Spelunking your Splunk – Part V (Splunk Stats)

By Tony Lee

Welcome to the fifth article of the Spelunking your Splunk series, all designed to help you understand your Splunk environment at a quick glance.  Here is a quick recap of the previous articles:

• Spelunking your Splunk Part I (Exploring Your Data) - A clever dashboard that can be used to quickly understand the indexes, sources, sourcetypes, and hosts in any Splunk environment.
• Spelunking your Splunk – Part II (Disk Usage) - A dashboard that can be used to monitor data distribution across multiple indexers.
• Spelunking your Splunk – Part III (License Usage) - A dashboard to understand license usage over time.
• Spelunking your Splunk – Part IV (User Metrics) - A dashboard to provide insight into user activity

This article focuses on understanding your Splunk environment at a high-level.  Have you ever wondered the following?

• How many events ingested over a user-defined time period
• How that equates to events per second (EPS)
• The distinct host count
• Number of indexes with data
• Number of sourcetypes
• Number of sources
• Visually what the data ingest looks like by total event count and by index

This dashboard will give it to you and do it fast!  As a bonus we will provide the dashboard code at the end of the article.

Figure 1:  Splunk Stats dashboard

Finding detailed index information quickly

There are at least two places within Splunk to discover index information. The first uses a RESTful call and provides detailed information about indexes. The second requires more calculation and is less efficient. For this exercise, lets try copying and pasting the following RESTful search into your Splunk search bar to see what data is returned:

| rest /services/data/indexes-extended

Figure 2:  Results of the restful search (remember to scroll right)

| dbinspect index=*

Figure 3:  Column headers from dbinspect (remember to scroll right)

Now try the following which combines both (thank you Splunk!):

| dbinspect index=* cached=t
| where NOT match(index, "^_")
| stats max(rawSize) AS raw_size max(eventCount) AS event_count BY bucketId, index
| stats sum(raw_size) AS raw_size sum(event_count) AS event_count dc(bucketId) AS buckets BY index
| eval raw_size_gb = round(raw_size / 1024 / 1024 / 1024 , 2) | fields index raw_size_gb event_count buckets
| join type=outer index [| rest /services/data/indexes-extended 
| table title maxTime minTime frozenTimePeriodInSecs
| eval minTime = case(minTime >= "0", minTime)
| stats max(maxTime) AS maxTime min(minTime) AS minTime max(frozenTimePeriodInSecs) AS retention BY title
| eval maxTime = replace(maxTime, "T", " "), maxTime = replace(maxTime, "\+0000", ""), minTime = replace(minTime, "T", " "), minTime = replace(minTime, "\+0000", ""), retention = round(retention / 86400, 0)." Days" 
| rename title AS index] | fields index raw_size_gb event_count buckets  minTime maxTime retention
            | rename raw_size_gb AS "Index Size (GB)" event_count AS "Total Event Count" buckets AS "Total Bucket Count" minTime AS "Earliest Event"  maxTime AS "Latest Event"   retention AS Retention


Now that you understand the basics, the sky is the limit.  :-)

Finding source, sourcetype, and host data quickly 

You may remember from the first article of this series (Spelunking your Splunk Part I (Exploring Your Data) called tstats.  In a nutshell, tstats can perform statistical queries on indexed fields—very very quickly.  These indexed fields by default are index, source, sourcetype, and host.  It just so happens that these are the fields that we need to understand the environment.  Best of all, even on an underpowered environment or one with lots of data ingested per day, these commands will still outperform the rest of your typical searches even over long periods of time.  This works great for our dashboard!

Conclusion

Splunk provides decent visibility into various features within Monitoring Console / DMC (Distributed management console), but we found this flexible and customizable dashboard to be quite helpful for gaining additional insight.  We hope this helps you too.  Enjoy!

