To export MySQL logs, you can configure MySQL to log queries, slow queries, and replication-related information. Tools like Filebeat or Fluentd can be used to collect and ship these logs for analysis.
For MySQL metrics, you can use Prometheus with the mysqld_exporter to collect and export MySQL performance metrics to Prometheus.
Here are some sample Prometheus monitoring rules for MySQL:
groups:
- name: mysql_metrics
rules:
- record: mysql_query_throughput
expr: rate(mysql_queries_total[5m])
- record: mysql_query_response_time_seconds
expr: histogram_quantile(0.95, rate(mysql_query_duration_seconds_bucket[5m]))
- record: mysql_slow_queries
expr: rate(mysql_slow_queries_total[5m])
- record: mysql_cpu_usage_percentage
expr: 100 - avg by (instance)(irate(node_cpu_seconds_total{mode="idle"}[5m]))
- record: mysql_memory_usage_bytes
expr: node_memory_MemTotal_bytes - node_memory_MemFree_bytes
- record: mysql_disk_io_operations
expr: rate(node_disk_io_time_seconds_total[5m])
- record: mysql_network_io_bytes
expr: rate(node_network_receive_bytes_total[5m]) + rate(node_network_transmit_bytes_total[5m])
Here are some example Prometheus alert rules for MySQL:
groups:
- name: mysql_alerts
rules:
- alert: HighQueryResponseTime
expr: mysql_query_response_time_seconds > 0.5
for: 5m
labels:
severity: critical
annotations:
summary: "High Query Response Time in MySQL"
description: "MySQL queries are experiencing high response time."
- alert: HighSlowQueries
expr: mysql_slow_queries > 10
for: 5m
labels:
severity: warning
annotations:
summary: "High Slow Queries in MySQL"
description: "MySQL is experiencing a high number of slow queries."
- alert: HighCPUUsage
expr: mysql_cpu_usage_percentage > 90
for: 5m
labels:
severity: critical
annotations:
summary: "High CPU Usage in MySQL"
description: "MySQL server CPU usage is above 90%."
- alert: HighMemoryUsage
expr: mysql_memory_usage_bytes > 536870912 # 512 MB
for: 5m
labels:
severity: warning
annotations:
summary: "High Memory Usage in MySQL"
description: "MySQL is using more than 512 MB of memory."
- alert: HighDiskIOOperations
expr: mysql_disk_io_operations > 100
for: 5m
labels:
severity: warning
annotations:
summary: "High Disk I/O Operations in MySQL"
description: "MySQL is performing a high number of disk I/O operations."
- alert: HighNetworkIO
expr: mysql_network_io_bytes > 10000000 # 10 MB/s
for: 5m
labels:
severity: warning
annotations:
summary: "High Network I/O in MySQL"
description: "MySQL is using more than 10 MB/s of network I/O."
For MySQL Grafana dashboard, you can find or create one that suits your needs. These dashboards typically include charts and visualizations for various MySQL performance metrics, such as query throughput, query response time, slow queries, CPU usage, memory usage, disk I/O, network I/O, replication lag, and more. You can import an existing dashboard using its ID or download a JSON file from the Grafana dashboard repository, and then customize and configure it according to your requirements.
To export PostgreSQL logs, configure PostgreSQL to log queries, errors, and other relevant information. You can use log shipping tools to collect and forward these logs for analysis.
For PostgreSQL metrics, use Prometheus with the pg_exporter to collect and export PostgreSQL performance metrics to Prometheus.
Here are some sample Prometheus monitoring rules for PostgreSQL:
groups:
- name: postgresql_metrics
rules:
- record: postgresql_transaction_throughput
expr: rate(postgresql_transactions_total[5m])
- record: postgresql_query_latency_seconds
expr: histogram_quantile(0.95, rate(postgresql_query_duration_seconds_bucket[5m]))
- record: postgresql_index_hit_rate
expr: rate(postgresql_index_hits_total[5m]) / rate(postgresql_index_scan_total[5m] + postgresql_index_hits_total[5m])
- record: postgresql_cpu_usage_percentage
expr: 100 - avg by (instance)(irate(node_cpu_seconds_total{mode="idle"}[5m]))
- record: postgresql_memory_usage_bytes
expr: node_memory_MemTotal_bytes - node_memory_MemFree_bytes
- record: postgresql_disk_space_usage_bytes
expr: node_filesystem_size_bytes{fstype="ext4"} - node_filesystem_free_bytes{fstype="ext4"}
- record: postgresql_active_connections
expr: postgresql_active_connections
- record: postgresql_idle_connections
expr: postgresql_idle_connections
- record: postgresql_lock_wait_time_seconds
expr: postgresql_lock_wait_time_seconds
Here are some example Prometheus alert rules for PostgreSQL:
groups:
- name: postgresql_alerts
rules:
- alert: HighQueryLatency
expr: postgresql_query_latency_seconds > 0.5
for: 5m
labels:
severity: critical
annotations:
summary: "High Query Latency in PostgreSQL"
description: "PostgreSQL queries are experiencing high latency."
