Big Data Analytics

OpTier provides an end-to-end analytics platform that fully integrates with our patented transaction capture technology (ACT). This technology enables us to capture every business transaction, complete with context, and permanently store it using Cassandra. Business transactions are captured and processed in real-time, even in customer production environments where volumes can exceed millions of transactions per minute.

The rich client interface, with drag-and-drop capabilities, empowers business analysts to design and control an analytics process that spans the entire life cycle: data capture and exploration, data filtering and augmentation, intermediate storage and data delivery.

Without any coding or application modifications, analysts can effortlessly build interactive, real-time dashboards that go beyond traditional reporting to produce powerful customer insights and immense business value.

Application Performance Management (APM)

The transaction data captured by OpTier’s lightweight agents is sent to our APM server, where a multi-dimensional analysis takes place.

First, we use all the information captured by our agents to generate a complete and accurate representation of each business transaction that transpired. Back to the shipping company analogy, we’re essentially assembling the full route each package (i.e. transaction) traveled, from origin to destination.

Next, the "transaction record" is saved to our Big Data store (i.e. Cassandra) where it can be used for application troubleshooting, problem-isolation or audit needs.

Living Application Topology

Based on historical transaction data aggregated by our server, we’re able to provide our enterprise customers with a living topology of their application. This is done out-of-the-box and since it’s calculated with the transaction data coming straight from the application itself, it automatically adapts to match any changes in the monitored application.

Valuable Transaction Context

Our server analyzes the data by the transaction types ('checkout' vs. 'login'), the end-user geo-location, the device used to interact with an application, and much more. All the information is being stored in a time-based manner, so it can be revisited and used to optimize the performance of an application, conduct change-impact analysis, server fine tunes and other tasks.

Code-Level Application Detail

Using non-intrusive technology, we’re also able to provide code and SQL-level visibility into the application, so you can tell which method took most of the time on a specific JBoss instance when executing a login transaction. And you don't need to change one line of code in your application!