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Percentile

As explained in gRPC Microservices in Go

P95 latency is the 95th-percentile response latency, below which 95 percent of observed latency values fall.

P95 latency is the response-latency value at or below which 95 percent of observed requests fall. It describes the latency distribution more reliably than an average when a small number of slow requests would otherwise distort the result. section 9.1.2

Use percentile latency to interpret production behavior:

  • Collect observed response latencies and order them before locating the requested percentile. section 9.1.2
  • Read P95 as a user-facing threshold: a value of 46.79 ms means 95 percent of measured latencies are 46.79 ms or less. section 9.3.6
  • Track percentile metrics over time rather than relying on a single aggregate value. section 9.2.4

In distributed services, percentile latency belongs alongside request rate and error rate. Jaeger can display service latency distributions and performance summaries from Prometheus time-series data, while traces help inspect request flow and related service or database spans. section 9.2.4 section 9.3.6

Order-service performance

A Jaeger service-performance view reports an Order-service P95 latency of 46.79 ms and a request rate of six requests per second. The percentile states the typical upper-bound experience for 95 percent of observed requests; traces and database-related spans support investigation of slower requests. section 9.3.6

Figure 9.14 Jaeger SPM

Inspect the Jaeger SPM performance summary showing P95 latency alongside request rate and error rate. section 9.3.6

How gRPC Microservices in Go covers it

How deep it goes
Explains ordering observations and interpreting P95, then stops short of implementation formulas or percentile-estimation algorithms.
Examples
Uses sorted latency values, a 95th-percentile interpretation, and an Order-service Jaeger result of 46.79 milliseconds.
What it assumes
Assumes observed response-latency values and teaches percentile interpretation by contrasting it with arithmetic averages.
What you can do after
Evaluate service performance by interpreting P95 latency alongside request rate, error rate, traces, and database spans.
How it connects
Connects percentile latency with latency distributions, observability, Jaeger, Prometheus, OpenTelemetry, tracing, and service metrics.

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This explainer was generated by Manning's knowledge graph from the text of gRPC Microservices in Go. The section links point to the parts of the book it draws on.