text: # Copyright 2021 Canonical Ltd.
  # See LICENSE file for licensing details.
  """## Overview.
  
  This document explains how to integrate with the Prometheus charm
  for the purpose of providing a metrics endpoint to Prometheus. It
  also explains how alternative implementations of the Prometheus charms
  may maintain the same interface and be backward compatible with all
  currently integrated charms. Finally this document is the
  authoritative reference on the structure of relation data that is
  shared between Prometheus charms and any other charm that intends to
  provide a scrape target for Prometheus.
  
  ## Provider Library Usage
  
  This Prometheus charm interacts with its scrape targets using its
  charm library. Charms seeking to expose metric endpoints for the
  Prometheus charm, must do so using the `MetricsEndpointProvider`
  object from this charm library. For the simplest use cases, using the
  `MetricsEndpointProvider` object only requires instantiating it,
  typically in the constructor of your charm (the one which exposes a
  metrics endpoint). The `MetricsEndpointProvider` constructor requires
  the name of the relation over which a scrape target (metrics endpoint)
  is exposed to the Prometheus charm. This relation must use the
  `prometheus_scrape` interface. By default address of the metrics
  endpoint is set to the unit IP address, by each unit of the
  `MetricsEndpointProvider` charm. These units set their address in
  response to the `PebbleReady` event of each container in the unit,
  since container restarts of Kubernetes charms can result in change of
  IP addresses. The default name for the metrics endpoint relation is
  `metrics-endpoint`. It is strongly recommended to use the same
  relation name for consistency across charms and doing so obviates the
  need for an additional constructor argument. The
  `MetricsEndpointProvider` object may be instantiated as follows
  
      from charms.prometheus_k8s.v0.prometheus_scrape import MetricsEndpointProvider
  
      def __init__(self, *args):
          super().__init__(*args)
          ...
          self.metrics_endpoint = MetricsEndpointProvider(self)
          ...
  
  Note that the first argument (`self`) to `MetricsEndpointProvider` is
  always a reference to the parent (scrape target) charm.
  
  An instantiated `MetricsEndpointProvider` object will ensure that each
  unit of its parent charm, is a scrape target for the
  `MetricsEndpointConsumer` (Prometheus) charm. By default
  `MetricsEndpointProvider` assumes each unit of the consumer charm
  exports its metrics at a path given by `/metrics` on port 80. These
  defaults may be changed by providing the `MetricsEndpointProvider`
  constructor an optional argument (`jobs`) that represents a
  Prometheus scrape job specification using Python standard data
  structures. This job specification is a subset of Prometheus' own
  [scrape
  configuration](https://prometheus.io/docs/prometheus/latest/configuration/configuration/#scrape_config)
  format but represented using Python data structures. More than one job
  may be provided using the `jobs` argument. Hence `jobs` accepts a list
  of dictionaries where each dictionary represents one `<scrape_config>`
  object as described in the Prometheus documentation. The currently
  supported configuration subset is: `job_name`, `metrics_path`,
  `static_configs`
  
  Suppose it is required to change the port on which scraped metrics are
  exposed to 8000. This may be done by providing the following data
  structure as the value of `jobs`.
  
  ```
  [
      {
          "static_configs": [
              {
                  "targets": ["*:8000"]
              }
          ]
      }
  ]
  ```
  
  The wildcard ("*") host specification implies that the scrape targets
  will automatically be set to the host addresses advertised by each
  unit of the consumer charm.
  
  It is also possible to change the metrics path and scrape multiple
  ports, for example
  
  ```
  [
      {
          "metrics_path": "/my-metrics-path",
          "static_configs": [
              {
                  "targets": ["*:8000", "*:8081"],
              }
          ]
      }
  ]
  ```
  
  More complex scrape configurations are possible. For example
  
  ```
  [
      {
          "static_configs": [
              {
                  "targets": ["10.1.32.215:7000", "*:8000"],
                  "labels": {
                      "some-key": "some-value"
                  }
              }
          ]
      }
  ]
  ```
  
  This example scrapes the target "10.1.32.215" at port 7000 in addition
  to scraping each unit at port 8000. There is however one difference
  between wildcard targets (specified using "*") and fully qualified
  targets (such as "10.1.32.215"). The Prometheus charm automatically
  associates labels with metrics generated by each target. These labels
  localise the source of metrics within the Juju topology by specifying
  its "model name", "model UUID", "application name" and "unit
  name". However unit name is associated only with wildcard targets but
  not with fully qualified targets.
  
  Multiple jobs with different metrics paths and labels are allowed, but
  each job must be given a unique name. For example
  
  ```
  [
      {
          "job_name": "my-first-job",
          "metrics_path": "one-path",
          "static_configs": [
              {
                  "targets": ["*:7000"],
                  "labels": {
                      "some-key": "some-value"
                  }
              }
          ]
      },
      {
          "job_name": "my-second-job",
          "metrics_path": "another-path",
          "static_configs": [
              {
                  "targets": ["*:8000"],
                  "labels": {
                      "some-other-key": "some-other-value"
                  }
              }
          ]
      }
  ]
  ```
  
  It is also possible to configure other scrape related parameters using
  these job specifications as described by the Prometheus
  [documentation](https://prometheus.io/docs/prometheus/latest/configuration/configuration/#scrape_config).
  The permissible subset of job specific scrape configuration parameters
  supported in a `MetricsEndpointProvider` job specification are:
  
  - `job_name`
  - `metrics_path`
  - `static_configs`
  - `scrape_interval`
  - `scrape_timeout`
  - `proxy_url`
  - `relabel_configs`
  - `metrics_relabel_configs`
  - `sample_limit`
  - `label_limit`
  - `label_name_length_limit`
  - `label_value_length_limit`
  
  ## Consumer Library Usage
  
  The `MetricsEndpointConsumer` object may be used by Prometheus
  charms to manage relations with their scrape targets. For this
  purposes a Prometheus charm needs to do two things
  
  1. Instantiate the `MetricsEndpointConsumer` object by providing it a
  reference to the parent (Prometheus) charm and optionally the name of
  the relation that the Prometheus charm uses to interact with scrape
  targets. This relation must confirm to the `prometheus_scrape`
  interface and it is strongly recommended that this relation be named
  `metrics-endpoint` which is its default value.
  
  For example a Prometheus charm may instantiate the
  `MetricsEndpointConsumer` in its constructor as follows
  
      from charms.prometheus_k8s.v0.prometheus_scrape import MetricsEndpointConsumer
  
      def __init__(self, *args):
          super().__init__(*args)
          ...
          self.metrics_consumer = MetricsEndpointConsumer(self)
          ...
  
  2. A Prometheus charm also needs to respond to the
  `TargetsChangedEvent` event of the `MetricsEndpointConsumer` by adding itself as
  an observer for these events, as in
  
      self.framework.observe(
          self.metrics_consumer.on.targets_changed,
          self._on_scrape_targets_changed,
      )
  
  In responding to the `TargetsChangedEvent` event the Prometheus
  charm must update the Prometheus configuration so that any new scrape
  targets are added and/or old ones removed from the list of scraped
  endpoints. For this purpose the `MetricsEndpointConsumer` object
  exposes a `jobs()` method that returns a list of scrape jobs. Each
  element of this list is the Prometheus scrape configuration for that
  job. In order to update the Prometheus configuration, the Prometheus
  charm needs to replace the current list of jobs with the list provided
  by `jobs()` as follows
  
      def _on_scrape_targets_changed(self, event):
          ...
          scrape_jobs = self.metrics_consumer.jobs()
          for job in scrape_jobs:
              prometheus_scrape_config.append(job)
          ...
  
  ## Alerting Rules
  
  This charm library also supports gathering alerting rules from all
  related `MetricsEndpointProvider` charms and enabling corresponding alerts within the
  Prometheus charm.  Alert rules are automatically gathered by `MetricsEndpointProvider`
  charms when using this library, from a directory conventionally named
  `prometheus_alert_rules`. This directory must reside at the top level
  in the `src` folder of the consumer charm. Each file in this directory
  is assumed to be in one of two formats:
  - the official prometheus alert rule format, conforming to the
  [Prometheus docs](https://prometheus.io/docs/prometheus/latest/configuration/alerting_rules/)
  - a single rule format, which is a simplified subset of the official format,
  comprising a single alert rule per file, using the same YAML fields.
  
  The file name must have the `.rule` extension.
  
  An example of the contents of such a file in the custom single rule
  format is shown below.
  
  ```
  alert: HighRequestLatency
  expr: job:request_latency_seconds:mean5m{my_key=my_value} > 0.5
  for: 10m
  labels:
    severity: Medium
    type: HighLatency
  annotations:
    summary: High request latency for {{ $labels.instance }}.
  ```
  
  The `MetricsEndpointProvider` will read all available alert rules and
  also inject "filtering labels" into the alert expressions. The
  filtering labels ensure that alert rules are localised to the metrics
  provider charm's Juju topology (application, model and its UUID). Such
  a topology filter is essential to ensure that alert rules submitted by
  one provider charm generates alerts only for that same charm. When
  alert rules are embedded in a charm, and the charm is deployed as a
  Juju application, the alert rules from that application have their
  expressions automatically updated to filter for metrics coming from
  the units of that application alone. This remove risk of spurious
  evaluation, e.g., when you have multiple deployments of the same charm
  monitored by the same Prometheus.
  
  Not all alerts one may want to specify can be embedded in a
  charm. Some alert rules will be specific to a user's use case. This is
  the case, for example, of alert rules that are based on business
  constraints, like expecting a certain amount of requests to a specific
  API every five minutes. Such alert rules can be specified via the
  [COS Config Charm](https://charmhub.io/cos-configuration-k8s),
  which allows importing alert rules and other settings like dashboards
  from a Git repository.
  
