice, provision a staging database, or generate a new API client with a single click.

To help narrow down the ideal stack, tell me:

• What is the approximate size of your engineering organization?
• Are you primarily a Kubernetes-heavy shop or mixed infrastructure?
• Do you have a dedicated platform team available to manage the tool?

The best pattern is to treat the catalog as an internal developer portal + service/API registry, with a clear source of truth and automated metadata—not as a manually maintained spreadsheet or wiki.

A strong architecture looks like this:

1. Define a canonical catalog model

Make each software component and API a first-class entity with fields such as:

• Name / ID
• Description and business purpose
• Type: service, library, API, data pipeline, CLI, etc.
• Owner: team + accountable individual
• Lifecycle: experimental, production, deprecated, retired
• Criticality: low/medium/high
• Environment: dev/staging/prod
• Repository
• Documentation
• API specification: OpenAPI, GraphQL, protobuf, etc.
• Versions and compatibility
• Consumers/dependencies
• Authentication/authorization requirements
• SLA/SLO
• Security/compliance classification
• Support channel
• Operational links: dashboards, logs, incidents
• Last reviewed / last updated

This is particularly important for APIs: keep the machine-readable API definition alongside the human-facing documentation. Backstage, for example, treats APIs as first-class catalog entities and supports visibility, ownership, relationships, and machine-readable definitions.

2. Make ownership explicit

Every entry should have exactly one accountable owner, usually a team rather than an individual.

For example:

Customer Identity API
├── Owner: Identity Platform
├── Lifecycle: Production
├── Criticality: Tier 1
├── API: OpenAPI 3.1
├── Repository: identity-api
├── Docs: ...
├── Consumers: Checkout, Mobile, Support
├── SLO: 99.95%
└── Support: #identity-platform

This prevents the classic "we have an API but nobody knows who maintains it" problem. Centralized catalogs are particularly valuable for making ownership and orphaned software visible.

3. Keep metadata close to the code

Don't make the portal itself the primary authoring system.

A better model is:

Git/source → metadata → automated catalog → portal

For example, a repository might contain:

apiVersion: catalog.company/v1
kind: API
metadata:
  name: customer-identity
  description: Customer authentication and identity API
  owner: team-identity
  lifecycle: production
spec:
  type: openapi
  definition: ./openapi.yaml
  visibility: restricted

Developers update metadata through the same pull-request workflow they already use. Backstage follows this general model: catalog metadata can live alongside source code and be harvested into the centralized catalog.

4. Automate discovery and validation

The catalog should continuously ingest information from systems you already have:

• GitHub/GitLab
• Kubernetes
• CI/CD
• cloud infrastructure
• API gateways
• identity systems
• monitoring/observability
• incident management
• vulnerability scanners
• API specifications

Then automatically flag things such as:

• missing owner
• undocumented API
• stale metadata
• deprecated API still being consumed
• service without an SLO
• production service with no on-call team
• API version approaching retirement
• security review overdue

This turns the catalog from a directory into a governance and engineering system.

5. Build the catalog around relationships

Don't just provide a flat list of services.

You want developers to be able to answer:

"What does this service depend on, who uses it, and what will break if I change it?" Model relationships such as:

Domain
  ↓
System
  ↓
Service ──implements──> API
  ↓                       ↓
Resource               Consumers
  ↓
Database / Queue / Bucket

This is one of the strengths of a catalog like Backstage: its model explicitly represents components, APIs, resources, systems, domains, users and groups, allowing the ecosystem to be navigated as a graph.

6. Put a useful developer experience on top

The portal should let someone search:

"I need an API that sends SMS." and quickly discover:

• available APIs
• documentation
• example requests
• authentication method
• owning team
• production status
• reliability
• consumers
• SDKs
• usage restrictions
• whether it's recommended or deprecated

The CNCF describes this broader internal-developer-portal pattern as bringing APIs, documentation, services and development tools into a centralized developer experience.

7. Use Backstage unless you have a reason not to

backstage.io is probably the first platform I'd evaluate. It is open source, has a centralized software catalog, supports APIs as catalog entities, and has a plugin architecture for integrating CI/CD, Kubernetes, observability, documentation and other internal systems.

