Data Overview

CircleCI exposes data across your entire CI/CD pipeline — from high-level project and pipeline records down to individual job runs and branch-level performance insights. Here's what you can access through Coupler.io.

Available entities

Entity	What it contains
Pipelines	Trigger source, status, creation time, VCS metadata
Workflows	Workflow name, status, duration, pipeline association
Jobs	Job name, number, status, start/stop times, executor type
Workflow jobs	Jobs scoped to a specific workflow run
Insights metrics	Success rate, throughput, mean duration, p95 duration
Insights branches	Per-branch pipeline metrics and failure counts
Projects	Project name, slug, VCS type, organization
Specific projects	Extended project details for a targeted project ID
Contexts	Context name, created date, environment variable keys
Self IDs	Authenticated user ID and external identifiers
Self collaborations	Orgs and projects the user collaborates on
Mes	User profile, login, analytics tracking ID

Metrics and dimensions

Pipeline metrics

Field	Type	Description
id	String	Unique pipeline identifier
state	String	Pipeline state (created, errored, etc.)
number	Integer	Sequential pipeline number
created_at	Timestamp	When the pipeline was triggered
trigger_type	String	What triggered the pipeline (push, API, schedule)
vcs_branch	String	Branch that triggered the pipeline
vcs_revision	String	Commit SHA

Workflow metrics

Field	Type	Description
id	String	Unique workflow identifier
name	String	Workflow name
status	String	Status (success, failed, running, on_hold)
created_at	Timestamp	Workflow start time
stopped_at	Timestamp	Workflow end time
pipeline_id	String	Parent pipeline ID
project_slug	String	Associated project

Job metrics

Field	Type	Description
job_number	Integer	Job number within the project
name	String	Job name
status	String	Job status (success, failed, canceled)
started_at	Timestamp	Job start time
stopped_at	Timestamp	Job completion time
executor_type	String	Executor (docker, machine, macos)
dependencies	Array	Upstream job dependencies

Insights metrics

Field	Type	Description
success_rate	Float	Percentage of successful pipeline runs
throughput	Float	Average number of runs per day
mean_duration_sec	Integer	Average run duration in seconds
median_duration_sec	Integer	Median run duration
p95_duration_sec	Integer	95th percentile duration
total_runs	Integer	Total number of runs in the period
failed_runs	Integer	Count of failed runs

Insights branches

Field	Type	Description
branch	String	Branch name
success_rate	Float	Success rate for this branch
total_runs	Integer	Total pipeline runs on this branch
mean_duration_sec	Integer	Average duration for this branch

Common metric combinations

• Workflow + Jobs — join on workflow_id to see which jobs are dragging down workflow duration

• Pipelines + Insights metrics — combine to correlate pipeline volume with success rate trends

• Insights branches + Projects — spot which branches and projects are failing most often

• Jobs + Workflows — use Aggregate to calculate average job duration grouped by workflow name

Use cases by role

Engineering managers

• Track deployment frequency and change failure rate across teams

• Monitor pipeline success rates over time to measure CI/CD stability

• Compare workflow duration trends before and after infrastructure changes

• Use Insights metrics to build a DORA-style dashboard in Looker Studio or BigQuery

DevOps / Platform teams

Development teams

Platform-specific notes

• Project ID vs. project slug — some entities require a project_id (UUID from project settings), while others use a project_slug (e.g., gh/myorg/myrepo). Check the entity's parameter field carefully.

• Workflow IDs — you can supply multiple workflow IDs (one per line) to pull data for several workflows in the same data flow source.

• Job number auto-fetch — if you don't specify a job number, Coupler.io will auto-fetch it from Workflow jobs, so you only need to set this manually for specific targeted pulls.

• Start date filtering — the start date applies to pipeline-based entities. Insights entities have their own aggregation window on the CircleCI side.

• Rate limits — CircleCI's API is rate-limited; very large orgs with many pipelines may see slower syncs on first historical load.