Dashboard XML code

Below is the dashboard code needed to enumerate your Splunk stats.  Feel free to modify the dashboard as needed:

<form>
  <label>Splunk Stats</label>
  <fieldset submitButton="true" autoRun="true">
    <input type="time" token="time">
      <label>Time Range Selector</label>
      <default>
        <earliest>-7d@h</earliest>
        <latest>now</latest>
      </default>
    </input>
  </fieldset>
  <row>
    <panel>
      <single>
        <title>Distinct Events</title>
        <search>
          <query>| tstats count where index=*</query>
          <earliest>$time.earliest$</earliest>
          <latest>$time.latest$</latest>
          <sampleRatio>1</sampleRatio>
        </search>
        <option name="drilldown">none</option>
        <option name="refresh.display">progressbar</option>
      </single>
    </panel>
    <panel>
      <single>
        <title>Events Per Second (EPS)</title>
        <search>
          <query>| tstats count where index=* | addinfo | eval diff = info_max_time - info_min_time | eval EPS = count / diff | table EPS</query>
          <earliest>$time.earliest$</earliest>
          <latest>$time.latest$</latest>
        </search>
        <option name="drilldown">none</option>
      </single>
    </panel>
    <panel>
      <single>
        <title>Distinct Hosts</title>
        <search>
          <query>| tstats dc(host) where index=*</query>
          <earliest>$time.earliest$</earliest>
          <latest>$time.latest$</latest>
          <sampleRatio>1</sampleRatio>
        </search>
        <option name="drilldown">none</option>
        <option name="refresh.display">progressbar</option>
      </single>
    </panel>
    <panel>
      <single>
        <title>Distinct Indexes with Data</title>
        <search>
          <query>| dbinspect index=* cached=t
| where NOT match(index, "^_")
| stats max(rawSize) AS raw_size max(eventCount) AS event_count BY bucketId, index
| stats sum(raw_size) AS raw_size sum(event_count) AS event_count dc(bucketId) AS buckets BY index
| eval raw_size_gb = round(raw_size / 1024 / 1024 / 1024 , 2) | fields index raw_size_gb event_count buckets
| join type=outer index [| rest /services/data/indexes-extended 
| table title maxTime minTime frozenTimePeriodInSecs
| eval minTime = case(minTime &gt;= "0", minTime)
| stats max(maxTime) AS maxTime min(minTime) AS minTime max(frozenTimePeriodInSecs) AS retention BY title
| eval maxTime = replace(maxTime, "T", " "), maxTime = replace(maxTime, "\+0000", ""), minTime = replace(minTime, "T", " "), minTime = replace(minTime, "\+0000", ""), retention = round(retention / 86400, 0)." Days" 
| rename title AS index] | fields index raw_size_gb event_count buckets  minTime maxTime retention
            | rename raw_size_gb AS "Index Size (GB)" event_count AS "Total Event Count" buckets AS "Total Bucket Count" minTime AS "Earliest Event"  maxTime AS "Latest Event"   retention AS Retention | stats count</query>
          <earliest>0</earliest>
          <latest></latest>
          <sampleRatio>1</sampleRatio>
        </search>
        <option name="drilldown">none</option>
        <option name="refresh.display">progressbar</option>
      </single>
    </panel>
    <panel>
      <single>
        <title>Distinct Sourcetypes</title>
        <search>
          <query>| tstats dc(sourcetype) where index=*</query>
          <earliest>$time.earliest$</earliest>
          <latest>$time.latest$</latest>
          <sampleRatio>1</sampleRatio>
        </search>
        <option name="drilldown">none</option>
        <option name="refresh.display">progressbar</option>
      </single>
    </panel>
    <panel>
      <single>
        <title>Distinct Sources</title>
        <search>
          <query>| tstats dc(source) where index=*</query>
          <earliest>$time.earliest$</earliest>
          <latest>$time.latest$</latest>
          <sampleRatio>1</sampleRatio>
        </search>
        <option name="drilldown">none</option>
        <option name="refresh.display">progressbar</option>
      </single>
    </panel>
  </row>
  <row>
    <panel>
      <chart>
        <title>Total Event Count Over Time</title>
        <search>
          <query>| tstats prestats=t count where index=* by _time | timechart  count</query>
          <earliest>$time.earliest$</earliest>
          <latest>$time.latest$</latest>
        </search>
        <option name="charting.chart">area</option>
        <option name="charting.drilldown">none</option>
        <option name="refresh.display">progressbar</option>
      </chart>
    </panel>
    <panel>
      <chart>
        <title>Event Count by Index Over Time</title>
        <search>
          <query>| tstats prestats=t count where index=* by index, _time | timechart count by index</query>
          <earliest>$time.earliest$</earliest>
          <latest>$time.latest$</latest>
        </search>
        <option name="charting.chart">area</option>
        <option name="charting.drilldown">none</option>
        <option name="refresh.display">progressbar</option>
      </chart>
    </panel>
  </row>
  <row>
    <panel>
      <table>
        <title>Indexes with Data</title>
        <search>
          <query>| dbinspect index=* cached=t
| where NOT match(index, "^_")
| stats max(rawSize) AS raw_size max(eventCount) AS event_count BY bucketId, index
| stats sum(raw_size) AS raw_size sum(event_count) AS event_count dc(bucketId) AS buckets BY index
| eval raw_size_gb = round(raw_size / 1024 / 1024 / 1024 , 2) | fields index raw_size_gb event_count buckets
| join type=outer index [| rest /services/data/indexes-extended 
| table title maxTime minTime frozenTimePeriodInSecs
| eval minTime = case(minTime &gt;= "0", minTime)
| stats max(maxTime) AS maxTime min(minTime) AS minTime max(frozenTimePeriodInSecs) AS retention BY title
| eval maxTime = replace(maxTime, "T", " "), maxTime = replace(maxTime, "\+0000", ""), minTime = replace(minTime, "T", " "), minTime = replace(minTime, "\+0000", ""), retention = round(retention / 86400, 0)." Days" 
| rename title AS index] | fields index raw_size_gb event_count buckets  minTime maxTime retention
            | rename raw_size_gb AS "Index Size (GB)" event_count AS "Total Event Count" buckets AS "Total Bucket Count" minTime AS "Earliest Event"  maxTime AS "Latest Event"   retention AS Retention</query>
          <earliest>0</earliest>
          <latest></latest>
        </search>
        <option name="drilldown">none</option>
        <option name="refresh.display">progressbar</option>
      </table>
    </panel>
  </row>
</form>