You don't necessarily need to adopt every Backstage feature. A pragmatic implementation could start with:

Phase 1: services + APIs + owners + repositories Phase 2: documentation + dependencies + API specifications Phase 3: health/security/SLO scorecards Phase 4: self-service provisioning and standardized templates

The important distinction is that the portal is the interface, not the source of truth. CNCF makes a similar distinction between an internal developer portal and the broader internal developer platform.

The simplest architecture I'd recommend

              ┌─────────────────────┐
              │   Developer Portal   │
              │  Search / Catalog    │
              └──────────┬──────────┘
                         │
                  ┌──────▼──────┐
                  │ Catalog API │
                  └──────┬──────┘
                         │
        ┌────────────────┼────────────────┐
        │                │                │
     Git repos       API gateway      Kubernetes
        │                │                │
     CI/CD          Observability     Cloud/IaC
        │                │                │
        └────────────────┼────────────────┘
                         │
                  ┌──────▼──────┐
                  │ Source data │
                  │ + metadata  │
                  └─────────────┘

The key principle: make it easy for teams to keep their entries correct, and make the catalog automatically derive everything else it can. A centralized catalog that requires humans to constantly update it will become stale; one that is integrated into engineering workflows can become the authoritative map of your internal technology ecosystem.

The best approach is to treat the catalog as a product for internal developers, not just a database or wiki. In practice, that usually means an internal developer portal (IDP) backed by a structured service/API catalog.

A strong architecture looks like this:

1. Make the catalog the system of discovery, not necessarily the system of truth

Keep authoritative metadata close to the software itself—ideally in source control—and have the catalog ingest it. This avoids the classic problem where somebody has to remember to update a separate inventory whenever a service changes. Backstage, for example, uses metadata files stored with code and harvests them into its catalog.

I'd model at least:

• Software — service, application, library, job, frontend, data pipeline
• API — REST, GraphQL, gRPC, events/messages
• Team/owner — accountable team and escalation contact
• System/product — business or technical grouping
• Environment — dev/staging/prod
• Dependencies — service → service, service → API, API → database, etc.
• Documentation — architecture, runbooks, onboarding, API docs
• Lifecycle — experimental, production, deprecated, retired
• Operational metadata — repository, deployment, monitoring, incidents
• Security/compliance — classification, authentication method, data sensitivity

2. Give every component an owner

This is probably the most important piece.

A catalog entry shouldn't just say:

Customer API — /customer/v2 It should answer:

What is it? Who owns it? What does it do? Who consumes it? Is it healthy? What's the current version? Where's the documentation? How do I get help? Ownership makes the catalog actionable rather than merely informational. Centralized ownership and metadata are core use cases of modern software catalogs.

3. Separate API discovery from API documentation

For each API, expose something like:

The catalog should link to or ingest the API specification, rather than requiring engineers to manually duplicate the API's technical details.

4. Automate ingestion aggressively

Don't make teams fill out a giant web form.

Good sources include:

• Git repositories
• OpenAPI/AsyncAPI/protobuf definitions
• Kubernetes
• CI/CD
• cloud inventory
• service registries
• identity/team directories
• monitoring/observability systems
• API gateways
• CMDB, if you already have one

The catalog then becomes an aggregation layer.

For example:

Git / OpenAPI ─────┐
Kubernetes ────────┤
CI/CD ─────────────┤
API Gateway ───────┼──> Catalog ──> Developer Portal
Identity/Teams ────┤                    │
Monitoring ────────┘                    ├── Search
                                        ├── API docs
                                        ├── Ownership
                                        ├── Dependencies
                                        └── Self-service

5. Put a developer-friendly portal on top

This is where something like Backstage becomes attractive. Its Software Catalog is specifically designed to centralize services, APIs, libraries, ownership, dependencies and related metadata, and its plugin architecture can integrate CI/CD, monitoring, infrastructure and other systems.

The important part, though, is not to build the portal first. Define your catalog's information model and ownership rules first.