  Gathering alert rules and generating rule files within the Prometheus
  charm is easily done using the `alerts()` method of
  `MetricsEndpointConsumer`. Alerts generated by Prometheus will
  automatically include Juju topology labels in the alerts. These labels
  indicate the source of the alert. The following labels are
  automatically included with each alert
  
  - `juju_model`
  - `juju_model_uuid`
  - `juju_application`
  
  ## Relation Data
  
  The Prometheus charm uses both application and unit relation data to
  obtain information regarding its scrape jobs, alert rules and scrape
  targets. This relation data is in JSON format and it closely resembles
  the YAML structure of Prometheus [scrape configuration]
  (https://prometheus.io/docs/prometheus/latest/configuration/configuration/#scrape_config).
  
  Units of Metrics provider charms advertise their names and addresses
  over unit relation data using the `prometheus_scrape_unit_name` and
  `prometheus_scrape_unit_address` keys. While the `scrape_metadata`,
  `scrape_jobs` and `alert_rules` keys in application relation data
  of Metrics provider charms hold eponymous information.
  
  """
  
  import json
  import logging
  import os
  import platform
  import subprocess
  from collections import OrderedDict
  from pathlib import Path
  from typing import Dict, List, Optional, Union
  
  import yaml
  from ops.charm import CharmBase, RelationRole
  from ops.framework import EventBase, EventSource, Object, ObjectEvents
  
  # The unique Charmhub library identifier, never change it
  from ops.model import ModelError
  
  LIBID = "bc84295fef5f4049878f07b131968ee2"
  
  # Increment this major API version when introducing breaking changes
  LIBAPI = 0
  
  # Increment this PATCH version before using `charmcraft publish-lib` or reset
  # to 0 if you are raising the major API version
  LIBPATCH = 17
  
  logger = logging.getLogger(__name__)
  
  
  ALLOWED_KEYS = {
      "job_name",
      "metrics_path",
      "static_configs",
      "scrape_interval",
      "scrape_timeout",
      "proxy_url",
      "relabel_configs",
      "metrics_relabel_configs",
      "sample_limit",
      "label_limit",
      "label_name_length_limit",
      "label_value_lenght_limit",
  }
  DEFAULT_JOB = {
      "metrics_path": "/metrics",
      "static_configs": [{"targets": ["*:80"]}],
  }
  
  
  DEFAULT_RELATION_NAME = "metrics-endpoint"
  RELATION_INTERFACE_NAME = "prometheus_scrape"
  
  DEFAULT_ALERT_RULES_RELATIVE_PATH = "./src/prometheus_alert_rules"
  
  
  class RelationNotFoundError(Exception):
      """Raised if there is no relation with the given name is found."""
  
      def __init__(self, relation_name: str):
          self.relation_name = relation_name
          self.message = "No relation named '{}' found".format(relation_name)
  
          super().__init__(self.message)
  
  
  class RelationInterfaceMismatchError(Exception):
      """Raised if the relation with the given name has a different interface."""
  
      def __init__(
          self,
          relation_name: str,
          expected_relation_interface: str,
          actual_relation_interface: str,
      ):
          self.relation_name = relation_name
          self.expected_relation_interface = expected_relation_interface
          self.actual_relation_interface = actual_relation_interface
          self.message = (
              "The '{}' relation has '{}' as interface rather than the expected '{}'".format(
                  relation_name, actual_relation_interface, expected_relation_interface
              )
          )
  
          super().__init__(self.message)
  
  
  class RelationRoleMismatchError(Exception):
      """Raised if the relation with the given name has a different role."""
  
      def __init__(
          self,
          relation_name: str,
          expected_relation_role: RelationRole,
          actual_relation_role: RelationRole,
      ):
          self.relation_name = relation_name
          self.expected_relation_interface = expected_relation_role
          self.actual_relation_role = actual_relation_role
          self.message = "The '{}' relation has role '{}' rather than the expected '{}'".format(
              relation_name, repr(actual_relation_role), repr(expected_relation_role)
          )
  
          super().__init__(self.message)
  
  
  def _validate_relation_by_interface_and_direction(
      charm: CharmBase,
      relation_name: str,
      expected_relation_interface: str,
      expected_relation_role: RelationRole,
  ):
      """Verifies that a relation has the necessary characteristics.
  
      Verifies that the `relation_name` provided: (1) exists in metadata.yaml,
      (2) declares as interface the interface name passed as `relation_interface`
      and (3) has the right "direction", i.e., it is a relation that `charm`
      provides or requires.
  
      Args:
          charm: a `CharmBase` object to scan for the matching relation.
          relation_name: the name of the relation to be verified.
          expected_relation_interface: the interface name to be matched by the
              relation named `relation_name`.
          expected_relation_role: whether the `relation_name` must be either
              provided or required by `charm`.
  
      Raises:
          RelationNotFoundError: If there is no relation in the charm's metadata.yaml
              with the same name as provided via `relation_name` argument.
          RelationInterfaceMismatchError: The relation with the same name as provided
              via `relation_name` argument does not have the same relation interface
              as specified via the `expected_relation_interface` argument.
          RelationRoleMismatchError: If the relation with the same name as provided
              via `relation_name` argument does not have the same role as specified
              via the `expected_relation_role` argument.
      """
      if relation_name not in charm.meta.relations:
          raise RelationNotFoundError(relation_name)
  
      relation = charm.meta.relations[relation_name]
  
      actual_relation_interface = relation.interface_name
      if actual_relation_interface != expected_relation_interface:
          raise RelationInterfaceMismatchError(
              relation_name, expected_relation_interface, actual_relation_interface
          )
  
      if expected_relation_role == RelationRole.provides:
          if relation_name not in charm.meta.provides:
              raise RelationRoleMismatchError(
                  relation_name, RelationRole.provides, RelationRole.requires
              )
      elif expected_relation_role == RelationRole.requires:
          if relation_name not in charm.meta.requires:
              raise RelationRoleMismatchError(
                  relation_name, RelationRole.requires, RelationRole.provides
              )
      else:
          raise Exception("Unexpected RelationDirection: {}".format(expected_relation_role))
  
  
  def _sanitize_scrape_configuration(job) -> dict:
      """Restrict permissible scrape configuration options.
  
      If job is empty then a default job is returned. The
      default job is
  
      ```
      {
          "metrics_path": "/metrics",
          "static_configs": [{"targets": ["*:80"]}],
      }
      ```
  
      Args:
          job: a dict containing a single Prometheus job
              specification.
  
      Returns:
          a dictionary containing a sanitized job specification.
      """
      sanitized_job = DEFAULT_JOB.copy()
      sanitized_job.update({key: value for key, value in job.items() if key in ALLOWED_KEYS})
      return sanitized_job
  
  
  class JujuTopology:
      """Class for storing and formatting juju topology information."""
  
      STUB = "%%juju_topology%%"
  
      def __new__(cls, *args, **kwargs):
          """Reject instantiation of a base JujuTopology class. Children only."""
          if cls is JujuTopology:
              raise TypeError("only children of '{}' may be instantiated".format(cls.__name__))
          return object.__new__(cls)
  
      def __init__(
          self,
          model: str,
          model_uuid: str,
          application: str,
          unit: Optional[str] = "",
          charm_name: Optional[str] = "",
      ):
          """Build a JujuTopology object.
  
          A `JujuTopology` object is used for storing and transforming
          Juju Topology information. This information is used to
          annotate Prometheus scrape jobs and alert rules. Such
          annotation when applied to scrape jobs helps in identifying
          the source of the scrapped metrics. On the other hand when
          applied to alert rules topology information ensures that
          evaluation of alert expressions is restricted to the source
          (charm) from which the alert rules were obtained.
  
          Args:
              model: a string name of the Juju model
              model_uuid: a globally unique string identifier for the Juju model
              application: an application name as a string
              unit: a unit name as a string
              charm_name: name of charm as a string
  
          Note:
              `JujuTopology` should not be constructed directly by charm code. Please
              use `ProviderTopology` or `AggregatorTopology`.
          """
          self.model = model
          self.model_uuid = model_uuid
          self.application = application
          self.charm_name = charm_name
          self.unit = unit
  
      @classmethod
      def from_charm(cls, charm):
          """Factory method for creating `JujuTopology` children from a given charm.
  
          Args:
              charm: a `CharmBase` object for which the `JujuTopology` has to be constructed
  
          Returns:
              a `JujuTopology` object.
          """
          return cls(
              model=charm.model.name,
              model_uuid=charm.model.uuid,
              application=charm.model.app.name,
              unit=charm.model.unit.name,
              charm_name=charm.meta.name,
          )
  
      @classmethod
      def from_relation_data(cls, data: dict):
          """Factory method for creating `JujuTopology` children from a dictionary.
  
          Args:
              data: a dictionary with four keys providing topology information. The keys are
                  - "model"
                  - "model_uuid"
                  - "application"
                  - "unit"
                  - "charm_name"
  
                  `unit` and `charm_name` may be empty, but will result in more limited
                  labels. However, this allows us to support payload-only charms.
  
          Returns:
              a `JujuTopology` object.
          """
          return cls(
              model=data["model"],
              model_uuid=data["model_uuid"],
              application=data["application"],
              unit=data.get("unit", ""),
              charm_name=data.get("charm_name", ""),
          )
  
      @property
      def identifier(self) -> str:
          """Format the topology information into a terse string."""
          # This is odd, but may have `None` as a model key
          return "_".join([str(val) for val in self.as_promql_label_dict().values()]).replace(
              "/", "_"
          )
  
      @property
      def promql_labels(self) -> str:
          """Format the topology information into a verbose string."""
          return ", ".join(
              ['{}="{}"'.format(key, value) for key, value in self.as_promql_label_dict().items()]
          )
  
      def as_dict(self, rename_keys: Optional[Dict[str, str]] = None) -> OrderedDict:
          """Format the topology information into a dict.
  
