Begin by ensuring you have both Tempo and Redis installed and running in your environment. Tempo is typically used for tracing data, while Redis is a fast, in-memory key-value store. You need access to the machine or network where these services are hosted.

Get familiar with the structure of the data stored in Tempo. Typically, Tempo stores trace data in a standard format such as Jaeger or OpenTelemetry. Understand how this data is organized, including key identifiers and metadata, which will help you in mapping this data to Redis.

Use the Tempo API to export the data you need. Tempo provides APIs to query and retrieve trace data. Craft a script or use command-line tools like `curl` to fetch the data programmatically. You might need to filter or paginate through the data if you have a large dataset.

Once you have exported the data, parse it into a format suitable for Redis. This may involve converting JSON structures from Tempo into key-value pairs. Use a programming language like Python or Node.js to write a script that can process and transform this data efficiently.

Set up your Redis database to receive the data. This might include configuring Redis with the appropriate memory settings and ensuring your data model aligns with Redis’s capabilities. Decide on the key structure you will use in Redis to store the trace data.

Use a Redis client library in your chosen programming language to insert the data into Redis. This involves writing a script that connects to your Redis instance and uses commands like `SET` or `HSET` to store the data. Ensure you handle connections and potential errors gracefully.

After moving the data to Redis, verify its integrity. This involves checking that all expected keys and values are correctly stored and match the original data from Tempo. You can write tests or use Redis commands to sample data and compare against your original export.