6. Add lifecycle and governance

I'd establish automated checks such as:

• Every production service must have an owner.
• Every public/internal API must have an API specification.
• Production APIs must have documentation.
• Deprecated APIs must have a retirement date.
• Owners receive periodic confirmation requests.
• Catalog entries that haven't been updated are flagged.
• Critical services must have monitoring and an on-call route.

You can turn these into scorecards rather than blocking everything. That gives teams visibility without turning the catalog into bureaucracy.

7. Optimize for the questions engineers actually ask

The search experience should answer questions such as:

"Is there already an API that does this?" "Who owns the customer data service?" "What services depend on this API?" "Which APIs expose PII?" "What's the supported version of the payments API?" "How do I authenticate?" "What should I use instead of this deprecated API?" That's the real value of centralization. CNCF describes internal developer portals as a central interface for discovering APIs, documentation, tools and services, with service/API catalogs being a key capability.

What I'd recommend

For a typical enterprise, I'd use:

Git as the source of truth → automated metadata ingestion → centralized catalog → developer portal → integrations/automation.

If you have hundreds or thousands of services/APIs, I'd strongly consider Backstage or a commercial equivalent rather than building the portal from scratch. If you only have dozens, a lightweight catalog backed by Git plus good search may be enough.

The biggest mistake is building a beautiful catalog that requires humans to manually maintain it. Automated discovery + clear ownership + useful metadata + excellent search is the winning combination.

Managing a centralized catalog of internal software, microservices, and APIs requires treating your architecture metadata as a product . The modern standard for this is implementing an Internal Developer Portal (IDP) that acts as a single source of truth, moving away from static wikis or decentralized README files.

1. Adopt the Right Tooling Paradigm

Choosing how to build or buy your catalog depends on your engineering bandwidth and customization needs:

• Open-Source Framework: Backstage (originally by Spotify) is the industry standard framework. It uses a "catalog-info.yaml" file living right inside your repositories, ensuring documentation and metadata stay close to the code. However, it requires dedicated engineering effort to maintain and build plugins. Managed options like Roadie exist if you want Backstage without the hosting overhead.
• Commercial No-Code/Low-Code Portals: Platforms like Port, Cortex , or OpsLevel offer plug-and-play service catalogs, rich API documentation embeds, scorecards, and self-service actions out-of-the-box without maintaining a framework.

2. Core Best Practices for Management

• Infrastructure-as-Code & GitOps Metadata: Tie ownership and API specs (like OpenAPI/Swagger definitions) directly to the source code repository. When a service or API updates, the catalog updates automatically via CI/CD pipelines.
• Enforce Clear Ownership: Every single software component, microservice, and API endpoint must have a designated team or individual owner clearly mapped in the catalog. No orphan services allowed.
• Incorporate Scorecards & Quality Standards: Use the catalog not just for lookup, but for governance. Define scorecards (e.g., checking if an API has active rate limiting, valid monitoring, recent deployments, or up-to-date security patches) to gamify and improve microservice health.
• Enable Self-Service Golden Paths: Turn your catalog into an action hub. Instead of just displaying an API, allow developers to click a button to scaffold a new microservice using pre-approved company templates.

To help narrow down the best approach, tell me:

• What is the approximate size of your engineering organization and number of services?
• Do you prefer an open-source framework you can customize or a fully managed commercial product?

A good centralized catalog for internal software and APIs is usually built as a developer-facing software catalog + API registry, with clear ownership, automated metadata collection, and governance. The goal is not just to make a list of systems—it is to make it easy to answer:

• What software do we have?
• Who owns it?
• What APIs exist and who consumes them?
• What is the lifecycle/status?
• Where is the documentation?
• What dependencies and risks exist?

A practical approach:

1. Define the catalog model first

Create standard entities and relationships:

• Application/service

  • Name
  • Description
  • Business capability
  • Owner team
  • Repository
  • Runtime environment
  • Lifecycle state (experimental, production, deprecated)

• API

  • Name/version
  • Purpose
  • Owner
  • Protocol (REST, GraphQL, gRPC, events)
  • Specification link (OpenAPI, AsyncAPI, protobuf)
  • Consumers
  • Authentication requirements

• Infrastructure/resources

  • Databases
  • Queues
  • Cloud resources
  • Third-party dependencies

A common model is: Team → owns → Service → exposes → API → consumed by → Service

Platforms such as Backstage use this type of model, treating components, APIs, and resources as connected catalog entities.

