Port's integration catalog: 200+ tools to power your context lake

Engineering teams run dozens of tools that all depend on each other - CI/CD talks to Kubernetes, incident management connects to your APM, Git repos feed security scanners. Each tool holds valuable data that matters, but it stays locked inside that tool, so together they turn into silos.

That means understanding a single incident has an engineer jumping across tools by hand: checking a deployment in one place, service health in another, the incident timeline somewhere else - because data from one tool isn’t correlated with the others.. Teams end up writing custom scripts and webhooks just to connect what should already be connected.

Port's Context Lake solves this. It unifies data from your entire engineering ecosystem into a single, queryable knowledge layer that powers AI agents and human developers alike.

Port offers more than 200 integrations for common tools across the SDLC. And you can also add integrations using our Ocean framework, data connectors, APIs, events, and MCPs.

This article maps key integrations by category so you can find what Port supports and what becomes possible when you connect them.

Git

GitHub, GitLab, Bitbucket, and Azure DevOps integrations pull code ownership and recent commits into service blueprints (Port's schema that defines service properties and relationships), so code activity becomes part of service context.

Use cases:

• Link code ownership to services so you know who to contact when a service has issues
• Surface recent commits and deployments alongside service health data
• Track PR activity and code review cycles as part of service health dashboards

Kubernetes 

Kubernetes integrations bring live cluster state, deployment status, service mesh topology, policy violations, and container vulnerabilities directly into service blueprints.

Use cases:

• Query live rollout status and replica counts without checking kubectl
• Detect policy violations before they reach production using Kyverno data
• Map service mesh topology and cross-namespace traffic patterns with Istio
• Track container vulnerabilities and remediation status with Trivy

CI/CD 

Port offers OOTB integrations with common tools, including Jenkins, GitHub Actions, GitLab Pipelines, Azure Pipelines, CircleCI, Codefresh, and Google Cloud Build. These connect build statuses, test results, and deployment cadences to the services they deploy.

Use cases:

• See which services have failing builds and drill into the logs without leaving Port
• Track deployment frequency and lead time for changes as part of DORA metrics
• Link CI failures to related services and incidents for faster root cause analysis
• Block deployments based on build status, test coverage, or security scan results

Incident Management

PagerDuty, OpsGenie, FireHydrant, Rootly, and ServiceNow integrations link incident history, MTTR metrics, and on-call assignments to services so you understand patterns and resilience.

Use cases:

• Show incident history and MTTR metrics as part of each service's context
• Query which services had critical incidents this quarter and what resolved them
• Surface on-call rotations so developers know who to page when they break something
• Correlate incident patterns with code changes and deployments to spot systemic issues

APM and Alerting 

Datadog, New Relic, Dynatrace, Prometheus, and Sentry integrations surface performance metrics, alerts, and health status directly into service blueprints so troubleshooting becomes a single query of the context lake.

Use cases:

• Display real-time memory, CPU, and latency metrics in service entities
• Surface active alerts so developers know what's wrong before they ask
• Correlate error spikes with recent deployments to speed troubleshooting
• Enforce SLO targets as part of service standards and send alerts when violated

Security and Compliance 

Snyk, Wiz, and Aikido integrations aggregate vulnerabilities, SAST findings, and compliance data into service context so you block risky deployments automatically.

Use cases:

• Block deployments of services with critical CVEs
• Surface open vulnerabilities and remediation status on each service
• Track compliance posture changes and flag non-compliant services
• Correlate vulnerabilities with deployment history to understand risk over time

Code Quality and Application Security 

SonarQube, Checkmarx, and StackHawk integrations ingest code scanning results, test coverage, and linting reports so code health appears alongside service health.

Use cases:

• Track code coverage trends and alert when coverage drops
• Surface SAST findings before code reaches production
• Enforce minimum code quality standards as part of deployment gates
• Correlate code quality metrics with incident frequency

Cloud Providers 

AWS, Azure, and GCP integrations map cloud resources, costs, and capacity to services so resource planning becomes service-centric.

Use cases:

• Show which EC2 instances, RDS databases, and load balancers belong to each service
• Track cloud resource costs by service and enforce budget limits
• Detect over-provisioned resources and recommend downsizing
• Map infrastructure to services for faster incident response

Infrastructure as Code 

Terraform, Terraform Cloud, and Pulumi integrations sync IaC state with services and detect drift so infrastructure configuration adheres to policies and code control.

Use cases:

• Detect when infrastructure was manually edited and alert teams to reconcile
• Show which resources are defined in code vs. manually provisioned
• Track workspace and module versions tied to each service
• Enforce IaC standards by blocking deployments of services with drift

Ticketing and Messaging 

Jira, Linear, Slack, and incident.io integrations surface open bugs, feature requests, and team discussions alongside service metadata in one place.

