# File contains default list of alerts for vm-single and vmagent services.
# The alerts below are just recommendations and may require some updates
# and threshold calibration according to every specific setup.
groups:
  - name: vm-health
    # note the `job` filter and update accordingly to your setup
    rules:
      # note the `job` filter and update accordingly to your setup
      - alert: TooManyRestarts
        expr: changes(process_start_time_seconds{job=~"victoriametrics|vmagent|vmalert"}[15m]) > 2
        labels:
          severity: critical
        annotations:
          summary: "{{ $labels.job }} too many restarts (instance {{ $labels.instance }})"
          description: "Job {{ $labels.job }} has restarted more than twice in the last 15 minutes.
            It might be crashlooping."

      - alert: ServiceDown
        expr: up{job=~"victoriametrics|vmagent|vmalert"} == 0
        for: 2m
        labels:
          severity: critical
        annotations:
          summary: "Service {{ $labels.job }} is down on {{ $labels.instance }}"
          description: "{{ $labels.instance }} of job {{ $labels.job }} has been down for more than 2 minutes."

      - alert: ProcessNearFDLimits
        expr: (process_max_fds - process_open_fds) < 100
        for: 5m
        labels:
          severity: critical
        annotations:
          summary: "Number of free file descriptors is less than 100 for \"{{ $labels.job }}\"(\"{{ $labels.instance }}\") for the last 5m"
          description: "Exhausting OS file descriptors limit can cause severe degradation of the process.
           Consider to increase the limit as fast as possible."

      - alert: TooHighMemoryUsage
        expr: (process_resident_memory_anon_bytes / vm_available_memory_bytes) > 0.9
        for: 5m
        labels:
          severity: critical
        annotations:
          summary: "It is more than 90% of memory used by \"{{ $labels.job }}\"(\"{{ $labels.instance }}\") during the last 5m"
          description: "Too high memory usage may result into multiple issues such as OOMs or degraded performance.
           Consider to either increase available memory or decrease the load on the process."

  # Alerts group for VM single assumes that Grafana dashboard
  # https://grafana.com/grafana/dashboards/10229 is installed.
  # Pls update the `dashboard` annotation according to your setup.
  - name: vmsingle
    interval: 30s
    concurrency: 2
    rules:
      - alert: DiskRunsOutOfSpaceIn3Days
        expr: |
          vm_free_disk_space_bytes / ignoring(path)
          (
             (
              rate(vm_rows_added_to_storage_total[1d]) -
              ignoring(type) rate(vm_deduplicated_samples_total{type="merge"}[1d])
             )
            * scalar(
              sum(vm_data_size_bytes{type!="indexdb"}) /
              sum(vm_rows{type!="indexdb"})
             )
          ) < 3 * 24 * 3600
        for: 30m
        labels:
          severity: critical
        annotations:
          dashboard: "http://localhost:3000/d/wNf0q_kZk?viewPanel=73&var-instance={{ $labels.instance }}"
          summary: "Instance {{ $labels.instance }} will run out of disk space soon"
          description: "Taking into account current ingestion rate, free disk space will be enough only
            for {{ $value | humanizeDuration }} on instance {{ $labels.instance }}.\n
            Consider to limit the ingestion rate, decrease retention or scale the disk space if possible."

      - alert: DiskRunsOutOfSpace
        expr: |
          sum(vm_data_size_bytes) by(instance) /
          (
           sum(vm_free_disk_space_bytes) by(instance) +
           sum(vm_data_size_bytes) by(instance)
          ) > 0.8
        for: 30m
        labels:
          severity: critical
        annotations:
          dashboard: "http://localhost:3000/d/wNf0q_kZk?viewPanel=53&var-instance={{ $labels.instance }}"
          summary: "Instance {{ $labels.instance }} will run out of disk space soon"
          description: "Disk utilisation on instance {{ $labels.instance }} is more than 80%.\n
            Having less than 20% of free disk space could cripple merges processes and overall performance.
            Consider to limit the ingestion rate, decrease retention or scale the disk space if possible."

