> For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://mezmo.ferndocs.com/about-mezmo-telemetry-pipelines/llms.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://mezmo.ferndocs.com/_mcp/server. # About Mezmo Telemetry Pipelines Mezmo Telemetry Pipeline enables organizations to take a new approach towards managing telemetry data. * Incorporate data from your existing Log Analysis environment, or from entirely new data streams like [AWS Kinesis Firehose](https://docs.mezmo.com/2.8/telemetry-pipelines/kinesis-firehose-source), and the [Mezmo Agent](https://docs.mezmo.com/2.8/telemetry-pipelines/mezmo-agent-source) to capture a diverse range of telemetry data, with new sources being added regularly * You can use Processors to [encrypt](https://docs.mezmo.com/2.8/telemetry-pipelines/encrypt-fields-processor), [filter](https://docs.mezmo.com/2.8/telemetry-pipelines/filter-processor), [route](https://docs.mezmo.com/2.8/telemetry-pipelines/route-processor), and automate other transformations of your data to make sure that it is tailored to your specific needs for storage and analysis * Send your processed data to destinations like [AWS S3 Storage](https://docs.mezmo.com/2.8/telemetry-pipelines/s3-destination), [ElasticSearch](https://docs.mezmo.com/2.8/telemetry-pipelines/elasticsearch-destination), and [Mezmo Log Analysis](https://docs.mezmo.com/2.8/telemetry-pipelines/mezmo-destination) so you always know that you will have the data you need in the right place at the right time * Use [Pipeline Taps](https://docs.mezmo.com/2.8/telemetry-pipelines/monitor-data-pipelines) to monitor the flow of data in your Pipeline, and [sample Pipeline data in real-time](https://docs.mezmo.com/2.8/telemetry-pipelines/view-pipeline-data) to use in constructing new Pipelines ## Video Overview