Importance of Log Analysis
Log Analysis is the procedure of understanding computer-generated records also known as – ‘Logs’. Logs are created by a variety of programmable technologies, including networking devices, operating systems, applications, etc.
As modern software is developing large scale, the volume of logs has augmented rapidly. In recent times, software logs have become vital in the reliability assurance mechanism of many software systems because they are often the only data available that record software runtime information. Examples of logs comprise: Sign-in and sign-out requests on a website. Financial Transactions made on a currency exchange. Calls made to an informational API.
Benefits of Log Analysis tools
Log analysis and management tools are effective in troubleshooting.
Meaningful data can be extracted from logs to pinpoint the root cause of any error.
Discover trends and patterns to drive business decisions, investigations, and security.
Log Analysis Processes
Normalization: Ensures that log entries from different sources convey information in the same format.
Recognizing Patterns: Compares incoming entries with stored patterns, thereby differentiating and triggering alerts.
Filter and Track: Categorizes log entries according to their attributes.
Correlation Analysis: Collects information from various sources, finds the entries from each of those sources that are relevant to a given known event.
Who can use Log Analysis Tools?
Below are some use roles where Log Analysis tools can be used to make better data-driven decisions:
DevOps Engineers
Security professionals
System Admins
Network administrators
Web Developers
Site Reliability Engineers
If you’re not already analyzing your logs, its high time you start doing that. Not only is it essential for security reasons and other regulatory compliances, but keeps your systems updated with the latest applications and users.
After the log data is processed, the extracted information serves as input to log analysis. Such analysis, which makes use of different algorithms, helps developers in detecting unexpected behavior, performance jams, or even security glitches. Log Analysis deals with information acquisition from log data for a specific purpose. Mining insights from log data is challenging due to the complexity of the systems generating that data.
There are typically 8 subcategories in this area: (1) anomaly detection, (2) security and privacy, (3) root cause analysis, (4) failure prediction, (5) quality assurance, (6) model inference and invariant mining, (7) reliability and dependability, and (8) platforms.
Log analysis tools help organization take a proactive approach to monitoring. You don’t have time to waste when a problem occurs. Instead, you need software that can not only enable faster troubleshooting but one that can help anticipate future problems so that you can avoid them.
Enter Avalanchio – whose Log Storage & Analysis tool is built on top big data products, and enables the organization to collect data from unlimited endpoints in real-time. The product has a built-in rule set to detect suspicious activities. It allows SOC analysts to write their own rules using simple to complex conditions, time filters, lookups, merging multiple datasets.
Book a demo today to understand how our Log Analysis tool benefits your organization.