jKool Blog

About Charley Rich

Charley is a Software Product Management & Marketing Professional with extensive experience working with application performance monitoring, IT Service Management and SaaS. He was also a contributor to four highly successful start-ups, including: InterWorld, Tivoli, SMARTS and Collation and holds a patent for Application Performance Monitoring. Prior to joining Nastel, Charley was the world-wide Product Manager for IBM's Tivoli Application Dependency Discovery Manager software, where he charted the product roadmap, managed product marketing and received the Tivoli General manager's Award. Earlier he held the Director of the Application Management Product Line position at SMARTS, and was the Director of Strategy and Planning and later Vice President of Field Marketing for eCommerce firm InterWorld. Charley is a sought after speaker and a published author.
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. […]

21 12, 2015

Capturing the Business Value of Big Data in Real Time

By |December 21st, 2015|Big Data, Big Data Analytics, Business|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.

Harnessing the power of big data analytics to create value is now considered a crucial component of any sound business development program. In fact, IDC estimates that worldwide spending on big data-related software, hardware, and services will grow to $125 billion in 2015.

Several steps in the data analysis pipeline must be completed before the business knowledge hidden in your data can be revealed. Data acquisition, generating the correct metadata, and ensuring security are all very important steps, but they typically do not fall into the purview of the business user. The business user wants to attain actionable insights that will impact the bottom line in a simple and cost-effective manner. […]

16 12, 2015

How DevOps can end finger pointing and improve team collaboration

By |December 16th, 2015|devops, Uncategorized|0 Comments

DevOps teams strive to improve the cadence of new releases, fix problems faster and provide the best possible user experience for their customers. However, it can be challenging to achieve these outcomes when problem resolution starts with finger pointing instead of effective collaboration.

Getting the right information can be a big help. The type of data needed is usually interaction data such as events with time-stamps. These interactions can be clicks, orders, or anything else measurable and important to your organization. Most often this data is rapidly changing, and is referred to as data-in-motion or fast data. As the data arrives, a series of questions should be asked to ensure you have what you need to identify and respond as fast and effectively as possible. These questions can help you eliminate finger pointing and reduce MTTR.

Ask (and answer) these questions: […]

4 12, 2015

Log Analytics is DEAD

By |December 4th, 2015|devops, log analytics|0 Comments

Yes, did I really say that?? Yes I did. Log Analytics is a process of investigating logs and hoping to derive actionable information that might be useful to the business. Many log analytics tools are used to gain visibility into web traffic, security, application behavior, etc. But how valuable and practical is log analytics […]

11 11, 2015

Analyze and visualize your data with jKool on Bluemix

By |November 11th, 2015|Big Data Analytics, bluemix, Java, log analytics, Real-time Analytics, SaaS|0 Comments

Applications can behave in unexpected ways and it’s often difficult to know whether this is appropriate behavior or if something is really wrong. Sound familiar? This is the same conundrum parents face… and often just as hard to solve.

But, for Java developers and members of DevOps, the ultimate advantage in this situation would […]

23 10, 2015

jKool’s RESTful API is available in IBM Bluemix

By |October 23rd, 2015|API|0 Comments

jKool Announces the Availability of the jKool RESTful API for Streaming, Time-series Data in the IBM Bluemix Catalog

jKool’s API using REST is now available for Bluemix developers who need to analyze and visualize time-series data.  Time-series data typically means interaction data such as: orders, clicks payments, claims and other event type data with time-stamps.  […]

20 06, 2015

Learn How to Unlock Big Data:

By |June 20th, 2015|Big Data, Big Data Analytics, operational analytics|0 Comments

Spot the Patterns in your Data that Lead to Actionable Insights

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.

Big data promises a lot, yet few businesses have mastered what it takes turn this data into actionable insights. Boardrooms see the value in analytics or business intelligence (BI) as a way to make business predictions and gain a competitive advantage. Many of the largest enterprises spend millions on database farms, DataMarts and even proprietary hardware to accomplish this. Often their output is produced in batch and unable to keep up with the velocity of their business. Even with all that expense and technical know-how, these firms are limited when it comes to very largest data volumes – Big Data. However smaller firms with limited budgets are unable to afford BI and do not have the resources financial and technical to take advantage of NoSQL. In addition these companies would like to move beyond batch and extract useful information from high velocity data streams in near real-time. […]

13 02, 2015

Analyzing time-series data – not as easy as it looks!

By |February 13th, 2015|Big Data Analytics, streaming analytics, time-series data|0 Comments

Analyzing time-series data is a lot more complex than just ingest bytes and inform user “done”.  There is a lot of “digestion” that must go on for the data to be useful in the near-term.  The working definition we use for big data, helps portray why this is so:

Big Data can be defined as: […]

3 02, 2015

A Better way to Monitor JVM Containers: StreamJMX

By |February 3rd, 2015|Java, open-source, streaming analytics|0 Comments

StreamJMX is a better way to monitor JVM containers. Typically JVMs are monitored by using remote JMX monitoring tools. There are significant problems with this approach. Examples: how do you monitor a farm of JVMs without having and administrative headache of setting up remote JMX configurations, ports, SSL, etc etc. With all the talk about cyber security, JMX remote connectivity opens up a way for hackers to exploit these administrative ports.

StreamJMX, open source JMX streaming framework, allows a developer accomplish just that. StreamJMX allows developers to stream JMX metrics from JVM out to the central location, or any other destination.

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30 01, 2015

Open-Source Connectors for jKool Streaming Analytics

By |January 30th, 2015|connectors, Java, open-source|0 Comments

Open-Source is a type of technology and it’s also a philosophy. The technology is one where the source code is published for anyone interested to see and use. The philosophy is about letting the community drive the direction of a product as opposed to the traditional method where an individual vendor provides the product roadmap.

As a Product Manager, I know that it is all too easy for a product to drift away from the needs of the market either due to not listening to the market or over listening to one customer and only one customer. The beauty of open-source is that the market drives the product; thus, in theory at least the product or project is always in synchronization with the changing needs of the market.

At jKool we have embraced open-source and having attended All Things Open in October we know there is a vibrant community out there for this approach. We are actively creating new open-source connectors to jKool, our SaaS solution for Streaming Analytics. We have just released two new connectors. They are: […]