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Impara Dashboards for Observability | Advanced Observability Practices
Observability Fundamentals in DevOps

bookDashboards for Observability

Dashboards are visual tools that display real-time data from your systems in a clear, organized way. In DevOps, dashboards help you see key information at a glance, such as metrics, logs, and traces:

  • Metrics: show numerical data, like CPU usage or error rates;
  • Logs: provide detailed records of system events and actions;
  • Traces: map the flow of requests through different services.

Dashboards bring all this information together, so you can quickly understand the health and performance of your applications. They make it easier to spot problems, track trends, and make informed decisions. By using dashboards, you can respond faster to issues, improve system reliability, and support better collaboration across your team.

Common Elements of Observability Dashboards

Observability dashboards help you monitor and understand systems by presenting data visually and in real time. Here are the most common elements you will find on these dashboards:

  • Charts: display trends and patterns over time using line charts, bar charts, or area charts;
  • Graphs: show relationships or distributions, such as network connections or error frequencies;
  • Alerts: notify you when metrics cross set thresholds, helping you react quickly to issues;
  • Tables: organize raw data or logs for quick scanning and detailed analysis;
  • Counters and Gauges: provide single-value metrics, like current memory usage or request rate, in a clear and immediate format;
  • Filters and Selectors: let you adjust the data shown by time range, service, or environment, so you can focus on what matters most.

By combining these elements, dashboards give you a clear overview and help you spot problems before they impact users.

Example: Using a Dashboard to Spot System Issues

Imagine you are part of a DevOps team managing an online store. Your dashboard displays several key metrics, including:

  • Total number of user logins;
  • Average response time for web pages;
  • Number of errors per minute;
  • Server CPU usage.

One morning, you notice a sudden spike in the "number of errors per minute" graph. At the same time, the "average response time" also increases. These changes are highlighted in red on your dashboard, making them easy to spot.

Because the dashboard brings this data together in one place, you can quickly see there is a problem affecting users. You alert your team, and together you investigate the cause before more customers are impacted. This quick response is possible because the dashboard made the issue visible right away.

question mark

What is the main purpose of dashboards in observability?

Select the correct answer

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Sezione 3. Capitolo 2

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bookDashboards for Observability

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Dashboards are visual tools that display real-time data from your systems in a clear, organized way. In DevOps, dashboards help you see key information at a glance, such as metrics, logs, and traces:

  • Metrics: show numerical data, like CPU usage or error rates;
  • Logs: provide detailed records of system events and actions;
  • Traces: map the flow of requests through different services.

Dashboards bring all this information together, so you can quickly understand the health and performance of your applications. They make it easier to spot problems, track trends, and make informed decisions. By using dashboards, you can respond faster to issues, improve system reliability, and support better collaboration across your team.

Common Elements of Observability Dashboards

Observability dashboards help you monitor and understand systems by presenting data visually and in real time. Here are the most common elements you will find on these dashboards:

  • Charts: display trends and patterns over time using line charts, bar charts, or area charts;
  • Graphs: show relationships or distributions, such as network connections or error frequencies;
  • Alerts: notify you when metrics cross set thresholds, helping you react quickly to issues;
  • Tables: organize raw data or logs for quick scanning and detailed analysis;
  • Counters and Gauges: provide single-value metrics, like current memory usage or request rate, in a clear and immediate format;
  • Filters and Selectors: let you adjust the data shown by time range, service, or environment, so you can focus on what matters most.

By combining these elements, dashboards give you a clear overview and help you spot problems before they impact users.

Example: Using a Dashboard to Spot System Issues

Imagine you are part of a DevOps team managing an online store. Your dashboard displays several key metrics, including:

  • Total number of user logins;
  • Average response time for web pages;
  • Number of errors per minute;
  • Server CPU usage.

One morning, you notice a sudden spike in the "number of errors per minute" graph. At the same time, the "average response time" also increases. These changes are highlighted in red on your dashboard, making them easy to spot.

Because the dashboard brings this data together in one place, you can quickly see there is a problem affecting users. You alert your team, and together you investigate the cause before more customers are impacted. This quick response is possible because the dashboard made the issue visible right away.

question mark

What is the main purpose of dashboards in observability?

Select the correct answer

Tutto è chiaro?

Come possiamo migliorarlo?

Grazie per i tuoi commenti!

Sezione 3. Capitolo 2
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