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Datadog | The Monitor blog

Introducing our open source AI-native SAST Instrument and monitor Boomi integration flows with OpenTelemetry and Datadog Not all index scans are equal: How we cut query latency by over 99% Platform engineering metrics: What to measure and what to ignore Integrate Recorded Future threat intelligence with Datadog Cloud SIEM CI/CD security: threat modeling using a MITRE-style threat matrix CI/CD security: How to secure your GitHub ecosystem Ingress NGINX is EOL: A practical guide for migrating to Kubernetes Gateway API Operating agentic AI with Amazon Bedrock AgentCore and Datadog LLM Observability: Lessons from NTT DATA Introducing the Datadog Code Security MCP Capture and analyze custom heatmaps in Session Replay Understand session replays faster with AI summaries and smart chapters Monitor ClickHouse query performance with Datadog Database Monitoring How we designed empathetic alert sounds for on-call engineers Search and act across Datadog to resolve issues faster with Bits Assistant Measure the business impact of every product change with Datadog Experiments Analyzing round trip query latency Configuring JavaScript caches for better performance Introducing Bits AI Dev Agent for Code Security Datadog achieves ISO 42001 certification for responsible AI Monitor Nutanix clusters, hosts, and VMs with Datadog Monitor Juniper Mist in Datadog A new Host Map for modern infrastructure Annotate traces to improve LLM quality with Datadog LLM Observability What’s new in Cloud SIEM: AI-powered investigations, enhanced threat intelligence, and scalable security operations Explore Kubernetes with native OpenTelemetry data Monitor Oracle Fusion Cloud Applications with Datadog Announcing the Datadog Terraform provider v4.0.0 Scaling Kubernetes workloads on custom metrics How to design cloud environments for AI-powered threat analysis Monitor Aruba Central in Datadog How we centralize and remediate risks with Datadog Case Management Accelerate incident response with Datadog and ServiceNow Monitor your application and network load balancer logs Understanding Karpenter architecture for Kubernetes autoscaling Tools for collecting metrics and logs from Karpenter Monitor Karpenter with Datadog What your product data is actually saying Key metrics for monitoring Karpenter Securing Datadog’s platform in the AI age: The role of observability data Four ways engineering teams use the Datadog MCP Server to power AI agents Approaching your observability migration with the right mindset Meet the new Bits AI SRE: Deeper reasoning, twice as fast Key learnings from the 2026 State of DevSecOps study Use plain English to query your multi-cloud infrastructure in Resource Catalog Simplifying troubleshooting across the user journey with Datadog Synthetic Monitoring Protect your OCI resources with Datadog Cloud Security This Month in Datadog - 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Simplify microservice governance with the Datadog Software Catalog
2022-08-02 · via Datadog | The Monitor blog

Moving from a monolith to microservices lets you simplify code deployments, improve the reliability of your applications, and give teams autonomy to work independently in their preferred languages and tooling. But adopting a microservices architecture can bring increased complexity that leads to gaps in your team members’ knowledge about how your services work, what dependencies they have, and which teams own them.

The Datadog Software Catalog helps you consolidate knowledge of your organization’s services and streamline communication between SREs, platform engineers, application developers, and service owners. The catalog is automatically populated for APM customers and takes only seconds to import records from other Datadog telemetry data, such as logs and metrics, or from another asset inventory like ServiceNow or Backstage. Taken together, this information helps you simplify service governance and improve the discoverability and reliability of your applications.

Screenshot of the Datadog Internal Developer Portal showing the Software Catalog. The left sidebar lists navigation options like Services, Datastores, and Queues. The main panel displays a table of services, with columns for scorecards, team, on-call contact, telemetry, and schema version.

In this post, we’ll demonstrate how the Software Catalog helps you improve how you organize and communicate information about your services, manage incidents that impact services and their downstream dependencies, and confidently deploy code updates to your services.

Diagram view in the Software Catalog showing upstream and downstream components linked in a flowchart. Colored service boxes connect through arrows, while the bottom panel displays scorecard metrics and active rules.

Centralize knowledge from your distributed architecture

When domain expertise about applications is distributed across teams, it can be hard to locate the people and information you need to resolve issues. And if there’s deep knowledge of your application held by just a single tenured engineer, teams may have difficulty quickly getting the answers they need to operate and troubleshoot their services. By providing a central repository of what your organization knows about its services, the Software Catalog helps engineering teams coordinate high-stakes activities like on-call rotations and incident management, as well as the day-to-day ownership and operation of your services.

The Software Catalog provides key data—such as documentation, runbooks, deployment history, and code libraries—that can help bridge the knowledge gap between new engineers and their experienced teammates, allowing them to gain an understanding of their systems and start contributing right away. The Software Catalog also helps you plan and implement enhancements and bug fixes by making it easy for independent teams to grasp the dependencies among services without having to rely on subject matter experts, spreadsheets, or unnecessary meetings.

The Software Catalog is automatically populated to include components that are instrumented for APM or RUM. It also includes components that are discovered via Universal Service Monitoring—a lightweight, kernel-based service discovery mechanism that requires no instrumentation. You can then specify ownership details of these monitored components in a Software Catalog definition, which is a YAML manifest that is colocated with your source code.

Screenshot of the Datadog UI showing the service definition for 'email-platform.' The code editor panel highlights ownership by 'communication' and includes linked resources: a demo dashboard in Datadog and multiple runbooks in a wiki for operations and deployment management.

