Database Monitoring Metrics
Open-source database systems can be divided into relational databases (e.g., MySQL, PostgreSQL) and NoSQL databases. Below are some common open-source databases and their corresponding monitoring configurations.
Relational Databases
- MySQL
- Performance Metrics: Query throughput, response time, slow queries.
- Resource Usage: CPU and memory usage, disk I/O, network I/O.
- Replication Status: Master-slave replication delay, replication errors.
- Connections and Threads: Active connections, thread wait times.
- PostgreSQL
- Performance Metrics: Transaction throughput, query latency, index hit rate.
- Resource Usage: CPU and memory usage, disk space.
- Connections: Current active and idle connection counts.
- Locks: Lock wait times and counts.
NoSQL Databases
- MongoDB
- Performance Metrics: Operation throughput, query response times.
- Resource Usage: Memory and disk usage, network traffic.
- Replication and Sharding: Replica set status, shard balancing.
- Connections: Currently open connections.
- Redis
- Performance Metrics: Commands processed per second, key hit/miss rate.
- Resource Usage: Memory usage, network bandwidth.
- Persistence: RDB and AOF status.
- Client Connections: Active connection count.
- Apache Cassandra
- Read/Write Performance: Read/write operation latency and throughput.
- Resource Usage: CPU and memory usage, disk I/O.
- Node Status: Health and status of nodes in the cluster.
- Replication: Data replication delay.
Configuring Monitoring Metrics
Monitoring these database systems typically involves the following steps:
- Enable database monitoring statistics: Most database systems have built-in performance monitoring and statistics features that need to be enabled in the configuration.
- Use dedicated monitoring tools:
- For relational databases, you can use tools like Prometheus with mysqld_exporter or pg_exporter for monitoring.
- For NoSQL databases, consider using exporters like Redis Exporter or Cassandra Exporter.
- Configure data collection and storage:
- Use Prometheus or similar tools to collect and store monitoring data.
- Visualization and alerts:
- Visualize monitoring data using Grafana or similar tools.
- Set up alert rules based on critical metrics and alert notification mechanisms.
- Log monitoring:
- Analyze database logs using ELK Stack or similar log management tools.
By configuring the above monitoring, you can effectively track the health, performance, and resource usage of your databases, detect and address issues in a timely manner, and ensure the stability and efficiency of your database systems.