Detecting Data Feed Issues with Splunk - Part I

by Tony Lee

As a Splunk admin, you don’t always control the devices that generate your data. As a result, you may only have control of the data once it reaches Splunk. But what happens when that data stops being sent to Splunk? How long does it take anyone to notice and how much data is lost in the meantime?

We have seen many customers struggle with monitoring and detecting data feed issues so we figured we would share some of the challenges and also a few possible methods for detecting and alerting on data feed issues.

Challenges

Before we discuss the solution, we want to highlight a few challenges to consider when trying to detect data feed issues:
1) This requires searching over a massive amount of data—thus searches in high volume environments may take a while to return.  We have you covered.
2) Complete loss of traffic may not be required—partial loss in traffic may be enough to warrant alerting.  We still have you covered.
3) There may be legitimate reductions in data (weekends) which may produce false alarms—thus the reduction percentage may need to be adjusted.  Yes, we still have you covered.

Constructing a solution

Given these challenges, we wanted to walk you through the solution we developed (Step 4 in the final solution if you want to skip straight to that for the sake of time). This solution can be adapted to monitor indexes, sources, or sourcetypes—depending on what makes the most sense to you. If each of your data sources goes in its own index, then index would make the most sense. If multiple data feeds share indexes, but are referenced by different sources or sourcetypes, then it may make the most sense to monitor by source or sourcetype. In order to change this, just change all instances of “index” (except for the first index=*) to “sourcetype” below.  Our example syntax below show index monitoring, but the screenshots show sourcetype monitoring--this is very flexible.

