Codefresh

Codefresh is a CI/CD platform built for Kubernetes and container-based workflows. It helps engineering teams build, test, and deploy software with pipelines, Helm charts, and runtime agents. Connecting Codefresh to Coupler.io lets you pull your pipeline runs, build records, audit logs, and analytics into any destination for reporting and analysis.

Why connect Codefresh to Coupler.io?

• Track build success rates, failure trends, and pipeline performance over time

• Centralize audit logs alongside data from other tools for compliance reporting

• Send CI/CD metrics to Google Sheets, BigQuery, or AI tools like ChatGPT or Gemini for deeper analysis

• Combine Codefresh data with project management sources using Join or Append transformations

Prerequisites

• A Codefresh account with access to the data you want to export

• A Codefresh API key (generated from your Codefresh user settings)

Quick start

Start with the Builds entity — it's the most actionable dataset for tracking pipeline health and catching failure patterns early.

How to connect

1

Create a new data flow in Coupler.io. From your Coupler.io dashboard, click Add data flow and search for Codefresh as your source.

2

Enter your Codefresh API key. In Codefresh, go to User Settings → API Keys and generate a new key. Copy it and paste it into the API key field in Coupler.io.

3

Select the entity you want to import. Choose from Builds, Pipelines, Audit logs, Analytics reports, or any of the other available entities. You can add more sources to the same data flow later.

4

Set your start date and report parameters. Use the date picker to set the earliest date for your data export. If you're pulling Analytics reports, also set the report granularity (daily, weekly, or monthly) and the report date range.

5

Choose a destination. Select where your data should land — Google Sheets, Excel, BigQuery, Looker Studio, or an AI destination like Claude, ChatGPT, or Gemini.

6

Run the data flow. Click Run to execute a manual sync and confirm data is arriving correctly.

Available entities

Entity	Description
Accounts	User accounts and account information
Account settings	Configuration settings and preferences
Agents	Runtime agents that execute pipelines
Builds	Build execution records with status and metadata
Audits	Audit logs of user actions and system events
Analytics metadata	Metadata definitions for analytics reports
Analytics reports	Generated reports with pipeline and build metrics
Execution contexts	Runtime environments for pipeline executions
Contexts	Shared variables and configuration contexts
Projects	Project definitions organizing pipelines
Pipelines	CI/CD pipeline definitions and configurations
Step types	Custom step type definitions used in pipelines
Helm repos	Helm chart repositories configured in Codefresh