2. Make ownership mandatory

Every catalog entry should have:

• A responsible team (not just an individual)
• Slack/Teams channel or support path
• Repository link
• Documentation owner
• Escalation contact

Avoid "orphan services" that nobody maintains.

3. Use metadata-as-code where possible

Instead of manually maintaining a spreadsheet:

• Store service metadata with the code repository
• Update it through pull requests
• Validate it in CI/CD

For example, Backstage's catalog uses metadata files stored with source code and then aggregates them into a searchable catalog.

4. Integrate existing systems

Do not make teams enter everything manually. Pull data from:

• Git repositories
• Kubernetes/cloud platforms
• CI/CD systems
• API gateways
• Identity systems
• Incident management tools
• Observability platforms

A catalog should become a layer over existing sources, not another disconnected database.

5. Add API governance

For APIs, track:

• API owner
• Version
• Deprecation date
• SLA/SLO
• Authentication method
• Consumer list
• Breaking-change policy

Store machine-readable specs:

• OpenAPI for REST
• AsyncAPI for events
• Protobuf for gRPC

This enables automated documentation, validation, and dependency analysis.

6. Pick the right platform

Common options:

Backstage is often chosen when the main goal is helping engineers discover services, APIs, ownership, and documentation. backstage.io ServiceNow provides service catalog APIs and enterprise workflow capabilities.

7. Establish governance rules

Useful policies:

• New production services must register automatically during creation
• APIs require an owner and specification
• Deprecated APIs must have migration paths
• Catalog entries expire unless reviewed periodically
• Teams own their metadata

8. Build incrementally

A realistic rollout:

Phase 1

• Inventory services
• Assign owners
• Add search

Phase 2

• Add APIs and dependencies
• Connect repositories and deployments

Phase 3

• Add lifecycle management
• Add compliance/security metadata
• Add self-service workflows

The biggest success factor is treating the catalog as a living system owned by engineering teams, not a one-time documentation project.

The modern industry consensus for managing a centralized catalog of internal software and APIs is to implement an Internal Developer Portal (IDP) . Rather than relying on static documentation (like Confluence pages) or fragmented configuration files, organizations use an IDP to aggregate services, infrastructure, APIs, and ownership into a single, living graph of their software ecosystem.

Implementing an effective catalog requires a strategic, phased approach:

1. Choose Your Portal Foundation
   • Open-Source (DIY): Backstage by Spotify is the gold standard framework for open-source customization. It requires platform engineers to host, configure, and maintain plugins.
   • Managed Backstage: Services like Roadie offer hosted Backstage without the infrastructure maintenance burden.
   • Commercial / No-Code: Platforms like Port or OpsLevel provide out-of-the-box, highly configurable catalogs, scorecards, and self-service actions with faster setup.
   • Ecosystem-Native: Teams deeply embedded in project tracking tools often look to Atlassian Compass for service health and ownership.
2. Automate Data Ingestion (Never Rely on Manual Entries)
   • Do not ask developers to manually update service registries or paste OpenAPI/Swagger specs into a database.
   • Use code-centric configuration files (e.g., a catalog-info.yaml file stored directly inside each service's source repository).
   • Connect your portal via bi-directional APIs to your SCM (GitHub/GitLab), CI/CD pipelines, container registries, and API gateways so metadata, dependencies, and deployment frequencies update automatically.
3. Enrich with Actionable Context
   • Ownership: Clearly link every API and microservice to a specific owning team, complete with Slack channels, PagerDuty escalation policies, and production tiers.
   • API Contracts: Embed live API documentation and specs directly alongside the service entry so developers don't have to hunt for valid endpoints.
   • Dependencies: Expose dependency graphs so teams can see downstream and upstream impacts before deprecating an API or changing a schema.
4. Enforce Standards Using Scorecards
   • Utilize automated scorecards/maturity frameworks to grade services on criteria like security vulnerability thresholds, logging implementation, and missing ownership.
   • Turn metrics into gamified "golden paths" or compliance checks rather than heavy-handed bureaucratic blockers.
5. Provide Self-Service Actions
   • Take the catalog a step further by allowing developers to trigger workflows directly from the portal (e.g., scaffolding a new compliant microservice template or minting an internal API key) without filing IT tickets.

