# Metaplane Documentation

## Guides
- [Alert mentions](https://docs.metaplane.dev/docs/alert-mentions.md): You can configure alerts to mention monitor owners by associating their Metaplane users with corresponding IDs from your Notification ID.
- [Alert routing](https://docs.metaplane.dev/docs/alert-routing.md)
- [dbt node level alerting](https://docs.metaplane.dev/docs/dbt-node-level-alerting.md)
- [Metaplane CLI](https://docs.metaplane.dev/docs/metaplane-cli.md): Free CLI providing miscellaneous tools for working with data stacks.
- [Microsoft Teams](https://docs.metaplane.dev/docs/microsoft-teams.md)
- [Slack](https://docs.metaplane.dev/docs/slack.md): Slack is a messaging app for business that connects people to the information they need. By bringing people together to work as one unified team, Slack transforms the way organizations communicate.
- [Tags](https://docs.metaplane.dev/docs/tags.md): Organize data assets and prioritize incidents
- [Google Chat Cloud Function](https://docs.metaplane.dev/docs/google-chat-cloud-function.md)
- [Webhooks](https://docs.metaplane.dev/docs/webhooks.md)
- [Hex](https://docs.metaplane.dev/docs/hex.md)
- [Looker](https://docs.metaplane.dev/docs/looker.md): Looker is an enterprise platform for BI, data applications, and embedded analytics that helps you explore and share insights in real time.
- [LookML Git Integration](https://docs.metaplane.dev/docs/lookml-git-integration.md): Connect your LookML Git repositories to Metaplane to supercharge your lineage and insights.
- [Sigma](https://docs.metaplane.dev/docs/sigma.md): Sigma is the only BI analytics tool purpose-built for your cloud data warehouse. Uniquely scalable, with an experience you already know: the spreadsheet.
- [Tableau](https://docs.metaplane.dev/docs/tableau.md): Tableau is a visual analytics platform transforming the way we use data to solve problems—empowering people and organizations to make the most of their data.
- [Metaplane Chrome Extension](https://docs.metaplane.dev/docs/metaplane-chrome-extension.md)
- [Data CI/CD](https://docs.metaplane.dev/docs/data-ci-cd.md): Prevent data quality issues from ever hitting the warehouse
- [Data Test Previews](https://docs.metaplane.dev/docs/data-test-previews.md): Automated testing to ensure you don't merge breaking changes to your dbt code
- [GitHub Integration](https://docs.metaplane.dev/docs/github-integration.md): Connect Metaplane and GitHub to get powerful testing and impact previews on your pull requests
- [GitLab Integration](https://docs.metaplane.dev/docs/gitlab-integration.md): Connect Metaplane and GitLab to get powerful testing and impact previews on your merge requests
- [Data Impact Previews](https://docs.metaplane.dev/docs/impact-analysis-previews.md): See the Downstream Impact Before You Merge
- [BigQuery](https://docs.metaplane.dev/docs/bigquery.md): BigQuery is a data warehouse from Google Cloud optimized for analytics workloads. Metaplane monitors the data within your BigQuery instance so you can be the first to know if potential data bugs.
- [ClickHouse](https://docs.metaplane.dev/docs/clickhouse.md): ClickHouse is an open-source column-oriented database management system designed to handle high-volume data workloads and provide fast query performance. Metaplane monitors the data within your ClickHouse instance so you can be the first to know of potential data bugs.
- [Databricks](https://docs.metaplane.dev/docs/databricks.md): Databricks is a data lakehouse that unifies the best of data warehouses and data lakes in one simple platform to handle all your data, analytics and AI use cases. It’s built on an open and reliable data foundation that efficiently handles all data types and applies one common security and governance approach across all of your data and cloud platforms.
- [Redshift](https://docs.metaplane.dev/docs/redshift.md): Redshift is a cloud data warehouse from Amazon Web Services optimized for analytics workloads. Metaplane monitors the data within your Redshift instance so you can be the first to know if potential data bugs. Metaplane supports both Redshift and Redshift Serverless.
- [Amazon S3](https://docs.metaplane.dev/docs/s3.md): Set up monitoring of your raw files stored in AWS S3 including S3 tables using Apache Iceberg
- [SAP S/4HANA](https://docs.metaplane.dev/docs/sap-s4hana.md): Send numeric KPIs from SAP S/4HANA (via its REST/OData APIs) into Metaplane so Metaplane can model trends and alert on anomalies for custom monitors.
