The Service Health view on the Deployments tab shows you the latency, error rate, and operation rate of your Key Operations (operations whose performance is strategic to the health of your system) on the selected service.
Key Operations are displayed in order of magnitude of change in performance (you can change the order). You can quickly see the top performance changes and compare performance during latency or error regression spikes with normal performance.
View top changes in performance
Lightstep Observability displays sparkline charts for Key Operations on the service. They show recent performance for Service Level Indicators (SLIs): latency, error rate, and operation rate. Shaded yellow bars to the left of the chart indicate the magnitude of the change.
If there’s a deployment marker visible, that change is measured as the difference between the selected version and all other versions. If there is no marker, the change is measured as the difference between the first and second half of the time period shown in the chart.
More About How Lightstep Observability Measures Change
When determining what has changed in your services, Lightstep Observability compares the SLI of the baseline SLI timeseries to the comparison SLI timeseries. Those time periods are determined using the data currently visible in the charts.
You can change the amount of time displayed using the time period dropdown at the top right of the page.
The baseline and comparison time periods are determined as follows:
If there is one or more deployment markers visible:
- For latency and error rates, Lightstep Observability compares the performance after the selected version to performance in all other versions.
- For operation rate, it compares the rate before the deployment marker to after the deployment marker.
If there are no deployment markers visible:
Lightstep Observability compares the performance of the first half of the time period to the second half.
Only changes that are relative (i.e. a change of 10ms to 500ms is ranked higher than one of 1s to 2s) are considered. The yellow bars on the sparkline chart indicate the amount of change. Lightstep Observability measures two aspects of change: size and continuity. A full bar indicates that a large, sustained change has happened. Smaller bars indicate either a smaller change or one that did not last for the full time period.
The yellow bar means that an SLI had an objectively large change, regardless of service or operation. Lightstep’s algorithm runs on each SLI independently. For example, when the bar displays for an operation’s latency, that means latency has changed – not that its change was greater compared to the other SLIs.
Select an operation’s sparkline charts to view larger charts for the latency, error rate, and operation rate. You use these larger charts to start your investigation.
Change the sparkline charts display
By default, the operations are sorted by the amount of detected change (largest to smallest). Use the dropdown to change the sort.
Also by default, only the latency percentile with the largest amount of change displays. You can change the sparkline charts to show more percentiles using the More ( ⋮ ) icon.
You can search for an operation using the Search field.
Change the reporting time period
By default, the data shown is from the last 60 minutes. You can customize that time period using the dropdown. Use the < > controls to move backwards and forwards through time. You can view data up to 3 days in the past.
You can also zoom in on a time period by clicking and dragging over the time period you want a closer look at. The charts redraw to report on just the period you selected.
The Service Health view on the Deployments tab provides the ability to see how deployments specifically affect performance of your services. When you implement an attribute to display versions of your service, a deployment marker displays at the time the deployment occurred, both in the Service Health view and in Change Intelligence.
These markers allow you to quickly correlate deployment with a possible regression.
When you have multiple versions in a time window, you can view the performance of each deployed version. For example, in this image of the Service Health view, multiple versions have been deployed. Hover over the chart to see the percentage of traffic in each version.
Learn more about how to use this view to monitor the health of your deployments.