Skip to content

4.3 Dashboard Configuration

Select deliverables or metrics such as dashboard and alerts for IT operations, production support, app/dev teams, and executives

This section guides you through configuring effective dashboards. The key is selecting metrics that not only align with specific business requirements but also provide actionable insights.

Start by identifying your target audience and setting clear expectations for the dashboard's purpose. To ensure accurate interpretation of the data, provide clear explanations of the source for each metric.

A well-designed dashboard acts as a powerful tool for decision-making. By tailoring metrics and visualizations to specific business objectives, you can empower users to make better decisions and drive positive outcomes.

Preparing for the Exam

  • Review the Getting Started with Dashboards guide. This resource provides step-by-step instructions to build a dashboard in 5-10 minutes and covers fundamental key concepts about dashboards.
  • Ensure you understand the different dashboard display settings, including relative vs. fixed-time intervals, global time override, and local widget time settings.
  • Create dashboards and familiarize yourself with the various data sources, categories, metrics, and measures available for widget configuration. Remember that each test type (category) will offer a different list of metrics depending on the data source.
  • Practice working with measures to understand how they affect the presentation of your data in widgets.

Key Concepts

Metrics

ThousandEyes tests provide a range of metrics, which can be viewed in the Views menu for Cloud and Enterprise Agents. Users can select specific metrics using a drop-down filter list within the interface.

Different test types offer distinct sets of metrics. For example:

Page Load Test metrics include:

  • Page Load Time
  • Errors
  • Timeouts
  • Completion

HTTP Test metrics include:

  • Availability
  • Response Time
  • Throughput

Agents running Page Load tests collect metrics specific to page load and HTTP, as well as network metrics such as loss, latency, and jitter. All these metrics are accessible in views and can be utilized in dashboard construction.

<ThousandEyes Views: Page Load Test Results>

ThousandEyes Views: Page Load Test Results

Dashboards

ThousandEyes dashboards provide customized live views of Enterprise & Cloud Agent tests, Endpoint Agent tests, device layer data, and Internet Insights. These dashboards allow users to visualize and monitor key performance indicators in real-time.

To illustrate, consider an "API Health Overview Dashboard." This dashboard could utilize Number widgets (from the data summary type) to display the average (mean) values for critical API metrics, such as:

  • API Transaction Time
  • API Call Time
  • DNS Time

By configuring these widgets to use the "Cloud and Enterprise Agents" data source, the "Web-API" category, and the relevant metrics, users can create a concise view of API performance.

Widgets

Widgets are customizable visual elements used to display data on ThousandEyes dashboards. They come in various types, including:

  • Live status (agent status, tests, alert lists)
  • Breakdown (stacked bar, grouped bar, and pie charts)
  • Data summary (tables, multi-metric tables, numbers)
  • Time series (line charts, stacked area charts, box and whisker plots)
  • Maps

Embedded Widgets

Embedded widgets allow you to display ThousandEyes data visualizations on external web pages, making the information accessible to a broader audience without requiring direct platform access.

Troubleshooting with Dashboard Drill Down

Dashboards serve as valuable tools for troubleshooting network issues. The API Health Overview Dashboard, for instance, provides a comprehensive view of API performance metrics, allowing engineers to monitor and troubleshoot efficiently. Let's walk through a troubleshooting scenario using this dashboard.

API Health Dashboard - Overview

API Health Overview Dashboard

The API Health (Mean) Widgets are configured using Number tiles from the data summary widget type. They use Cloud and Enterprise Agents as the data source, focusing on Web-API category metrics such as API transaction time, call time, and DNS time, with mean as the measure.

These widgets are ideal for monitoring API performance based on average values for transaction, call, and DNS time for specific tests.

Widget Configuration

Widget Configuration

In our scenario, let's say the engineer finds that the 1.57s API transaction time is high compared to how their API usually performs. To investigate further, the engineer clicks on the mean transaction time widget, which brings up a window with links to the tests associated with the widget.

Clicking on the Problematic Metric

Upon clicking on the widget, the engineer is taken to the exact point in time for the metric shown in the widget. Here, they can contrast API transaction time with other metrics such as API completion, packet loss, latency, and jitter to correlate this particular event.

Drilling Down to the Relevant Test Data

From this page, the engineer can also switch from the API layer view to the Agent to Server network layer view.

Switching to the Network Layer View

In this view, the engineer can look at the path visualization, which can help root-cause network performance issues affecting the API Transaction time. For example, in the image above, notice the yellow color for the agent. This indicates that for this test round, the agent had an 8% packet loss. You can see a peak for both end-to-end packet loss and API transaction time.

Analyzing Path Visualization

By expanding the nodes in the path visualization, the engineer can find links with latency, further aiding in the root-cause analysis of network performance issues affecting the API Transaction time.

This drill-down capability of ThousandEyes dashboards is a powerful troubleshooting tool, allowing engineers to move from high-level overviews to detailed, specific data points quickly and efficiently. For a deeper dive into these features, refer to the Troubleshooting with Dashboard Drill Down documentation.

Resources

Sample Questions

The following sample questions require you to analyze data presented in two ThousandEyes dashboards used to monitor its application service at https://thousandeyes.com:

Refer to the data in these dashboards to answer the questions below.

4.3 Question 1

Which type of test are we using for these dashboards?

  • A) HTTP server
  • B) Page Load
  • C) Agent to server
  • D) FTP

4.3 Question 2

Which type of widgets were used in the executive dashboard? (Select all that apply)

  • A) Agent status
  • B) Map
  • C) Line
  • D) Number
  • E) Color Grid

4.3 Question 3

Analyzing the IT operations dashboard, which agent has a better HTTP Connect Time?

  • A) San Jose CA (AT&T)
  • B) Mexico City Mexico (TelMex)

4.3 Question 4

In the IT operations dashboard, what is the alert trigger reason?

  • A) Page Load Packet Loss
  • B) Network jitter
  • C) Network packet loss
  • D) Page Load Latency

4.3 Question 5

In the executive dashboard, what is the page completion time for the Mexico City agent?

  • A) 100%
  • B) 83.4%
  • C) 15.2%
  • D) 99.67%

4.3 Question 6

In the executive dashboard, what is the total error count for ThousandEyes web page in the last 15 days?

  • A) 520
  • B) 1.58
  • C) 4610
  • D) 4805

4.3 Question 7

In the IT operations dashboard, while comparing the latest metrics, what is the time difference between Page Load time and DOM time?

  • A) 120.6 ms
  • B) 125.3 ms
  • C) 100 ms
  • D) 150.4 ms

4.3 Question 8

A network monitoring engineer is tasked with creating a widget that displays the average packet loss from an agent installed as a Linux package. What is the data source and measure that should be selected?

  • A) Endpoint Agents and Median
  • B) Cloud & Enterprise Agents and Mean
  • C) Routing and Standard Deviation
  • D) Devices and nth Percentile