Create Splunk dashboard with data from excel file

1. Can Saved Searches Update an Excel File with Predefined Columns?

Not directly. Splunk saved searches export results in formats like:

CSV

JSON

XML

But you can:

Schedule a saved search to export as a CSV.

Use a script (Python, PowerShell, etc.) outside of Splunk to:

Watch the exported file.

Insert data into a predefined Excel template.

Save it as .xlsx.

Example:

Use the outputcsv command in your saved search:

your search query

| outputcsv my_output.csv

Then use Python (with pandas and openpyxl) to map this CSV into a predefined Excel template.

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2. Can You Use Excel Files to Create Splunk Dashboards?

No, not directly. Splunk dashboards rely on:

Indexed data in Splunk

Real-time or scheduled searches

Lookups (CSV-based), not .xlsx

But you can:

Convert your Excel file to CSV

Upload it as a lookup table in Splunk

Use it in searches like:

| inputlookup my_excel_data.csv

From there, you can create dashboards.

How to optimise Splunk Queries

Optimizing Splunk queries is key to getting faster results, reducing system load, and improving the efficiency of your dashboards and alerts. Here's a practical guide to help you optimize your Splunk searches:

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1. Filter Early, Filter Often

Narrow your time range as much as possible.

Use index=, sourcetype=, and source= as early as possible in the query:

index=security sourcetype=syslog error

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2. Avoid Wildcards at the Beginning

Bad:

index=*security*

Good:

index=security

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3. Use fields to Limit Output Columns

If you only need certain fields, extract them early:

index=web | fields host, status, uri_path

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4. Use where Instead of search After the Pipe

where is more efficient for numerical or conditional filtering:

| where status=500 AND duration > 1000

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5. Avoid Expensive Commands Early (like join, stats, lookup)

Push expensive commands as late as possible. Consider using stats instead of join when possible.

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6. Replace join with stats

Instead of:

index=a | join user_id [ search index=b | fields user_id, role ]

Use:

(index=a OR index=b) | stats values(role) as role by user_id

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7. Use tstats for Data Models

| tstats is faster than raw searches for data models:

| tstats count from datamodel=Web.Web by Web.src, Web.dest

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8. Schedule Reports and Use Summary Indexes

For repeated heavy queries, schedule them and store the results in a summary index to reduce runtime in dashboards.

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9. Avoid Subsearches with Large Output

Subsearches should return <50,000 results; otherwise, they can slow down or fail.

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10. Use eventstats Instead of stats if You Need to Keep Raw Events

| eventstats avg(duration) as avg_duration