Datadog cli tool to sync resources across organizations.
The purpose of the datadog-sync-cli package is providing an easy way to sync resources across Datadog organizations.
The source organization will not be modified, but the destination organization will have resources created and updated during by sync command.
- Python >= v3.7
Usage: datadog-sync COMMAND [OPTIONS]
Initialize cli
Options:
--source-api-key TEXT Datadog source organization API key. [required]
--source-app-key TEXT Datadog source organization APP key. [required]
--source-api-url TEXT Datadog source organization API url.
--destination-api-key TEXT Datadog destination organization API key. [required]
--destination-app-key TEXT Datadog destination organization APP key. [required]
--destination-api-url TEXT Datadog destination organization API url.
--http-client-retry-timeout INTEGER The HTTP request retry timeout period. Defaults to `60s`.
--resources TEXT Optional comma separated list of resource to
import. All supported resources are imported
by default.
-v, --verbose Enable verbose logging.
--filter TEXT Filter imported resources. See [Filtering] section for more details.
--filter-operator TEXT Filter operator when multiple filters are passed. Supports `AND` or `OR`.
--config FILE Read configuration from FILE. See [Config] section for more details.
--max-workers INTEGER Max number of workers when running
operations in multi-threads. Defaults to the number of processors on the machine, multiplied by 5.
--skip-failed-resource-connections BOOLEAN Skip resource if resource connection fails. [default: True] [sync + import only]
--force-missing-dependencies Force importing and syncing resources that
could be potential dependencies to the
requested resources. [sync only]
--help Show this message and exit.
Commands:
diffs Log resource diffs.
import Import Datadog resources.
sync Sync Datadog resources to destination.
Datadog sync cli tool supports filtering resources during import. Multiple filter flags can be passed.
Filter option accepts a string made up of key=value pairs separated by ;. For example
--filter 'Type=<resource>;Name=<attribute_name>;Value=<attribute_value>;Operator=<operator>'
Available keys:
Type: Resource e.g. Monitors, Dashboards, etc. [required]Name: Attribute key to filter on. This can be any top level key in the individual resources retrieved from their respective list all endpoints. [required]- For example: Dashboards list all endpoint returns dashboard summary response which contains the following attributes available for filtering:
author_handle, created_at, description, id, is_read_only, layout_type, modified_at, title, url
- For example: Dashboards list all endpoint returns dashboard summary response which contains the following attributes available for filtering:
Value: Attribute value to filter by. [required]Operator: Available operators are below. All invalid operator's default toExactMatch.SubString: Sub string matchingExactMatch: Exact string match.
By default, if multiple filters are passed for the same resource, OR logic is applied to the filters. This behavior can be adjusted using the --filter-operator option.
Custom config textfile can be passed in place of options. Example config file:
# config
destination_api_url="https://api.datadoghq.eu"
destination_api_key="<API_KEY>"
destination_app_key="<APP_KEY>"
source_api_key="<API_KEY>"
source_app_key="<APP_KEY>"
source_api_url="https://api.datadoghq.com"
filter=["Type=Dashboards;Name=title;Value=Test screenboard", "Type=Monitors;Name=tags;Value=sync:true"]
Usage: datadog-sync --config config import
- Clone the project repo
- CD into the repo directory and install the datadog-sync-cli via
pip install . - Run cli tool
datadog-sync <command> <options>
- Clone the project repo
- CD into the repo directory and build the docker image
docker build . -t datadog-sync - Run the docker image using entrypoint below:
docker run --rm -v $(pwd):/datadog-sync:rw \
-e DD_SOURCE_API_KEY=<DATADOG_API_KEY> \
-e DD_SOURCE_APP_KEY=<DATADOG_APP_KEY> \
-e DD_SOURCE_API_URL=<DATADOG_API_URL> \
-e DD_DESTINATION_API_KEY=<DATADOG_API_KEY> \
-e DD_DESTINATION_APP_KEY=<DATADOG_APP_KEY> \
-e DD_DESTINATION_API_URL=<DATADOG_API_URL> \
datadog-sync:latest <command> <options>
Note: The above docker run command will mount your current working directory to the container.
To use the tool, first run the import command, which will read the wanted items from the specified resources and save them locally.
Then, you can run the sync command which will use that local cache (unless --force-missing-dependencies is passed) to create
the resources on the destination, and saves locally what has been pushed.
- roles
- users
- synthetics_private_locations
- synthetics_tests
- synthetics_global_variables
- monitors
- downtimes
- service_level_objectives
- slo_corrections
- dashboards
- dashboard_lists
- logs_custom_pipelines
- notebooks
- host_tags
- logs_indexes
- logs_metrics
- logs_restriction_queries
- metric_tag_configurations
Many Datadog resources are interdependent. For example, Users resource references Roles and Dashboards can include widgets which use Monitors or Synthetics. To ensure these dependencies are not broken, the datadog-sync tool imports and syncs these in a specific order. See the order(top -> bottom) in the Supported resources section below.
If importing/syncing resources individually, ensure resource dependencies are imported and synced as well:
| Resource | Dependencies |
|---|---|
| roles | - |
| users | roles |
| synthetics_private_locations | - |
| synthetics_tests | synthetics_private_locations |
| synthetics_global_variables | synthetics_tests |
| monitors | roles |
| downtimes | monitors |
| service_level_objectives | monitors, synthetics_tests |
| slo_corrections | service_level_objectives |
| dashboards | monitors, roles, service_level_objectives |
| dashboard_lists | dashboards |
| logs_custom_pipelines | - |
| notebooks | - |
| host_tags | - |
| logs_indexes | - |
| logs_metrics | - |
| logs_restriction_queries | roles |
| metric_tag_configurations | - |