Observability Platform-4.2: Alert Management for Cache/MQ/TQ Middleware

2023-12-14 17:21:58 浏览数 (1)

Redis Alert Configuration Reference

For Redis performance metrics, we provide configurations for Redis log metrics exporter, Prometheus monitoring rules (in YAML format), alert rules, and a suitable Grafana dashboard configuration.

Redis Log Metrics Exporter

Log/Metrics Exporters:

  • Redis Logs: You can capture log data using Redis's log files. This typically involves configuring Redis to output logs to a file and then using tools like Filebeat to collect these logs and send them to a log analysis platform.
  • Redis Metrics: You can use redis_exporter, which is a Redis metrics exporter designed for Prometheus. It can collect and export Redis performance metrics such as command statistics, memory usage, CPU usage, etc. Redis Service Prometheus Monitoring Rules (YAML)

Monitoring Rules

代码语言：yaml复制
groups:
- name: redis_metrics
  rules:
  - record: redis_commands_processed_total
    expr: rate(redis_commands_processed_total[5m])

  - record: redis_memory_usage_bytes
    expr: redis_memory_used_bytes

  - record: redis_cpu_usage_percentage
    expr: rate(redis_cpu_user_seconds_total[5m])   rate(redis_cpu_system_seconds_total[5m])

  - record: redis_net_input_bytes
    expr: rate(redis_net_input_bytes_total[5m])

  - record: redis_net_output_bytes
    expr: rate(redis_net_output_bytes_total[5m])

Redis Service Prometheus Alert Rules (YAML)

Alert Rules

代码语言：yaml复制
groups:
- name: redis_alerts
  rules:
  - alert: HighMemoryUsage
    expr: redis_memory_usage_bytes > (redis_memory_max_bytes * 0.8)
    for: 5m
    labels:
      severity: critical
    annotations:
      summary: "High Memory Usage in Redis"
      description: "Redis server {{ $labels.instance }} is using more than 80% of its configured max memory."

  - alert: HighCommandRate
    expr: redis_commands_processed_total > 10000
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "High Command Rate on Redis"
      description: "Redis server {{ $labels.instance }} is processing more than 10000 commands per second."

Redis Backend Service Grafana Dashboard

For Grafana dashboards, you can find specialized dashboards designed for Redis on the Grafana Dashboards website. These dashboards typically include key performance metrics such as command statistics, throughput, latency, memory usage, CPU usage, network bandwidth, and more.

A typical example could be the "Redis Overview" dashboard, providing a comprehensive view of essential performance metrics for your Redis instances. You can add these dashboards to your Grafana instance by importing the dashboard ID or by downloading the JSON file directly from the website.

These configurations and dashboards may need to be customized and adjusted according to your specific requirements and environment.

Kafka Alert Configuration Reference

Kafka Log Metrics Exporter

For Kafka log metrics exporter, you can use Kafka's built-in JMX support and JMX Exporter to capture Kafka's performance metrics. This requires enabling Kafka's JMX feature and then using JMX Exporter to export these metrics and send them to Prometheus.

Kafka Service Prometheus Monitoring Rules (YAML)

代码语言：yaml复制
groups:
- name: kafka_metrics
  rules:
  - record: kafka_messages_per_second
    expr: rate(kafka_server_brokertopicmetrics_messagesin_total{topic="your_topic"}[5m])

  - record: kafka_latency_seconds
    expr: kafka_server_brokertopicmetrics_totaltime_seconds{topic="your_topic"} / kafka_server_brokertopicmetrics_messagesin_total{topic="your_topic"}

  - record: kafka_queue_size
    expr: kafka_server_brokertopicmetrics_messagesin_total{topic="your_topic"} - kafka_server_brokertopicmetrics_messagesout_total{topic="your_topic"}

  - record: kafka_cpu_usage_percentage
    expr: 100 - avg by (instance)(irate(node_cpu_seconds_total{mode="idle"}[5m]))

  - record: kafka_memory_usage_bytes
    expr: node_memory_MemTotal_bytes - node_memory_MemFree_bytes

  - record: kafka_error_rate
    expr: rate(kafka_server_brokertopicmetrics_failedfetchrequests_total{topic="your_topic"}[5m]) / rate(kafka_server_brokertopicmetrics_requests_total{topic="your_topic"}[5m])

  - record: kafka_retry_count
    expr: sum(kafka_consumer_rebalance_total{topic="your_topic"})

  - record: kafka_client_connections
    expr: kafka_server_metadata_response_version{version="0.9.0.1"} / ignoring(version) count(kafka_server_metadata_response_version{version="0.9.0.1"})

  - record: kafka_client_connection_failures
    expr: sum(kafka_network_handlers_total{result="NetworkError"})

Please note that the "your_topic" part in the above rules should be replaced with your Kafka topic name.

