How to load data from Jenkins to S3 Glue

Learn how to use Airbyte to synchronize your Jenkins data into S3 Glue within minutes.

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Building in-house pipelines

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

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  • Reliable and accurate
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  • 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 S3 Glue 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 S3 Glue 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.

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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.

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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.

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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

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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.”

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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."

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How to Sync to Manually

Step 1: Install and Configure AWS CLI on Jenkins Server

To interact with AWS services from Jenkins, install the AWS Command Line Interface (CLI) on the Jenkins server. Download and install the latest version from the AWS CLI website. Configure it using `aws configure`, providing your AWS Access Key, Secret Key, region, and output format.

Step 2: Create an S3 Bucket

Log in to your AWS Management Console and navigate to the S3 service. Create a new S3 bucket that will store the data files from Jenkins. Make sure you choose a unique bucket name and configure permissions to allow access from your Jenkins server.

Step 3: Prepare Data in Jenkins

Ensure that the data you want to move from Jenkins is available in a format suitable for S3. This could be log files, build artifacts, or any other data generated by Jenkins jobs. Use Jenkins job configurations to create or gather these data files in a known directory on the Jenkins server.

Step 4: Use Jenkins Job to Upload Data to S3

Create or update a Jenkins job to include a build step that executes shell commands to upload files to S3. Use the AWS CLI `s3 cp` command to copy files from the Jenkins server to your S3 bucket. For example:
```
aws s3 cp /path/to/data s3://your-s3-bucket/path/ --recursive
```
Ensure that the Jenkins user has the necessary IAM permissions to perform this operation.

Step 5: Set Up AWS Glue Crawler

In the AWS Management Console, navigate to AWS Glue and create a new crawler. Configure the crawler to point to your S3 bucket where the data is stored. Define the IAM role that the crawler will assume, ensuring it has permissions to access the S3 bucket and create Glue resources.

Step 6: Run the AWS Glue Crawler

Execute the Glue crawler to scan the data in your S3 bucket. The crawler will automatically create a metadata table in the AWS Glue Data Catalog, reflecting the structure of your data. This table will allow you to query your data using AWS Glue and other AWS analytics services.

Step 7: Schedule Regular Data Transfers and Crawler Runs

Automate the data transfer from Jenkins to S3 by scheduling the Jenkins job to run at desired intervals. Similarly, schedule the AWS Glue crawler to run after each data transfer, ensuring the Glue Data Catalog remains up-to-date with the latest data.
By following these steps, you can efficiently move data from Jenkins to Amazon S3 and make it accessible for processing with AWS Glue, all without relying on third-party connectors or integrations.