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Microservices Expo Authors: Elizabeth White, Carmen Gonzalez, Liz McMillan, Jason Bloomberg, Pat Romanski

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AppDynamics Brings Big Data Science to APM in Summer ’14 Release

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Today I am pleased to announce the availability of the AppDynamics Summer ‘14 Release.  With this release, AppDynamics brings the first event store to capture and process big data streams in real-time to the APM industry.  Large and complex applications generate data at an extremely high velocity, requiring a monitoring platform to scale along with them. Many business critical applications and operational insights are hidden in the data generated by these applications. This unified platform delivers a central, massively scalable platform to manage all tiers of the application infrastructure.

This release has major enhancements for each of the three layers of the Application Intelligence platform:

Clear, meaningful data visualization

AppDynamics was the first to market with transaction-based topology views of applications that make managing and scaling service oriented architectures easier than ever.  In our latest release, we’ve raised the bar again by offering clear, meaningful data visualization powered by self-learning algorithms for today’s leading enterprise companies.

Advanced flow map visualizations

Self-aggregating flow maps

AppDynamics introduces advanced flow maps that are powered by sophisticated algorithms to make complex architectures more manageable by condensing and de-condensing information to enable intelligent zooming in and out of the topology. These visualization techniques also deliver the right level of granularity of application health indicators and traffic reports to match the zoom level.

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Self-organizing layouts

In the Summer ‘14 release, the dashboards self-organize complex graphs of service and tier dependencies by using auto-grouping heuristics to dynamically determine tier and node weightages. These auto-grouping heuristics rely on dynamic patterns detected across static data such as application tier profiles and dynamic KPIs such as transaction response times, business data complexity, etc.  These algorithms then surface up the business-critical nodes and tiers to application owners and administrators for appropriate attention.

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Self-learning transaction engine

Application owners can benefit greatly if they are armed with smart engines that automatically identify and group these transactions taking away the guesswork out of the exercise. This is based on a combination of historical as well as statistical analysis of large volumes of live execution data.  AppDynamics uniquely does live traffic introspection and creates groupings of business transactions from millions of requests of live traffic to improve business manageability.

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Smart dashboards

Managing and monitoring large deployments with thousands of nodes and tiers can be overwhelming for the APM professional. Creating a separate dashboard for each of the thousand nodes and tiers individually is a near impossible task. In this release, AppDynamics introduces powerful dashboarding templates that auto-generate dashboards based on configurable parameterized characteristics of the nodes or tiers. This new feature enhances monitoring productivity by making the dashboards reusable for all nodes without having to replicate efforts.

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Platform to capture and process Big Data streams in real-time

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A new infinitely scalable event service that captures real-time events generated by an application. With this event service, organizations can flexibly define structured and unstructured events, and start capturing them with a public API. This infinitely scalable service has been certified for up to 10 trillion events. Archives of these events can be captured forever, and can be used for historical analyses as well.

A new Hadoop-powered metrics service that crunches massive volumes of time-series data to deliver key application and business metrics in real-time. With its new enhancements, organizations can easily roll-up metrics at the tier levels, application levels, or time-series levels with no loss in granularity of the information. Leveraging the new complex algorithms that can crunch billions of metrics, this metrics service generates self-learning baselines that are refreshed reflecting the up to the minute application and business performance.

We’ve also improved our real-time percentile metrics capabilities that put application and business performance in context. Metrics without a statistical context often don’t reveal the real picture. SLA metrics are more meaningful when presented with the context of percentiles, and when the outliers are automatically identified and surfaced up with alerts for immediate attention or automated remediation.  The percentile functionality in AppDynamics is now configurable, allowing teams to define what percentiles they want to be collected.

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This unified platform delivers a central, linearly scalable platform to manage all tiers of their application infrastructure. Through a single pane of glass, IT organizations can break down application tier silos and monitor their business with comprehensive end-to-end visibility. This unified platform lowers the total cost of ownership of their application infrastructure while lowering their time to issue resolution.

Industry’s most comprehensive monitoring and data collection offering

The AppDynamics Summer ‘14 Release includes several new and enhanced features related to data collection and monitoring, including distributed transaction correlation among all of the languages we support.

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With the industry’s first Node.js distributed transaction monitoring users can now monitor distributed Node.js transactions across all application tiers including Java, .NET and PHP. Node.js can automatically correlate downstream calls to quickly and efficiently isolate and troubleshoot performance bottlenecks.

Screen Shot 2014-08-13 at 11.15.17 AM

AppDynamics adds support for instrumenting native C++ applications with the beta release of the AppDynamics C++ SDK, which provides visibility into C++ applications and tiers. We’ve also added support for Java 8, which makes it easier for businesses to deploy and integrate AppDynamics into the latest generation of Java and Scala applications.

Finally, we’ve announced support for monitoring .NET asynchronous transactions. AppDynamics gives customers the ability to automatically identify asynchronous transactions in dashboards, troubleshoot asynchronous calls in transaction snapshots and analyze async activity in the metric browser.

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If you’d like to try these new capabilities out for yourself, start your free trial of AppDynamics today.

 

The post AppDynamics Brings Big Data Science to APM in Summer ’14 Release written by appeared first on Application Performance Monitoring Blog from AppDynamics.

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