Key Performance Indicators (KPIs) for APIs
As an API monitoring tool, APImetrics focuses on the ‘hard’ KPIs, and looking beyond the obvious ones that passive monitoring tools and solutions capture and at the critical numbers you need to focus on to understand how an API works and the impact that it is having on the services you deliver, integrate to, or provide.
Focusing on measurable metrics, APImetrics API performance monitoring focuses on the following:
- Call Latency – broken down into the key metrics available like Networking times, server process and upload and download speeds
- Total pass and error rates – the measured success rates in terms of HTTP or other codes
- Effective pass rates – the pass rate when you take outliers or ‘passing errors’ (like a HTTP 200 OK! hiding an error) into account
- The Cloud API Service Consistency score which takes into account the consistency of service
Multiple ways to measure APIs and the impact they may have on your services, customers and critical interdependencies. But outside of what you can measure with your current products.
With active monitoring, we can control the queries and functionally validate what comes back and how it works, then score the API over time to measure how it stacks up to past performance, or even performance against other APIs in class.
Measured Pass Rate
The pass rate is the actual measured success rate for an API call from a specific location.
But APIs can pass at different rates from different locations. So don’t just assume that HTTP-200 means ‘All OK’. Just because your API gateway or APM stack logs show 200 codes doesn’t mean that everything is working well – or even at all.
Effective Pass Rate
It’s entirely possible to have two APIs doing the same thing, but with wildly different effective pass rates.
Even with a 100% pass rate, there may be events and performance issues that cause timeouts and other problems. You need to take into account the performance, including latencies and items that may affect end users.
Location Impact on KPIs
Latency is complex for APIs. Using a common ‘ping’ tool won’t tell you what you need to know. API calls include multiple steps:
- Connect Time
- DNS Look Up
- Server Side Processing Time
- Internet Travel Time
- Total Call Time
And each of these vary by geography. You need careful analysis to measure an API call and to identify the KPIs that might matter.
A slow API might not be a problem. But an API that is slow only sometimes might well be. Systems measuring average performance can miss significant performance issues lasting many hours.
This is why APImetrics uses CASC (Cloud API Service Consistency) scoring. It’s like-for-like comparisons between different APIs that show performance as a single, 3-digit score.
A KPI which relies just on one dimension could be misleading and lead to measurement of the wrong things.