          Use an OrderedDict so we can rely on the insertion order on Python 3.5 (and 3.6,
          which still does not guarantee it).
  
          Args:
              rename_keys: A dictionary mapping old key names to new key names, which will
                  be substituted when invoked.
          """
          ret = OrderedDict(
              [
                  ("model", self.model),
                  ("model_uuid", self.model_uuid),
                  ("application", self.application),
                  ("unit", self.unit),
                  ("charm_name", self.charm_name),
              ]
          )
  
          ret["unit"] or ret.pop("unit")
          ret["charm_name"] or ret.pop("charm_name")
  
          # If a key exists in `rename_keys`, replace the value
          if rename_keys:
              ret = OrderedDict(
                  (rename_keys.get(k), v) if rename_keys.get(k) else (k, v) for k, v in ret.items()  # type: ignore
              )
  
          return ret
  
      def as_promql_label_dict(self):
          """Format the topology information into a dict with keys having 'juju_' as prefix."""
          vals = {
              "juju_{}".format(key): val
              for key, val in self.as_dict(rename_keys={"charm_name": "charm"}).items()
          }
          # The leader is the only unit that sets alert rules, if "juju_unit" is present,
          # then the rules will only be evaluated for that unit
          if "juju_unit" in vals:
              vals.pop("juju_unit")
  
          return vals
  
      def render(self, template: str):
          """Render a juju-topology template string with topology info."""
          return template.replace(JujuTopology.STUB, self.promql_labels)
  
  
  class AggregatorTopology(JujuTopology):
      """Class for initializing topology information for MetricsEndpointAggregator."""
  
      @classmethod
      def create(cls, model: str, model_uuid: str, application: str, unit: str):
          """Factory method for creating the `AggregatorTopology` dataclass from a given charm.
  
          Args:
              model: a string representing the model
              model_uuid: the model UUID as a string
              application: the application name
              unit: the unit name
  
          Returns:
              a `AggregatorTopology` object.
          """
          return cls(
              model=model,
              model_uuid=model_uuid,
              application=application,
              unit=unit,
          )
  
      def as_promql_label_dict(self):
          """Format the topology information into a dict with keys having 'juju_' as prefix."""
          vals = {"juju_{}".format(key): val for key, val in self.as_dict().items()}
  
          # FIXME: Why is this different? I have no idea. The uuid length should be the same
          vals["juju_model_uuid"] = vals["juju_model_uuid"][:7]
  
          return vals
  
  
  class ProviderTopology(JujuTopology):
      """Class for initializing topology information for MetricsEndpointProvider."""
  
      @property
      def scrape_identifier(self):
          """Format the topology information into a scrape identifier."""
          # This is used only by Metrics[Consumer|Provider] and does not need a
          # unit name, so only check for the charm name
          return "juju_{}_prometheus_scrape".format(self.identifier)
  
  
  class InvalidAlertRulePathError(Exception):
      """Raised if the alert rules folder cannot be found or is otherwise invalid."""
  
      def __init__(
          self,
          alert_rules_absolute_path: Path,
          message: str,
      ):
          self.alert_rules_absolute_path = alert_rules_absolute_path
          self.message = message
  
          super().__init__(self.message)
  
  
  def _is_official_alert_rule_format(rules_dict: dict) -> bool:
      """Are alert rules in the upstream format as supported by Prometheus.
  
      Alert rules in dictionary format are in "official" form if they
      contain a "groups" key, since this implies they contain a list of
      alert rule groups.
  
      Args:
          rules_dict: a set of alert rules in Python dictionary format
  
      Returns:
          True if alert rules are in official Prometheus file format.
      """
      return "groups" in rules_dict
  
  
  def _is_single_alert_rule_format(rules_dict: dict) -> bool:
      """Are alert rules in single rule format.
  
      The Prometheus charm library supports reading of alert rules in a
      custom format that consists of a single alert rule per file. This
      does not conform to the official Prometheus alert rule file format
      which requires that each alert rules file consists of a list of
      alert rule groups and each group consists of a list of alert
      rules.
  
      Alert rules in dictionary form are considered to be in single rule
      format if in the least it contains two keys corresponding to the
      alert rule name and alert expression.
  
      Returns:
          True if alert rule is in single rule file format.
      """
      # one alert rule per file
      return set(rules_dict) >= {"alert", "expr"}
  
  
  class AlertRules:
      """Utility class for amalgamating prometheus alert rule files and injecting juju topology.
  
      An `AlertRules` object supports aggregating alert rules from files and directories in both
      official and single rule file formats using the `add_path()` method. All the alert rules
      read are annotated with Juju topology labels and amalgamated into a single data structure
      in the form of a Python dictionary using the `as_dict()` method. Such a dictionary can be
      easily dumped into JSON format and exchanged over relation data. The dictionary can also
      be dumped into YAML format and written directly into an alert rules file that is read by
      Prometheus. Note that multiple `AlertRules` objects must not be written into the same file,
      since Prometheus allows only a single list of alert rule groups per alert rules file.
  
      The official Prometheus format is a YAML file conforming to the Prometheus documentation
      (https://prometheus.io/docs/prometheus/latest/configuration/alerting_rules/).
      The custom single rule format is a subsection of the official YAML, having a single alert
      rule, effectively "one alert per file".
      """
  
      # This class uses the following terminology for the various parts of a rule file:
      # - alert rules file: the entire groups[] yaml, including the "groups:" key.
      # - alert groups (plural): the list of groups[] (a list, i.e. no "groups:" key) - it is a list
      #   of dictionaries that have the "name" and "rules" keys.
      # - alert group (singular): a single dictionary that has the "name" and "rules" keys.
      # - alert rules (plural): all the alerts in a given alert group - a list of dictionaries with
      #   the "alert" and "expr" keys.
      # - alert rule (singular): a single dictionary that has the "alert" and "expr" keys.
  
      def __init__(self, topology: Optional[JujuTopology] = None):
          """Build and alert rule object.
  
          Args:
              topology: an optional `JujuTopology` instance that is used to annotate all alert rules.
          """
          self.topology = topology
          self.alert_groups = []  # type: List[dict]
  
      def _from_file(self, root_path: Path, file_path: Path) -> List[dict]:
          """Read a rules file from path, injecting juju topology.
  
          Args:
              root_path: full path to the root rules folder (used only for generating group name)
              file_path: full path to a *.rule file.
  
          Returns:
              A list of dictionaries representing the rules file, if file is valid (the structure is
              formed by `yaml.safe_load` of the file); an empty list otherwise.
          """
          with file_path.open() as rf:
              # Load a list of rules from file then add labels and filters
              try:
                  rule_file = yaml.safe_load(rf)
  
              except Exception as e:
                  logger.error("Failed to read alert rules from %s: %s", file_path.name, e)
                  return []
  
              if _is_official_alert_rule_format(rule_file):
                  alert_groups = rule_file["groups"]
              elif _is_single_alert_rule_format(rule_file):
                  # convert to list of alert groups
                  # group name is made up from the file name
                  alert_groups = [{"name": file_path.stem, "rules": [rule_file]}]
              else:
                  # invalid/unsupported
                  logger.error("Invalid rules file: %s", file_path.name)
                  return []
  
              # update rules with additional metadata
              for alert_group in alert_groups:
                  # update group name with topology and sub-path
                  alert_group["name"] = self._group_name(
                      str(root_path),
                      str(file_path),
                      alert_group["name"],
                  )
  
                  # add "juju_" topology labels
                  for alert_rule in alert_group["rules"]:
                      if "labels" not in alert_rule:
                          alert_rule["labels"] = {}
  
                      if self.topology:
                          alert_rule["labels"].update(self.topology.as_promql_label_dict())
                          # insert juju topology filters into a prometheus alert rule
                          alert_rule["expr"] = self.topology.render(alert_rule["expr"])
  
              return alert_groups
  
      def _group_name(self, root_path: str, file_path: str, group_name: str) -> str:
          """Generate group name from path and topology.
  
          The group name is made up of the relative path between the root dir_path, the file path,
          and topology identifier.
  
          Args:
              root_path: path to the root rules dir.
              file_path: path to rule file.
              group_name: original group name to keep as part of the new augmented group name
  
          Returns:
              New group name, augmented by juju topology and relative path.
          """
          rel_path = os.path.relpath(os.path.dirname(file_path), root_path)
          rel_path = "" if rel_path == "." else rel_path.replace(os.path.sep, "_")
  
          # Generate group name:
          #  - name, from juju topology
          #  - suffix, from the relative path of the rule file;
          group_name_parts = [self.topology.identifier] if self.topology else []
          group_name_parts.extend([rel_path, group_name, "alerts"])
          # filter to remove empty strings
          return "_".join(filter(None, group_name_parts))
  
      @classmethod
      def _multi_suffix_glob(
          cls, dir_path: Path, suffixes: List[str], recursive: bool = True
      ) -> list:
          """Helper function for getting all files in a directory that have a matching suffix.
  
          Args:
              dir_path: path to the directory to glob from.
              suffixes: list of suffixes to include in the glob (items should begin with a period).
              recursive: a flag indicating whether a glob is recursive (nested) or not.
  
          Returns:
              List of files in `dir_path` that have one of the suffixes specified in `suffixes`.
          """
          all_files_in_dir = dir_path.glob("**/*" if recursive else "*")
          return list(filter(lambda f: f.is_file() and f.suffix in suffixes, all_files_in_dir))
  
      def _from_dir(self, dir_path: Path, recursive: bool) -> List[dict]:
          """Read all rule files in a directory.
  
