Machine Data Intelligence Insights
Read our latest posts to gain insights into all things related to machine data intelligence, time series data, infrastructure monitoring, and IoT from the experts at Circonus
Circonus Spring 2020 Release Includes Kubernetes Monitoring Solution
This week, we announced the availability of our Spring 2020 release. The highlight of the release is our Kubernetes monitoring solution, which provides health-based alerting and horizontal pod auto-scaling. Additional…
Monitoring Latency SLOs with Histograms and CAQL
Latency SLOs help us quantify the performance of an API endpoint over a period of time. A typical latency SLO reads as follows: The proportion of valid* requests served over…
Using CAQL to Identify Hosts with Top CPU Usage
A common task that users want to perform when monitoring their infrastructure is to identify their top resource consumers. Although the following techniques can be applied to numerous different resource…
We’re Not Going Back
In a conversation with my sister last week, I was musing whether we would go back to shaking hands in the aftermath of the coronavirus and in general what the…
Percentile Aggregation with Histograms and CAQL
Percentiles are commonly used for measuring statistics, particularly when analyzing things like latency. Unfortunately, people frequently get tripped up when they want to take multiple percentiles and aggregate them. For…
Circonus Dark Mode Is Here
Today we want to talk about a welcome change to Circonus’ user interface: the addition of dark mode. Once found only in apps themselves, dark mode is now supported by…