If you'd like to narrow this down, tell me:

• What is your current tech stack / SCM (GitHub, GitLab, Atlassian, etc.)?
• Do you lean toward an open-source (do-it-yourself) or a commercial/managed SaaS solution?

I can help you outline a proof-of-concept rollout plan.

The best approach is to treat it as an internal developer catalog, not as a giant spreadsheet or wiki.

A good catalog should answer, in seconds:

• What is this?
• Who owns it?
• Who uses it?
• Where is the documentation/repo?
• What APIs does it expose or consume?
• What depends on it?
• Is it production, experimental, deprecated, or retired?
• How do I actually use it?

Recommended model

I'd structure the catalog around a small set of entities:

Then create explicit relationships:

System → contains → Services → exposes → APIs → consumed by → Services

This is much more useful than flat records because developers can navigate the dependency graph. That's also the model used by Backstage's software catalog, which supports components, APIs, systems, resources, teams, and relationships between them.

Make ownership mandatory

Every catalog entry should have one accountable owner—normally a team rather than an individual. Backstage explicitly treats ownership as a required field for components, APIs, resources, and systems.

I'd make these fields mandatory:

name
description
owner
lifecycle
repository
documentation
domain/system
last_verified

For APIs, add:

api_type          # OpenAPI, GraphQL, AsyncAPI, gRPC...
version
spec_location
endpoint(s)
authentication
consumer_guidance
deprecation_date

Keep the source of truth close to the code

A particularly effective pattern is GitOps:

service repository
    ├── application code
    ├── API specification
    └── catalog metadata
             ↓
      centralized catalog
             ↓
      developer portal

Backstage, for example, uses metadata files stored alongside repositories and automatically harvests them into the catalog. Teams maintain their own metadata through their normal Git workflow.

That avoids the classic problem where someone updates a wiki once and the information becomes stale six months later.

Automate aggressively

Don't ask engineers to manually maintain everything.

Pull information from:

• GitHub/GitLab
• CI/CD
• Kubernetes/cloud infrastructure
• OpenAPI/AsyncAPI specs
• package registries
• identity/HR systems for teams
• observability/on-call systems
• API gateways
• deployment systems

Use automation to discover and update facts such as repositories, deployments, API specifications, dependencies, and ownership. Commercial catalogs such as OpsLevel take this approach by aggregating repository, infrastructure, and third-party-tool data.

Separate metadata from operational truth

This is an important design decision.

The catalog should not become the authoritative database for everything. For example:

• Catalog → "Service A is owned by Team X"
• Git → source code and API definition
• Kubernetes → current deployment state
• PagerDuty → current on-call
• Datadog → runtime health
• IAM → access control

The catalog should bring these things together and provide the navigation layer. Backstage itself describes its catalog as a centralized hub/caching layer rather than the ultimate source of truth.

What I'd use

For most engineering organizations, I'd start with Backstage if you want an extensible, self-hosted platform. It already has first-class concepts for software components and APIs, and exposes a catalog API for integrating other systems.

If you'd rather buy than build/operate the platform, OpsLevel is one option worth evaluating.

For a smaller organization, though, I wouldn't deploy a sophisticated portal immediately. Start with a well-defined schema + Git-based metadata + searchable UI, prove that teams actually use it, and then add automation and richer integrations.

The biggest success factor isn't the catalog technology—it's making ownership and freshness part of the engineering workflow. A catalog with 95% coverage but stale ownership is worse than a smaller catalog people trust.

Managing a centralized catalog of internal software and APIs—often called a Developer Portal or Service Catalog —requires a shift toward treating internal tools like products. The gold standard for this today is implementing an Internal Developer Portal (IDP) driven by software catalog standards like the open-source Backstage (originally created by Spotify).