- [Snowflake (Native Application)](https://docs.metaplane.dev/docs/snowflake-native-application.md): Set up best-in-class monitoring on your Snowflake account without giving out any Snowflake credentials or allowing sensitive data leave the warehouse.
- [Snowflake](https://docs.metaplane.dev/docs/snowflake.md): Snowflake is a multi-cloud data cloud optimized for analytics workloads and requiring little maintenance. Metaplane monitors the data within your Snowflake instance so you can be the first to know of potential data bugs.
- [Airbyte](https://docs.metaplane.dev/docs/airbyte.md): Airbyte is a data movement platform with an expansive catalog of connectors, allowing users to seamlessly sync data between systems.
- [Segment](https://docs.metaplane.dev/docs/segment.md): Twilio Segment is a Customer Data Platform (CDP) that consolidates, unifies, and provides insights into user data across various sources. The Segment platform enables you to move customer data to and from your cloud data platforms.
- [Jira integration](https://docs.metaplane.dev/docs/jira-integration.md)
- [End-to-End Lineage](https://docs.metaplane.dev/docs/end-to-end-lineage.md)
- [Configuring monitors](https://docs.metaplane.dev/docs/configuring-monitors.md): How to schedule monitors, add manual thresholds, and filter by rolling time windows.
- [Group By monitors](https://docs.metaplane.dev/docs/group-by-monitors.md): Monitor logical groups within tables/views so you can detect subtle quality issues and quickly diagnosis root cause
- [Import Historical Observations](https://docs.metaplane.dev/docs/importing-historical-data.md)
- [Incidents](https://docs.metaplane.dev/docs/incidents.md)
- [Monitor Forecasts](https://docs.metaplane.dev/docs/monitor-forecasts.md)
- [Monitor types](https://docs.metaplane.dev/docs/monitor-types.md): Metaplane supports the following types of monitors out-of-the-box, from monitoring row counts and freshness to mean and standard deviation.
- [Monitors as Code](https://docs.metaplane.dev/docs/monitors-as-code.md)
- [New Normal Annotations](https://docs.metaplane.dev/docs/new-normal-annotations.md)
- [Providing model feedback](https://docs.metaplane.dev/docs/providing-model-feedback.md)
- [Rules](https://docs.metaplane.dev/docs/rules.md): Define criteria to automatically add monitors to specific parts of your database and schema.
- [Source-to-Target Monitors](https://docs.metaplane.dev/docs/source-to-target-monitors.md): Monitor the flow of data from a source system to a target one
- [Creating monitors](https://docs.metaplane.dev/docs/test-fundamentals.md)
- [Dashboards](https://docs.metaplane.dev/docs/dashboards.md): With dashboards, you're able to see the information most relevant to you - whether that's objects related to marketing analytics or critical outages that'd impact executive reporting.
- [Pinning schema](https://docs.metaplane.dev/docs/pinning-schema.md): Pin schemas, tables, and columns for quick access—so your most important data is always front and center.
- [Getting started](https://docs.metaplane.dev/docs/overview.md): You can add observability to your data stack in less than 10 minutes. To get started, you only have to do three things: add a source, integrate Slack, and add monitors.
- [Proactive Incident Prevention](https://docs.metaplane.dev/docs/proactive-incident-prevention.md)
- [Setting up Metaplane (Advanced)](https://docs.metaplane.dev/docs/setting-up-metaplane-advanced.md)
- [Setting up Metaplane for the first time](https://docs.metaplane.dev/docs/setting-up-metaplane-for-the-first-time.md)
- [Tips for Managing your Metaplane Account](https://docs.metaplane.dev/docs/tips-for-managing-your-metaplane-account.md)
- [Census](https://docs.metaplane.dev/docs/census.md): Census is a Data Activation and Reverse ETL platform that delivers trusted data and audiences from your data warehouse into 150+ operational tools.
- [Hightouch](https://docs.metaplane.dev/docs/hightouch.md): Hightouch syncs your data to CRM, e-mail, advertising tools and more. No engineering, manual work, or costly CDP required.
- [Model Troubleshooting Guide](https://docs.metaplane.dev/docs/model-troubleshooting-guide.md): Trying to figure out how to get better results out of the machine learning models that power your monitors? Start with the steps below.
- [Azure Synapse](https://docs.metaplane.dev/docs/azure-synapse.md)
- [MySQL](https://docs.metaplane.dev/docs/mysql.md): MySQL is an open-source relational database management system (RDBMS).