          All rules from files for the same directory are loaded into a single
          group. The generated name of this group includes juju topology.
          By default, only the top directory is scanned; for nested scanning, pass `recursive=True`.
  
          Args:
              dir_path: directory containing *.rule files (alert rules without groups).
              recursive: flag indicating whether to scan for rule files recursively.
  
          Returns:
              a list of dictionaries representing prometheus alert rule groups, each dictionary
              representing an alert group (structure determined by `yaml.safe_load`).
          """
          alert_groups = []  # type: List[dict]
  
          # Gather all alerts into a list of groups
          for file_path in self._multi_suffix_glob(dir_path, [".rule", ".rules"], recursive):
              alert_groups_from_file = self._from_file(dir_path, file_path)
              if alert_groups_from_file:
                  logger.debug("Reading alert rule from %s", file_path)
                  alert_groups.extend(alert_groups_from_file)
  
          return alert_groups
  
      def add_path(self, path: str, *, recursive: bool = False) -> None:
          """Add rules from a dir path.
  
          All rules from files are aggregated into a data structure representing a single rule file.
          All group names are augmented with juju topology.
  
          Args:
              path: either a rules file or a dir of rules files.
              recursive: whether to read files recursively or not (no impact if `path` is a file).
  
          Returns:
              True if path was added else False.
          """
          path = Path(path)  # type: Path
          if path.is_dir():
              self.alert_groups.extend(self._from_dir(path, recursive))
          elif path.is_file():
              self.alert_groups.extend(self._from_file(path.parent, path))
          else:
              logger.warning("path does not exist: %s", path)
  
      def as_dict(self) -> dict:
          """Return standard alert rules file in dict representation.
  
          Returns:
              a dictionary containing a single list of alert rule groups.
              The list of alert rule groups is provided as value of the
              "groups" dictionary key.
          """
          return {"groups": self.alert_groups} if self.alert_groups else {}
  
  
  class TargetsChangedEvent(EventBase):
      """Event emitted when Prometheus scrape targets change."""
  
      def __init__(self, handle, relation_id):
          super().__init__(handle)
          self.relation_id = relation_id
  
      def snapshot(self):
          """Save scrape target relation information."""
          return {"relation_id": self.relation_id}
  
      def restore(self, snapshot):
          """Restore scrape target relation information."""
          self.relation_id = snapshot["relation_id"]
  
  
  class MonitoringEvents(ObjectEvents):
      """Event descriptor for events raised by `MetricsEndpointConsumer`."""
  
      targets_changed = EventSource(TargetsChangedEvent)
  
  
  class MetricsEndpointConsumer(Object):
      """A Prometheus based Monitoring service."""
  
      on = MonitoringEvents()
  
      def __init__(self, charm: CharmBase, relation_name: str = DEFAULT_RELATION_NAME):
          """A Prometheus based Monitoring service.
  
          Args:
              charm: a `CharmBase` instance that manages this
                  instance of the Prometheus service.
              relation_name: an optional string name of the relation between `charm`
                  and the Prometheus charmed service. The default is "metrics-endpoint".
                  It is strongly advised not to change the default, so that people
                  deploying your charm will have a consistent experience with all
                  other charms that consume metrics endpoints.
  
          Raises:
              RelationNotFoundError: If there is no relation in the charm's metadata.yaml
                  with the same name as provided via `relation_name` argument.
              RelationInterfaceMismatchError: The relation with the same name as provided
                  via `relation_name` argument does not have the `prometheus_scrape` relation
                  interface.
              RelationRoleMismatchError: If the relation with the same name as provided
                  via `relation_name` argument does not have the `RelationRole.requires`
                  role.
          """
          _validate_relation_by_interface_and_direction(
              charm, relation_name, RELATION_INTERFACE_NAME, RelationRole.requires
          )
  
          super().__init__(charm, relation_name)
          self._charm = charm
          self._relation_name = relation_name
          self._transformer = PromqlTransformer(self._charm)
          events = self._charm.on[relation_name]
          self.framework.observe(events.relation_changed, self._on_metrics_provider_relation_changed)
          self.framework.observe(
              events.relation_departed, self._on_metrics_provider_relation_departed
          )
  
      def _on_metrics_provider_relation_changed(self, event):
          """Handle changes with related metrics providers.
  
          Anytime there are changes in relations between Prometheus
          and metrics provider charms the Prometheus charm is informed,
          through a `TargetsChangedEvent` event. The Prometheus charm can
          then choose to update its scrape configuration.
  
          Args:
              event: a `CharmEvent` in response to which the Prometheus
                  charm must update its scrape configuration.
          """
          rel_id = event.relation.id
  
          self.on.targets_changed.emit(relation_id=rel_id)
  
      def _on_metrics_provider_relation_departed(self, event):
          """Update job config when a metrics provider departs.
  
          When a metrics provider departs the Prometheus charm is informed
          through a `TargetsChangedEvent` event so that it can update its
          scrape configuration to ensure that the departed metrics provider
          is removed from the list of scrape jobs and
  
          Args:
              event: a `CharmEvent` that indicates a metrics provider
                 unit has departed.
          """
          rel_id = event.relation.id
          self.on.targets_changed.emit(relation_id=rel_id)
  
      def jobs(self) -> list:
          """Fetch the list of scrape jobs.
  
          Returns:
              A list consisting of all the static scrape configurations
              for each related `MetricsEndpointProvider` that has specified
              its scrape targets.
          """
          scrape_jobs = []
  
          for relation in self._charm.model.relations[self._relation_name]:
              static_scrape_jobs = self._static_scrape_config(relation)
              if static_scrape_jobs:
                  scrape_jobs.extend(static_scrape_jobs)
  
          return scrape_jobs
  
      def alerts(self) -> dict:
          """Fetch alerts for all relations.
  
          A Prometheus alert rules file consists of a list of "groups". Each
          group consists of a list of alerts (`rules`) that are sequentially
          executed. This method returns all the alert rules provided by each
          related metrics provider charm. These rules may be used to generate a
          separate alert rules file for each relation since the returned list
          of alert groups are indexed by that relations Juju topology identifier.
          The Juju topology identifier string includes substrings that identify
          alert rule related metadata such as the Juju model, model UUID and the
          application name from where the alert rule originates. Since this
          topology identifier is globally unique, it may be used for instance as
          the name for the file into which the list of alert rule groups are
          written. For each relation, the structure of data returned is a dictionary
          representation of a standard prometheus rules file:
  
          {"groups": [{"name": ...}, ...]}
  
          per official prometheus documentation
          https://prometheus.io/docs/prometheus/latest/configuration/alerting_rules/
  
          The value of the `groups` key is such that it may be used to generate
          a Prometheus alert rules file directly using `yaml.dump` but the
          `groups` key itself must be included as this is required by Prometheus.
  
          For example the list of alert rule groups returned by this method may
          be written into files consumed by Prometheus as follows
  
          ```
          for topology_identifier, alert_rule_groups in self.metrics_consumer.alerts().items():
              filename = "juju_" + topology_identifier + ".rules"
              path = os.path.join(PROMETHEUS_RULES_DIR, filename)
              rules = yaml.dump(alert_rule_groups)
              container.push(path, rules, make_dirs=True)
          ```
  
          Returns:
              A dictionary mapping the Juju topology identifier of the source charm to
              its list of alert rule groups.
          """
          alerts = {}  # type: Dict[str, dict] # mapping b/w juju identifiers and alert rule files
          for relation in self._charm.model.relations[self._relation_name]:
              if not relation.units:
                  continue
  
              alert_rules = json.loads(relation.data[relation.app].get("alert_rules", "{}"))
              if not alert_rules:
                  continue
  
              identifier = None
              try:
                  scrape_metadata = json.loads(relation.data[relation.app]["scrape_metadata"])
                  identifier = ProviderTopology.from_relation_data(scrape_metadata).identifier
                  alerts[identifier] = self._transformer.apply_label_matchers(alert_rules)
  
              except KeyError as e:
                  logger.debug(
                      "Relation %s has no 'scrape_metadata': %s",
                      relation.id,
                      e,
                  )
                  identifier = self._get_identifier_by_alert_rules(alert_rules)
  
              if not identifier:
                  logger.error(
                      "Alert rules were found but no usable group or identifier was present"
                  )
                  continue
              alerts[identifier] = alert_rules
  
          return alerts
  
      def _get_identifier_by_alert_rules(self, rules: dict) -> Union[str, None]:
          """Determine an appropriate dict key for alert rules.
  
          The key is used as the filename when writing alerts to disk, so the structure
          and uniqueness is important.
  
          Args:
              rules: a dict of alert rules
          """
          if "groups" not in rules:
              logger.warning("No alert groups were found in relation data")
              return None
  
          # Construct an ID based on what's in the alert rules if they have labels
          for group in rules["groups"]:
              try:
                  labels = group["rules"][0]["labels"]
                  identifier = "{}_{}_{}".format(
                      labels["juju_model"],
                      labels["juju_model_uuid"],
                      labels["juju_application"],
                  )
                  return identifier
              except KeyError:
                  logger.debug("Alert rules were found but no usable labels were present")
                  continue
  
          logger.warning(
              "No labeled alert rules were found, and no 'scrape_metadata' "
              "was available. Using the alert group name as filename."
          )
          try:
              for group in rules["groups"]:
                  return group["name"]
          except KeyError:
              logger.debug("No group name was found to use as identifier")
  
          return None
  
      def _static_scrape_config(self, relation) -> list:
          """Generate the static scrape configuration for a single relation.
  