If you use unified service tagging, related telemetry data such as metrics and logs will also be pulled in automatically. Without adding any data manually, you’ll see the dependency map (shown in the following screenshot) plus performance data such as requests, errors, and latency. You’ll also see information about the service’s reliability, security, cloud costs, and pipeline velocity.

Datadog Software Catalog dependency view for the 'email-delivery-monitor-job' service. Left sidebar highlights upstream component 'orders-app' and downstream components 'emailer,' 'email-handler,' and 'email-mysqldefaultdb.' The main panel shows a flow diagram linking 'orders-app' through 'email-delivery-monitor-job' to downstream email services.

You don’t need any Datadog telemetry data to take advantage of the Software Catalog. The flexible Entity Model enables you to keep track of organization-specific object types like cron jobs, packages, and repositories. It also centralizes organizational knowledge about software components alongside observed systems.

Manage incidents effectively from a shared context

The Software Catalog makes it easy for engineers to see on-call contact information for other services—including PagerDuty schedules—so they can quickly communicate with the right people during a live incident. It also gives them critical and current information about services—from performance metrics, dependencies, SLOs, and underlying infrastructure to service owner contact information, documentation, and runbooks. New engineers who are on call may need to quickly learn information that hasn’t been documented, and even experienced incident responders need resources that allow them to confidently investigate and fix problems. The Software Catalog helps on-call engineers reduce incident response time by providing authoritative information—such as code repositories and relevant libraries—within their unified observability platform.

A failing dependency is sometimes the key to understanding an incident, and the Software Catalog’s dependency map makes it easy to see whether a service’s dependencies are in an alert state. You can drill down to get more information about each service—including performance metrics, error rates, and SLO status—as well as recent activity like deployments and incidents. All this information helps you fully understand the state of the services you depend on. By providing at-a-glance status and performance information about your organization’s services—as well as service owner contact information and PagerDuty on-call schedules—the dependency map brings deep context to your troubleshooting and incident management processes.

Datadog Software Catalog view for the 'web-store' service marked Critical. The left panel lists services including 'volume-shipping-job' and 'user-auth.' The right-side metadata panel shows team ownership (Shopist), operator (core-resilience), linked code repositories, documentation links, and runbooks.

Deploy reliable code more frequently and confidently

Successful teams deploy code updates frequently, fixing bugs to maximize reliability and performance and adding features to improve customer satisfaction. But even if you release service updates carefully, each deployment presents a risk to the performance and availability of that service and all the services that depend on it. The Software Catalog makes it easy to see which services call yours so you know the potential blast radius of a faulty deployment.

To help teams collaborate to ensure smooth deployments, you can add service owner contact information to each Software Catalog entry—including a link to the relevant team’s Slack channel. The Software Catalog makes it easy for team members to reach out for ad-hoc communication before or during a deployment. It also shows them performance and reliability information about services, giving all parties a single source of truth to boost collaboration and help troubleshoot any unexpected behavior.

Screenshot showing deployment details for the 'web-store' service. Left sidebar lists service monitoring sections like Endpoints, Deployments, and Dependencies. Center column displays recent activity including database changes, crash loop alerts, and deployments. Right column highlights a new 'payments-go' deployment with commit history, links to source code, on-call contacts, and performance stats.

Provide service observability to the entire organization

The Software Catalog provides information that’s critical to stakeholders throughout the organization—not just service owners. Although teams outside of engineering may not need the same information as the engineers who operate services and resolve incidents, the Software Catalog lets them independently gather key data to answer important questions.

For example, during an active incident, the Software Catalog helps you ensure that stakeholders throughout the organization—such as support teams and technical account managers—have easy access to the key information they need to manage communication. The Software Catalog can also help you coordinate game days and other reliability exercises by providing contact information for the owners of all relevant services and endpoints.

The Software Catalog brings a high-level view into your organization’s services and can be a vital tool for engineering leadership to recognize observability blindspots. By centralizing all of your service knowledge, the Software Catalog helps engineering managers spot services that aren’t instrumented for tracing or profiling, don’t generate sufficient logs, or that have been orphaned without being properly deprecated. Engineering managers can also use data from the Software Catalog to ensure standardization of reliability practices such as SLO status, deployment frequency, PagerDuty on-call coverage, correlation between logs and traces, and integration between your APM and RUM data.

Datadog Software Catalog hierarchy view for the 'Product Recommendation' system. The central node connects to components including 'Products,' 'product-recommendation,' 'Shopist User Trends,' and 'orders-app.' Each box displays metrics such as request rates and error percentages. The right-hand panel describes the system as surfacing personalized product suggestions and provides links to system and team pages.

Know more with the Software Catalog

The Software Catalog is a powerful way to collect knowledge of your services within the Datadog platform, helping you eliminate knowledge gaps even as your environment scales to comprise hundreds of services. Together with Scorecards and Self-Service Actions, the Software Catalog is a foundational piece of Datadog’s Internal Developer Portal (IDP) product. Many of its features are generally available and free to use for all Datadog customers as part of the platform. Advanced features, such as custom entities, are part of IDP and may come with additional costs. See the pricing page for details. See the Software Catalog docs to start using the Software Catalog, and if you’re not already using Datadog, you can start today with a 14-day free trial.