- alert: LowIndexHitRate
expr: postgresql_index_hit_rate < 0.9
for: 5m
labels:
severity: warning
annotations:
summary: "Low Index Hit Rate in PostgreSQL"
description: "PostgreSQL index hit rate is below 90%."
- alert: HighCPUUsage
expr: postgresql_cpu_usage_percentage > 90
for: 5m
labels:
severity: critical
annotations:
summary: "High CPU Usage in PostgreSQL"
description: "PostgreSQL server CPU usage is above 90%."
- alert: HighMemoryUsage
expr: postgresql_memory_usage_bytes > 536870912 # 512 MB
for: 5m
labels:
severity: warning
annotations:
summary: "High Memory Usage in PostgreSQL"
description: "PostgreSQL is using more than 512 MB of memory."
- alert: LowFreeDiskSpace
expr: postgresql_disk_space_usage_bytes < 5368709120 # 5 GB
for: 5m
labels:
severity: warning
annotations:
summary: "Low Free Disk Space in PostgreSQL"
description: "PostgreSQL has less than 5 GB of free disk space."
- alert: HighLockWaitTime
expr: postgresql_lock_wait_time_seconds > 1
for: 5m
labels:
severity: warning
annotations:
summary: "High Lock Wait Time in PostgreSQL"
description: "PostgreSQL queries are waiting for locks for more than 1 second."
For PostgreSQL Grafana dashboard, you can find or create one that suits your needs. These dashboards typically include charts and visualizations for various PostgreSQL performance metrics, such as transaction throughput, query latency, index hit rate, CPU usage, memory usage, disk space, connection counts, and lock wait times. You can import an existing dashboard using its ID or download a JSON file from the Grafana dashboard repository, and then customize and configure it according to your requirements.
To export MongoDB logs, you can configure MongoDB to log operations, query response times, and other information. Then, you can use log collection tools like Filebeat or Fluentd to collect and send these logs for analysis.
For MongoDB metrics, you can use Prometheus with the MongoDB Exporter to collect and export MongoDB performance metrics to Prometheus.
Here are some sample Prometheus monitoring rules for MongoDB:
groups:
- name: mongodb_metrics
rules:
- record: mongodb_operations_throughput
expr: rate(mongodb_operations_total[5m])
- record: mongodb_query_response_time_seconds
expr: histogram_quantile(0.95, rate(mongodb_query_response_time_seconds_bucket[5m]))
- record: mongodb_memory_usage_bytes
expr: mongodb_memory_usage_bytes
- record: mongodb_disk_usage_bytes
expr: mongodb_disk_usage_bytes
- record: mongodb_network_traffic_bytes
expr: rate(mongodb_network_traffic_bytes_total[5m])
- record: mongodb_replica_set_status
expr: mongodb_replica_set_status
- record: mongodb_shard_balance
expr: mongodb_shard_balance
Here are some example Prometheus alert rules for MongoDB:
groups:
- name: mongodb_alerts
rules:
- alert: HighQueryResponseTime
expr: mongodb_query_response_time_seconds > 0.5
for: 5m
labels:
severity: critical
annotations:
summary: "High Query Response Time in MongoDB"
description: "MongoDB queries are experiencing high response time."
- alert: HighMemoryUsage
expr: mongodb_memory_usage_bytes > 536870912 # 512 MB
for: 5m
labels:
severity: warning
annotations:
summary: "High Memory Usage in MongoDB"
description: "MongoDB is using more than 512 MB of memory."
- alert: HighDiskUsage
expr: mongodb_disk_usage_bytes > 10737418240 # 10 GB
for: 5m
labels:
severity: warning
annotations:
summary: "High Disk Usage in MongoDB"
description: "MongoDB is using more than 10 GB of disk space."
- alert: HighNetworkTraffic
expr: mongodb_network_traffic_bytes > 10000000 # 10 MB/s
for: 5m
labels:
severity: warning
annotations:
summary: "High Network Traffic in MongoDB"
description: "MongoDB is generating more than 10 MB/s of network traffic."
- alert: ReplicaSetNotHealthy
expr: mongodb_replica_set_status != 1
for: 5m
labels:
severity: critical
annotations:
summary: "MongoDB Replica Set Not Healthy"
description: "MongoDB replica set status is not healthy."