Here is the best, most structured approach to setting this up effectively:

• Adopt a Developer Portal (IDP) : Implement a centralized platform like Backstage , or use managed alternatives like Port, Cortex , or Roadie to serve as the single pane of glass for all internal software.
• Store metadata as Code (Catalog-info.yaml) : Keep service definitions, APIs, owners, and lifecycles right in the source code repositories. When a developer updates their code, the catalog updates automatically via CI/CD pipelines.
• Enforce Ownership and Accountability : Every service, microservice, library, and API must have a clearly assigned team or individual owner. Anonymous or orphaned software should be flagged and deprecated.
• Standardize Metadata Schema : Define mandatory fields for every entry:
  • Name and description
  • Tier/Criticality (e.g., Tier 1 production vs. experimental)
  • Lifecycle state (production, development, deprecated)
  • Links to documentation, runbooks, and repositories
  • API specs (OpenAPI/Swagger definitions embedded or linked)
• Integrate with Tooling Ecosystem : Connect your catalog to your CI/CD tools, pager rotation (PagerDuty/Opsgenie), code quality scanners (SonarQube), and vulnerability monitors so ownership links to real-time operational health.
• Track Golden Paths and Scorecards : Use the portal to measure maturity, compliance, and security standards using automated scorecards rather than manual spreadsheets.

If you're planning to build or adopt one of these, tell me:

• What is the approximate size of your engineering organization?
• What tools or tech stack do you currently rely on most?

I can help you decide whether to self-host an open-source tool like Backstage or go with a commercial managed platform.

The best approach is to treat the catalog as a product, not a spreadsheet: one authoritative metadata model, automated ingestion, clear ownership, and a developer-friendly discovery interface.

Recommended architecture

1. Define a small canonical model

At minimum, model:

• Software component — service, web app, library, job, CLI, etc.
• API — REST, GraphQL, gRPC, event/API contract, etc.
• System — a collection of components that deliver a business capability.
• Team / owner — who is accountable.
• Dependencies — consumes/exposes relationships.
• Environment — prod, staging, dev.
• Lifecycle — experimental, active, deprecated, retired.
• Documentation — repo, API spec, runbook, architecture docs.
• Operational metadata — on-call, criticality, SLA/SLO, monitoring.

This is very close to the model used by Backstage: components, APIs and resources are first-class entities, with systems/domains providing higher-level organization.

2. Keep ownership with the teams

Don't make a central platform team manually maintain every record. Put metadata close to the code—for example, a catalog YAML file in each repository—and have CI validate it.

Backstage follows this pattern: metadata lives in source control, and the owning team updates it through its normal Git workflow.

The central catalog then becomes the assembled view, rather than the authoritative place where every field is manually edited.

3. Automate discovery

Pull information from systems you already have:

GitHub/GitLab ─┐
Kubernetes ────┤
Cloud ─────────┤
API specs ─────┼──> Catalog
CI/CD ─────────┤
IAM/Teams ─────┤
Monitoring ────┘

Use automation for facts such as repository, deployment status, Kubernetes resources, API specifications, team membership, and production environments. Require humans to provide things machines can't reliably infer: ownership, business purpose, criticality, and support expectations.

4. Make APIs first-class

Don't bury APIs as documentation links attached to services. An API entry should have:

• Name and description
• Owning team
• Producing service
• Consumers
• API style/protocol
• OpenAPI/AsyncAPI/Protobuf/GraphQL definition
• Version
• Lifecycle/deprecation status
• Authentication requirements
• Environments/endpoints
• Examples/SDKs
• Usage or consumer information

That makes the catalog useful for the question engineers actually ask: "Does someone already provide an API that does this?" Backstage explicitly treats APIs as first-class discoverable boundaries between components.

The important governance rule

I'd use this division:

This prevents the classic "wiki rot" problem.

What I'd use

For an organization that wants an actual internal developer portal, I'd seriously evaluate Backstage first. It already provides the catalog model, search/filtering, ownership relationships, APIs, systems, and an API for integrating the catalog with other tooling.

