Observing your compute resources is essential for maintaining both system performance and reliability. By carefully monitoring CPU usage, you gain insight into how efficiently your applications and services are running. High CPU utilization over extended periods can signal a need for optimization or scaling, while consistently low usage might indicate over-provisioned resources. For instance, in a web server environment, a sudden spike in CPU usage could mean a surge in user traffic or a runaway process that needs immediate attention.

Memory usage is equally important to monitor. Insufficient memory can lead to swapping or out-of-memory errors, causing applications to slow down or crash. Tracking memory consumption helps you identify memory leaks or inefficient applications, which can be particularly problematic in environments running containerized workloads. For example, a microservice that gradually consumes more memory over time may indicate a leak, requiring code review and remediation.

I/O operations, which include disk reads and writes, play a critical role in application responsiveness. High disk latency or throughput issues often result in sluggish application performance and can be caused by poorly optimized queries, excessive logging, or hardware limitations. In a database server, for example, monitoring I/O patterns can reveal bottlenecks that, if addressed, significantly improve transaction speeds and user experience.

Network activity is another vital metric to observe. Unusual spikes in network traffic may suggest security incidents, such as DDoS attacks, or misconfigured services generating excessive outbound requests. In distributed systems, monitoring network latency and throughput ensures reliable communication between services and helps prevent cascading failures caused by network congestion.