> For the complete documentation index, see [llms.txt](https://docs.scanner.dev/scanner/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.scanner.dev/scanner/using-scanner-complete-feature-reference/data-ingestion/sources/osquery.md). # Osquery Scanner supports Osquery logs, which contain information about events related to the operating system and hardware of the servers or laptops where Osquery is running. In order for Scanner to see them, you can configure Osquery to forward its logs to an AWS Kinesis Data Firehose, and then write them into an S3 bucket that Scanner is linked to. ## Step 1: Publish to S3 Follow the Osquery documentation to configure your logger to push log events to a Kinesis Data Firehose in your AWS account. See: [Logging osquery to AWS](https://osquery.readthedocs.io/en/stable/deployment/logging/). A Kinesis Data Firehose can push logs to various destinations. We want to push to an S3 bucket that Scanner is linked to. Follow the AWS documentation to configure the Firehose to write to an S3 bucket. See: [Understand data delivery in Amazon Data Firehose](https://docs.aws.amazon.com/firehose/latest/dev/basic-deliver.html). ## Step 2: Ingest via Scanner Collect Follow the [Create an Index Rule](/scanner/using-scanner-complete-feature-reference/data-ingestion/create-an-index-rule.md) guide to ingest logs from S3 via Scanner Collect. --- # 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.scanner.dev/scanner/using-scanner-complete-feature-reference/data-ingestion/sources/osquery.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.