Observability Platform-4.2: Alert Management for Cache/MQ/TQ Middleware
原创Observability Platform-4.2: Alert Management for Cache/MQ/TQ Middleware
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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
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
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)
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)
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:
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_loadCelery 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:
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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原创声明：本文系作者授权腾讯云开发者社区发表，未经许可，不得转载。
如有侵权，请联系 cloudcommunity@tencent.com 删除。