The first challenge to consider in our searches is the massive amount of data we need to search.  We could use traditional searches such as index=*, but the searches would never finish even in smaller environments.  For this reason we use the tstats command.  In one fairly large environment, it was able to search through 3,663,760,230 events from two days worth of traffic in just 28.526 seconds.

The first solution we arrived at was the following:

Step 1)  View data sources and traffic:

| tstats prestats=t count where earliest=-2d@d latest=-0d@d index=* by index, _time span=1d | timechart useother=false limit=0 span=1d count by index

Figure 1:  Viewing your traffic

Step 2)  Transpose the data:

| tstats prestats=t count where earliest=-2d@d latest=-0d@d index=* by index, _time span=1d | timechart useother=false limit=0 span=1d count by index |  eval _time=strftime(_time,"%Y-%m-%d") | transpose | rename "row 1" AS TwoDaysAgo, "row 2" AS Yesterday

Figure 2:  Transposing the data to get the columns where we need them.

Step 3)  Alert Trigger for dead data source (Yesterday=0):

| tstats prestats=t count where earliest=-2d@d latest=-0d@d index=* by index, _time span=1d | timechart useother=false limit=0 span=1d count by index |  eval _time=strftime(_time,"%Y-%m-%d") | transpose | rename "row 1" AS TwoDaysAgo, "row 2" AS Yesterday | where Yesterday=0


The problem with this solution is that it would not detect partial losses of traffic.  Even if one event was sent, you would not receive an alert.  Thus we changed this to detected a percentage of drop off.

Figure 3:  Detecting a complete loss in traffic.  May not be the best solution.

Final solution:  Alert for percentage of drop off (Example below alerts on reduction of 25% or greater):

| tstats prestats=t count where earliest=-2d@d latest=-0d@d index=* by index, _time span=1d | timechart useother=false limit=0 span=1d count by index |  eval _time=strftime(_time,"%Y-%m-%d") | transpose | rename column AS DataSource, "row 1" AS TwoDaysAgo, "row 2" AS Yesterday | eval PercentageDiff=((Yesterday/TwoDaysAgo)*100) | where PercentageDiff<75

Figure 4:  Final solution to detect a percentage of decline in traffic

Caveats:

The solution above should get most people to where they need to be.  However, depending on your environment, you may need to make some adjustments—such as the percentage of traffic reduction, but that is a simple change of the 75 above.  We have included some additional caveats below that we have encountered:
1) There may be legitimate indexes with low events or possibly naturally occurring 0 events, use “index!=<name>” after the index=* in the |tstats command to ignore these indexes
2) Reminder:  Maybe you send multiple data feeds into a single index, but instead separate it out by sourcetype.  No problem, just change the searches above to use sourcetype instead of index.

Conclusion

The final step is to click the “Save As” button and select “Alert”.  It could be scheduled to run daily with results are greater than 0.  There may be a better way to monitor for data feed loss and we would love to hear it!  There is most likely a way to use _internal logs since Splunk logs information about itself.  😉  If you have that solution, please feel free to share in the comments section.  As you know, with Splunk, there is always more than one way to solve a problem.

Spelunking your Splunk – Part I (Explore Your Data)

By Tony Lee

Introduction

Have you ever inherited a Splunk instance that you did not build?  This means that you probably have no idea what data sources are being sent into Splunk.  You probably don’t know much about where the data is being stored.  And you certainly do not know who the highest volume hosts are within the environment.

As a consultant, this is reality for nearly every engagement we encounter:  We did not build the environment and documentation is sparse or inaccurate if we are lucky enough to even have it.  So, what do we do?  We could run some fairly complex queries to figure this out, but many of those queries are not efficient enough to search over vast amounts of data or long periods of time—even on highly optimized environments.  All is not lost though, we have some tricks (and a handy dashboard) that we would like to share.

Note:  Maybe you did build the environment, but you need a sanity check to make sure you don’t have any misconfigured or run-away hosts.  You will also find value here.

tstats to the rescue!

