Cortex Documentation

website·Indexed 38 days ago

https://docs.cortex.io

Cortex is an EngOps Platform designed to accelerate engineering excellence. It provides a software catalog for managing entities such as services, domains, and teams, along with features for data modeling, scorecards, workflows, and engineering intelligence. The platform includes AI capabilities via Cortex AI Chat and the Cortex MCP (Model Context Protocol) server to bring engineering data into AI tools.

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What's inside Cortex

Overview of Cortex MCP
Cortex MCP is a Model Context Protocol server designed to integrate engineering data into existing developer tools. It allows users to perform natural language queries across the Cortex catalog, Scorecards, metrics, and Initiatives, providing grounded, AI-assisted insights and recommendations based on the organization's actual workspace structure. It supports complex, multi-part queries and includes a query_docs tool for querying Cortex's own documentation and knowledge base.
https://docs.cortex.io/llms-full.txt?llms-doc=cortex-mcpwebsitellms
Overview of Google Cloud Platform integration for Cortex
The GCP integration allows Cortex to automatically discover GCP entities (such as Cloud Run services, BigQuery datasets, and GKE clusters) and add them to the service catalog. It enables linking entities to dependent services, pulling Service Level Objectives (SLOs) from Google Cloud Observability, and powering Scorecards and CQL queries based on GCP configuration and ownership. The integration uses a read-only service account and does not make changes to cloud resources.
https://docs.cortex.io/llms-full.txt?llms-doc=google-cloud-platformwebsitellms
Overview of Team entities in Cortex
Teams are a default entity type in Cortex used to bridge organizational structure with the software catalog. They serve as the foundation for ownership; instead of assigning entities to individuals, ownership is assigned to a team. This ensures that when team composition changes, ownership remains accurate. Team entities include details such as Scorecard performance tracking, on-call information, Slack channels, and parent-child hierarchies to model organizational structures from squads to departments.
https://docs.cortex.io/llms-full.txt?llms-doc=adding-teamswebsitellms
Overview of Cortex On-call Assistant
The On-call Assistant leverages the PagerDuty integration to automatically surface vital information about entity health and metadata when an incident is triggered. It notifies responsible users via Slack with details on the affected entity, recent deployments, ownership, and links to dependencies, runbooks, and logs to help reduce MTTR.
Constraint: On-call Assistant only works for service-level PagerDuty registrations.
https://docs.cortex.io/llms-full.txt?llms-doc=using-on-call-assistant-for-incident-notificationswebsitellms
Overview of Cortex AI Chat
Cortex AI is an AI-powered chat assistant that answers plain-language questions about engineering data. It uses the same data that powers Scorecards, dashboards, and reports to provide grounded answers. It is currently in Research Preview, meaning responses may be slow, not all data is reachable, and it cannot perform write actions (e.g., it cannot create or edit Scorecards, Initiatives, Dashboards, or Workflows).
https://docs.cortex.io/llms-full.txt?llms-doc=cortex-ai-chatwebsitellms
Overview of Bitbucket integration with Cortex
Integrating Bitbucket with Cortex allows organizations to discover and track ownership of Bitbucket entities, view repository data on entity pages, implement GitOps workflows, track pull request information on the engineering homepage, and use Bitbucket metrics within Eng Intelligence and Scorecards to drive project alignment.
https://docs.cortex.io/llms-full.txt?llms-doc=bitbucketwebsitellms
Overview of Grouping Entities in Cortex
Groups are free-form, non-hierarchical tags used to slice the Cortex catalog. They allow developers to categorize entities by dimensions such as priority (e.g., tier-0), tech stack (e.g., python), or architectural role (e.g., backend). Groups are additive, meaning an entity can belong to multiple groups. They are primarily used to filter Scorecards, catalogs, and CQL reports, or to aggregate production readiness scores by specific categories.
https://docs.cortex.io/llms-full.txt?llms-doc=grouping-entitieswebsitellms
Overview of the Cortex Kubernetes integration
The Cortex Kubernetes (K8s) agent is a lightweight tool that collects information from your cluster to surface it in the Cortex workspace. It allows users to discover and import entities directly from clusters to keep the catalog in sync, view infrastructure data on entity pages, and create Scorecards to enforce Kubernetes best practices.
The agent supports the following Kubernetes workload types:
- Deployments
- StatefulSets
- Argo Rollouts
- CronJobs
https://docs.cortex.io/llms-full.txt?llms-doc=kuberneteswebsitellms
Overview of Service entities in Cortex
Services are a default entity type in Cortex used to represent codebase-like modules such as microservices, libraries, and components. Every service is defined by a cortex.yaml file which declares its identity, ownership, dependencies, and links to supporting tools (CI/CD, observability, on-call, documentation). Once defined, services are enriched with live data from integrations to provide a centralized view of ownership, dependencies, and operational maturity.
https://docs.cortex.io/llms-full.txt?llms-doc=adding-serviceswebsitellms
Overview of Cortex EngOps Platform
Cortex is an EngOps platform designed to coordinate engineering organizations by reducing friction and incidents. It provides a foundation for engineering excellence through four primary pillars:
- Security: Continuous compliance checks, vulnerability remediation via Initiatives, and standardized CI/CD processes.
- Reliability: Production-readiness automation via Scorecards, DORA metric tracking, and incident response Workflows.
- Velocity: Automated 'golden paths' for service bootstrapping, velocity/DORA dashboards, and task automation via Workflows.
- Efficiency: Visibility into orphaned services and stale dependencies, and the use of Initiatives to align teams on migrations.
https://docs.cortex.io/llms-full.txt?llms-doc=cortex-documentationwebsitellms
Overview of the Cortex Terraform Provider
The Cortex Terraform Provider allows developers to manage and provision Cortex resources—such as Scorecards, integrations, and entities—using an infrastructure-as-code approach. It serves as a wrapper around the public Cortex API.
https://docs.cortex.io/llms-full.txt?llms-doc=manage-entities-using-cortex-terraform-providerwebsitellms
Overview of Anthropic integration in Cortex
The Anthropic integration brings Claude Code usage data into Cortex to measure AI adoption and impact across an organization. Cortex supports two distinct Anthropic product types, each requiring a specific credential type. Each Cortex configuration connects to one Anthropic organization; multiple organizations require separate configurations with unique aliases.
https://docs.cortex.io/llms-full.txt?llms-doc=anthropicwebsitellms