> For the complete documentation index, see [llms.txt](https://docs.zingg.ai/zingg/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.zingg.ai/zingg/security-and-privacy/telemetry-and-usage-metrics.md). # Telemetry and Usage Metrics Zingg captures a small set of runtime metrics to help improve the product. No input data, output data, or user data is ever captured or transmitted. Zingg captures a small set of anonymous runtime metrics like execution time, Zingg version, Java version, model ID, and record count, to help the team understand how Zingg is used in real deployments and prioritise improvements. The telemetry is intentionally minimal. No field values, no record content, no personally identifiable information, and no user data leaves your environment. If you prefer not to send any telemetry at all, it can be disabled with a single config setting. {% hint style="success" icon="right-long" %} Telemetry events are sent to Zingg servers when `collectMetrics` is `true` (the default). Setting `collectMetrics` to `false` logs a blank event and prevents any data from being sent. {% endhint %} ### **What is captured**
MetricDescription
Data source typeFormat of your data source (e.g. CSV, Snowflake, Parquet)
Fields countNumber of fields configured for matching
Record countTotal number of records passing through Zingg
Execution timeDuration of the phase run
Running phaseWhich Zingg phase was executed
Matches and non-matchesCount of matched and non-matched records in the model
JDK informationJDK version and flavour
OS informationOperating system type
Zingg versionVersion of Zingg being used
No field values, record content, or personally identifiable information is included in any telemetry event. **Disabling telemetry** Set `collectMetrics` to `false` in your config: **Python API** ```python args.setCollectMetrics(False) ``` **JSON config** ```json { "collectMetrics": false } ``` When `collectMetrics` is `false`, a blank event is logged and no data is sent to Zingg servers. **Viewing what is captured** To see exactly what telemetry data is logged during a run, edit `log4j2.properties` and set the logging level of `zingg_analytics` to `warn` . ```bash logger.zingg_analytics.level=warn ``` An example telemetry event (when `collectMetrics` is `true`). ```json { "client_id": "localhost", "events": [ { "name": "match", "params": { "executionTime": "1.743246748E9", "zingg_version": "0.5.0", "modelId": "100", "domain": "localhost", "java_version": "11.0.18", "dataCount": "65.0" } } ], "user_id": "zingg" } ``` --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.zingg.ai/zingg/security-and-privacy/telemetry-and-usage-metrics.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.