- [Airflow](https://docs.metaplane.dev/docs/airflow.md): Apache Airflow™ is an open-source platform for developing, scheduling, and monitoring batch-oriented workflows. Airflow’s extensible Python framework enables you to build workflows connecting with virtually any technology.
- [dbt Core](https://docs.metaplane.dev/docs/dbt-core.md)
- [dbt Cloud](https://docs.metaplane.dev/docs/dbt.md): dbt is a data transformation tool that enables data analysts and engineers to transform, test and document data in the cloud data warehouse.

## API Reference
- [List all](https://docs.metaplane.dev/reference/getallconnections.md): List all connections
- [Sync status](https://docs.metaplane.dev/reference/getconnectionstatus.md): Get the current sync status of a connection
- [Sync](https://docs.metaplane.dev/reference/syncconnection.md): Kicks of a task to re-sync the connection. Please note that this method returning 200 does not means the connection has finished syncing. You can poll the connection status api to determine when the sync has finished
- [Update private key](https://docs.metaplane.dev/reference/updateprivatekey.md): Updates the private key for a connection to the newly passed in value.
- [Bulk get monitors on tables](https://docs.metaplane.dev/reference/bulkgettablemonitors.md): Get all monitors on the input table paths. Limit of 200 table paths per request.
- [Create Monitor](https://docs.metaplane.dev/reference/createmonitor.md): Create a new monitor on a given absolute path like "{database}.{schema}.{table}.{column}"
- [List for connection](https://docs.metaplane.dev/reference/getallmonitorsforsource.md): List all monitors for a specific connection
- [Evaluation History](https://docs.metaplane.dev/reference/getevaluationhistory.md): Get historical evaluations of the monitor ordered by evaluation creation time descending. By default this will return pages of 500 evaluations. To page through all data, specify the `createdAt` request to get the next chunk of data. Even though this is a post request, no data is mutated.
- [Get monitor](https://docs.metaplane.dev/reference/getmonitor.md): Fetch an existing monitor
- [Get for database entity](https://docs.metaplane.dev/reference/getmonitors.md): Get all monitors targeting a specific absolute path like "{database}.{schema}.{table}.{column}"
- [Status (deprecated)](https://docs.metaplane.dev/reference/getmonitorstatus.md): Get the latest status of a monitor. Will return a 404 if the monitor has not yet been run and modeled
- [Status](https://docs.metaplane.dev/reference/getmonitorstatus2.md): Get the latest status of a monitor. Will return a 404 if the monitor has not yet been run and modeled
- [Import Historic Data](https://docs.metaplane.dev/reference/importhistoricdataformonitor.md): Import historic data for the monitor. Full documentation at https://docs.metaplane.dev/docs/importing-historical-data#limitations. Setting `isPreview` to  true will validate the import without actually inserting data.
- [Ingest Datapoint](https://docs.metaplane.dev/reference/ingestdatapoint.md): Sends a datapoint to add to the target monitorId with the current timestamp and then modeled. In private Beta, reach out for access.
- [Run](https://docs.metaplane.dev/reference/runmonitors.md): Enqueue a list of existing monitors to be immediately run. Note that a success here just means that we have enqueued the monitors to be run, not that they have finished running
- [Update monitor](https://docs.metaplane.dev/reference/updatemonitor.md): Update an existing monitor. Omitted update fields will not be change in the underlying monitor
- [Batch fetch tag definitions](https://docs.metaplane.dev/reference/fetchtagdefinitions.md): Fetch the Metaplane definition for the given tag name. POST is just for a more expressive request body, no mutation occurs
- [Fetch monitors for a tag](https://docs.metaplane.dev/reference/fetchtaggedmonitors.md): Fetch all monitors associated with a tag
- [Fetch all objects for tag](https://docs.metaplane.dev/reference/fetchtaggedobjects.md): Fetches all objects that have the target tag. This response is paginated
- [Remove monitor tags](https://docs.metaplane.dev/reference/removemonitortags.md): Removes specified tags from a monitor
- [Remove table tags](https://docs.metaplane.dev/reference/removetabletags.md): Remove specified tags from the table at "{database}.{schema}.{table}"
- [Batch tag monitors](https://docs.metaplane.dev/reference/tagmonitors.md): Apply a tag to a collection of monitors
- [Batch tag tables](https://docs.metaplane.dev/reference/tagtables.md): Apply a tag to a collection of tables identified by absolute paths like "{database}.{schema}.{table}"