How to load data from Jenkins to Convex

Learn how to use Airbyte to synchronize your Jenkins data into Convex within minutes.

Building your pipeline or Using Airbyte

Airbyte is the only open source solution empowering data teams  to meet all their growing custom business demands in the new AI era.

Building in-house pipelines

Bespoke pipelines are:
  • Inconsistent and inaccurate data
  • Laborious and expensive
  • Brittle and inflexible
Furthermore, you will need to build and maintain Y x Z pipelines with Y sources and Z destinations to cover all your needs.

After Airbyte

Airbyte connections are:
  • Reliable and accurate
  • Extensible and scalable for all your needs
  • Deployed and governed your way
All your pipelines in minutes, however custom they are, thanks to Airbyte’s connector marketplace and AI Connector Builder.

Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a Jenkins connector in Airbyte

Connect to or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up Convex for your extracted Jenkins data

Select where you want to import data from your source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the Jenkins to Convex in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.

Take a virtual tour

Check out our interactive demo and our how-to videos to learn how you can sync data from any source to any destination.

Demo video of Airbyte Cloud

Demo video of AI Connector Builder

Setup Complexities simplified!

You don’t need to put hours into figuring out how to use Airbyte to achieve your Data Engineering goals.

Simple & Easy to use Interface

Airbyte is built to get out of your way. Our clean, modern interface walks you through setup, so you can go from zero to sync in minutes—without deep technical expertise.

Guided Tour: Assisting you in building connections

Whether you’re setting up your first connection or managing complex syncs, Airbyte’s UI and documentation help you move with confidence. No guesswork. Just clarity.

Airbyte AI Assistant that will act as your sidekick in building your data pipelines in Minutes

Airbyte’s built-in assistant helps you choose sources, set destinations, and configure syncs quickly. It’s like having a data engineer on call—without the overhead.

What sets Airbyte Apart

Modern GenAI Workflows

Streamline AI workflows with Airbyte: load unstructured data into vector stores like Pinecone, Weaviate, and Milvus. Supports RAG transformations with LangChain chunking and embeddings from OpenAI, Cohere, etc., all in one operation.

Move Large Volumes, Fast

Quickly get up and running with a 5-minute setup that enables both incremental and full refreshes for databases of any size, seamlessly scaling to handle large data volumes. Our optimized architecture overcomes performance bottlenecks, ensuring efficient data synchronization even as your datasets grow from gigabytes to petabytes.

An Extensible Open-Source Standard

More than 1,000 developers contribute to Airbyte’s connectors, different interfaces (UI, API, Terraform Provider, Python Library), and integrations with the rest of the stack. Airbyte’s AI Connector Builder lets you edit or add new connectors in minutes.

Full Control & Security

Airbyte secures your data with cloud-hosted, self-hosted or hybrid deployment options. Single Sign-On (SSO) and Role-Based Access Control (RBAC) ensure only authorized users have access with the right permissions. Airbyte acts as a HIPAA conduit and supports compliance with CCPA, GDPR, and SOC2.

Fully Featured & Integrated

Airbyte automates schema evolution for seamless data flow, and utilizes efficient Change Data Capture (CDC) for real-time updates. Select only the columns you need, and leverage our dbt integration for powerful data transformations.

Enterprise Support with SLAs

Airbyte Self-Managed Enterprise comes with dedicated support and guaranteed service level agreements (SLAs), ensuring that your data movement infrastructure remains reliable and performant, and expert assistance is available when needed.

What our users say

Raman Singh

Tech Lead at Symend

Predictable, straightforward pricing model that simplified budgeting and significantly reduced overall spend

Learn more
Chase Zieman headshot

Chase Zieman

Chief Data Officer

“Airbyte helped us accelerate our progress by years, compared to our competitors. We don’t need to worry about connectors and focus on creating value for our users instead of building infrastructure. That’s priceless. The time and energy saved allows us to disrupt and grow faster.”

Learn more

Rupak Patel

Operational Intelligence Manager

"With Airbyte, we could just push a few buttons, allow API access, and bring all the data into Google BigQuery. By blending all the different marketing data sources, we can gain valuable insights."

Learn more

How to Sync to Manually

Step 1: Set Up Jenkins Job for Data Export

Begin by creating or configuring a Jenkins job that will export the data you wish to move. This involves setting up the job to run a script or command that extracts the relevant data from the Jenkins environment. For example, if the data is in a Jenkins build log, you might configure the job to copy the log to a local file system or output it in a specific format, such as JSON or CSV.

Step 2: Format Data for Transfer

Once the data is exported, ensure it is formatted correctly for easy parsing and insertion into Convex. This might involve converting the data into JSON, which is a commonly supported format for many databases and data platforms. Ensure the data structure aligns with the schema or expected format in Convex.

Step 3: Install Necessary Tools on Jenkins Server

Ensure that the Jenkins server has the necessary tools to facilitate data transfer. This could include command-line tools like curl or wget, which can be used to send HTTP requests. If using a script, make sure that the programming language's runtime (such as Python or Node.js) is installed and configured.

Step 4: Write a Script for Data Transfer

Develop a script that will handle the data transfer from Jenkins to Convex. This script should include logic to read the exported data, format it if necessary, and send it to Convex using HTTP requests. Ensure it handles authentication, if required, and includes error handling to manage any issues during the transfer.

Step 5: Securely Store and Use Credentials

If Convex requires authentication, store any necessary credentials securely. Avoid hardcoding them directly into scripts. Instead, use Jenkins’ credential management system to store sensitive information and access it programmatically within your script. This ensures security and ease of management.

Step 6: Automate the Data Transfer Process

Incorporate the data transfer script into the Jenkins job as a post-build action or as a part of a pipeline. This ensures that every time the Jenkins job runs, the data is automatically exported and transferred to Convex. Test this setup thoroughly to ensure reliability and that no data is lost during the process.

Step 7: Monitor and Log Data Transfers

Implement logging within your data transfer script and set up Jenkins to capture these logs. This will help in monitoring the success or failure of data transfers. You can use Jenkins’ built-in logging features to view logs and set up alerts for any failures. This step is crucial for ensuring data integrity and troubleshooting any issues that arise.