          If the relation data includes `scrape_metadata` then the value
          of this key is used to annotate the scrape jobs with Juju
          Topology labels before returning them.
  
          Args:
              relation: an `ops.model.Relation` object whose static
                  scrape configuration is required.
  
          Returns:
              A list (possibly empty) of scrape jobs. Each job is a
              valid Prometheus scrape configuration for that job,
              represented as a Python dictionary.
          """
          if not relation.units:
              return []
  
          scrape_jobs = json.loads(relation.data[relation.app].get("scrape_jobs", "[]"))
  
          if not scrape_jobs:
              return []
  
          scrape_metadata = json.loads(relation.data[relation.app].get("scrape_metadata", "{}"))
  
          if not scrape_metadata:
              return scrape_jobs
  
          job_name_prefix = ProviderTopology.from_relation_data(scrape_metadata).scrape_identifier
  
          hosts = self._relation_hosts(relation)
  
          labeled_job_configs = []
          for job in scrape_jobs:
              config = self._labeled_static_job_config(
                  _sanitize_scrape_configuration(job),
                  job_name_prefix,
                  hosts,
                  scrape_metadata,
              )
              labeled_job_configs.append(config)
  
          return labeled_job_configs
  
      def _relation_hosts(self, relation) -> dict:
          """Fetch unit names and address of all metrics provider units for a single relation.
  
          Args:
              relation: An `ops.model.Relation` object for which the unit name to
                  address mapping is required.
  
          Returns:
              A dictionary that maps unit names to unit addresses for
              the specified relation.
          """
          hosts = {}
          for unit in relation.units:
              # TODO deprecate and remove unit.name
              unit_name = relation.data[unit].get("prometheus_scrape_unit_name") or unit.name
              # TODO deprecate and remove "prometheus_scrape_host"
              unit_address = relation.data[unit].get(
                  "prometheus_scrape_unit_address"
              ) or relation.data[unit].get("prometheus_scrape_host")
              if unit_name and unit_address:
                  hosts.update({unit_name: unit_address})
  
          return hosts
  
      def _labeled_static_job_config(self, job, job_name_prefix, hosts, scrape_metadata) -> dict:
          """Construct labeled job configuration for a single job.
  
          Args:
  
              job: a dictionary representing the job configuration as obtained from
                  `MetricsEndpointProvider` over relation data.
              job_name_prefix: a string that may either be used as the
                  job name if the job has no associated name or used as a prefix for
                  the job if it does have a job name.
              hosts: a dictionary mapping host names to host address for
                  all units of the relation for which this job configuration
                  must be constructed.
              scrape_metadata: scrape configuration metadata obtained
                  from `MetricsEndpointProvider` from the same relation for
                  which this job configuration is being constructed.
  
          Returns:
              A dictionary representing a Prometheus job configuration
              for a single job.
          """
          name = job.get("job_name")
          job_name = "{}_{}".format(job_name_prefix, name) if name else job_name_prefix
  
          labeled_job = job.copy()
          labeled_job["job_name"] = job_name
  
          static_configs = job.get("static_configs")
          labeled_job["static_configs"] = []
  
          # relabel instance labels so that instance identifiers are globally unique
          # stable over unit recreation
          instance_relabel_config = {
              "source_labels": ["juju_model", "juju_model_uuid", "juju_application"],
              "separator": "_",
              "target_label": "instance",
              "regex": "(.*)",
          }
  
          # label all static configs in the Prometheus job
          # labeling inserts Juju topology information and
          # sets a relable config for instance labels
          for static_config in static_configs:
              labels = static_config.get("labels", {}) if static_configs else {}
              all_targets = static_config.get("targets", [])
  
              # split all targets into those which will have unit labels
              # and those which will not
              ports = []
              unitless_targets = []
              for target in all_targets:
                  host, port = target.split(":")
                  if host.strip() == "*":
                      ports.append(port.strip())
                  else:
                      unitless_targets.append(target)
  
              # label scrape targets that do not have unit labels
              if unitless_targets:
                  unitless_config = self._labeled_unitless_config(
                      unitless_targets, labels, scrape_metadata
                  )
                  labeled_job["static_configs"].append(unitless_config)
  
              # label scrape targets that do have unit labels
              for host_name, host_address in hosts.items():
                  static_config = self._labeled_unit_config(
                      host_name, host_address, ports, labels, scrape_metadata
                  )
                  labeled_job["static_configs"].append(static_config)
                  if "juju_unit" not in instance_relabel_config["source_labels"]:
                      instance_relabel_config["source_labels"].append("juju_unit")  # type: ignore
  
          # ensure topology relabeling of instance label is last in order of relabelings
          relabel_configs = job.get("relabel_configs", [])
          relabel_configs.append(instance_relabel_config)
          labeled_job["relabel_configs"] = relabel_configs
  
          return labeled_job
  
      def _set_juju_labels(self, labels, scrape_metadata) -> dict:
          """Create a copy of metric labels with Juju topology information.
  
          Args:
              labels: a dictionary containing Prometheus metric labels.
              scrape_metadata: scrape related metadata provided by
                  `MetricsEndpointProvider`.
  
          Returns:
              a copy of the `labels` dictionary augmented with Juju
              topology information with the exception of unit name.
          """
          juju_labels = labels.copy()  # deep copy not needed
          juju_labels.update(
              ProviderTopology.from_relation_data(scrape_metadata).as_promql_label_dict()
          )
  
          return juju_labels
  
      def _labeled_unitless_config(self, targets, labels, scrape_metadata) -> dict:
          """Static scrape configuration for fully qualified host addresses.
  
          Fully qualified hosts are those scrape targets for which the
          address are specified by the `MetricsEndpointProvider` as part
          of the scrape job specification set in application relation data.
          The address specified need not belong to any unit of the
          `MetricsEndpointProvider` charm. As a result there is no reliable
          way to determine the name (Juju topology unit name) for such a
          target.
  
          Args:
              targets: a list of addresses of fully qualified hosts.
              labels: labels specified by `MetricsEndpointProvider` clients
                   which are associated with `targets`.
              scrape_metadata: scrape related metadata provided by `MetricsEndpointProvider`.
  
          Returns:
              A dictionary containing the static scrape configuration
              for a list of fully qualified hosts.
          """
          juju_labels = self._set_juju_labels(labels, scrape_metadata)
          unitless_config = {"targets": targets, "labels": juju_labels}
          return unitless_config
  
      def _labeled_unit_config(
          self, unit_name, host_address, ports, labels, scrape_metadata
      ) -> dict:
          """Static scrape configuration for a wildcard host.
  
          Wildcard hosts are those scrape targets whose name (Juju unit
          name) and address (unit IP address) is set into unit relation
          data by the `MetricsEndpointProvider` charm, which sets this
          data for ALL its units.
  
          Args:
              unit_name: a string representing the unit name of the wildcard host.
              host_address: a string representing the address of the wildcard host.
              ports: list of ports on which this wildcard host exposes its metrics.
              labels: a dictionary of labels provided by
                  `MetricsEndpointProvider` intended to be associated with
                  this wildcard host.
              scrape_metadata: scrape related metadata provided by `MetricsEndpointProvider`.
  
          Returns:
              A dictionary containing the static scrape configuration
              for a single wildcard host.
          """
          juju_labels = self._set_juju_labels(labels, scrape_metadata)
  
          juju_labels["juju_unit"] = unit_name
  
          static_config = {"labels": juju_labels}
  
          if ports:
              targets = []
              for port in ports:
                  targets.append("{}:{}".format(host_address, port))
              static_config["targets"] = targets  # type: ignore
          else:
              static_config["targets"] = [host_address]  # type: ignore
  
          return static_config
  
  
  def _resolve_dir_against_charm_path(charm: CharmBase, *path_elements: str) -> str:
      """Resolve the provided path items against the directory of the main file.
  
      Look up the directory of the `main.py` file being executed. This is normally
      going to be the charm.py file of the charm including this library. Then, resolve
      the provided path elements and, if the result path exists and is a directory,
      return its absolute path; otherwise, raise en exception.
  
      Raises:
          InvalidAlertRulePathError, if the path does not exist or is not a directory.
      """
      charm_dir = Path(str(charm.charm_dir))
      if not charm_dir.exists() or not charm_dir.is_dir():
          # Operator Framework does not currently expose a robust
          # way to determine the top level charm source directory
          # that is consistent across deployed charms and unit tests
          # Hence for unit tests the current working directory is used
          # TODO: updated this logic when the following ticket is resolved
          # https://github.com/canonical/operator/issues/643
          charm_dir = Path(os.getcwd())
  
      alerts_dir_path = charm_dir.absolute().joinpath(*path_elements)
  
      if not alerts_dir_path.exists():
          raise InvalidAlertRulePathError(alerts_dir_path, "directory does not exist")
      if not alerts_dir_path.is_dir():
          raise InvalidAlertRulePathError(alerts_dir_path, "is not a directory")
  
      return str(alerts_dir_path)
  
  
  class MetricsEndpointProvider(Object):
      """A metrics endpoint for Prometheus."""
  
      def __init__(
          self,
          charm,
          relation_name: str = DEFAULT_RELATION_NAME,
          jobs=None,
          alert_rules_path: str = DEFAULT_ALERT_RULES_RELATIVE_PATH,
      ):
          """Construct a metrics provider for a Prometheus charm.
  
          If your charm exposes a Prometheus metrics endpoint, the
          `MetricsEndpointProvider` object enables your charm to easily
          communicate how to reach that metrics endpoint.
  
