jKool Announces the Availability of the jKool RESTful API for Streaming, Time-Series Data
MELVILLE, NY, (PRWEB) September 17, 2015 -- Starting today, developers can use the jKool RESTful API to stream time-series data to the jKool cloud-based SaaS solution and analyze and visualize application data in real-time. The jKool RESTful API provides easy application access to a cloud service for real-time log file analytics, operational intelligence, analytics and visualization.
The jKool RESTful API is a cloud-enabled service that can be engaged by any application that uses REST. Developers using the RESTful API will benefit from an easy-to-use method to send JSON formatted data to the cloud service. The jKool API is integrated with Swagger so that developers can use the Swagger SDK Generator to auto-generate a client API making it even easier to engage with the jKool Cloud Service.
jKool’s real-time log file analytics, operational intelligence, analytics and visualization provides immediate value to businesses needing greater insight into their application behavior especially those looking to find and fix problems faster. jKool's real-time diagnostics can be applied to an entire Java application – logs, metrics and transactions. It can help users make data-driven decisions, detect anomalies, discover topologies, analyze application behavior and rapidly determine problem causality.
jKool can help businesses who have adopted a DevOps approach and those exploiting the value in the Internet of Things (IoT), retail, audit, compliance and digital healthcare. jKool provides instant insight into the perishable opportunities hidden in big data in these industries and others. Connect up to the API and start with jKool’s free tier, today.
The jKool SaaS automatically visualizes time-series data in real-time from any RESTful source as well those from Java, Log4j, Logback, SLF4J, HTTP, Syslog and Apache Spark. Using SaaS, there are no servers, database or schemas to manage. jKool’s real-time scorecard provides immediate insight to developers, DevOps,IT Ops professionals and business analysts who can now make split-second decisions based on data in motion such as orders, clicks, payments, claims and searches. They learn what they didn’t already know, take advantage of perishable insights, detect preventable losses and uncover new opportunities.
jKool visualization includes behavior, performance, location and topology displayed on a real-time dashboard. Users can subscribe to topics of interest or interactively ask a question using an easy-to-use, English-like query language. jKool, a multi-tenant solution is built on an Apache open-source foundation including: the NoSQL database Cassandra and Solr from DataStax, along with Kafka, Spark and STORM all orchestrated in-concert via jKool FatPipes™ technology.
"Until recently, analyzing and visualizing streaming data in real-time was just not possible for most businesses,” said Charley Rich, vice president of product management at jKool. “jKool’s new RESTful API for streaming time-series data makes it easy to add real-time log file analytics and visualization to your applications. jKool analyzes machine data, in real-time, in-memory, offers extreme scalability and provides the vital insight you need to act now.”
To learn more about jKool’s real-time visualization and analytics SaaS offering, visit: https://www.jkoolcloud.com.
About jKool, LLC
jKool, LLC provides open source technology and a cloud-based service to provide real-time log file analytics, operational intelligence, visualization and analytics from streaming data for Java Developers, DevOps, IT Ops and applications in the Internet of Things (IoT), Retail, Finance and Digital Healthcare. Differentiating via ease-of-use and scale, jKool helps developers, DevOps, data scientists and business analysts visualize, analyze and detect trends, providing them with real-time insight into their data.
For more information about the company, visit http://www.jkoolcloud.com.
Charles Rich, jKool, LLC, http://www.jkoolcloud.com, +1 (631) 761-9100 Ext: 9128, [email protected]
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