From production monitoring to security concerns, businesses need to analyze and review their logs on a daily basis to make sure their system is up to par. Here are the reasons why analyzing your log data is so important.
If you landed here, chances are you probably know what logs are, but we’ll start off with a short explanation of what it is. Typically, application logs capture timestamped data related to actions serviced by applications, decisions taken by applications, actions initiated by applications, and runtime characteristics of applications.
The analysis of log data, also known as data logging, is a process of making sense of computer-generated records (logs). This process helps businesses comply with security policies, audits or regulations, comprehend system troubleshoots as well as understand online user behavior. Businesses must review their logs daily to search for errors, anomalies, or suspicious activity that deviates from the norm. In fact, log analysis needs to interpret messages within the context of an application or system and map varying terminologies from log sources. It then turns them into a uniform terminology that sees to it that reports and statistics are clear.
So why is data logging analysis necessary? Well, here are some examples that will prove to you that it is not just important, but it is actually vital for any business that is looking to succeed, no matter the industry.
Apps and systems are constantly growing in both size and complexity, and the use of logging platforms is now becoming a must for any growing business. By analyzing your key trends across your different systems, debugging as well as troubleshooting you’ll be able to create opportunities for improved operations on a smaller budget as well as new revenues. This is what Coralogix is all about: shortening the time a business needs to detect and solve production problems. The data, after all, is all there. It all depends on the ways in which organizations decide to utilize them to their advantage.
When it comes to your system performance, often your software is not at fault, but rather your requests of the server are those that cause an overload your system has trouble dealing with. Tracking your resource usage will enable you to understand when the system is close to overload, so you’ll be able to prevent it from happening by adding additional capacity when needed.
A common use of log analysis is searching for HTTP errors. Through your analysis, you’ll be able to understand your HTTP errors, and on what pages they occurred so you can fix the problem and essentially prevent yourself from losing potential clients.
By analyzing your log data, you’ll be able to detect when users are not getting the information they need or if this data is taking too long to load. By tracking slow queries, you’ll be able to see how your DB queries are performing and guarantee your user’s experience is up to par.
If you’re under a DNS attack in which someone hammers your site to break your servers, your log data analysis will reveal a lot of useful information regarding your attackers. Your analysis will even be able to assist you in blocking them from accessing your site by their IP address. Search engine spiders are able to discover many errors that may not be noticed by your users but need to be promptly addressed.
Log analysis may be the most under-appreciated, unsexy aspect of infosecurity. However, it is also one of the most important. From a security point of view, the purpose of a log is to act as a red flag when something bad is happening. As SANS Institute puts it,
Analyzing your logs on a regular basis will allow your business a quicker response time to security threats as well as better security program effectiveness. According to Security Metrics, by performing log analysis and daily monitoring, you’ll be able to “demonstrate your willingness to comply with PCI DSS and HIPAA requirements, (and) it will also help you defend against insider and outsider threats.”
Log data analysis will help you understand not only how many visitors have entered your site.platform, but on what pages they spent the most time, what they were doing on your site.platform, why there are changes in the number of visitors, etc. Trends and patterns like this will help you identify opportunities. As stated by Dave Talks, “examples include when to release a new version or product, when to send out a mailing or announcement, when to take down your website to test your new shopping cart, when to offer discounts, and much more.”
In short, analyzing your log data means you’ll be able to catch errors before your users have discovered them. Since your business is dealing with a vast amount of log data generated by your systems, using an ML-powered log analytics software is the best solution you could make if you don’t want to spend your time reviewing logs manually.