          By default, a charm instantiating this object has the metrics
          endpoints of each of its units scraped by the related Prometheus
          charms. The scraped metrics are automatically tagged by the
          Prometheus charms with Juju topology data via the
          `juju_model_name`, `juju_model_uuid`, `juju_application_name`
          and `juju_unit` labels. To support such tagging `MetricsEndpointProvider`
          automatically forwards scrape metadata to a `MetricsEndpointConsumer`
          (Prometheus charm).
  
          Scrape targets provided by `MetricsEndpointProvider` can be
          customized when instantiating this object. For example in the
          case of a charm exposing the metrics endpoint for each of its
          units on port 8080 and the `/metrics` path, the
          `MetricsEndpointProvider` can be instantiated as follows:
  
              self.metrics_endpoint_provider = MetricsEndpointProvider(
                  self,
                  jobs=[{
                      "static_configs": [{"targets": ["*:8080"]}],
                  }])
  
          The notation `*:<port>` means "scrape each unit of this charm on port
          `<port>`.
  
          In case the metrics endpoints are not on the standard `/metrics` path,
          a custom path can be specified as follows:
  
              self.metrics_endpoint_provider = MetricsEndpointProvider(
                  self,
                  jobs=[{
                      "metrics_path": "/my/strange/metrics/path",
                      "static_configs": [{"targets": ["*:8080"]}],
                  }])
  
          Note how the `jobs` argument is a list: this allows you to expose multiple
          combinations of paths "metrics_path" and "static_configs" in case your charm
          exposes multiple endpoints, which could happen, for example, when you have
          multiple workload containers, with applications in each needing to be scraped.
          The structure of the objects in the `jobs` list is one-to-one with the
          `scrape_config` configuration item of Prometheus' own configuration (see
          https://prometheus.io/docs/prometheus/latest/configuration/configuration/#scrape_config
          ), but with only a subset of the fields allowed. The permitted fields are
          listed in `ALLOWED_KEYS` object in this charm library module.
  
          It is also possible to specify alert rules. By default, this library will look
          into the `<charm_parent_dir>/prometheus_alert_rules`, which in a standard charm
          layouts resolves to `src/prometheus_alert_rules`. Each alert rule goes into a
          separate `*.rule` file. If the syntax of a rule is invalid,
          the  `MetricsEndpointProvider` logs an error and does not load the particular
          rule.
  
          To avoid false positives and negatives in the evaluation of alert rules,
          all ingested alert rule expressions are automatically qualified using Juju
          Topology filters. This ensures that alert rules provided by your charm, trigger
          alerts based only on data scrapped from your charm. For example an alert rule
          such as the following
  
              alert: UnitUnavailable
              expr: up < 1
              for: 0m
  
          will be automatically transformed into something along the lines of the following
  
              alert: UnitUnavailable
              expr: up{juju_model=<model>, juju_model_uuid=<uuid-prefix>, juju_application=<app>} < 1
              for: 0m
  
          Args:
              charm: a `CharmBase` object that manages this
                  `MetricsEndpointProvider` object. Typically this is
                  `self` in the instantiating class.
              relation_name: an optional string name of the relation between `charm`
                  and the Prometheus charmed service. The default is "metrics-endpoint".
                  It is strongly advised not to change the default, so that people
                  deploying your charm will have a consistent experience with all
                  other charms that provide metrics endpoints.
              jobs: an optional list of dictionaries where each
                  dictionary represents the Prometheus scrape
                  configuration for a single job. When not provided, a
                  default scrape configuration is provided for the
                  `/metrics` endpoint polling all units of the charm on port `80`
                  using the `MetricsEndpointProvider` object.
              alert_rules_path: an optional path for the location of alert rules
                  files.  Defaults to "./prometheus_alert_rules",
                  resolved relative to the directory hosting the charm entry file.
                  The alert rules are automatically updated on charm upgrade.
  
          Raises:
              RelationNotFoundError: If there is no relation in the charm's metadata.yaml
                  with the same name as provided via `relation_name` argument.
              RelationInterfaceMismatchError: The relation with the same name as provided
                  via `relation_name` argument does not have the `prometheus_scrape` relation
                  interface.
              RelationRoleMismatchError: If the relation with the same name as provided
                  via `relation_name` argument does not have the `RelationRole.provides`
                  role.
          """
          _validate_relation_by_interface_and_direction(
              charm, relation_name, RELATION_INTERFACE_NAME, RelationRole.provides
          )
  
          try:
              alert_rules_path = _resolve_dir_against_charm_path(charm, alert_rules_path)
          except InvalidAlertRulePathError as e:
              logger.warning(
                  "Invalid Prometheus alert rules folder at %s: %s",
                  e.alert_rules_absolute_path,
                  e.message,
              )
  
          super().__init__(charm, relation_name)
          self.topology = ProviderTopology.from_charm(charm)
  
          self._charm = charm
          self._alert_rules_path = alert_rules_path
          self._relation_name = relation_name
          # sanitize job configurations to the supported subset of parameters
          jobs = [] if jobs is None else jobs
          self._jobs = [_sanitize_scrape_configuration(job) for job in jobs]
  
          events = self._charm.on[self._relation_name]
          self.framework.observe(events.relation_joined, self._set_scrape_job_spec)
          self.framework.observe(events.relation_changed, self._set_scrape_job_spec)
  
          # dirty fix: set the ip address when the containers start, as a workaround
          # for not being able to lookup the pod ip
          for container_name in charm.unit.containers:
              self.framework.observe(
                  charm.on[container_name].pebble_ready,
                  self._set_unit_ip,
              )
  
          self.framework.observe(self._charm.on.upgrade_charm, self._set_scrape_job_spec)
  
      def _set_scrape_job_spec(self, event):
          """Ensure scrape target information is made available to prometheus.
  
          When a metrics provider charm is related to a prometheus charm, the
          metrics provider sets specification and metadata related to its own
          scrape configuration. This information is set using Juju application
          data. In addition each of the consumer units also sets its own
          host address in Juju unit relation data.
          """
          self._set_unit_ip(event)
  
          if not self._charm.unit.is_leader():
              return
  
          alert_rules = AlertRules(topology=self.topology)
          alert_rules.add_path(self._alert_rules_path, recursive=True)
          alert_rules_as_dict = alert_rules.as_dict()
  
          for relation in self._charm.model.relations[self._relation_name]:
              relation.data[self._charm.app]["scrape_metadata"] = json.dumps(self._scrape_metadata)
              relation.data[self._charm.app]["scrape_jobs"] = json.dumps(self._scrape_jobs)
  
              if alert_rules_as_dict:
                  # Update relation data with the string representation of the rule file.
                  # Juju topology is already included in the "scrape_metadata" field above.
                  # The consumer side of the relation uses this information to name the rules file
                  # that is written to the filesystem.
                  relation.data[self._charm.app]["alert_rules"] = json.dumps(alert_rules_as_dict)
  
      def _set_unit_ip(self, _):
          """Set unit host address.
  
          Each time a metrics provider charm container is restarted it updates its own
          host address in the unit relation data for the prometheus charm.
  
          The only argument specified is an event and it ignored. this is for expediency
          to be able to use this method as an event handler, although no access to the
          event is actually needed.
          """
          for relation in self._charm.model.relations[self._relation_name]:
              relation.data[self._charm.unit]["prometheus_scrape_unit_address"] = str(
                  self._charm.model.get_binding(relation).network.bind_address
              )
              relation.data[self._charm.unit]["prometheus_scrape_unit_name"] = str(
                  self._charm.model.unit.name
              )
  
      @property
      def _scrape_jobs(self) -> list:
          """Fetch list of scrape jobs.
  
          Returns:
             A list of dictionaries, where each dictionary specifies a
             single scrape job for Prometheus.
          """
          return self._jobs if self._jobs else [DEFAULT_JOB]
  
      @property
      def _scrape_metadata(self) -> dict:
          """Generate scrape metadata.
  
          Returns:
              Scrape configuration metadata for this metrics provider charm.
          """
          return self.topology.as_dict()
  
  
  class PrometheusRulesProvider(Object):
      """Forward rules to Prometheus.
  
      This object may be used to forward rules to Prometheus. At present it only supports
      forwarding alert rules. This is unlike :class:`MetricsEndpointProvider`, which
      is used for forwarding both scrape targets and associated alert rules. This object
      is typically used when there is a desire to forward rules that apply globally (across
      all deployed charms and units) rather than to a single charm. All rule files are
      forwarded using the same 'prometheus_scrape' interface that is also used by
      `MetricsEndpointProvider`.
  
      Args:
          charm: A charm instance that `provides` a relation with the `prometheus_scrape` interface.
          relation_name: Name of the relation in `metadata.yaml` that
              has the `prometheus_scrape` interface.
          dir_path: Root directory for the collection of rule files.
          recursive: Whether or not to scan for rule files recursively.
      """
  
      def __init__(
          self,
          charm: CharmBase,
          relation_name: str = DEFAULT_RELATION_NAME,
          dir_path: str = DEFAULT_ALERT_RULES_RELATIVE_PATH,
          recursive=True,
      ):
          super().__init__(charm, relation_name)
          self._charm = charm
          self._relation_name = relation_name
          self.topology = ProviderTopology.from_charm(charm)
          self._recursive = recursive
  
          try:
              dir_path = _resolve_dir_against_charm_path(charm, dir_path)
          except InvalidAlertRulePathError as e:
              logger.warning(
                  "Invalid Prometheus alert rules folder at %s: %s",
                  e.alert_rules_absolute_path,
                  e.message,
              )
          self.dir_path = dir_path
  
          events = self._charm.on[self._relation_name]
          event_sources = [
              events.relation_joined,
              events.relation_changed,
              self._charm.on.leader_elected,
              self._charm.on.upgrade_charm,
          ]
  
          for event_source in event_sources:
              self.framework.observe(event_source, self._update_relation_data)
  
      def _reinitialize_alert_rules(self):
          """Reloads alert rules and updates all relations."""
          self._update_relation_data(None)
  
      def _update_relation_data(self, _):
          """Update application relation data with alert rules for all relations."""
          if not self._charm.unit.is_leader():
              return
  
          alert_rules = AlertRules()
          alert_rules.add_path(self.dir_path, recursive=self._recursive)
          alert_rules_as_dict = alert_rules.as_dict()
  
          logger.info("Updating relation data with rule files from disk")
          for relation in self._charm.model.relations[self._relation_name]:
              relation.data[self._charm.app]["alert_rules"] = json.dumps(
                  alert_rules_as_dict,
                  sort_keys=True,  # sort, to prevent unnecessary relation_changed events
              )
  
  
  class MetricsEndpointAggregator(Object):
      """Aggregate metrics from multiple scrape targets.
  
