Your IT applications, systems, servers, and networks generate large volumes of log data. But do you know how much of that data is analyzed? Most teams have a log management tool that deals only with data collection, storage, and retention but requires manual intervention to analyze and make sense of what’s causing problems in running your IT infrastructure correctly.
Log analysis software allows you to analyze the log data generated by IT resources, such as hardware and software systems, to detect and troubleshoot issues. It analyzes system-generated log files to understand the root cause of performance issues. This helps reduce troubleshooting time and identify anomalies that would otherwise go undetected.
In this buyers guide, we explain what log analysis software is, its common features and benefits, and the considerations and market trends you should keep in mind when buying software.
Here's what we'll cover:
What is log analysis software?
Log analysis software is a software tool that analyzes system-generated log files to help detect and troubleshoot IT issues. It not only identifies system or network errors, vulnerabilities, and threats but also pinpoints the root cause of these issues. It documents the log files for record-keeping, helps identify trends or patterns in log activity, and offers log monitoring capabilities to predict and prevent issues in the future.
A log analyzer allows businesses to understand performance failures, remediate them, and learn how to prevent them in the future, with the overall goal of improving system and application performance and reliability. The tool is mostly used by DevOps teams, system and web server administrators, and IT security analysts.
Audit trail of system logs in Logz.io (Source)
Common features of log analysis software
Software features vary by product or vendor, but most log analyzer tools offer the following overlapping features:
||Access a centralized dashboard to organize, view, and monitor log data and related performance metrics in real time.
||Use interactive charts, graphs, tables, maps, and other elements to visualize log data.
||Analyze log data to detect and troubleshoot issues, extract insights, identify trends or patterns in log activity, and much more.
||Access detailed reports to identify the root cause of log events such as software install or update failure, unauthorized system access, application crash, and hacking attempts.
||Automatically identify unusual activity or anomalies in log files. An anomaly is any deviation from the consistent structure of a log entry or a group of entries.
||Search and filter through the log database to find specific entries and quickly fix issues such as system errors or vulnerabilities.
||Receive alerts and notifications about system errors, potential cyberattacks, or any unusual log event.
||Collect and store log files from servers, networks, firewalls, systems, applications, users, and other IT resources.
|Pattern detection and recognition
||Analyze log messages to identify patterns and trends in log activity and detect anomalies such as unauthorized system access.
||Record the sequence of events and changes in your IT systems and applications. Log messages contain information that can be traced back to errors or anomalies.
What type of buyer are you?
Most log analysis software buyers belong to one of the following categories:
- Small and midsize companies (up to 500 employees): Compared to the big players, small and midsize businesses (SMBs) have smaller IT teams and lack dedicated security professionals. A feature-rich log analyzer is desirable but could be an overkill for SMBs that have few staff members and tight IT security budgets. Instead, these buyers should opt for a tool that provides just enough functionality to collect and monitor event logs from multiple sources, including applications, systems, and networking devices. A free or open source cloud-based platform with log collection, search, filtering, and reporting functionality would be suitable for them.
- Large enterprises (over 500 employees): Large enterprises need extensive IT security management because they have more users and devices in their IT infrastructure. They’re often the prime targets of data breaches, so they also have to comply with various industry standards and regulations. These buyers need more than just basic log analysis capabilities. They should opt for an all-in-one platform that not only monitors and analyzes proprietary log data but also offers threat detection, real-time log monitoring, user activity monitoring, pattern detection and recognition, and detailed log analytics, among other advanced features.
Benefits of log analysis software
The key benefits of implementing a log analysis tool include:
- Enhanced regulatory compliance: Log files are the best way to demonstrate your business is complying with regulations such as the Payment Card Industry Data Security Standard (PCI DSS) and General Data Protection Regulation (GDPR). You can use the stored log data to track if you’re meeting industry benchmarks and compliance requirements over time. The collected logs can also come in handy as evidence during audits.
- Improved performance: Your employees rely on IT resources such as systems and software applications to complete their daily tasks. Log analysis tools continuously monitor the log files generated by these resources to spot errors or vulnerabilities and fix them quickly. This proactive approach ensures your business doesn’t face any service disruption or downtime.
- Greater security: With a log analysis tool, you can track down suspicious requests and vulnerabilities, block malicious traffic, and limit access to protect your IT infrastructure from threats. The software sends real-time alerts about failed authentication attempts or other security events to help you act quickly. The trends and patterns detected from log files can also help predict and prevent future attacks.
- Better troubleshooting: A log analysis tool can troubleshoot your servers, networks, and systems for various issues—from application crashes and configuration errors to hardware failure. Troubleshooting with log analysis is often used for production monitoring, as it lets your DevOps teams detect and solve critical system errors faster.
Here are a few considerations to help plan your software purchase:
- Functionality: Different businesses use log analysis software for different purposes. Most use it because they don’t want to spend a lot of time wading through volumes of log files to detect threats. Others rely on the tool to spot unknown or hidden errors, understand the reasons for recurring crashes, and spot trends or patterns. These tools are also used to monitor access to enterprise data and prevent frauds. Therefore, assess your requirements and then select a tool that offers the log management functionality you want.
- Scalability and speed: As your business grows, the volume of data it generates will also increase. Therefore, select a log analysis tool that has the scalability to support your future data growth. Another thing to keep in mind is speed. When an issue occurs, you can’t afford to wait for a minute or two until a query returns results. So, select a tool that gives instant results, regardless of the volume of log data you’re collecting or querying.
Market trends to understand
Here’s a recent trend in the log analysis software market that you should know:
- Machine learning (ML) algorithms are making IT systems smarter. The use of ML technology in log management software can make IT systems smarter. Systems become proactive in detecting and reacting to anomalies and unusual patterns, much before the end users experience them. By applying ML algorithms, tech teams can categorize application logs rapidly, identify issues automatically, and get alerts about threats and vulnerabilities in real time, among other benefits. An ML-powered log management solution can also eliminate routine, repeatable tasks so users can focus on tasks that need human assistance, such as problem-solving.
Note: The application selected in this guide is an example to show a feature in context and is not intended as an endorsement or a recommendation. It has been taken from sources believed to be reliable at the time of publication.