If you have not discovered or used the tstats command, we recommend that you become familiar with it even if it is at a very high-level.  In a nutshell, tstats can perform statistical queries on indexed fields—very very quickly.  These indexed fields by default are index, source, sourcetype, and host.  It just so happens that these are the fields that we need to understand the environment.  Best of all, even on an underpowered environment or one with lots of data ingested per day, these commands will still outperform the rest of your typical searches even over long periods of time.  Ok, time to answer some questions!

Common questions

These are common questions we ask during consulting engagements and this is how we get answers FAST.  Most of the time 7 days’ worth of data is enough to give us a good understanding of the environment and week out anomalies.

How many events are we ingesting per day?

| tstats count where index=* by _time

Figure 1:  Events per day

What are my most active indexes (events per day)?

| tstats prestats=t count where index=* by index, _time span=1d | timechart span=1d count by index

Figure 2:  Most active indexes

What are my most active sourcetypes (events per day)?

| tstats prestats=t count where index=* by sourcetype, _time span=1d | timechart span=1d count by sourcetype

Figure 3:  Most active sourcetypes

What are my most active sources (events per day)?

| tstats prestats=t count where index=* by source, _time span=1d | timechart span=1d count by source

Figure 4:  Most active sources

What is the noisiest host (events per day)?

| tstats prestats=t count where index=* by host, _time span=1d | timechart span=1d count by host

Figure 5:  Most active hosts

Dashboard Code

To make things even easier for you, try this dashboard out (code at the bottom) that combines the searches we provided above and as a bonus adds a filter to specify the index and time range.

Figure 6:  Data Explorer dashboard

Conclusion

Splunk is a very powerful search platform but it can grow to be a complicated beast--especially over time.  Feel free to use the searches and dashboard provided to regain control and really understand your environment.  This will allow you to trim the waste and regain efficiency.  Happy Splunking.

Dashboard XML code is below:

<form>   <label>Data Explorer</label>   <fieldset submitButton="true" autoRun="true">     <input type="time" token="time">       <label>Time Range Selector</label>       <default>         <earliest>-7d@h</earliest>         <latest>now</latest>       </default>     </input>     <input type="text" token="index">       <label>Index</label>       <default>*</default>       <initialValue>*</initialValue>     </input>   </fieldset>   <row>     <panel>       <chart>         <title>Most Active Indexes</title>         <search>           <query>| tstats prestats=t count where index=$index$ by index, _time span=1d | timechart span=1d count by index</query>           <earliest>$time.earliest$</earliest>           <latest>$time.latest$</latest>         </search>         <option name="charting.chart">column</option>         <option name="charting.drilldown">none</option>       </chart>     </panel>   </row>   <row>     <panel>       <chart>         <title>Most Active Sourcetypes</title>         <search>           <query>| tstats prestats=t count where index=$index$ by sourcetype, _time span=1d | timechart span=1d count by sourcetype</query>           <earliest>$time.earliest$</earliest>           <latest>$time.latest$</latest>         </search>         <option name="charting.chart">column</option>         <option name="charting.drilldown">none</option>       </chart>     </panel>   </row>   <row>     <panel>       <chart>         <title>Most Active Sources</title>         <search>           <query>| tstats prestats=t count where index=$index$ by source, _time span=1d | timechart span=1d count by source</query>           <earliest>$time.earliest$</earliest>           <latest>$time.latest$</latest>         </search>         <option name="charting.chart">column</option>         <option name="charting.drilldown">none</option>       </chart>     </panel>   </row>   <row>     <panel>       <chart>         <title>Most Active Hosts</title>         <search>           <query>| tstats prestats=t count where index=$index$ by host, _time span=1d | timechart span=1d count by host</query>           <earliest>$time.earliest$</earliest>           <latest>$time.latest$</latest>           <sampleRatio>1</sampleRatio>         </search>         <option name="charting.chart">column</option>         <option name="charting.drilldown">none</option>       </chart>     </panel>   </row> </form>