      `MetricsEndpointAggregator` collects scrape target information from one
      or more related charms and forwards this to a `MetricsEndpointConsumer`
      charm, which may be in a different Juju model. However it is
      essential that `MetricsEndpointAggregator` itself resides in the same
      model as its scrape targets, as this is currently the only way to
      ensure in Juju that the `MetricsEndpointAggregator` will be able to
      determine the model name and uuid of the scrape targets.
  
      `MetricsEndpointAggregator` should be used in place of
      `MetricsEndpointProvider` in the following two use cases:
  
      1. Integrating one or more scrape targets that do not support the
      `prometheus_scrape` interface.
  
      2. Integrating one or more scrape targets through cross model
      relations. Although the [Scrape Config Operator](https://charmhub.io/cos-configuration-k8s)
      may also be used for the purpose of supporting cross model
      relations.
  
      Using `MetricsEndpointAggregator` to build a Prometheus charm client
      only requires instantiating it. Instantiating
      `MetricsEndpointAggregator` is similar to `MetricsEndpointProvider` except
      that it requires specifying the names of three relations: the
      relation with scrape targets, the relation for alert rules, and
      that with the Prometheus charms. For example
  
      ```python
      self._aggregator = MetricsEndpointAggregator(
          self,
          {
              "prometheus": "monitoring",
              "scrape_target": "prometheus-target",
              "alert_rules": "prometheus-rules"
          }
      )
      ```
  
      `MetricsEndpointAggregator` assumes that each unit of a scrape target
      sets in its unit-level relation data two entries with keys
      "hostname" and "port". If it is required to integrate with charms
      that do not honor these assumptions, it is always possible to
      derive from `MetricsEndpointAggregator` overriding the `_get_targets()`
      method, which is responsible for aggregating the unit name, host
      address ("hostname") and port of the scrape target.
  
      `MetricsEndpointAggregator` also assumes that each unit of a
      scrape target sets in its unit-level relation data a key named
      "groups". The value of this key is expected to be the string
      representation of list of Prometheus Alert rules in YAML format.
      An example of a single such alert rule is
  
      ```yaml
      - alert: HighRequestLatency
        expr: job:request_latency_seconds:mean5m{job="myjob"} > 0.5
        for: 10m
        labels:
          severity: page
        annotations:
          summary: High request latency
      ```
  
      Once again if it is required to integrate with charms that do not
      honour these assumptions about alert rules then an object derived
      from `MetricsEndpointAggregator` may be used by overriding the
      `_get_alert_rules()` method.
  
      `MetricsEndpointAggregator` ensures that Prometheus scrape job
      specifications and alert rules are annotated with Juju topology
      information, just like `MetricsEndpointProvider` and
      `MetricsEndpointConsumer` do.
  
      By default `MetricsEndpointAggregator` ensures that Prometheus
      "instance" labels refer to Juju topology. This ensures that
      instance labels are stable over unit recreation. While it is not
      advisable to change this option, if required it can be done by
      setting the "relabel_instance" keyword argument to `False` when
      constructing an aggregator object.
      """
  
      def __init__(self, charm, relation_names, relabel_instance=True):
          """Construct a `MetricsEndpointAggregator`.
  
          Args:
              charm: a `CharmBase` object that manages this
                  `MetricsEndpointAggregator` object. Typically this is
                  `self` in the instantiating class.
              relation_names: a dictionary with three keys. The value
                  of the "scrape_target" and "alert_rules" keys are
                  the relation names over which scrape job and alert rule
                  information is gathered by this `MetricsEndpointAggregator`.
                  And the value of the "prometheus" key is the name of
                  the relation with a `MetricsEndpointConsumer` such as
                  the Prometheus charm.
              relabel_instance: A boolean flag indicating if Prometheus
                  scrape job "instance" labels must refer to Juju Topology.
          """
          super().__init__(charm, relation_names["prometheus"])
  
          self._charm = charm
          self._target_relation = relation_names["scrape_target"]
          self._prometheus_relation = relation_names["prometheus"]
          self._alert_rules_relation = relation_names["alert_rules"]
          self._relabel_instance = relabel_instance
  
          # manage Prometheus charm relation events
          prometheus_events = self._charm.on[self._prometheus_relation]
          self.framework.observe(prometheus_events.relation_joined, self._set_prometheus_data)
  
          # manage list of Prometheus scrape jobs from related scrape targets
          target_events = self._charm.on[self._target_relation]
          self.framework.observe(target_events.relation_changed, self._update_prometheus_jobs)
          self.framework.observe(target_events.relation_departed, self._remove_prometheus_jobs)
  
          # manage alert rules for Prometheus from related scrape targets
          alert_rule_events = self._charm.on[self._alert_rules_relation]
          self.framework.observe(alert_rule_events.relation_changed, self._update_alert_rules)
          self.framework.observe(alert_rule_events.relation_departed, self._remove_alert_rules)
  
      def _set_prometheus_data(self, event):
          """Ensure every new Prometheus instances is updated.
  
          Any time a new Prometheus unit joins the relation with
          `MetricsEndpointAggregator`, that Prometheus unit is provided
          with the complete set of existing scrape jobs and alert rules.
          """
          jobs = []  # list of scrape jobs, one per relation
          for relation in self.model.relations[self._target_relation]:
              targets = self._get_targets(relation)
              if targets:
                  jobs.append(self._static_scrape_job(targets, relation.app.name))
  
          groups = []  # list of alert rule groups, one group per relation
          for relation in self.model.relations[self._alert_rules_relation]:
              unit_rules = self._get_alert_rules(relation)
              if unit_rules:
                  appname = relation.app.name
                  rules = self._label_alert_rules(unit_rules, appname)
                  group = {"name": self._group_name(appname), "rules": rules}
                  groups.append(group)
  
          event.relation.data[self._charm.app]["scrape_jobs"] = json.dumps(jobs)
          event.relation.data[self._charm.app]["alert_rules"] = json.dumps({"groups": groups})
  
      def _set_target_job_data(self, targets: dict, app_name: str, **kwargs) -> None:
          """Update scrape jobs in response to scrape target changes.
  
          When there is any change in relation data with any scrape
          target, the Prometheus scrape job, for that specific target is
          updated. Additionally, if this method is called manually, do the
          sameself.
  
          Args:
              targets: a `dict` containing target information
              app_name: a `str` identifying the application
          """
          # new scrape job for the relation that has changed
          updated_job = self._static_scrape_job(targets, app_name, **kwargs)
  
          for relation in self.model.relations[self._prometheus_relation]:
              jobs = json.loads(relation.data[self._charm.app].get("scrape_jobs", "[]"))
              # list of scrape jobs that have not changed
              jobs = [job for job in jobs if updated_job["job_name"] != job["job_name"]]
              jobs.append(updated_job)
              relation.data[self._charm.app]["scrape_jobs"] = json.dumps(jobs)
  
      def _update_prometheus_jobs(self, event):
          """Update scrape jobs in response to scrape target changes.
  
          When there is any change in relation data with any scrape
          target, the Prometheus scrape job, for that specific target is
          updated.
          """
          targets = self._get_targets(event.relation)
          if not targets:
              return
  
          # new scrape job for the relation that has changed
          updated_job = self._static_scrape_job(targets, event.relation.app.name)
  
          for relation in self.model.relations[self._prometheus_relation]:
              jobs = json.loads(relation.data[self._charm.app].get("scrape_jobs", "[]"))
              # list of scrape jobs that have not changed
              jobs = [job for job in jobs if updated_job["job_name"] != job["job_name"]]
              jobs.append(updated_job)
              relation.data[self._charm.app]["scrape_jobs"] = json.dumps(jobs)
  
      def _remove_prometheus_jobs(self, event):
          """Remove scrape jobs when a target departs.
  
          Any time a scrape target departs, any Prometheus scrape job
          associated with that specific scrape target is removed.
          """
          job_name = self._job_name(event.relation.app.name)
          unit_name = event.unit.name
  
          for relation in self.model.relations[self._prometheus_relation]:
              jobs = json.loads(relation.data[self._charm.app].get("scrape_jobs", "[]"))
              if not jobs:
                  continue
  
              changed_job = [j for j in jobs if j.get("job_name") == job_name]
              if not changed_job:
                  continue
              changed_job = changed_job[0]
  
              # list of scrape jobs that have not changed
              jobs = [job for job in jobs if job.get("job_name") != job_name]
  
              # list of scrape jobs for units of the same application that still exist
              configs_kept = [
                  config
                  for config in changed_job["static_configs"]  # type: ignore
                  if config.get("labels", {}).get("juju_unit") != unit_name
              ]
  
              if configs_kept:
                  changed_job["static_configs"] = configs_kept  # type: ignore
                  jobs.append(changed_job)
  
              relation.data[self._charm.app]["scrape_jobs"] = json.dumps(jobs)
  
      def _update_alert_rules(self, event):
          """Update alert rules in response to scrape target changes.
  
