jKool Blog

23 02, 2016

5 ways to spice up DevOps with jKool

By |February 23rd, 2016|blog, devops, Java, log analytics, operational analytics, operational intelligence, performance monitoring, SaaS, streaming analytics, transaction tracking|0 Comments

Eliminate finger pointing, reduce blame

jKool allows application owners to track and audit transactions; from browser all the way to application servers and middleware. Ability to track transactions is critical if you want to know if your app is slow; and where and why it is slow. How often is the blame placed on you or your team […]

11 02, 2016

What does APM have to do with Fast Data?

By |February 11th, 2016|Apps, Big Data, Big Data Analytics, Fast Data, Java, log analytics, operational analytics, operational intelligence, performance monitoring, Real-time Analytics, streaming analytics, transaction tracking|0 Comments

Fast Data is about processing high velocity data in real-time as it happens. Think of Fast Data as Big Data in real-time.

So what does APM have to do with Fast Data?

Everything.

APM is all about processing lots and lots of data as close as possible to real-time.
Tracking transactions, analyzing logs, sampling metrics, figuring out relationships, […]

22 01, 2016

Operational Analytics Seen Boosting IT Performance

By |January 22nd, 2016|Big Data Analytics, log analytics, operational analytics, operational intelligence|0 Comments

The industry-sponsored report compiled by market researcher Enterprise
Management Associates (EMA) noted that investments in operations analytics and the
management of application performance could be applied across multiple use cases. One reason …

[…] Read the source article at EnterpriseTech
Original Author: EnterpriseTek

21 12, 2015

Getting Operational Intelligence from Logs, Metrics, and Transactions

By |December 21st, 2015|Big Data Analytics, operational intelligence, transaction tracking|0 Comments

jKool, a SaaS solution for real-time analytics, forensics and transaction tracking provides instant insight from fast data, making it easy to detect the hidden patterns and anomalies that offer opportunities for business value.

For Java developers, IT ops professionals and members of the DevOps group, the ultimate advantage would be to know everything as it happens in their business— and everything that could happen. To know all and see all with complete vision is the competitive ideal: operations managers detecting performance problems before delays arise, the company discovering trends the moment they form. If there is a function in modern technology that offers anything close to this ideal of omniscience, it’s analyzing and visualizing machine data in real time.

Such awareness is so difficult to attain, and it is often impossible for companies to know in advance what events need to be analyzed and when analysis must happen. IT must store everything and analyze everything or risk missing the most important evidence of operational lags, risks or rising customer trends. For security compliance reasons alone, enterprises are required to maintain good logs, store logs for one year, secure these logs—and review them daily. […]

2 10, 2015

Live Q & A Transcript: Capture Real-Time Operational Intelligence from Big Data

By |October 2nd, 2015|Big Data Analytics, devops, log analytics, operational intelligence|0 Comments

If you missed the recent  Live Q and A with jKool CTO Albert Mavashev, get caught up with this transcript of the event.

The post Live Q & A Transcript: Capture Real-Time Operational Intelligence from Big Data appeared first on Data Informed.
Albert Mavashev: Hi, my name is Albert Mavashev. I am here to answer your questions about jKool, a platform for analyzing machine data in real-time, time series data like logs, metrics, transactions….
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