Correlsense has delivered Release 3.5 of its SharePath software.
This version includes a wide variety of enhancements designed to broaden the product’s footprint in the enterprise:
- Reduced cost of ownership by monitoring more applications in less time
- Increased scalability by managing more applications with the same hardware
- Enhanced method-level hot spot detection and code analytics for multiple programming languages
- Advanced search features for its integral big data store
- Flexible and intuitive business transaction naming
- Expanded alerting and notification options
SharePath is designed for enterprise environments where there are multiple server platforms, programming languages, software applications, middleware products, and a variety of endpoints.
SharePath monitors languages like Java and C, integration components like queue managers and enterprise service busses, and a wide variety of operating systems and databases. A highly scalable backend allows customers to use hundreds of collectors to monitor many operational applications using a common management server.
“Delivering software for the enterprise requires a level of sophistication that most APM vendors simply don’t have,” said Lanir Shacham, founder and CTO, Correlsense. “SharePath’s unique ability to correlate big data streams and to detect a broad range of performance issues across all components and tiers is unmatched in the industry.”
Large corporations often rely on composite applications spanning new software, legacy code, and packaged solutions. Employees and customers may access them from Internet browsers, terminals, or rich clients like desktop workstations. A single user transaction may touch dozens of servers and applications inside the company and in the cloud.
SharePath tracks individual user transactions across all hops in this long journey and isolates the source of a problem. Once identified, SharePath customers can easily view the details and determine the best course of corrective action. SharePath also helps customers identify potential problems and capture information that may be used to provide better customer service and more efficient revenue generating applications.
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