          When there is any change in alert rule relation data for any
          scrape target, the list of alert rules for that specific
          target is updated.
          """
          unit_rules = self._get_alert_rules(event.relation)
          if not unit_rules:
              return
  
          appname = event.relation.app.name
          rules = self._label_alert_rules(unit_rules, appname)
          # the alert rule group that has changed
          updated_group = {"name": self._group_name(appname), "rules": rules}
  
          for relation in self.model.relations[self._prometheus_relation]:
              alert_rules = json.loads(relation.data[self._charm.app].get("alert_rules", "{}"))
              groups = alert_rules.get("groups", [])
              # list of alert rule groups that have not changed
              groups = [group for group in groups if updated_group["name"] != group["name"]]
              groups.append(updated_group)
              relation.data[self._charm.app]["alert_rules"] = json.dumps({"groups": groups})
  
      def _remove_alert_rules(self, event):
          """Remove alert rules for departed targets.
  
          Any time a scrape target departs any alert rules associated
          with that specific scrape target is removed.
          """
          group_name = self._group_name(event.relation.app.name)
          unit_name = event.unit.name
  
          for relation in self.model.relations[self._prometheus_relation]:
              alert_rules = json.loads(relation.data[self._charm.app].get("alert_rules", "{}"))
              if not alert_rules:
                  continue
  
              groups = alert_rules.get("groups", [])
              if not groups:
                  continue
  
              changed_group = [group for group in groups if group["name"] == group_name]
              if not changed_group:
                  continue
              changed_group = changed_group[0]
  
              # list of alert rule groups that have not changed
              groups = [group for group in groups if group["name"] != group_name]
  
              # list of alert rules not associated with departing unit
              rules_kept = [
                  rule
                  for rule in changed_group.get("rules")  # type: ignore
                  if rule.get("labels").get("juju_unit") != unit_name
              ]
  
              if rules_kept:
                  changed_group["rules"] = rules_kept  # type: ignore
                  groups.append(changed_group)
  
              relation.data[self._charm.app]["alert_rules"] = (
                  json.dumps({"groups": groups}) if groups else "{}"
              )
  
      def _get_targets(self, relation) -> dict:
          """Fetch scrape targets for a relation.
  
          Scrape target information is returned for each unit in the
          relation. This information contains the unit name, network
          hostname (or address) for that unit, and port on which an
          metrics endpoint is exposed in that unit.
  
          Args:
              relation: an `ops.model.Relation` object for which scrape
                  targets are required.
  
          Returns:
              a dictionary whose keys are names of the units in the
              relation. There values associated with each key is itself
              a dictionary of the form
              ```
              {"hostname": hostname, "port": port}
              ```
          """
          targets = {}
          for unit in relation.units:
              port = relation.data[unit].get("port", 80)
              hostname = relation.data[unit].get("hostname")
              if hostname:
                  targets.update({unit.name: {"hostname": hostname, "port": port}})
  
          return targets
  
      def _get_alert_rules(self, relation) -> dict:
          """Fetch alert rules for a relation.
  
          Each unit of the related scrape target may have its own
          associated alert rules. Alert rules for all units are returned
          indexed by unit name.
  
          Args:
              relation: an `ops.model.Relation` object for which alert
                  rules are required.
  
          Returns:
              a dictionary whose keys are names of the units in the
              relation. There values associated with each key is a list
              of alert rules. Each rule is in dictionary format. The
              structure "rule dictionary" corresponds to single
              Prometheus alert rule.
          """
          rules = {}
          for unit in relation.units:
              unit_rules = yaml.safe_load(relation.data[unit].get("groups", ""))
              if unit_rules:
                  rules.update({unit.name: unit_rules})
  
          return rules
  
      def _job_name(self, appname) -> str:
          """Construct a scrape job name.
  
          Each relation has its own unique scrape job name. All units in
          the relation are scraped as part of the same scrape job.
  
          Args:
              appname: string name of a related application.
  
          Returns:
              a string Prometheus scrape job name for the application.
          """
          return "juju_{}_{}_{}_prometheus_scrape".format(
              self.model.name, self.model.uuid[:7], appname
          )
  
      def _group_name(self, appname) -> str:
          """Construct name for an alert rule group.
  
          Each unit in a relation may define its own alert rules. All
          rules, for all units in a relation are grouped together and
          given a single alert rule group name.
  
          Args:
              appname: string name of a related application.
  
          Returns:
              a string Prometheus alert rules group name for the application.
          """
          return "juju_{}_{}_{}_alert_rules".format(self.model.name, self.model.uuid[:7], appname)
  
      def _label_alert_rules(self, unit_rules, appname) -> list:
          """Apply juju topology labels to alert rules.
  
          Args:
              unit_rules: a list of alert rules, where each rule is in
                  dictionary format.
              appname: a string name of the application to which the
                  alert rules belong.
  
          Returns:
              a list of alert rules with Juju topology labels.
          """
          labeled_rules = []
          for unit_name, rules in unit_rules.items():
              for rule in rules:
                  rule["labels"].update(
                      AggregatorTopology.create(
                          self.model.name, self.model.uuid, appname, unit_name
                      ).as_promql_label_dict()
                  )
                  labeled_rules.append(rule)
  
          return labeled_rules
  
      def _static_scrape_job(self, targets, application_name, **kwargs) -> dict:
          """Construct a static scrape job for an application.
  
          Args:
              targets: a dictionary providing hostname and port for all
                  scrape target. The keys of this dictionary are unit
                  names. Values corresponding to these keys are
                  themselves a dictionary with keys "hostname" and
                  "port".
              application_name: a string name of the application for
                  which this static scrape job is being constructed.
  
          Returns:
              A dictionary corresponding to a Prometheus static scrape
              job configuration for one application. The returned
              dictionary may be transformed into YAML and appended to
              the list of any existing list of Prometheus static configs.
          """
          juju_model = self.model.name
          juju_model_uuid = self.model.uuid
          job = {
              "job_name": self._job_name(application_name),
              "static_configs": [
                  {
                      "targets": ["{}:{}".format(target["hostname"], target["port"])],
                      "labels": {
                          "juju_model": juju_model,
                          "juju_model_uuid": juju_model_uuid,
                          "juju_application": application_name,
                          "juju_unit": unit_name,
                          "host": target["hostname"],
                      },
                  }
                  for unit_name, target in targets.items()
              ],
              "relabel_configs": self._relabel_configs + kwargs.get("relabel_configs", []),
          }
          job.update(kwargs.get("updates", {}))
  
          return job
  
      @property
      def _relabel_configs(self) -> list:
          """Create Juju topology relabeling configuration.
  
          Using Juju topology for instance labels ensures that these
          labels are stable across unit recreation.
  
          Returns:
              a list of Prometheus relabling configurations. Each item in
              this list is one relabel configuration.
          """
          return (
              [
                  {
                      "source_labels": [
                          "juju_model",
                          "juju_model_uuid",
                          "juju_application",
                          "juju_unit",
                      ],
                      "separator": "_",
                      "target_label": "instance",
                      "regex": "(.*)",
                  }
              ]
              if self._relabel_instance
              else []
          )
  
  
  class PromqlTransformer:
      """Uses promql-transform to inject label matchers into alert rule expressions."""
  
      _path = None
      _disabled = False
  
      @property
      def path(self):
          """Lazy lookup of the path of promql-transform."""
          if self._disabled:
              return None
          if not self._path:
              self._path = self._get_transformer_path()
              if not self._path:
                  logger.debug("Skipping injection of juju topology as label matchers")
                  self._disabled = True
          return self._path
  
      def __init__(self, charm):
          self._charm = charm
  
      def apply_label_matchers(self, rules):
          """Will apply label matchers to the expression of all alerts in all supplied groups."""
          if not self.path:
              return rules
          for group in rules["groups"]:
              rules_in_group = group.get("rules", [])
              for rule in rules_in_group:
                  topology = {}
                  # if the user for some reason has provided juju_unit, we'll need to honor it
                  # in most cases, however, this will be empty
                  for label in [
                      "juju_model",
                      "juju_model_uuid",
                      "juju_application",
                      "juju_charm",
                      "juju_unit",
                  ]:
                      if label in rule["labels"]:
                          topology[label] = rule["labels"][label]
  
                  rule["expr"] = self._apply_label_matcher(rule["expr"], topology)
          return rules
  
      def _apply_label_matcher(self, expression, topology):
          if not topology:
              return expression
          if not self.path:
              logger.debug(
                  "`promql-transform` unavailable. leaving expression unchanged: %s", expression
              )
              return expression
          args = [str(self.path)]
          args.extend(
              ["--label-matcher={}={}".format(key, value) for key, value in topology.items()]
          )
  
          args.extend(["{}".format(expression)])
          # noinspection PyBroadException
          try:
              return self._exec(args)
          except Exception as e:
              logger.debug('Applying the expression failed: "{}", falling back to the original', e)
              return expression
  
      def _get_transformer_path(self) -> Optional[Path]:
          arch = platform.processor()
          arch = "amd64" if arch == "x86_64" else arch
          res = "promql-transform-{}".format(arch)
          try:
              path = self._charm.model.resources.fetch(res)
              os.chmod(path, 0o777)
              return path
          except NotImplementedError:
              logger.debug("System lacks support for chmod")
          except (NameError, ModelError):
              logger.debug('No resource available for the platform "{}"'.format(arch))
          return None
  
      def _exec(self, cmd):
          result = subprocess.run(cmd, check=False, stdout=subprocess.PIPE)
          output = result.stdout.decode("utf-8").strip()
          return output
  