Dashboard creation in Elasticsearch

Introduction

A dashboard helps you see important data all in one place. It makes understanding your data easy and quick.

You want to track sales numbers every day in one view.

You need to monitor website traffic and user behavior live.

You want to compare product performance across regions.

You need to share key business metrics with your team regularly.

You want to spot problems quickly by watching data trends.

Syntax

Elasticsearch

1. Create visualizations (charts, tables) using Elasticsearch queries.
2. Open Kibana Dashboard.
3. Click 'Create new dashboard'.
4. Add saved visualizations or create new ones directly.
5. Arrange and resize visualizations on the dashboard canvas.
6. Save the dashboard with a clear name.

Dashboards in Elasticsearch are usually built using Kibana, the visualization tool.

You can add filters and time ranges to make dashboards interactive.

Examples

This query gets the total sales amount to use in a visualization.

Elasticsearch

GET /sales/_search
{
  "size": 0,
  "aggs": {
    "total_sales": { "sum": { "field": "amount" } }
  }
}

This metric will display the total sales number on the dashboard.

Elasticsearch

In Kibana, create a 'Metric' visualization showing total sales using the above aggregation.

This chart helps see sales trends day by day.

Elasticsearch

Create a 'Line chart' visualization showing sales over time using a date histogram aggregation.

Sample Program

This example shows how to create a dashboard with a sales trend line and total sales metric.

Elasticsearch

1. Run this Elasticsearch query to get total sales by month:
GET /sales/_search
{
  "size": 0,
  "aggs": {
    "sales_over_time": {
      "date_histogram": {
        "field": "date",
        "calendar_interval": "month"
      },
      "aggs": {
        "monthly_sales": { "sum": { "field": "amount" } }
      }
    }
  }
}

2. In Kibana, create a Line chart visualization using this aggregation.
3. Create a Metric visualization showing total sales sum.
4. Open Kibana Dashboard, create a new dashboard.
5. Add both visualizations.
6. Arrange them side by side.
7. Save the dashboard as 'Monthly Sales Overview'.

Important Notes

Always name your dashboards clearly so others understand their purpose.

Use filters and time pickers in Kibana to make dashboards interactive and user-friendly.

Keep dashboards simple and focused on key metrics to avoid clutter.

Summary

Dashboards collect important visualizations in one place for easy data viewing.

Use Elasticsearch queries to create visualizations, then add them to Kibana dashboards.

Arrange and save dashboards to share insights with your team quickly.

Practice

1. What is the main purpose of a dashboard in Elasticsearch's Kibana?

easy

A. To display multiple visualizations together for easy data analysis

B. To write complex Elasticsearch queries

C. To store raw data from Elasticsearch indexes

D. To manage user permissions for Elasticsearch

Solution

1. Step 1: Understand dashboard function

   A dashboard groups visualizations so users can see data insights in one place.

2. Step 2: Compare options

   Options A, B, and C describe other tasks not related to dashboard display.

3. Final Answer:

   To display multiple visualizations together for easy data analysis -> Option A

4. Quick Check:

   Dashboard = multiple visualizations [OK]

Hint: Dashboards show many visuals together for quick insights [OK]

Common Mistakes:

• Confusing dashboards with query writing
• Thinking dashboards store raw data
• Mixing dashboards with user management

2. Which syntax correctly adds a saved visualization to a Kibana dashboard?

easy

A. dashboard.addVisualization('vis_id')

B. dashboard.add('vis_id')

C. Dashboard.addVisualization('vis_id')

D. Dashboard.add('vis_id')

Solution

1. Step 1: Recall Kibana dashboard API

   The correct method to add a visualization is Dashboard.add('vis_id') with capital D.

2. Step 2: Check case sensitivity and method name

   dashboard.add('vis_id') uses lowercase dashboard object; options C and D use incorrect method name 'addVisualization'.

3. Final Answer:

   <code>Dashboard.add('vis_id')</code> -> Option D

4. Quick Check:

   Correct method is Dashboard.add() [OK]

Hint: Dashboard object is capitalized; method is add() [OK]

Common Mistakes:

• Using lowercase 'dashboard' instead of 'Dashboard'
• Using wrong method name like addVisualization
• Confusing method parameters

3. Given this Elasticsearch query used in a visualization:

{"query": {"match": {"status": "error"}}}

What will the visualization show when added to a dashboard?

medium

A. All documents with status 'error' count or details

B. All documents regardless of status

C. Documents with status 'success' only

D. An error message due to invalid query

Solution

1. Step 1: Analyze the query filter

   The query matches documents where the field 'status' equals 'error'.

2. Step 2: Understand visualization output

   The visualization will display data filtered to only those documents with status 'error'.

3. Final Answer:

   All documents with status 'error' count or details -> Option A

4. Quick Check:

   Query filters status='error' so visualization shows those docs [OK]

Hint: Match query filters data shown in visualization [OK]

Common Mistakes:

• Assuming it shows all documents
• Confusing 'error' with 'success'
• Thinking query syntax is invalid

4. You tried to add a visualization to a Kibana dashboard but it does not appear. Which is the most likely cause?

medium

A. The dashboard is already full and cannot add more visualizations

B. The Elasticsearch cluster is offline

C. The visualization ID used in the add command is incorrect

D. The visualization was created in a different tool

Solution

1. Step 1: Check visualization ID correctness

   If the ID is wrong, the dashboard cannot find and add the visualization.

2. Step 2: Evaluate other options

   Cluster offline would cause broader failures; dashboards do not have fixed limits; visualizations must be from Kibana.

3. Final Answer:

   The visualization ID used in the add command is incorrect -> Option C

4. Quick Check:

   Wrong ID means visualization won't load [OK]

Hint: Verify visualization ID matches exactly [OK]

Common Mistakes:

• Assuming dashboard has max visualization limit
• Ignoring ID typos
• Blaming Elasticsearch cluster without checking

5. You want to create a dashboard that shows error counts by hour and success counts by hour side by side. Which approach is best?

hard

A. Create a dashboard with only one visualization and switch filters manually

B. Create two visualizations with filters for 'error' and 'success', then add both to the dashboard

C. Create one visualization with a combined filter for 'error' and 'success' together

D. Create visualizations in different dashboards and link them

Solution

1. Step 1: Understand requirement for side-by-side comparison

   Two separate visualizations filtered by 'error' and 'success' allow clear side-by-side display.

2. Step 2: Evaluate other options

   Create one visualization with a combined filter for 'error' and 'success' together mixes filters, losing clarity; A requires manual switching; D separates data, not side-by-side.

3. Final Answer:

   Create two visualizations with filters for 'error' and 'success', then add both to the dashboard -> Option B

4. Quick Check:

   Separate filtered visuals show side-by-side data clearly [OK]

Hint: Use separate filtered visuals for clear side-by-side comparison [OK]

Common Mistakes:

• Combining filters in one visualization losing clarity
• Using one visualization and switching filters manually
• Splitting visuals across dashboards