Dogmover

Dogmover

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⚠️ Dogmover has been deprecated in favor of the Datadog Sync CLI Tool ⚠️

https://github.com/DataDog/datadog-sync-cli

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This tool is built to help migrate Datadog dashboards, monitors, users, synthetic api tests, synthetic browser tests, aws accounts, log pipelines, notebooks, and slos from one Datadog organization (eg. in US) to another (eg. in EU). The tool also supports moving these resources within the same instances (eg. EU to EU or US to US).

Note: It does not move any historical data (eg., metrics, log messages, synthetic test results) as this is not supported due to security reasons.

Install

1. Clone this repository.
2. Install all python dependencies: pip install -r requirements.txt --upgrade
3. Add your api_key, app_key to config.json for both the source (the organization where you will pull the resources from) and the destination (to where you will be pushing the resources to). See config.json.example.

Usage

To pull (export) dashboards, run:

./dogmover.py pull dashboards --dry-run

To push (import) dashboards, run:

./dogmover.py push dashboards --dry-run

The arguments supported are:

./dogmover.py pull|push dashboards|monitors|users|synthetics_api_tests|synthetics_browser_tests|awsaccounts|logpipelines|notebooks|slos [--dry-run] [-h]

If you feel safe with the output Dogmover is giving you, run without --dry-run to commit your push/pull into your Datadog account.

(optional) Usage via container

Install via container

1. Create image with Python 3 and relevant dependencies docker build -t "dogmover" .
2. Make sure the dogmover.py is executable chmod +x dogmover.py
3. Add your api_key, app_key to config.json for both the source (the organization where you will pull the resources from) and the destination (to where you will be pushing the resources to). See config.json.example.

Usage via container

Usage is similar to the one without container: docker run --rm -v $(pwd):/dogmover dogmover pull|push dashboards|monitors|users|synthetics_api_tests|synthetics_browser_tests|awsaccounts|logpipelines|notebooks|slos [--dry-run] [-h]

Notes

The --dry-run argument

If you are not using the --dry-run argument, all your pulls will create a JSON file locally on your file system, which can be useful if you are looking to backup your resources (for say, version controlling) or to modify the contents before pushing. The files are stored in:

./dashboards/*.json
./monitors/*.json
./users/*.json
./synthetics_api_tests/*.json
./synthetics_browser_tests/*.json
./awsaccounts/*.json
./logpipelines/*.json
./notebooks/*.json
./slos/*.json

The --tag argument

You can choose to pull specific synthetic tests|monitors based on their tags, example usage: dogmover.py pull synthetics_api_tests --tag env:prod --tag application:abc dogmover.py pull monitors --tag team:web

--tag is currently only supported for synthetics_api_tests, synthetics_browser_tests and monitors.

Pushing monitors will schedule a managed downtime

Pushing monitors will automatically schedule a managed downtime for all your monitors, this is to suppress false/positive alerts. You can remove this scheduled downtime by navigating to Monitors -> Manage downtime in Datadog.

Author

• Misiu Pajor ([email protected])

Contributors

Evangelos Thomatos ([email protected])