Learn How to use Sumo Logic Analyze your logs & Analyze Event and Create powerful BI reports What Is a Log Analyzer? When we say log analyzer, we’re referring to software designed for use in log management and log analysis. Log analysis tools that are leveraged to collect, parse, and analyze the data written to log files. Log analyzers provide functionality that helps developers and operations personnel monitor their applications as well as visualize log data in formats that help contextualize the data. This, in turn, enables the development team to gain insight into issues within their applications and identify opportunities for improvement. As you will see, log analysis offers many benefits. But these benefits cannot be realized if the processes for log management and log file analysis are not optimized for the task. Development teams can achieve this level of optimization through the use of log analyzers. How Do You Analyze Logs? One of the traditional ways to analyze logs was to export the files and open them in Excel. This time-consuming process has been abandoned as tools like Sumo Logic have entered the market. With Sumo Logic, you can integrate with several different environments using IIS web servers, NGINX, and others. With free trials available to test out their log analysis tooling at no risk, the time has never been better to see how log analyzers can help improve your strategies for log analysis and the processes described above Ensuring Effective Log Analysis with Log Analyzers Effective log analysis requires the use of modern log analysis concepts, tooling, and practices. The following tactics can increase the effectiveness of an organization’s log analysis strategy, simplify the process for incident response, and improve application quality. Real-Time Log Analysis Real-time log analysis refers to the process of collecting and aggregating log event information in a manner that is readable by humans, thereby providing insight into an application in real-time. With the assistance of a log aggregator and analysis software, a DevOps team will have several distinct advantages when their logs are analyzed in this way. When log analysis is performed in real-time, development teams are alerted to potential problems within their applications at the earliest possible moment. This enables them to be as proactive as possible, thereby limiting the impact that an incident has on the end users. The types of incidents that previously went unreported and undetected by the DevOps team will now have the team’s attention in a matter of minutes. This provides the necessary framework for increasing application availability and reliability. In addition to notifying the development team of application issues nearly instantly, real-time log file analysis provides developers with critical context that enables them to resolve incidents quickly and completely. This limits the amount of downtime experienced by the customer while also adding to the likelihood that the issue will be thoroughly resolved. Centralized Log Collection & Analysis In any application built with visibility and observability in mind, log events are being generated all the time. As end users utilize the application, they are creating log events that need to be captured and evaluated in order for the DevOps team to understand how their application is being used and the state that it’s in. To illustrate this point, imagine that you have a web app. As users navigate the app, log events are generated with each page request. Request data can provide meaningful insights, but the painstaking and tedious process of combing through massive log files on individual web servers would be too much for human beings to handle productively. Instead, these log events should be consumed by a log analyzer that centralizes all log data for all instances of the application. This enables human beings to digest the log data more efficiently and more completely, which in turn allows team members to readily evaluate the overall health of the application at any given time.
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