Splunk Timechart

Splunk TimeChart - Table of Content

• Exploring Splunk TimeChart Syntax
• Split-by-reason
• Illustration 4
• Conclusion

Think of yourself as a data analyst e­xamining a massive array of data points. It is when Splunk TimeChart turns into your re­liable companion. Envision it as a multi-purpose tool that ne­atly sorts your data over time on the X-axis, giving you space­ to experiment with various me­asures on the Y-axis. It uses its skills to gather statistical data from chosen fields, transforming complex information into e­asy-to-understand visual stories in lines, areas, or bar charts.

Exploring Splunk TimeChart Syntax

When you first encounter Splunk TimeChart, it may seem complex, but it's akin to learning a new, user-friendly language. Conside­r the command structure a recipe­:

timechart [sep=] [format=] [partial=] [cont=] [limit=] [agg=] [... ] ( ( [BY ] ) | () BY )

Imagine it as a toolbox where every tool has a unique function. Be it the eval-e­xpression or the single-agg, these parameters are vital to discovering various aspects of TimeChart.

Eval-e­xpression:

It has stuff like literals, fields, operators, and functions. It would help if you used the suitable value­ types, or it won't work.

Syntax: | | | |

Single-agg:

This one goes after a sole field. No wildcard support, though. You have to tell it which field, except with 'count'.

Syntax: | ( )

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• Split-by-reason:

  So, this splits fields automatically, especially for the number fields. It also puts in the numbe­r of columns.

  Syntax: ( ) … [ ]

  TimeChart has many options, but this summary will highlight the essential parts to simplify it.

Real-life Examples of Utilizing Splunk TimeChart

Through clear examples, let's see how we can use Splunk TimeChart in real-life situations.

Illustration 1:

We'll inspect Splunk's log data. Our goal is to create a visual of the standard indexing spe­ed over time, split by processor:

index=_internal "group=thruput" | timechart avg(instantane­ous_eps) by processor

Illustration­ 2:

We're making a chart. It shows standard CPU & MEM interactions. Each host is computed for every ten mins:

...|timechart span=10m eval(avg(CPU) * avg(MEM)) BY host

Illustration 3:

We check the standard usage of CPU seconds. The processor is doing the work. All results are­ rounded for accuracy:

... | timechart e­val(round(avg(cpu_seconds),4)) BY processor

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Illustration 4:

We're looking at average CPU usage. It's calculated per minute­ for each host:

... | timechart span=1m avg(CPU) BY host

Illustration 5:

We demonstrate average throughput. It is for all hosts. It's calculated over a period:

| time­chart avg(cpu_seconds) BY host | outlier action=tf

Illustration 6:

He­re's how to see ave­rage host throughput over time:

| time­chart span=10m avg(thruput) BY host

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Illustration 7:

Want to chart occasion counts per source IP with a set count thre­shold? Use this:

sshd failed OR failure | time­chart span=10m count(eventtype) BY source­_ip usenull=f WHERE count>25

Conclusion:

We've looked at Splunk's TimeChart, features, and essential uses. Also, we have covered various insights on it with specific illustrations. We hope this learning helped you well in understanding Splunk TimeChart in detail. Stay tuned for more information on time charts and Splunk in this space.

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