10 Splunk Logging Best Practices

Logging is a critical part of any application or system. It provides visibility into the inner workings of the application and can be used for debugging, troubleshooting, and auditing.

There are many different logging tools available, but Splunk is one of the most popular. Splunk can collect and index log data from a variety of sources, making it easy to search and analyze.

In this article, we will discuss 10 Splunk logging best practices that will help you get the most out of your Splunk deployment.

1. Use the correct log level

The log level is the priority of the message. The lower the number, the higher the priority. For example, “emergency” (level 0) is the highest priority, and “debug” (level 7) is the lowest priority.

If you use the wrong log level, it can have a few different effects.

1.

If the log level is too high, then important messages might not be logged at all.

2.

If the log level is too low, then there might be so many messages that it’s hard to find the important ones.

3.

If the log level is just right, then you’ll have the perfect balance of information.

To get the perfect balance, you need to understand what each log level means, and you need to use them correctly. Here’s a quick overview of each log level:

| Log Level | Description |
| — | — |
| 0 | Emergency: system is unusable |
| 1 | Alert: action must be taken immediately |
| 2 | Critical: critical conditions |
| 3 | Error: error conditions |
| 4 | Warning: warning conditions |
| 5 | Notice: normal but significant condition |
| 6 | Informational: informational messages |
| 7 | Debug: debug-level messages |

As you can see, each log level has a specific purpose. Use them wisely, and you’ll be able to find the perfect balance for your Splunk logging.

2. Log to a file, not stdout/stderr

When you log to stdout/stderr, your logs are intermingled with other data that’s going to stdout/stderr. This makes it difficult to parse and query your logs later on. It also means that if something goes wrong with Splunk, your logs could be lost.

Logging to a file instead gives you more control over your logs. You can rotate your logs, so they don’t get too big. And if something does go wrong with Splunk, your logs will still be there.

3. Include context in your logs

When you’re troubleshooting an issue, the first thing you need to do is reproduce it. But if you don’t have enough information in your logs, it can be very difficult (if not impossible) to do that.

For example, let’s say you have a web application and you’re seeing some strange behavior. You check the logs and see that there’s an error, but it doesn’t give you any information about what caused the error. Was it a user inputting invalid data? Or was it something else?

If you had included context in your logs (e.g. the user ID, the URL, etc.), then it would be much easier to reproduce the issue and figure out what went wrong.

So, always make sure to include enough context in your logs so that you can easily troubleshoot issues when they arise.

4. Don’t include sensitive information

When you’re troubleshooting an issue, you want to be able to share your logs with others who can help. But if those logs contain sensitive information, you may not be able to do that. So it’s important to make sure that any sensitive information is removed before you add the logs to Splunk.

There are a few ways to do this. One is to use Splunk’s built-in filters to remove sensitive information. You can also create your own custom filters. Or you can use third-party tools to scrub the sensitive information from your logs before sending them to Splunk.

Whichever method you choose, the important thing is to make sure that sensitive information is removed before it gets into Splunk. That way, you can feel confident sharing your logs with others without worry about exposing sensitive data.

5. Be consistent with your logging format

When your logs are in the same format, it’s much easier for Splunk to parse them and extract the relevant information. This is because Splunk uses regex to parse log files, and if the format of the logs is not consistent, the regex will not be able to accurately parse the data.

Not only will this make it more difficult for Splunk to parse the data, but it will also make it more difficult for you to query the data and get the results you’re looking for. So if you want to get the most out of Splunk, be sure to format your logs consistently.

6. Avoid using print statements for debugging

Print statements are useful for debugging because they allow you to see the value of a variable at a specific point in the code. However, once you’re done debugging and your code is ready for production, those print statements need to be removed.

The problem is that if you forget to remove them, they’ll still be there when your code goes into production. And if something goes wrong in production, those print statements could give away sensitive information or provide clues that could be used by an attacker.

It’s much better to use a logging library that allows you to specify the level of detail you want in your logs. That way, you can leave debug-level logging enabled during development and testing, but disable it before your code goes into production.

7. Use structured logging where possible

While Splunk can parse and extract data from unstructured logs, it’s much easier (and therefore more efficient) to work with structured data. This is because, with structured data, each piece of information is stored in a separate field, which makes it easier to query and analyze.

For example, let’s say you have the following log message:

“ERROR: Failed to connect to database.”

This log message is unstructured because all of the information is stored in a single field. In contrast, a structured version of this log message might look like this:

“level”: “error”,
“message”: “Failed to connect to database.”,
“timestamp”: “2020-01-01T12:00:00Z”

As you can see, each piece of information is stored in its own field, which makes it much easier to query and analyze.

So, if you’re using Splunk for logging, one of the best practices is to use structured logging where possible. This will make it easier to query and analyze your data, and ultimately help you troubleshoot issues more quickly and efficiently.

8. Write tests for your logging code

When you’re dealing with logging, it’s important to have confidence that your logs are being generated correctly. The only way to be absolutely sure is to write tests.

Tests will also help you catch any edge cases that you might not have thought of. And if you ever need to make changes to your logging code, tests will give you a safety net to fall back on.

Finally, tests serve as documentation for your code. They’ll help you remember how your code works, and they’ll be a valuable resource for future developers who work on the project.

9. Rotate and compress your logs

When you have a lot of log data, it can quickly fill up your storage space. If you don’t have enough storage space, Splunk will stop collecting logs, which can result in data loss. To avoid this, it’s important to rotate and compress your logs so that they take up less space.

Splunk also recommends that you set up alerts for when your logs are getting close to filling up your storage space. That way, you can take action before it’s too late.

Finally, Splunk also recommends that you keep your logs for at least 90 days. This gives you plenty of time to troubleshoot any issues that might arise.

10. Monitor your logs

Your logs contain a wealth of information about your system, and if you’re not monitoring them, you could be missing out on important insights. By monitoring your logs, you can detect issues early and prevent them from becoming bigger problems.

There are a few different ways to monitor your logs. You can use Splunk’s native monitoring features, or you can use third-party tools.

If you’re using Splunk’s native monitoring features, you can set up alerts to notify you when certain conditions are met. For example, you can set up an alert to notify you when an error occurs.

If you’re using third-party tools, you can use them to monitor your logs and send you notifications when certain conditions are met. Some of the most popular logging monitoring tools include Loggly, Papertrail, and Sumo Logic.

No matter which method you choose, monitoring your logs is an important Splunk logging best practice.