feat(resilience4j): add new integration

resilience4j/CHANGELOG.md

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+# CHANGELOG - Resilience4j
+
+## 1.0.0 / YYYY-MM-DD
+
+***Added***:
+
+* Initial Release
+

resilience4j/README.md

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+# Agent Check: Resilience4j
+
+## Overview
+
+[Resilience4j](https://github.com/resilience4j/resilience4j) is a lightweight fault tolerance library inspired by Netflix Hystrix, but designed for functional programming. This check monitors [Resilience4j][1] through the Datadog Agent.
+
+## Setup
+
+### Installation
+
+To install the Resilience4j check on your host:
+
+
+1. Install the [developer toolkit]
+(https://docs.datadoghq.com/developers/integrations/python/)
+ on any machine.
+
+2. Run `ddev release build resilience4j` to build the package.
+
+3. [Download the Datadog Agent][2].
+
+4. Upload the build artifact to any host with an Agent and
+ run `datadog-agent integration install -w
+ path/to/resilience4j/dist/<ARTIFACT_NAME>.whl`.
+
+### Configuration
+
+1. Edit the `resilience4j/conf.yaml` file, in the `conf.d/` folder at the root of your Agent's configuration directory to start collecting your Resilience4j performance data. See the [sample resilience4j/conf.yaml][4] for all available configuration options.
+
+2. [Restart the Agent][5].
+
+### Validation
+
+[Run the Agent's status subcommand][6] and look for `resilience4j` under the Checks section.
+
+## Data Collected
+
+### Metrics
+
+See [metadata.csv][7] for a list of metrics provided by this integration.
+
+### Service Checks
+
+See [service_checks.json][11] for a list of service checks provided by this integration.
+
+### Events
+
+Resilience4j does not include any events.
+
+## Troubleshooting
+
+Need help? Contact [Datadog support][3].
+
+[1]: **LINK_TO_INTEGRATION_SITE**
+[2]: https://app.datadoghq.com/account/settings/agent/latest
+[3]: https://docs.datadoghq.com/agent/kubernetes/integrations/
+[4]: https://github.com/DataDog/integrations-extras/blob/master/resilience4j/datadog_checks/resilience4j/data/conf.yaml.example
+[5]: https://docs.datadoghq.com/agent/guide/agent-commands/#start-stop-and-restart-the-agent
+[6]: https://docs.datadoghq.com/agent/guide/agent-commands/#agent-status-and-information
+[7]: https://github.com/DataDog/integrations-extras/blob/master/resilience4j/metadata.csv
+[8]: https://github.com/DataDog/integrations-extras/blob/master/resilience4j/assets/service_checks.json
+[9]: https://docs.datadoghq.com/help/
+

resilience4j/assets/configuration/spec.yaml

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+name: Resilience4j
+files:
+- name: resilience4j.yaml
+  options:
+  - template: init_config
+    options:
+    - template: init_config/default
+  - template: instances
+    options:
+    - template: instances/default

resilience4j/assets/dashboards/resilience4j_overview.json

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+Please build an out-of-the-box dashboard for your integration following our best practices here: https://datadoghq.dev/integrations-core/guidelines/dashboards/#best-practices

resilience4j/assets/service_checks.json

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+[
+    {
+        "agent_version": "7.59.0",
+        "integration": "resilience4j",
+        "check": "resilience4j.prometheus.health",
+        "statuses": [
+            "ok",
+            "critical"
+        ],
+        "groups": [
+            "host",
+            "endpoint"
+        ],
+        "name": "Resilience4j endpoint health",
+        "description": "Returns `CRITICAL` if the Agent is unable to connect to the Resilience4j endpoint, otherwise returns `OK`."
+    }
+]

resilience4j/datadog_checks/__init__.py

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+
+__path__ = __import__('pkgutil').extend_path(__path__, __name__)  # type: ignore

resilience4j/datadog_checks/resilience4j/__about__.py

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+
+__version__ = '1.0.0'

resilience4j/datadog_checks/resilience4j/__init__.py

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+
+from .__about__ import __version__
+from .check import Resilience4jCheck
+
+__all__ = ['__version__', 'Resilience4jCheck']

resilience4j/datadog_checks/resilience4j/check.py

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+from datadog_checks.base import OpenMetricsBaseCheck, ConfigurationError
+
+from .metrics import METRIC_MAP
+
+
+class Resilience4jCheck(OpenMetricsBaseCheck):
+    DEFAULT_METRIC_LIMIT = 0
+
+    def __init__(self, name, init_config, instances):
+        default_instances = {
+            'resilience4j': {
+                'metrics': [METRIC_MAP],
+                'send_distribution_sums_as_monotonic': 'true',
+                'send_distribution_counts_as_monotonic': 'true',
+            }
+        }
+
+        super(Resilience4jCheck, self).__init__(
+            name, init_config, instances, default_instances=default_instances, default_namespace='resilience4j'
+        )
+
+    def _http_check(self, url, check_name):
+        try:
+            response = self.http.get(url)
+            response.raise_for_status()
+        except Exception as e:
+            self.service_check(check_name, self.CRITICAL, message=str(e))
+        else:
+            if response.status_code == 200:
+                self.service_check(check_name, self.OK)
+            else:
+                self.service_check(check_name, self.WARNING)
+
+    def check(self, instance):
+        prometheus_url = instance.get("prometheus_url")
+        if prometheus_url is None:
+            raise ConfigurationError("Each instance must have a url to the metrics endpoint")
+
+        super(Resilience4jCheck, self).check(instance)