Kafka Service Prometheus Alert Rules (YAML)

代码语言：yaml复制
groups:
- name: kafka_alerts
  rules:
  - alert: HighLatency
    expr: kafka_latency_seconds > 0.5
    for: 5m
    labels:
      severity: critical
    annotations:
      summary: "High Latency in Kafka"
      description: "Kafka topic 'your_topic' is experiencing high latency."

  - alert: HighErrorRate
    expr: kafka_error_rate > 0.05
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "High Error Rate in Kafka"
      description: "Kafka topic 'your_topic' has a high error rate."

  - alert: HighQueueSize
    expr: kafka_queue_size > 1000
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "High Queue Size in Kafka"
      description: "Kafka topic 'your_topic' has a large queue size."

  - alert: ConnectionFailures
    expr: kafka_client_connection_failures > 10
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "Kafka Connection Failures"
      description: "Kafka clients are experiencing connection failures."

Similarly, the "your_topic" part in the above rules should be replaced with your Kafka topic name.

Kafka Backend Service Grafana Dashboard

There are many Grafana dashboards available for Kafka, and you can choose one that suits your needs. These dashboards typically include charts and visualizations of key performance metrics such as throughput, latency, queue size, CPU usage, memory usage, error rate, retry count, client connections, and more. You can find these dashboards in the Grafana dashboard library or the Grafana community, and customize and configure them as needed.

Celery Alert Configuration Reference

Here is the Celery configuration for monitoring tasks related to the task queue:

Celery Log Metrics Exporter

For the Celery log metrics exporter, you can use Celery's built-in logging functionality to capture performance metrics of Celery tasks. This typically involves configuring Celery to log task execution information to log files and then using tools like Filebeat to collect these logs and send them to a log analysis platform.

Celery Service Prometheus Monitoring Rules (YAML)

Here are some example monitoring rules that can be used to monitor the performance of the Celery task queue:

代码语言：yaml复制
groups:
- name: celery_metrics
  rules:
  - record: celery_task_throughput
    expr: rate(celery_task_processed_total[5m])

  - record: celery_task_latency_seconds
    expr: celery_task_processing_time_seconds

  - record: celery_queue_length
    expr: celery_queue_size

  - record: celery_memory_usage_bytes
    expr: celery_memory_used_bytes

  - record: celery_cpu_usage_percentage
    expr: 100 - avg by (instance)(irate(node_cpu_seconds_total{mode="idle"}[5m]))

  - record: celery_task_success_rate
    expr: celery_task_successful_total / celery_task_processed_total

  - record: celery_task_failure_count
    expr: celery_task_failed_total

  - record: celery_task_retry_count
    expr: celery_task_retry_total

  - record: celery_queue_service_status
    expr: celery_service_status

  - record: celery_connection_errors
    expr: celery_connection_failures_total

  - record: celery_worker_count
    expr: celery_active_workers_total

  - record: celery_worker_load
    expr: celery_worker_load

Celery Service Prometheus Alert Rules (YAML)

Here are some example alert rules that can be used to monitor the health and performance issues of the Celery task queue:

代码语言：yaml复制
groups:
- name: celery_alerts
  rules:
  - alert: HighTaskLatency
    expr: celery_task_latency_seconds > 10
    for: 5m
    labels:
      severity: critical
    annotations:
      summary: "High Task Latency in Celery"
      description: "Celery tasks are experiencing high latency."

  - alert: HighQueueLength
    expr: celery_queue_length > 100
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "High Queue Length in Celery"
      description: "Celery queue has a large number of pending tasks."

  - alert: HighMemoryUsage
    expr: celery_memory_usage_bytes > 536870912  # 512 MB
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "High Memory Usage in Celery"
      description: "Celery is using more than 512 MB of memory."

  - alert: ConnectionFailures
    expr: celery_connection_errors > 10
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "Celery Connection Failures"
      description: "Celery is experiencing connection failures to the backend."

  - alert: HighTaskFailureRate
    expr: celery_task_failure_count / celery_task_processed_total > 0.1
    for: 5m
    labels:
      severity: critical
    annotations:
      summary: "High Task Failure Rate in Celery"
      description: "Celery tasks are failing at a high rate."

Celery Backend Service Grafana Dashboard

For the Celery backend service Grafana dashboard, you can choose one that suits your needs. These dashboards typically include charts and visualizations of key performance metrics such as task throughput, task latency, queue length, memory usage, CPU usage, task success rate, task failure count, task retry count, connection errors, worker count, worker load, and more. You can find these dashboards in the Grafana dashboard library or the Grafana community, and customize and configure them as needed.

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