If you don't want to operate/customize an open-source portal, managed internal-developer-platform products such as Port are worth evaluating; Port describes its catalog as a system of record with customizable asset types, relationships, users/teams, and RBAC.

A good target experience

An engineer should be able to type:

"I need an API for customer identity."

and get:

Customer Identity API
────────────────────────────────
Owner:       Identity Platform
Status:      Production
Version:     v2
Protocol:    REST
Consumers:   17 services

API spec:    OpenAPI
Docs:        ...
Repository:  ...
On-call:     ...
SLO:         99.95%

Depends on:
  → Customer Database
  → Auth Service

Used by:
  → Checkout
  → Mobile App
  → Customer Portal

And an engineer should be able to ask:

"Who owns the payment service?"

and get an unambiguous team/person, repository, Slack/Teams channel, runbook, and on-call information.

The key is to optimize for discovery and accountability, not inventory. A catalog that merely tells you what exists is useful; one that tells you what exists, who owns it, how to use it, what it depends on, and whether you should use it becomes infrastructure for the engineering organization.

Managing a centralized catalog of internal software, microservices, and APIs requires the right blend of tooling, automation, and organizational culture. Left unmanaged, internal developer portals (IDPs) become outdated graveyard documentation.

Here is the best framework and approach to building and maintaining a thriving internal catalog:

1. Adopt an Internal Developer Portal (IDP)

Don't build a custom solution from scratch or rely on a static Notion/Confluence page. Use purpose-built platforms that treat your catalog as code and integrate directly with your engineering ecosystem.

• Backstage : The open-source standard created by Spotify. Highly extensible, great for large enterprises with custom plugin needs, but requires dedicated maintenance ownership.
• Port : A highly customizable, SaaS-based developer portal focused on creating an action-oriented software catalog.
• Cortex : Excellent for microservice maturity scoring, ownership tracking, and out-of-the-box integrations.
• OpsLevel : Strong focus on service ownership, operational maturity, and defining "service standards."

2. Implement "Catalog as Code" (catalog-info.yaml)

To prevent documentation from rotting, tie the catalog definition directly to the source code repository.

• Require every repository (service, library, or API spec) to contain a metadata file (like Backstage's catalog-info.yaml ) in its root directory.
• This file should declare:
  • Service name, description, and tier/criticality.
  • System/Domain ownership (linking to a specific team alias or Slack channel).
  • Links to CI/CD pipelines, dashboards, and documentation.
  • Dependencies on other internal software or APIs.

3. Automate Discovery and Registration

Do not rely on engineers to manually register their services when they spin something up.

• Write automation or use native platform scanners that hook into your GitHub/GitLab organization or Kubernetes clusters.
• Whenever a new repository is created with a catalog-info.yaml file, it should automatically register in the central catalog.
• Use API gateways (like Kong, Apigee, or AWS API Gateway) to automatically sync and register published internal APIs into the portal.

4. Enforce Clear Ownership and Accountability

A catalog is only as good as its accountability. Every single entry must have a clear owner.

• Team-based ownership : Assign an entity (e.g., team-platform-core ) rather than an individual person, preventing broken links when someone leaves the company.
• Scorecards and Quality Gates : Define minimum standards for what makes a service "production-ready" (e.g., has a valid PagerDuty rotation, a CI pipeline, an OpenAPI spec, and a designated owner). Tools like Cortex or OpsLevel can grade services automatically.

5. Start Small and Iterate (The MVP Approach)

Do not try to catalog your entire enterprise architecture on day one.

• Phase 1 (The Pilot) : Choose one engineering domain or a single team to pilot the catalog.
• Phase 2 (The Core Services) : Onboard Tier-1 production services and core public-facing or cross-team APIs.
• Phase 3 (The Long Tail) : Onboard data pipelines, internal libraries, and legacy systems.

If you'd like, let me know:

• How large your engineering organization is
• What version control and CI/CD tools you currently use (GitHub, GitLab, AWS, etc.)

I can help you decide between an open-source tool like Backstage versus a managed SaaS portal.