resilience4j/datadog_checks/resilience4j/config_models/__init__.py

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+
+
+# This file is autogenerated.
+# To change this file you should edit assets/configuration/spec.yaml and then run the following commands:
+#     ddev -x validate config -s <INTEGRATION_NAME>
+#     ddev -x validate models -s <INTEGRATION_NAME>
+
+
+from .instance import InstanceConfig
+from .shared import SharedConfig
+
+
+class ConfigMixin:
+    _config_model_instance: InstanceConfig
+    _config_model_shared: SharedConfig
+
+    @property
+    def config(self) -> InstanceConfig:
+        return self._config_model_instance
+
+    @property
+    def shared_config(self) -> SharedConfig:
+        return self._config_model_shared

resilience4j/datadog_checks/resilience4j/config_models/defaults.py

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+
+
+# This file is autogenerated.
+# To change this file you should edit assets/configuration/spec.yaml and then run the following commands:
+#     ddev -x validate config -s <INTEGRATION_NAME>
+#     ddev -x validate models -s <INTEGRATION_NAME>
+
+
+def instance_empty_default_hostname():
+    return False
+
+
+def instance_min_collection_interval():
+    return 15

resilience4j/datadog_checks/resilience4j/config_models/instance.py

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+
+
+# This file is autogenerated.
+# To change this file you should edit assets/configuration/spec.yaml and then run the following commands:
+#     ddev -x validate config -s <INTEGRATION_NAME>
+#     ddev -x validate models -s <INTEGRATION_NAME>
+
+
+from __future__ import annotations
+
+from typing import Optional
+
+from pydantic import BaseModel, ConfigDict, field_validator, model_validator
+
+from datadog_checks.base.utils.functions import identity
+from datadog_checks.base.utils.models import validation
+
+from . import defaults, validators
+
+
+class InstanceConfig(BaseModel):
+    model_config = ConfigDict(
+        validate_default=True,
+        arbitrary_types_allowed=True,
+        frozen=True,
+    )
+    empty_default_hostname: Optional[bool] = None
+    min_collection_interval: Optional[float] = None
+    service: Optional[str] = None
+    tags: Optional[tuple[str, ...]] = None
+
+    @model_validator(mode='before')
+    def _initial_validation(cls, values):
+        return validation.core.initialize_config(getattr(validators, 'initialize_instance', identity)(values))
+
+    @field_validator('*', mode='before')
+    def _validate(cls, value, info):
+        field = cls.model_fields[info.field_name]
+        field_name = field.alias or info.field_name
+        if field_name in info.context['configured_fields']:
+            value = getattr(validators, f'instance_{info.field_name}', identity)(value, field=field)
+        else:
+            value = getattr(defaults, f'instance_{info.field_name}', lambda: value)()
+
+        return validation.utils.make_immutable(value)
+
+    @model_validator(mode='after')
+    def _final_validation(cls, model):
+        return validation.core.check_model(getattr(validators, 'check_instance', identity)(model))

resilience4j/datadog_checks/resilience4j/config_models/shared.py

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+
+
+# This file is autogenerated.
+# To change this file you should edit assets/configuration/spec.yaml and then run the following commands:
+#     ddev -x validate config -s <INTEGRATION_NAME>
+#     ddev -x validate models -s <INTEGRATION_NAME>
+
+
+from __future__ import annotations
+
+from typing import Optional
+
+from pydantic import BaseModel, ConfigDict, field_validator, model_validator
+
+from datadog_checks.base.utils.functions import identity
+from datadog_checks.base.utils.models import validation
+
+from . import defaults, validators
+
+
+class SharedConfig(BaseModel):
+    model_config = ConfigDict(
+        validate_default=True,
+        arbitrary_types_allowed=True,
+        frozen=True,
+    )
+    service: Optional[str] = None
+
+    @model_validator(mode='before')
+    def _initial_validation(cls, values):
+        return validation.core.initialize_config(getattr(validators, 'initialize_shared', identity)(values))
+
+    @field_validator('*', mode='before')
+    def _validate(cls, value, info):
+        field = cls.model_fields[info.field_name]
+        field_name = field.alias or info.field_name
+        if field_name in info.context['configured_fields']:
+            value = getattr(validators, f'shared_{info.field_name}', identity)(value, field=field)
+        else:
+            value = getattr(defaults, f'shared_{info.field_name}', lambda: value)()
+
+        return validation.utils.make_immutable(value)
+
+    @model_validator(mode='after')
+    def _final_validation(cls, model):
+        return validation.core.check_model(getattr(validators, 'check_shared', identity)(model))

resilience4j/datadog_checks/resilience4j/config_models/validators.py

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+
+
+# Here you can include additional config validators or transformers
+#
+# def initialize_instance(values, **kwargs):
+#     if 'my_option' not in values and 'my_legacy_option' in values:
+#         values['my_option'] = values['my_legacy_option']
+#     if values.get('my_number') > 10:
+#         raise ValueError('my_number max value is 10, got %s' % str(values.get('my_number')))
+#
+#     return values