What is Log Parser Lizard?
Log Parser Lizard GUI can parse logs and query data. Log Parser can read various logs from different applications or systems so that you can run SQL queries against them. Log Parser Lizard provides a Graphical User Interface (GUI), to Microsoft Log Parser 2.2. This advanced file parsing engine by Microsoft runs on all Windows versions. Log Parser Lizard supports developers, auditors, auditors, and information security teams by providing powerful SQL querying of structured log data, such as web server logs, Windows event logs, and application log files (log4j.log4net. nlog. serilog), CSV. TSV. JSON. XML. LPL can query remote databases such as Microsoft SQL Server and SQLite, MySQL, OLE DB, and many others. Log Parser Lizard can be used to log analysis, threat detection, and data collection. It also allows for easy data export, visualization (BI), business intelligence (BI), reporting, and extract transform load tasks.
Log Parser Lizard, the best GUI for MS Log parser, is a powerful engine that can parse and analyze different data types, including text-based log files for IIS and Exchange, SharePoint, SharePoint, Windows Event Logs, and File system.
Access system event logs, text data, or Active Directory information. You can also execute queries for the IIS web server, various databases and access text-based data. Log Parser Lizard can be used to transform, load, and collect log files to support security teams. It also supports SQL querying text-based data, Web Server logs, Windows System Events, and application log files. Log Parser Lizard provides a fantastic Graphical User Interface (GUI), to Log Parser 2.2, a powerful file parsing engine by Microsoft that runs on all Windows OS versions. It does not require a web server or cloud. This versatile desktop tool allows you to automate SQL queries on any system log or text-based data, including Web Server Logs (IIS), Apache, W3C SharePoint, MS Exchange, MS Exchange, FTP, etc...), Windows System Events, and application log files (generated using log4net, Nlog. SeriLog etc.). It is also great for Data Visualization, Business Intelligence, and Extract Transform Load tasks (ETL). SQL queries can be run against plain text files or other sources by running the following commands: SELECT DISTINCT src–IP FROM firewall.log WHERE action=’DROP’ SELECT TOP 100 * FROM webserver.log WHERE SC-status > 200 SELECT to_lowercase (extract_extension(cs–Uri-stem),) AS PageType, SUM() FROM ex131119.log, ex131119.log
Log Parser LizardAmazing Features
To read logs, use SQL.
It is simple to query large quantities of log data to find specific information using familiar SQL syntax. Even complex SQL queries can be written (with functions, grouping by, joins and unions),
Look & Feel
To ensure the best user experience, we put a lot into creating an Office-inspired Multiple Document Interface with ribbons & tabs. If you spend a lot of time looking at log files, you want an application that looks good.
Query editor
The query editor features syntax highlighting, code auto-completion, and code snippets. It also has query constants and in-line VB.NET codes.
Query Manager
Log Parser query management is a great way to organize them.
Easy Navigation and Data Visualization
You can view the results in a default grid view (data grid) similar to Excel but has more advanced features. You can sort, group, search, filter, filter, conditional formatting, and formula fields. You can also transform data in Excel, HTML, or MHT reports and combine it into a chart to make it easier to read. To automate the process, you can use the command line.
Data Filtering
From Instant Find and Query Builder to Auto-Filter row. Excel-inspired UI that allows you to create advanced filter expressions for in-memory data.
Large log files can be opened.
Log parser can process any file size. Log parser can process large files. It takes only seconds to count all rows within gigabytes of log files. This depends on the hardware.
Understanding Custom Log Formats
Regular Expressions and Grok are currently the best ways to convert unstructured log data into structured, queryable information. Logs can be compressed and read without having to unpack them. LPL input types can also read encrypted.gz logs. Out-of-the-box support for Log4net/log4j XML also exists.
Pivot table and treemap
A pivot table and treemap with advanced features provide business users unparalleled insight into their daily operations and data mining.
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