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SAN FRANCISCO – April 29, 2014 – AppDynamics the application intelligence leader for software-defined businesses, today announced AppDynamics Transaction Analytics, an important new solution allowing businesses to see in real-time the commercial or business value of user-transactions and how they correlate with operational data and overall application performance. The traditional “siloed” approach for optimizing in-production applications in real-time and for managing IT Infrastructure is no longer fit-for-purpose. Business transactions, and the business context they contain, are now the primary unit of management as opposed to managing servers and physical infrastructure availability.
AppDynamics Transaction Analytics strengthens AppDynamics existing operational analytics and real-time business metrics capabilities. Available as a cloud service, hybrid or on-premise solution, Transaction Analytics enables customers to maximize revenue and optimize business operations. Transaction Analytics extracts the rich contextual transaction data contained within every customer transaction to reveal real-time, actionable operational and business intelligence.
Transaction Analytics is an integral and core component of the AppDynamics Application Intelligence Platform also announced today. The AppDynamics Application Intelligence Platform is the industry’s first scalable, secure and lightweight platform providing real-time management, automation and analytics for enterprise applications.
Missing from today’s business intelligence and analytics solutions is the automatic correlation of business and operational data. AppDynamics Transaction Analytics breaks new ground by bringing to market a powerful analytics solution that is real-time, massively scalable, easily implemented. Additionally, it requires no change to the application code or infrastructure. The solution will enable companies to use contextually based transaction data to make better IT operations and business decisions.
Extracting Business Intelligence Among Millions of Lines of Code
Applications built for today’s modern enterprise contain millions of lines of code within complex, multi-tiered, distributed architectures. These new application frameworks leverage a combination of cloud, agile development, service oriented architecture, mobile devices and big data databases. Currently available analytics solutions fail to extract in-production application intelligence from all transactions across all nodes of these next-generation apps.
As an example, current monitoring-only solutions might be able to identify the root cause of a performance problem, but are unable to identify the resulting business impact of poor performance in terms of lost revenue or the exact list of users impacted. In addition, these solutions do not give visibility into the distribution of this lost revenue across different marketing campaigns, product categories, partner services etc. Other solutions may be able to collect log data, but don’t collect transaction payload information or other application performance metrics and carry no context for making intelligent IT operations and business decisions.
AppDynamics Transaction Analytics does all this and more by automatically collecting the data being processed by distributed, mission-critical applications in real-time and then enables users to intuitively analyze the resulting dataset.
“Every company is now a technology company,” said Jyoti Bansal, founder and CEO of AppDynamics. “In the age of the software-defined business, the ability to develop, test, deploy, operate and analyze applications within highly complex and distributed architectures is inextricably tied to the success of any company. Our breakthrough transaction analytics product provides insight into how users interact with the application and provides real-time information regarding the overall health of the business to optimize IT operations and business strategy and maximize revenue.”
Features of AppDynamics Transaction Analytics:
For more details about today’s news please read the AppDynamics blog here.
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