Before the need for log correlation, there was a time not so long ago when reading software application logs was simple. Your application would output log files in sequential order, and you’d read through them. In the event of a bug, software outage, or security incident, you could easily parse what happened and when. It was a tedious process, but it was simple.
That’s not the case any more. In the interest of scaling our software to service millions of users, that software is significantly more complicated. In today’s software landscape, logs originate from dozens of sources. Even a relatively simple web application has client logs, logs from a load balancer, logs from the web server, database logs, and logs from worker services that handle longer-running tasks. If your application has even slightly more advanced capabilities, your logging requirements expand considerably. Every new feature requires more logging in order to monitor correctly.
So how do we handle all these logging demands? That’s where log correlation comes in. What is log correlation, you ask? Keep reading. In this post, we’ll define log correlation and talk about why it’s so important.
When Something Goes Wrong, Challenges Arise
One of the negative side effects of this level of complexity is that troubleshooting issues is complicated. Few bugs are simple, but complicated architectures mean that even pinpointing a bug is time-consuming.
As user activities propagate between different parts of the system, they generate log events. As an engineer, you can track down those log events, but it’s going to take some time. On busy systems, there’s an extra layer of complication. Similar application actions will generate similar log entries. Do you know if that database log entry came from the bugged request, or a similar one that completed successfully?
Sometimes, the challenge can come from just finding the logs. Where does your web server log to? What about your database? Managing logs in modern applications can feel like trying to solve a maze in the dark when you don’t know if there’s an exit.
This is the complexity we’re talking about. Eventually, you’ll figure out where each log entry came from, and you’ll be able to sort out the root cause of your bug. That’s good! But it’s likely that it’s going to take you hours, and when there’s a production bug, your bosses aren’t likely to be excited by hours before you even know what the bug is.
This delay is even more significant when dealing with a suspected security event. When you think someone has compromised your system, a few hours can be the difference between repelling them and a major security breach.
Different Services Log Differently
Another significant complication stems from the fact that different services have different log formats. In the heat of the moment, you want someone who’s an expert on the service experiencing the bug. But reading Apache logs is a lot different from reading log output from Postgres. Someone who’s an expert in Apache might have to guess what’s happening with a log from another application. This amplifies the difficulty of tracing an event through your system’s logs. Each level of communication overhead introduces another place where your process can fail. Each failure pushes back the time necessary to resolve your problem.
Log Correlation Tackles Those Challenges
Thankfully, you don’t have to live with all of this complexity. Log correlation software, like Log Management from XPLG brings all of your logs into a single location. By moving all logs to a centralized location, a significant element of complexity is removed. When something goes wrong, you know right where to look.
But log correlation software isn’t simply the act of bringing all logs into a singular location. While that’s helpful, log correlation is much more powerful than just that.
Tying the Threads Together
Instead, log correlation fills a much more valuable purpose. It’s able to track actions throughout your system and trace the logs they generate. That’s the “correlate” part of log correlation. Under the hood, log correlation is a terrific bit of engineering. Application programmers build pattern-matching software which is able to direct the software to determine which parts of disparate logs represent the same action. Quality log correlation software comes with these rules built in by default. It’ll also let your team define custom rules. All that hard-earned knowledge about how to trace an action through your system is fed directly into the system. Instead of hours spent tracking actions through the system, the same logic is executed in milliseconds.
Working Automatically With Different Systems
One significant benefit of software like XPLG is that it features a robust application store where you can add log plugins based on the services you use. Because these parsing tools are written by experts in their technology, picking up one of these plugins is like adding that expert right to your debugging team. Now, you eliminate that communication overhead. Your team doesn’t need to constantly talk back and forth to figure out where an event originated. The logs are effectively sequenced in order from the start of an event to the end. You’re able to quickly and smoothly determine how a bug traced through your system, and root out the cause in minutes.
What’s more, slight configuration differences in systems can cause big problems in log collection. An effective log correlation service will help smooth over those bumps so you’re getting the right data, every time.
The Next Level: Log Analysis
When you run an application that serves millions of users, waiting for a bug or security event to announce itself means you’re behind. Especially with the case of security events. As we noted before, every minute lost when an intruder is trying to compromise your system is the potential for real trouble.
Instead, log correlation and management systems can alert you when unexpected behavior is happening, before a user even knows something is wrong. You’re able to see the overall health of your system in real time. For instance, imagine that a network link between your web server and database is severed. In a traditional logging environment, you don’t know about this problem for some time. You first need to receive reports that requests are failing. Then you need to begin tracing each of those events through disparate system logs. It won’t be until you’ve done two or three that your team will suspect there’s a network outage issue.
Instead, with an effective log correlation system, you’ll be able to recognize that a high percentage of requests are failing to reach the database in just minutes. The time saved turns an outage of hours into one that takes minutes to resolve. Log correlation systems can even provide configuration options to automatically notify team members when an unexpected number of errors occur. It could be that the first time you learn your network is down isn’t from a customer, but from an automated system. You can fix the problem before someone even knows something is wrong.
Log Correlation Lets You Focus on What’s Important
In today’s software world, complexity is everywhere. It grows constantly, and it’s nearly impossible to avoid. Every new feature request means adding a new layer of complexity to your software. Most of the time, this doesn’t impact your team. When things are running well, complexity isn’t a source of stress. But when things break, that complexity can feel back-breaking. Log correlation is a tool to reduce the weight of that complexity. It provides real ways to simplify how you visualize data flowing through your systems. When implemented correctly, it even helps your team take action proactively. Best of all, XPLG makes it easy to start, for free. What are you waiting for?