      - alert: RequestErrorsToAPI
        expr: increase(vm_http_request_errors_total[5m]) > 0
        for: 15m
        labels:
          severity: warning
        annotations:
          dashboard: "http://localhost:3000/d/wNf0q_kZk?viewPanel=35&var-instance={{ $labels.instance }}"
          summary: "Too many errors served for path {{ $labels.path }} (instance {{ $labels.instance }})"
          description: "Requests to path {{ $labels.path }} are receiving errors.
            Please verify if clients are sending correct requests."

      - alert: ConcurrentFlushesHitTheLimit
        expr: avg_over_time(vm_concurrent_addrows_current[1m]) >= vm_concurrent_addrows_capacity
        for: 15m
        labels:
          severity: warning
        annotations:
          dashboard: "http://localhost:3000/d/wNf0q_kZk?viewPanel=59&var-instance={{ $labels.instance }}"
          summary: "VictoriaMetrics on instance {{ $labels.instance }} is constantly hitting concurrent flushes limit"
          description: "The limit of concurrent flushes on instance {{ $labels.instance }} is equal to number of CPUs.\n
            When VictoriaMetrics constantly hits the limit it means that storage is overloaded and requires more CPU."

      - alert: TooManyLogs
        expr: sum(increase(vm_log_messages_total{level!="info"}[5m])) by (job, instance) > 0
        for: 15m
        labels:
          severity: warning
        annotations:
          dashboard: "http://localhost:3000/d/wNf0q_kZk?viewPanel=67&var-instance={{ $labels.instance }}"
          summary: "Too many logs printed for job \"{{ $labels.job }}\" ({{ $labels.instance }})"
          description: "Logging rate for job \"{{ $labels.job }}\" ({{ $labels.instance }}) is {{ $value }} for last 15m.\n
           Worth to check logs for specific error messages."

      - alert: RowsRejectedOnIngestion
        expr: sum(rate(vm_rows_ignored_total[5m])) by (instance, reason) > 0
        for: 15m
        labels:
          severity: warning
        annotations:
          dashboard: "http://localhost:3000/d/wNf0q_kZk?viewPanel=58&var-instance={{ $labels.instance }}"
          summary: "Some rows are rejected on \"{{ $labels.instance }}\" on ingestion attempt"
          description: "VM is rejecting to ingest rows on \"{{ $labels.instance }}\" due to the
            following reason: \"{{ $labels.reason }}\""

      - alert: TooHighChurnRate
        expr: |
          (
             sum(rate(vm_new_timeseries_created_total[5m])) by(instance)
             /
             sum(rate(vm_rows_inserted_total[5m])) by (instance)
           ) > 0.1
        for: 15m
        labels:
          severity: warning
        annotations:
          dashboard: "http://localhost:3000/d/wNf0q_kZk?viewPanel=66&var-instance={{ $labels.instance }}"
          summary: "Churn rate is more than 10% on \"{{ $labels.instance }}\" for the last 15m"
          description: "VM constantly creates new time series on \"{{ $labels.instance }}\".\n
            This effect is known as Churn Rate.\n
            High Churn Rate tightly connected with database performance and may
            result in unexpected OOM's or slow queries."

      - alert: TooHighChurnRate24h
        expr: |
          sum(increase(vm_new_timeseries_created_total[24h])) by(instance)
          >
          (sum(vm_cache_entries{type="storage/hour_metric_ids"}) by(instance) * 3)
        for: 15m
        labels:
          severity: warning
        annotations:
          dashboard: "http://localhost:3000/d/wNf0q_kZk?viewPanel=66&var-instance={{ $labels.instance }}"
          summary: "Too high number of new series on \"{{ $labels.instance }}\" created over last 24h"
          description: "The number of created new time series over last 24h is 3x times higher than
            current number of active series on \"{{ $labels.instance }}\".\n
            This effect is known as Churn Rate.\n
            High Churn Rate tightly connected with database performance and may
            result in unexpected OOM's or slow queries."

