Reports & Dashboards 

Logster visualization platform displays reports from your applications on the Reports page. It can be reached by  the Reports button in the main menu where you can use following features

  • Filter Reports
  • Sort Reports
  • Search for Reports
  • Set Up Badges
  • Upload Reports

Secure Storage Format

We designed a few data formats for each log data type (logs, events, metrics, etc). Each format has been adapted to specific use cases for efficient extraction, display, and analysis. In addition, all data will be encrypted using the latest technology advances in this area. All this ensures that data is protected and enables our clients to store large volumes of log data without incurring high storage costs. 
The Logster platform support following data type: 

  • Dev logs with different severity levels and unlimited custom attributes 
  • System metrics is a set of ​predefined metrics for each type of system components
  • Custom metrics allow you to create different type of metric with unlimited custom attributes
  • Events 
  • Crash reports is special lod data type which will help to analyze application crashes and provide quick fixes

Quick Start with Log Adapters

 To use the Logster platform you just need to complete a few simple following steps: 

  • Login in to the Logser web console
  • Switch to the Applications tab and click Create New Application.
  • Specify the application name and description, then click Create and get your APP Key and APP Token.
  • Choose and download the appropriate adapter for your application    

Well done! now you can send logging data to the Logster platform via the adapter from your application.

Sensitive Data Detection

This feature will help you for supporting  regional DPAs (contractually commit to compliance with EU and US laws with GDPR and CCPA) and avoiding leaks of customer sensitive data. 
Technically, we use neural network algorithms to detect parts of sensitive and the Logster platform provides the automation to mask or remove this data. ML models can be integrated to an adaptor or enabled on log data the processing pipeline.