Many—maybe most?—organizations treat their logging approach as a mere troubleshooting mechanism, failing to realize the tremendous opportunities that lie dormant in their log files. At the same time, their competitors may have realized the importance of techniques such as log analysis long ago and are already reaping the benefits. Guess who has more chances of remaining competitive in the dog-eat-dog tech world we live in?

However, there’s no need to despair if your organization belongs to the former group: you can still make up lost ground. And this post is here to help you. By offering an introductory guide to log analysis, we’ll help you take your first steps into your log analysis journey so you’re able, eventually, to extract the tremendous value stored inside your log entries. Let’s get started.

Magnifing glass on Scalyr logo signifying log analysis

What’s Logging?

In the simplest terms, logging refers to the act of recording information about relevant events to a permanent medium so people can read the information afterward. This seems a straightforward enough definition, right?

However, it raises more questions. Who logs? What does “relevant events” mean? Where are logs stored? And most importantly: what’s the point of doing all that?

Logs in All Shapes and Sizes

Your operating system generates logs. And so do web servers, database systems, and application software. And even though some people might equate logs to “bad news,” the events that end up in log files aren’t necessarily errors or problems. Most platforms have some way of classifying log events according to their severity, and there are certainly ways to categorize an event as a regular, good—or at least neutral—occurrence.

And though we call them “log files,” there’s nothing preventing you from logging to other destinations, such as the database or the console, a particular email address, or the cloud, among many others.

What’s the Purpose of a Log File?

Why bother logging? The most common answer is that logging helps you troubleshoot issues. When things go wrong in production, logs are often the difference between hours of fruitless, painless debugging, and a quick diagnosis and fix.

However, logging can be so much more than that. Instead of using logging as a way to put out fires, you can use it to prevent the fires from starting in the first place. That’s the kind of power that log analysis might give you.

Taking Your Logging Approach to the Next Level: Enter Log Analysis

Up until now, we’ve covered the fundamentals of logging. Now is where the fun begins: you’ll learn about log analysis, its benefits, its components, and more.

Defining Log Analysis

Log analysis is the process of analyzing data from log entries and turning that data into useful knowledge. Such knowledge can then be put to use in the decision-making process. Though the definition of log analysis is quite simple, it begets more questions:

  • Who does the analysis?
  • Is a special tool or program required to analyze logs?
  • Do I have to do something to my logs before they can be analyzed?

We’ll soon see the answer to all of the questions above. For now, let’s cover another essential topic: what’s the point of doing log analysis?

log analysis

What Is the Benefit of Log Analysis?

Is log analysis really worth it? The answer is a resounding “yes.” The advantages of log analysis come in three successively sophisticated levels.

Level 1: Troubleshooting

For starters, log analysis can boost the troubleshooter aspect of logging. Log analysis tools often come with fast search and great visualization capabilities, which might help reduce the time to diagnose and fix issues.

Level 2: Predicting Issues

However, log analysis can help you go a step further and prevent issues before they happen. By analyzing past events, you can learn to detect trends that indicate that problems are coming. Log analysis might help you identify security breach attempts, traffic spikes on your web servers, and more.

Level 3: Business Intelligence

You don’t have to stop there, though, since a sophisticated log analysis approach can get you even further by providing business insights. When you have tons of log data from disparate sources centralized in a single location, exciting possibilities open up for you. You could, for instance, correlate database and application logs to find out that poor database performance correlates with lower conversion rates. Such findings can, in turn, be used to justify more investment in database performance.

What’s Involved in Log Analysis?

After talking at length about the “why” of log analysis, let’s turn our attention to the “how.” How do you actually perform log analysis? What are its components? That’s what we’ll discuss now.

Who Performs Log Analysis?

Let’s start by answering a question we posed earlier in the post. Who performs log analysis? Is it a person just peeking at the logs?

Yes, people perform log analysis, but with the help of specialized tooling, such as log management software. Such applications might take different forms, such as programs installed ad-hoc or cloud-based solutions. Human intelligence and ingenuity are essential parts of log analysis. However, the volume of log data produced by most organizations nowadays is simply much larger than any person would be able to handle.

log analysis

So, think of log analysis as a team effort between humans and tools. Sophisticated tools do the heavy lifting: they centralize the log data, do the necessary preparations for it, and then analyze it. All of that would be pretty useless without talented and smart people who can not only maintain and tweak the log analysis setup but also act on the insights it provides.

The Components of Log Analysis

What are the components, or steps, of a log analysis approach? You’ve just seen that you need specialized tools to analyze logs, but what do such tools actually do?

Bringing It All Together

A typical organization will have logs that originated from many different sources. You have application logs, database logs, and OS logs, to name a few. To analyze all of them, you must first collect them in a single place.

Parsing and Cleaning

A side effect of aggregating logs from disparate sources is the myriad of conflicting standards and formatting choices used by each source. This includes data formats, time zones, and things like different names for log levels. A log analysis approach needs to take this variety of formats into account and develop ways to parse the data from the logs, extracting meaning from them, regardless of the conflicts in formats.

Cleaning the data is also essential. Your log data will invariably contain information that isn’t useful. Missing and incorrect data is also an inevitable reality. A log analysis approach needs strategies to deal with such cases, either by applying transformations to the data or employing default data.

The Cherry on Top: Visualization, Analytics, and More Goodies

Once you’ve used your log analysis tool to help you aggregate, clean, and organize your log data, you’ll finally be ready to do some fun stuff. You’ll be able to use visualization capabilities from your tool to literally see your log data in compelling and useful ways. You’ll also be able to search through your data using sophisticated and incredibly fast searching capabilities.

log analysis

Last, but not least, you’ll gain analytics capabilities you can use to obtain the insights you’ve been reading about in this post. As a result of such analysis, you’ll be able to not only solve issues quicker but also prevent them from happening entirely. You’ll also be able to make better business decisions and, better yet, justify those decisions as being backed by real data and insights.

Don’t Waste the Potential of Log Analysis

Pretty much every single layer of your technological infrastructure generates logs: from the operating system to the applications, going through databases and many other tools and processes. The accumulated data from all your logs offer a unique opportunity. By analyzing the data, you can have a glimpse at all parts of your organization at once. It’s like having Superman’s x-ray vision. Being able to leverage log analysis and choosing not to is like passing the chance to have superpowers.

Who in their right mind would do that?

I hope this post has convinced you of the importance of log analysis. If it has, a natural next step for you would be to consider your options when it comes to which tool to use. We invite you to take a look at Scalyr, a comprehensive log management solution with super-fast search, amazing visualization capabilities, and much more.

Thanks for reading, and until next time.

This post was written by Carlos Schults. Carlos is a .NET software developer with experience in both desktop and web development, and he’s now trying his hand at mobile. He has a passion for writing clean and concise code, and he’s interested in practices that help you improve app health, such as code review, automated testing, and continuous build.

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