- alert: ShardNotBalanced
expr: mongodb_shard_balance != 1
for: 5m
labels:
severity: warning
annotations:
summary: "MongoDB Shard Not Balanced"
description: "MongoDB shard balance is not optimal."
For MongoDB Grafana dashboard, you can find or create one that suits your needs. These dashboards typically include charts and visualizations for various MongoDB performance metrics, such as operation throughput, query response time, memory usage, disk usage, network traffic, replica set status, and shard balance. You can import an existing dashboard using its ID or download a JSON file from the Grafana dashboard repository, and then customize and configure it according to your requirements.
To export Cassandra logs, you can configure Cassandra to log read/write operation latency, node status, and data replication latency, among other information. Then, you can use log collection tools to collect and send these logs for analysis.
For Cassandra metrics, you can use Prometheus with the Cassandra Exporter to collect and export Cassandra performance metrics to Prometheus.
Here are some sample Prometheus monitoring rules for Cassandra:
groups:
- name: cassandra_metrics
rules:
- record: cassandra_read_latency_seconds
expr: histogram_quantile(0.95, rate(cassandra_read_latency_seconds_bucket[5m]))
- record: cassandra_write_latency_seconds
expr: histogram_quantile(0.95, rate(cassandra_write_latency_seconds_bucket[5m]))
- record: cassandra_read_throughput
expr: rate(cassandra_reads_total[5m])
- record: cassandra_write_throughput
expr: rate(cassandra_writes_total[5m])
- record: cassandra_cpu_usage_percentage
expr: 100 - avg by (instance)(irate(node_cpu_seconds_total{mode="idle"}[5m]))
- record: cassandra_memory_usage_bytes
expr: node_memory_MemTotal_bytes - node_memory_MemFree_bytes
- record: cassandra_disk_io_operations
expr: rate(node_disk_io_time_seconds_total[5m])
- record: cassandra_network_io_bytes
expr: rate(node_network_receive_bytes_total[5m]) + rate(node_network_transmit_bytes_total[5m])
- record: cassandra_node_status
expr: cassandra_node_status
- record: cassandra_replication_delay_seconds
expr: cassandra_replication_delay_seconds
Here are some example Prometheus alert rules for Cassandra:
groups:
- name: cassandra_alerts
rules:
- alert: HighReadLatency
expr: cassandra_read_latency_seconds > 0.5
for: 5m
labels:
severity: critical
annotations:
summary: "High Read Latency in Cassandra"
description: "Cassandra read operations are experiencing high latency."
- alert: HighWriteLatency
expr: cassandra_write_latency_seconds > 0.5
for: 5m
labels:
severity: critical
annotations:
summary: "High Write Latency in Cassandra"
description: "Cassandra write operations are experiencing high latency."
- alert: HighCPUUsage
expr: cassandra_cpu_usage_percentage > 90
for: 5m
labels:
severity: critical
annotations:
summary: "High CPU Usage in Cassandra"
description: "Cassandra server CPU usage is above 90%."
- alert: HighMemoryUsage
expr: cassandra_memory_usage_bytes > 536870912 # 512 MB
for: 5m
labels:
severity: warning
annotations:
summary: "High Memory Usage in Cassandra"
description: "Cassandra is using more than 512 MB of memory."
- alert: HighDiskIOOperations
expr: cassandra_disk_io_operations > 100
for: 5m
labels:
severity: warning
annotations:
summary: "High Disk I/O Operations in Cassandra"
description: "Cassandra is performing a high number of disk I/O operations."
- alert: HighNetworkIO
expr: cassandra_network_io_bytes > 10000000 # 10 MB/s
for: 5m
labels:
severity: warning
annotations:
summary: "High Network I/O in Cassandra"
description: "Cassandra is using more than 10 MB/s of network I/O."
- alert: NodeNotHealthy
expr: cassandra_node_status != 1
for: 5m
labels:
severity: critical
annotations:
summary: "Cassandra Node Not Healthy"
description: "Cassandra node status is not healthy."
- alert: ReplicationDelayTooHigh
expr: cassandra_replication_delay_seconds > 60
for: 5m
labels:
severity: warning
annotations:
summary: "High Replication Delay in Cassandra"
description: "Cassandra data replication delay is exceeding 60 seconds."
For Cassandra Grafana dashboard, you can find or create one that suits your needs. These dashboards typically include charts and visualizations for various Cassandra performance metrics, such as read/write operation latency, CPU usage, memory usage, disk I/O, network I/O, node status, and data replication delay. You can import an existing dashboard using its ID or download a JSON file from the Grafana dashboard repository, and then customize and configure it according to your requirements.
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。
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。