jKool analyzes security violations on a set of Unix servers in the Viewlet presented on the right.
As this is a real-time query, authentication issues will instantly appear in the Viewlet.
This type of security issue occurs when someone is trying repeatedly to logon to a server with a variety of different passwords. jKool detects this pattern instantly.
While, this could be either user error or a hack attempt, this example appears to more of a hack. We know this from jKool’s analysis of the time between events.
The lower the time, the more frequent the activity is. High frequency of logon attempts points most likely to a break-in attempt.
Analyzing Garbage Collection (GC) behavior is critical for performance of your java applications. GC collections are analyzed across multiple JVMs with automatically computed upper and lower bands (normal bands). Bands auto-adjust, dynamically based on the incoming GC frequency and duration.
jKool automatically spots anomalies, when GC frequency or duration rises above the upper band.
Click on the screen to drill down into the details.
On the subsequent screen, we see GC details with additional information about the GC activity on this application server.
jKool automatically keeps track of exceptions in your environment by quickly identifying exceptions and errors across multiple JVM, application, server instances.
Logs, metrics, transactions (syslog, log4j, slf4j, logback, logstash, flume, java) are streamed from one or more locations to a central jKool respistory to track errors, performance such as: response times, I/O, SQL, LDAP, web requests, socket exceptions and application specific exceptions in real-time. Application teams can drill further down into the “What, When and Why” and fix problems fast.
In the Viewlet on the near right we are seeing a column chart illustrating application exceptions grouped by resource. We see many exceptions from application servers. If we drill into the app server column, we see details of the underlying failures.
In the Viewlet on the far right we have drilled into the event detail and are viewing the exception stack trace behind the SQL exception, invalid object name.
Know What Happened
Log analytics illustrated in the image on the near right, while important, are not enough. Logs can be cumbersome to work with and lack metrics for proper root cause analysis and diagnostics. DevOps teams need more – application logs, metrics and transactions as well as data about servers, network and more.
Logs alone are insufficient when you need to know the location of an order, how long it took to execute or why it timed out and didn’t complete.
jKool shown in the image on the bottom far right, shows an enrichment of logs with metrics, transactions and other relevant data in context. This unified view can lead to root cause in as few as 2 clicks.
Logs, metrics and transactions are necessary to get the visibility you need to “know what happened” and answer what might happen in the future.
jKool delivers a true unified view of your application – logs, metrics and transactions in a single view.