Member-only story
2 min readMar 21, 2025
–
We understand the critical role metrics play in monitoring and understanding our applications. We’ve likely encountered terms like “count,” “gauge,” and “histogram,” but truly grasping their nuances is essential for effective observability. Let’s break down these metric types with concrete examples, focusing on the conceptual differences rather than diving into specific code implementations.
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The Foundation: What are Metrics?
Metrics are numerical representations of data measured over time. They allow us to track performance, identify anomalies, and make informed decisions about our systems.
Count: The Accumulator
Concept: A count metric represents a cumulative total of…
Member-only story
2 min readMar 21, 2025
–
We understand the critical role metrics play in monitoring and understanding our applications. We’ve likely encountered terms like “count,” “gauge,” and “histogram,” but truly grasping their nuances is essential for effective observability. Let’s break down these metric types with concrete examples, focusing on the conceptual differences rather than diving into specific code implementations.
Press enter or click to view image in full size
The Foundation: What are Metrics?
Metrics are numerical representations of data measured over time. They allow us to track performance, identify anomalies, and make informed decisions about our systems.
Count: The Accumulator
Concept: A count metric represents a cumulative total of events. It’s an ever-increasing value that tracks the number of times something has occurred.
Use Cases:
- Number of requests received.
- Number of errors encountered.
- Number of database queries executed.
Example: Imagine a server tracking the number of incoming HTTP requests.
- At the start, the count is 0.
- After the first request, it’s 1.
- After the second, it’s 2.