      - alert: TooHighSlowInsertsRate
        expr: |
          (
             sum(rate(vm_slow_row_inserts_total[5m])) by(instance)
             /
             sum(rate(vm_rows_inserted_total[5m])) by (instance)
           ) > 0.5
        for: 15m
        labels:
          severity: warning
        annotations:
          dashboard: "http://localhost:3000/d/wNf0q_kZk?viewPanel=68&var-instance={{ $labels.instance }}"
          summary: "Percentage of slow inserts is more than 50% on \"{{ $labels.instance }}\" for the last 15m"
          description: "High rate of slow inserts on \"{{ $labels.instance }}\" may be a sign of resource exhaustion
            for the current load. It is likely more RAM is needed for optimal handling of the current number of active time series."

      - alert: LabelsLimitExceededOnIngestion
        expr: sum(increase(vm_metrics_with_dropped_labels_total[5m])) by (instance) > 0
        for: 15m
        labels:
          severity: warning
        annotations:
          dashboard: "http://localhost:3000/d/wNf0q_kZk?viewPanel=74&var-instance={{ $labels.instance }}"
          summary: "Metrics ingested in ({{ $labels.instance }}) are exceeding labels limit"
          description: "VictoriaMetrics limits the number of labels per each metric with `-maxLabelsPerTimeseries` command-line flag.\n
           This prevents from ingesting metrics with too many labels. Please verify that `-maxLabelsPerTimeseries` is configured
           correctly or that clients which send these metrics aren't misbehaving."

  # Alerts group for vmagent assumes that Grafana dashboard
  # https://grafana.com/grafana/dashboards/12683 is installed.
  # Pls update the `dashboard` annotation according to your setup.
  - name: vmagent
    interval: 30s
    concurrency: 2
    rules:
      - alert: PersistentQueueIsDroppingData
        expr: sum(increase(vm_persistentqueue_bytes_dropped_total[5m])) by (job, instance) > 0
        for: 10m
        labels:
          severity: critical
        annotations:
          dashboard: "http://localhost:3000/d/G7Z9GzMGz?viewPanel=49&var-instance={{ $labels.instance }}"
          summary: "Instance {{ $labels.instance }} is dropping data from persistent queue"
          description: "Vmagent dropped {{ $value | humanize1024 }} from persistent queue
              on instance {{ $labels.instance }} for the last 10m."

      - alert: RejectedRemoteWriteDataBlocksAreDropped
        expr: sum(increase(vmagent_remotewrite_packets_dropped_total[5m])) by (job, instance) > 0
        for: 15m
        labels:
          severity: warning
        annotations:
          dashboard: "http://localhost:3000/d/G7Z9GzMGz?viewPanel=79&var-instance={{ $labels.instance }}"
          summary: "Job \"{{ $labels.job }}\" on instance {{ $labels.instance }} drops the rejected by 
          remote-write server data blocks. Check the logs to find the reason for rejects."

      - alert: TooManyScrapeErrors
        expr: sum(increase(vm_promscrape_scrapes_failed_total[5m])) by (job, instance) > 0
        for: 15m
        labels:
          severity: warning
        annotations:
          dashboard: "http://localhost:3000/d/G7Z9GzMGz?viewPanel=31&var-instance={{ $labels.instance }}"
          summary: "Job \"{{ $labels.job }}\" on instance {{ $labels.instance }} fails to scrape targets for last 15m"

      - alert: TooManyWriteErrors
        expr: |
          (sum(increase(vm_ingestserver_request_errors_total[5m])) by (job, instance)
          +
          sum(increase(vmagent_http_request_errors_total[5m])) by (job, instance)) > 0
        for: 15m
        labels:
          severity: warning
        annotations:
          dashboard: "http://localhost:3000/d/G7Z9GzMGz?viewPanel=77&var-instance={{ $labels.instance }}"
          summary: "Job \"{{ $labels.job }}\" on instance {{ $labels.instance }} responds with errors to write requests for last 15m."

