AppDynamics Summer '14 Release Brings Big Data Science to APM
August 14, 2014
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AppDynamics announced the availability of the AppDynamics Summer '14 release.

With this latest release AppDynamics brings sophisticated data visualizations and big data techniques for behavioral-learning and stream processing to the platform. Combined with the deepest and broadest support for collecting data from applications and infrastructure, this allows AppDynamics to monitor and manage ultra-large scale application deployments that generate large volume of business transactional data in real-time, detect patterns, and take action to improve application performance and optimize digital revenue streams. As the complexity and variety of large enterprise web and mobile applications grows, the Summer '14 release enables IT operations management (ITOM) and Operational Analytics professionals to pinpoint issues, fix them fast and Automate wherever possible, all whilst driving the business agenda.

"AppDynamics is the only APM solution in the market today that completely addresses the management challenges associated with large scale enterprise deployments. As the size and complexity of our customers' applications continue to grow, we are uniquely positioned to simplify the challenges that are commonplace in ultra-large scale deployments," said Jyoti Bansal, founder and CEO, AppDynamics. "With the AppDynamics Summer '14 Release, our Application Intelligence Platform embraces innovative big data techniques to power solutions that provide unprecedented support for the applications that business' now depend on."

The AppDynamics Summer '14 Release improves the value delivered to development, operations and business teams by providing:

- Intuitive, powerful drill-down data visualization capabilities, a self-learning business transaction engine that automatically sorts business critical transactions, smart dashboards and advanced analytics.

- A newly architected big data platform with massively scalable big data infrastructure components such as Hadoop to handle large numbers of events, metrics and metadata.

- A deeper and broader set of data visibility and collection capabilities with support for new applications that leverage our Automatic Code Injection, and Dynamic Context Propagation techniques for end to end business transaction monitoring.

Together, these enhancements harness the power and value of big data management and visualization techniques to deliver to customers a single-pane-of-glass-view into the health of their digital business. This addresses the customer need for simple, intelligent insights and decision-making while hiding away all the underlying complexity associated with large and ultra-large scale deployments.

New and Enhanced Features of the Summer '14 Release Include:

- Self-aggregating flow maps that make complex architectures more manageable by condensing and de-condensing information to enable intelligent zooming in and out of application, tier, node, business transaction, and snapshot flow maps

- Self-organizing layouts that heuristically determine tier and node weightings based on millions of data points to elevate visibility of the business critical nodes and tiers

- A self-learning transaction engine that statistically analyzes historical as well as live execution data to surface those business transactions that critical to business performance

- Powerful smart dashboards that eliminate huge amounts of manual work by auto-generating based on node or tier characteristics and patterns

- Easy, drag-and-drop correlation analysis of any two metrics across any given time range, allowing IT Operations teams to quickly identify cause and effect of metric fluctuations over time

- A new infinitely scalable event service that provides a single store for all events generated by ultra-large scale application deployments

- A new Hadoop-powered metrics service that does easy drill down and drill up of data for tier, application, and time series levels without any loss of granularity

- Real-time percentile metrics that dynamically baselines application performance and alerts based on outliers from a historical perspective that is sensitive to the time of day

- Application performance monitoring support for Java 8 that enables monitoring of Java 8 and Scala application features such as lambda expressions and parallel operations

- Industry's first distributed transaction monitoring for Node.js applications that allows monitoring of transactions spanning Node.js, Java, .NET, and PHP application tiers.

- Beta support for C++ SDK that delivers native visibility and code-level drill down by allowing native instrumentation of C++ applications

- Industry's first capability for monitoring asynchronous transactions in .NET applications

- Updates and enhancements to the strong ecosystem that offers more than one hundred extensions

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