Monitor service health and performance changes

We will be introducing new workflows to replace the Deployments tab and RCA view. As a result, they will soon no longer be supported. Instead, use notebooks for your investigation where you can run ad-hoc queries, view data over a longer time period, and run Cloud Observability’s correlation feature.

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.

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 from your retention window (default is three days).

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.

View top changes in performance

Cloud 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.

The operations are initially sorted by highest change during the visible time period (you can change that time period) and you can also change the sorting order).

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 Cloud Observability Measures Change

When determining what has changed in your services, Cloud 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, Cloud 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:
Cloud 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. Cloud 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. Cloud Observability’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.

Expandable end

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.larger charts are highlighted on the right

View associated spans

Span samples for the selected operation are shown in a table below the charts (click View spans). Click a span’s row to view the span in it’s trace. Span samples

Monitor deployments

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 on all charts in Cloud Observability.

We will be introducing new workflows to replace the Deployments tab and RCA view. As a result, they will soon no longer be supported. Instead, use notebooks for your investigation where you can run ad-hoc queries, view data over a longer time period, and run Cloud Observability’s correlation feature.

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.Multiple markers

Learn more about how to use this view to monitor the health of your deployments.

See also

Monitor deployments

Updated Jun 1, 2020