      - alert: TooManyRemoteWriteErrors
        expr: sum(rate(vmagent_remotewrite_retries_count_total[5m])) by(job, instance, url) > 0
        for: 15m
        labels:
          severity: warning
        annotations:
          dashboard: "http://localhost:3000/d/G7Z9GzMGz?viewPanel=61&var-instance={{ $labels.instance }}"
          summary: "Job \"{{ $labels.job }}\" on instance {{ $labels.instance }} fails to push to remote storage"
          description: "Vmagent fails to push data via remote write protocol to destination \"{{ $labels.url }}\"\n
            Ensure that destination is up and reachable."

      - alert: RemoteWriteConnectionIsSaturated
        expr: rate(vmagent_remotewrite_send_duration_seconds_total[5m]) > 0.9
        for: 15m
        labels:
          severity: warning
        annotations:
          dashboard: "http://localhost:3000/d/G7Z9GzMGz?viewPanel=84&var-instance={{ $labels.instance }}"
          summary: "Remote write connection from \"{{ $labels.job }}\" (instance {{ $labels.instance }}) to {{ $labels.url }} is saturated"
          description: "The remote write connection between vmagent \"{{ $labels.job }}\" (instance {{ $labels.instance }}) and destination \"{{ $labels.url }}\"
            is saturated by more than 90% and vmagent won't be able to keep up.\n
            This usually means that `-remoteWrite.queues` command-line flag must be increased in order to increase
            the number of connections per each remote storage."

      - alert: PersistentQueueForWritesIsSaturated
        expr: rate(vm_persistentqueue_write_duration_seconds_total[5m]) > 0.9
        for: 15m
        labels:
          severity: warning
        annotations:
          dashboard: "http://localhost:3000/d/G7Z9GzMGz?viewPanel=98&var-instance={{ $labels.instance }}"
          summary: "Persistent queue writes for instance {{ $labels.instance }} are saturated"
          description: "Persistent queue writes for vmagent \"{{ $labels.job }}\" (instance {{ $labels.instance }})
            are saturated by more than 90% and vmagent won't be able to keep up with flushing data on disk. 
            In this case, consider to decrease load on the vmagent or improve the disk throughput."

      - alert: PersistentQueueForReadsIsSaturated
        expr: rate(vm_persistentqueue_read_duration_seconds_total[5m]) > 0.9
        for: 15m
        labels:
          severity: warning
        annotations:
          dashboard: "http://localhost:3000/d/G7Z9GzMGz?viewPanel=99&var-instance={{ $labels.instance }}"
          summary: "Persistent queue reads for instance {{ $labels.instance }} are saturated"
          description: "Persistent queue reads for vmagent \"{{ $labels.job }}\" (instance {{ $labels.instance }})
            are saturated by more than 90% and vmagent won't be able to keep up with reading data from the disk. 
            In this case, consider to decrease load on the vmagent or improve the disk throughput."

      - alert: SeriesLimitHourReached
        expr: (vmagent_hourly_series_limit_current_series / vmagent_hourly_series_limit_max_series) > 0.9
        labels:
          severity: critical
        annotations:
          dashboard: "http://localhost:3000/d/G7Z9GzMGz?viewPanel=88&var-instance={{ $labels.instance }}"
          summary: "Instance {{ $labels.instance }} reached 90% of the limit"
          description: "Max series limit set via -remoteWrite.maxHourlySeries flag is close to reaching the max value. 
            Then samples for new time series will be dropped instead of sending them to remote storage systems."

      - alert: SeriesLimitDayReached
        expr: (vmagent_daily_series_limit_current_series / vmagent_daily_series_limit_max_series) > 0.9
        labels:
          severity: critical
        annotations:
          dashboard: "http://localhost:3000/d/G7Z9GzMGz?viewPanel=90&var-instance={{ $labels.instance }}"
          summary: "Instance {{ $labels.instance }} reached 90% of the limit"
          description: "Max series limit set via -remoteWrite.maxDailySeries flag is close to reaching the max value. 
            Then samples for new time series will be dropped instead of sending them to remote storage systems."