Site Reliability Engineering (SRE) is all about using software engineering principles to operate systems reliably. But you can’t improve what you don’t measure. Effective monitoring is the cornerstone of SRE, enabling proactive identification and resolution of issues before they impact users. While the possibilities for monitoring are endless, focusing on the right metrics is crucial. This post outlines seven essential monitoring metrics for SREs, explaining why they matter and how to use them effectively.
1. Error Rate: The Pulse of Your System’s Health
What it is: The percentage of requests that result in errors. This can include HTTP 5xx errors, application-level exceptions, or any other indication of a failed operation.
Why it matters: Error rate is a direct indicator of user-facing problems. A spike in error rate signals an immediate issue that needs investigation. Tracking it over time helps identify trends and potential regressions. It’s a key component of Service Level Indicators (SLIs) and Service Level Objectives (SLOs).
What to look for: Sudden spikes, consistent increases, and deviations from established baselines.
2. Latency: Measuring User Experience
What it is: The time it takes to process a request, measured from the client’s perspective. This includes network latency, application processing time, and database query time.
Why it matters: Latency directly impacts user experience. Slow responses lead to frustration and abandonment. Tracking latency distributions (e.g., P50, P90, P99 percentiles) helps identify performance bottlenecks and ensure consistently fast responses for all users.
What to look for: Increasing P99 latency, which indicates that a small percentage of users are experiencing significant delays. Also, consistently high P50 latency suggests a systemic performance issue.
3. CPU Utilization: The Core Workload Indicator
What it is: The percentage of CPU resources being used by your applications and services.
Why it matters: High CPU utilization can indicate that your systems are overloaded or that there are inefficient processes consuming excessive resources. Monitoring CPU usage helps proactively scale resources and optimize code.
What to look for: Sustained high CPU utilization (e.g., above 80%) and spikes that coincide with performance issues.
4. Memory Utilization: Preventing Out-of-Memory Errors
What it is: The percentage of memory being used by your applications and services.
Why it matters: Running out of memory can cause applications to crash or become unresponsive. Monitoring memory usage helps identify memory leaks and prevent out-of-memory errors.
What to look for: Increasing memory usage over time, especially if it doesn’t correlate with increased traffic. Also, look for sudden drops in available memory.
5. Disk I/O: Assessing Storage Performance
What it is: The rate at which data is being read from and written to disk.
Why it matters: Slow disk I/O can significantly impact application performance. Monitoring disk I/O helps identify storage bottlenecks and ensure that your applications have sufficient access to data.
What to look for: High disk I/O wait times and sustained high disk utilization.
6. Network Traffic: Detecting Anomalies and Bottlenecks
What it is: The amount of data being sent and received over your network.
Why it matters: Unexpected spikes or drops in network traffic can indicate security breaches, DDoS attacks, or network congestion. Monitoring network traffic helps identify these issues and ensure network stability.
What to look for: Sudden increases in inbound or outbound traffic, and anomalies in traffic patterns.
7. Saturation: Understanding System Capacity
What it is: A measure of how “full” a resource is, indicating how close it is to its maximum capacity. This can apply to CPU, memory, disk, or network.
Why it matters: Saturation is a leading indicator of future problems. When a resource is saturated, even small increases in load can cause significant performance degradation. Proactively addressing saturation prevents outages and ensures system stability.
What to look for: Resources consistently operating at high utilization levels (e.g., above 80-90%).
Conclusion
These seven metrics provide a solid foundation for SRE monitoring. Remember that monitoring is not just about collecting data; it’s about acting on that data. Configure alerts to notify you when metrics exceed established thresholds, and use that information to proactively identify and resolve issues before they impact your users. By focusing on the right metrics and taking action on the insights they provide, you can build and operate highly reliable systems.
