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Merge branch 'master' into sy/bump-librdkafka
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‎kubernetes_cluster_autoscaler/README.md

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2020
2. [Restart the Agent][5].
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#### Metric collection
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Make sure that the Prometheus-formatted metrics are exposed in your `kubernetes_cluster_autoscaler` cluster.
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For the Agent to start collecting metrics, the `kubernetes_cluster_autoscaler` pods need to be annotated.
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[Kubernetes Cluster Autoscaler][11] has metrics and livenessProbe endpoints that can be accessed on port `8085`. These endpoints are located under `/metrics` and `/health-check` and provide valuable information about the state of your cluster during scaling operations.
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**Note**: To change the default port, use the `--address` flag.
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To configure the Cluster Autoscaler to expose metrics, do the following:
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1. Enable access to the `/metrics` route and expose port `8085` for your Cluster Autoscaler deployment:
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```
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ports:
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--name: app
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containerPort: 8085
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```
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b) instruct your Prometheus to scrape it, by adding the following annotation to your Cluster Autoscaler service:
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```
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prometheus.io/scrape: true
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```
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**Note**: The listed metrics can only be collected if they are available. Some metrics are generated only when certain actions are performed.
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The only parameter required for configuring the `kubernetes_cluster_autoscaler` check is `openmetrics_endpoint`. This parameter should be set to the location where the Prometheus-formatted metrics are exposed. The default port is `8085`. To configure a different port, use the `METRICS_PORT` [environment variable][10]. In containerized environments, `%%host%%` should be used for [host autodetection][3].
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```yaml
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apiVersion: v1
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kind: Pod
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# (...)
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metadata:
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name: '<POD_NAME>'
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annotations:
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ad.datadoghq.com/controller.checks: |
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{
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"kubernetes_cluster_autoscaler": {
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"init_config": {},
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"instances": [
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{
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"openmetrics_endpoint": "http://%%host%%:8085/metrics"
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}
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]
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}
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}
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# (...)
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spec:
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containers:
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- name: 'controller'
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# (...)
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```
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### Validation
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[Run the Agent's status subcommand][6] and look for `kubernetes_cluster_autoscaler` under the Checks section.
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[7]: https://github.com/DataDog/integrations-core/blob/master/kubernetes_cluster_autoscaler/metadata.csv
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[8]: https://github.com/DataDog/integrations-core/blob/master/kubernetes_cluster_autoscaler/assets/service_checks.json
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[9]: https://docs.datadoghq.com/help/
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[10]: https://kubernetes.io/docs/tasks/inject-data-application/define-environment-variable-container/
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[11]: https://github.com/kubernetes/autoscaler/blob/master/cluster-autoscaler/FAQ.md#how-can-i-monitor-cluster-autoscaler

‎mongo/changelog.d/17730.added

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Include namespace in DBM samples operation_metadata

‎mongo/datadog_checks/mongo/dbm/operation_samples.py

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"truncated": self._get_command_truncation_state(command),
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"client": self._get_operation_client(operation),
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"user": self._get_operation_user(operation),
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"ns": namespace,
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}
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def _get_operation_stats(self, operation: dict) -> OperationSampleOperationStats:
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"shard": operation_metadata["shard"],
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"collection": operation_metadata["collection"],
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"comment": operation_metadata["comment"],
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"ns": operation_metadata["ns"],
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},
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"query_truncated": operation_metadata["truncated"],
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},

‎mongo/datadog_checks/mongo/dbm/types.py

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truncated: Optional[str]
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client: OperationSampleClient
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user: Optional[str]
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ns: Optional[str]
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class OperationSampleActivityRecord(

‎mongo/tests/results/operation-samples-mongos.json

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"op": "query",
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"shard": "shard04",
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"collection": "users",
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"comment": "sort"
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"comment": "sort",
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"ns": "integration.$cmd"
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},
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"query_truncated": "not_truncated"
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},

