How to load data from K6 Cloud to Convex

Learn how to use Airbyte to synchronize your K6 Cloud data into Convex within minutes.

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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.
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Airbyte connections are:
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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 K6 Cloud 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 K6 Cloud 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 K6 Cloud 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.
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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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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.

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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.

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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.

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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.

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Tech Lead at Symend

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How to Sync to Manually

Step 1: Understand Your Data Structure in k6 Cloud

Begin by thoroughly understanding the data structure you have in k6 Cloud. Identify the key metrics and data points that you need to export. This could include test results, performance metrics, or any other data relevant to your needs. Knowing the structure will help in efficiently extracting and transferring the data.

Use k6 Cloud's API to export the desired data. You can access the API by authenticating with your k6 Cloud credentials and using the appropriate endpoints to fetch the data. For example, use the `GET /v1/runs/{run_id}` endpoint to retrieve test run data. Ensure you handle pagination if the data is large.

Once you have the raw data, transform it into a format that can be easily imported into Convex. Typically, JSON or CSV formats are good choices due to their compatibility and simplicity. Write a script or use tools like jq or Python to convert and clean the data as necessary.

Set up a new database in Convex where you'll import the data. Define the schema based on the transformed data structure, ensuring that all necessary fields are included. If Convex allows, create necessary collections or tables that will hold the imported data.

Write a script to import the transformed data into Convex. This script will interact with Convex's API to insert records into your database. Make sure to handle authentication and error checking to ensure data is imported correctly. Use Convex's REST API or any other supported method for data insertion.

After importing the data, verify its integrity and completeness in Convex. Cross-check a sample of records against the original data in k6 Cloud to ensure accuracy. This step is crucial to confirm that the data transfer was successful and that no corruption occurred during the process.

If you need to regularly move data from k6 Cloud to Convex, consider automating the process. Use cron jobs or a similar scheduling system to periodically run your export and import scripts. This will save time and reduce the risk of human error in manual data transfers.

By following these steps, you can effectively move your data from k6 Cloud to Convex without relying on third-party connectors or integrations.