Use cases:

• Display open bugs and feature requests tied to each service
• Surface recent Slack discussions about a service without context-switching
• Link work items to deployments and incidents for full context
• Alert teams when security tickets are opened against their services

SSO and Identity 

Okta, OneLogin, Azure AD, Google Workspace, and JumpCloud integrations sync team membership and access controls automatically so permissions stay current.

Use cases:

• Automatically sync team membership from your directory to service ownership
• Enforce role-based access control on services based on directory groups
• Surface team contact info and on-call schedules from directory data
• Update permissions automatically when someone joins or leaves a team

Feature Management 

LaunchDarkly and Split integrations track feature flag status by service so you correlate rollouts with performance and block incomplete deployments.

Use cases:

• Display which features are rolled out to which services and user segments
• Query rollout status across your fleet without checking multiple dashboards
• Correlate feature rollouts with performance changes and incidents
• Block deployments if a service has unresolved feature flags

Cost Management 

KubeCost and OpenCost integrations import cloud spending data and correlate costs to services so teams own their cloud spend.

Use cases:

• Show cost per service and alert when costs spike unexpectedly
• Identify services running in multiple regions and consolidate if needed
• Enforce budget limits as part of provisioning workflows
• Surface cost attribution data by team / service / LOB

API Management 

Swagger and AsyncAPI integrations manage API specifications and track breaking changes so dependent services know when contracts shift.

Use cases:

• Display API contracts alongside service definitions
• Alert dependent services when an API introduces a breaking change
• Surface API versioning and deprecation dates
• Track API usage and performance metrics

AI Agents

Claude AI, OpenAI, Cursor, n8n, and GitHub Copilot integrations monitor AI tool usage, costs, and performance so teams understand AI adoption impact.

Use cases:

• Track AI agent usage and cost allocation across teams
• Monitor inference latency and cost by model and prompts to optimize efficiencies
• Surface which services are using AI capabilities and for what
• Alert when AI costs spike or error rates increase

Developer Portals 

Backstage and other portal integrations bridge Port's Context Lake to your existing developer portal so teams access unified context in their familiar tools and can easily extend their software catalog via the context lake for agentic SDLC work.

Use cases:

• Surface Port data inside your existing developer portal
• Sync service metadata between Port and your portal
• Unify developer experience across tools
• Build agentic use cases on top of your existing software catalog data

Custom Integrations

Port Ocean connects any REST API or HTTP service - internal tools, proprietary systems, legacy platforms - into the Context Lake without custom coding.

Use cases:

• Push data from internal billing systems into Port every hour
• Sync custom metadata from your internal tools
• Stream events from any system that supports webhooks
• Build custom connectors for tools Port doesn't natively support

How These Integrations Work Together

Engineering teams see value when everything is connected in one place: a single service entity in Port pulls data from Git (code ownership, recent commits, deployments), CI/CD (build status, test results, pipeline state, deployment frequency), Kubernetes (live workload state, resource utilization), APM (performance metrics, error rates, latency), Incident Management (recent incidents, MTTR, on-call assignments), Security (vulnerabilities, compliance status, policy violations), Ticketing (bugs, feature requests, security tickets), and Cost controls (spend, resource allocation, budget status).

Because all of this lives in one place, you can, for example, gate deployments on any of it or correlate signals with recent deployments and incidents to find root cause, not just symptoms.

When an engineer asks "what's wrong with this service?", both on-call engineers or an SDLC  agent can query the Context Lake once and return the complete picture so nobody’s switching between tools or having to piece together information through multiple queries or manual efforts. One query surfaces who owns the service, what changed recently, what's currently broken, who's on call, and what similar incidents happened before.

For example, our customer GitHub does exactly this. Their engineering org runs one query to get a full picture across roughly 1,300 engineers and hundreds of applications and SLOs in a multi-cloud setup. The same data is then shaped per role: an engineering manager sees their team's services, a VP sees the whole org.Building on top of a  unified context

The power of these integrations multiplies when you leverage them with Port's agentic capabilities. Your AI agents don't just have access to raw tools. They have a complete, interconnected knowledge base.

Platform teams use agents to query the full stack, onboard new services, enforce standards, and detect configuration drift without involving operators. Developers see services with real-time health, ownership, dependencies, recent changes, and open issues. Troubleshooting shifts from "check five dashboards" to "ask Port." Security teams get proactive alerts when agents surface vulnerabilities, non-compliance, or risky configurations tied to the teams and services affected. SREs gain incident response context instantly: what changed, who owns it, what similar incidents happened before, and what resolved them.

Getting Started

Start small. Connect your top three tools and watch how unified context changes how your team works. Then expand. Each additional integration makes the existing data more valuable - the same question returns a fuller answer, until querying the Context Lake eliminates the need to go into any single point-tool. 

VisitPort's integrations page to explore all 200+ supported tools and set up the ones that matter to your team.