‎mongo/tests/results/operation-samples-standalone.json

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"op": "query",
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"shard": null,
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"collection": "products",
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"comment": "find"
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"comment": "find",
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"ns": "integration.products"
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},
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"query_truncated": "not_truncated"
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},

‎requirements-agent-release.txt

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datadog-sidekiq==1.4.0
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datadog-silk==2.2.1
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datadog-singlestore==2.2.0
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datadog-snmp==7.3.0
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datadog-snmp==7.3.1
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datadog-snowflake==5.6.0
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datadog-solr==1.13.0
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datadog-sonarqube==3.2.2

‎snmp/CHANGELOG.md

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<!-- towncrier release notes start -->
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## 7.3.1 / 2024-06-05
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***Fixed***:
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* Use a forced metric type of gauge for ccmRejectedPhones and ccmUnregisteredPhones so they are not incorrectly inferred to be rate types. ([#17722](https://github.com/DataDog/integrations-core/pull/17722))
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## 7.3.0 / 2024-04-26 / Agent 7.54.0
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***Added***:

‎snmp/datadog_checks/snmp/__about__.py

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# All rights reserved
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# Licensed under a 3-clause BSD style license (see LICENSE)
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__version__ = '7.3.0'
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__version__ = '7.3.1'

‎snmp/datadog_checks/snmp/data/default_profiles/_cisco-voice.yaml

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name: ccmRegisteredPhones
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OID: 1.3.6.1.4.1.9.9.156.1.5.5.0
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- MIB: CISCO-CCM-MIB
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metric_type: gauge
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symbol:
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name: ccmRejectedPhones
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OID: 1.3.6.1.4.1.9.9.156.1.5.7.0
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- MIB: CISCO-CCM-MIB
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metric_type: gauge
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symbol:
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name: ccmUnregisteredPhones
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OID: 1.3.6.1.4.1.9.9.156.1.5.6.0

‎snmp/tests/test_profiles.py

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for cvp in cvp_gauges:
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aggregator.assert_metric('snmp.{}'.format(cvp), metric_type=aggregator.GAUGE, tags=tags)
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ccms_counts = ["ccmRejectedPhones", "ccmUnregisteredPhones"]
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ccms_gauges = ["ccmRegisteredGateways", "ccmRegisteredPhones"]
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for ccm in ccms_counts:
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aggregator.assert_metric('snmp.{}'.format(ccm), metric_type=aggregator.RATE, tags=tags)
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ccms_gauges = ["ccmRegisteredGateways", "ccmRegisteredPhones", "ccmRejectedPhones", "ccmUnregisteredPhones"]
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for ccm in ccms_gauges:
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aggregator.assert_metric('snmp.{}'.format(ccm), metric_type=aggregator.GAUGE, tags=tags)

‎sqlserver/changelog.d/17750.fixed

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[sqlserver] fix missing sqlserver_version

‎sqlserver/datadog_checks/sqlserver/sqlserver.py

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)
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def set_resolved_hostname(self):
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# load static information cache
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self.load_static_information()
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if self._resolved_hostname is None:
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def check(self, _):
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self.load_static_information()
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# configure custom queries for the check
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if self._query_manager is None:
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# use QueryManager to process custom queries

