Downsampling in Tech Insights Monitoring Metric Trends and KPIs

Introduction

Downsampling is the process of reducing the sampling rate of a set of data. With downsampling, the end result, a KPI or trend in Tech Insights Monitoring examples, is not displaying the results of all data points, but rather is picking up one out of N samples of the metric’s dataset where N is set to various integers to control how many data points are plotted in total.

For example, if we have a trend where Category = Calls + Metric = Call Streams with a time window of Last 24 Hours, you’ll notice there are data points plotted in every 10 minute increments. That exact metric when viewed with a time window of Last 4 Hours shows data points in every 1 minute increments. The underlying data to power 1 minute increments is there to power any time window, but to help performance and maintain feasibility, the Last 24 Hours trend is downsampled.

The end result is that the metric for Last 24 hours is downsampled to ultimately plot the aggregation (max, min, su, average, or latest) of the underlying data in every 10 minute window.

Why is it needed?

To illustrate the need for downsampling, consider a “Last 30 Days” Tech Insights Monitoring time window for a trend. If no downsampling were in effect and we were to display one data point per minute, that would be over 43,000 data points to plot which is roughly 4x more than the number of pixels the standard screen has today - that’s simply not possible. With large data volumes there’s often a technical requirement to downsample results in order to feasibly plot datasets. Additionally, there are serious application performance implications when dealing with datasets that large and downsampling drastically improves performance.

When does WXP Collaboration Use Downsampling?

If the time window in Tech Insights monitoring is greater than 4 hours, downsampling is in effect. That means any selection at or below the “Last 24 hours” selection in the “LAST HOURS/DAYS” time picker section or any selection in the “CUSTOM DATE/TIME” section of the picker where the end time is more than 4 hours past the start time will have downsampling in effect.

When downsampling applies

Downsampling when the selected time window is > 4 hours (points are grouped into larger buckets, such as 10 minutes). This applies to:

• Preset windows (for example, Last 24 hours)

• Custom date/time ranges where end − start > 4 hours

• No downsampling when the selected time window is ≤ 4 hours (charts use 1-minute points).

Target Audience

• Tech Insights Monitoring users (analysts, admins, operators)

• Anyone reviewing real-time or historical trends in WXP Collaboration

Scope

• Applies to Tech Insights Monitoring charts (KPIs and trends)

• Focuses on display granularity, not data collection frequency

Prerequisites

• Access to Tech Insights Monitoring dashboards

• Basic familiarity with chart time windows and aggregation

Best practices related to downsampling:

• Using “Last 4 Hours” as the time horizon is the best way to have the largest window with 1 minute granularity on the x-axis and no downsampling in effect.

  • To maintain a 4 hour window while navigating to different points in time in the past, simply hit the pause button when in “Last 4 Hours” and navigate back/forward in 4 hour increments with the rewind/fast forward buttons

• Use broad time windows (anything beyond 4 hours) to look for general themes and outliers in the data. Once a point if interest is found, hone in on that point in time with a 4 hour window (or less) around it.

• When using a broad time window (anything beyond 4 hours), consider using a different aggregation than WXP Collaboration’s standard “latest” function so you can avoid potentially arbitrary “latest” values.

  • In general, “Average” is a great aggregation to use for large time windows.

  Note: If an aggregation is not specified or available in a trend/KPI configuration, the WXP Collaboration default is to use “latest”

Limitations and notes

• Downsampling changes display granularity, not the underlying data collected.

• Bucket sizes may vary by window to balance performance and readability.

• Some charts may restrict which aggregations are available.

Troubleshooting

1. Why don’t I see per-minute points?

   A) Your window is > 4 hours. Switch to Last 4 hours or a smaller custom range.

2. Why does my value look off in a long window?

   A) Check the aggregation. Try Average or Max/Min instead of Latest.

3. Why does the chart feel slow?

   A) Reduce the time window or filter the dataset (fewer series or entities).