# Copyright 2023 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#      http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Missing request for CPU resources.

Error means that HPA is unable to calculate the number of replicas
that should be scaled up or down based on the current metrics
because there is no request for CPU resources specified in the deployment
or pod.The HPA requires at least one metric to be specified to scale the
deployment or replica set.
"""

from gcpdiag import lint, models
from gcpdiag.lint.gke import util
from gcpdiag.queries import apis, gke, logs

MATCH_STR_1 = 'missing request for cpu'
logs_by_project = {}


def prepare_rule(context: models.Context):
  clusters = gke.get_clusters(context)
  for project_id in {c.project_id for c in clusters.values()}:
    logs_by_project[project_id] = logs.query(
        project_id=project_id,
        resource_type='k8s_cluster',
        log_name='log_id("events")',
        filter_str=f'jsonPayload.message:"{MATCH_STR_1}"',
    )


def _filter_f(log_entry):
  try:
    return MATCH_STR_1 in log_entry['jsonPayload']['message']
  except KeyError:
    return False


def run_rule(context: models.Context, report: lint.LintReportRuleInterface):
  # skip entire rule is logging disabled
  if not apis.is_enabled(context.project_id, 'logging'):
    report.add_skipped(None, 'logging api is disabled')
    return
  # Any work to do?
  clusters = gke.get_clusters(context)
  if not clusters:
    report.add_skipped(None, 'no clusters found')
    # Search the logs.

  bad_clusters = util.gke_logs_find_bad_clusters(
      context=context, logs_by_project=logs_by_project, filter_f=_filter_f)
  # Create the report.
  for _, c in sorted(clusters.items()):
    if c in bad_clusters:
      report.add_failed(c, logs.format_log_entry(bad_clusters[c]))
    else:
      report.add_ok(c)