In an earlier Post, I talked about how SLOs can be misleading, and the Service Level Indicator in consideration was Uptime. There is another SLI which is almost impossible to be accurate about, Latency.
Like Uptime is measured as % and aggregated over a month/year/week, based on time window choice, Latency is for a unit of time (ms and s.), and the preferred aggregate is percentile.
The purpose of this post is to debunk common mistakes that I did while dealing with Percentiles.
Why is it important to understand percentiles in depth? Because one of the critical Indicators of software performance, Latency, is measured using Percentiles. Somebody cannot deal with something as clinical as performance without understanding the behavior of its yardstick. …
An illustrated summary of Developers -> DevOps -> SRE
To the other side
So they deployed people on the other side
Wikipedia defines Root Cause Analysis (RCA) as “a method of problem-solving used for identifying the root causes of faults or problems.”
Essentially, root cause analysis means to dive deeper into an issue to find what caused a non-conformance. What’s important to understand here is that Root Cause Analysis does not mean just looking at superficial causes of a problem. Rather, it means finding the highest-level cause- the thing that started a chain of cause-effect reactions and ultimately led to the issue at hand.
Root cause analysis methodology is widely used in IT operations, telecommunications, healthcare industry, etc. …
SLO is an acronym for Service Level Objective. But before I explain SLO, you need one more acronym SLI (Service Level Indicator)
An SLI is a quantitative measurement of a (and not the) quality of a Service. It may be unique to each use-case, but there are certain standard qualities of services that practitioners tend to follow.