‎traefik_mesh/README.md

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In addition, a small subset of metrics can be collected by communicating with different API endpoints. Specifically:
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- `/api/version`: Version information on the Traefik proxy.
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- `/api/status/nodes`: Ready status of nodes visible by the Traefik [controller][12].
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- `/api/status/nodes`: Ready status of nodes visible by the Traefik [controller][5].
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- `/api/status/readiness`: Ready status of the Traefik controller.
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**Note**: This check uses [OpenMetrics][11] for metric collection, which requires Python 3.
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When configuring the Traefik Mesh check, you can use the following parameters:
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- `openmetrics_endpoint`: This parameter should be set to the location where the Prometheus-formatted metrics are exposed. The default port is `8082`, but it can be configured using the `--entryPoints.metrics.address`. In containerized environments, `%%host%%` can be used for [host autodetection][3].
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- `traefik_proxy_api_endpooint:` This parameter is optional. The default port is `8080` and can be configured using `--entryPoints.traefik.address`. In containerized environments, `%%host%%` can be used for [host autodetection][3].
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- `traefik_controller_api_endpoint`: This parameter is optional. The default port is set to `9000`.
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- `traefik_controller_api_endpoint`: This parameter is optional. The default port is set to `9000`.
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#### Traefik Proxy
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```yaml
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# (...)
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metadata:
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name: '<POD_NAME>'
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annotations:
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ad.datadoghq.com/<CONTAINER_NAME>.checks: |
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{
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"traefik_mesh": {
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"init_config": {},
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"instances": [
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{
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"openmetrics_endpoint": "http://%%host%%:8082/metrics",
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"traefik_proxy_api_endpoint": "http://%%host%%:8080"
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}
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]
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}
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}
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# (...)
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spec:
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containers:
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- name: <CONTAINER_NAME>
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# (...)
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```
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#### Traefik Controller
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```yaml
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# (...)
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metadata:
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name: '<POD_NAME>'
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annotations:
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ad.datadoghq.com/<CONTAINER_NAME>.checks: |
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{
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"traefik_mesh": {
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"init_config": {},
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"instances": [
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{
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"traefik_controller_api_endpoint": "http://%%host%%:9000"
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}
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]
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}
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}
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# (...)
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spec:
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containers:
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- name: <CONTAINER_NAME>
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# (...)
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```
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See the [sample traefik_mesh.d/conf.yaml][4] for all available configuration options.
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### Log collection
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_Available for Agent versions >6.0_
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Traefik Mesh logs can be collected from the different Traefik Mesh pods through Kubernetes. Collecting logs is disabled by default in the Datadog Agent. To enable it, see [Kubernetes Log Collection][12].
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See the [Autodiscovery Integration Templates][3] for guidance on applying the parameters below.
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| Parameter | Value |
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| -------------- | ---------------------------------------------------- |
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| `<LOG_CONFIG>` | `{"source": "traefik_mesh", "service": "<SERVICE_NAME>"}` |
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### Validation
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[2]: https://app.datadoghq.com/account/settings/agent/latest
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[3]: https://docs.datadoghq.com/agent/kubernetes/integrations/
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[4]: https://github.com/DataDog/integrations-core/blob/master/traefik_mesh/datadog_checks/traefik_mesh/data/conf.yaml.example
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[5]: https://docs.datadoghq.com/agent/guide/agent-commands/#start-stop-and-restart-the-agent
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[5]: https://doc.traefik.io/traefik-mesh/api/
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[6]: https://docs.datadoghq.com/agent/guide/agent-commands/#agent-status-and-information
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[7]: https://github.com/DataDog/integrations-core/blob/master/traefik_mesh/metadata.csv
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[8]: https://github.com/DataDog/integrations-core/blob/master/traefik_mesh/assets/service_checks.json
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[9]: https://docs.datadoghq.com/help/
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[10]: https://doc.traefik.io/traefik/observability/metrics/overview/
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[11]: https://docs.datadoghq.com/integrations/openmetrics/
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[12]: https://doc.traefik.io/traefik-mesh/api/
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[12]: https://docs.datadoghq.com/containers/kubernetes/log/

‎windows_service/changelog.d/17749.fixed

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Using constant values instead of reassigning variables in each check run

‎windows_service/datadog_checks/windows_service/windows_service.py

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}
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STARTUP_TYPE_DELAYED_AUTO = "automatic_delayed_start"
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STARTUP_TYPE_UNKNOWN = "unknown"
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DISPLAY_NAME_UNKNOWN = "Not_Found"
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def __init__(self, scm_handle, name):
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# if a name doesn't match anything (wrong name or no permission to access the service), report UNKNOWN
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display_name = "Not_Found"
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tags = ['windows_service:{}'.format(service)]
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tags.extend(custom_tags)
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if not instance.get('disable_legacy_service_tag', False):
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self._log_deprecation('service_tag', 'windows_service')

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