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AppDynamics Introduces Application Analytics

AppDynamics announced AppDynamics Application Analytics, a powerful new solution that provides real-time IT operations and business operations intelligence from across distributed application environments.

Application Analytics automatically collects meaningful data in its business context from the entire application stack, no matter how complex or distributed. This data with business context enables IT not only to manage IT operations, but also to provide business units with vital metrics they can use to optimize user engagement, conversion, and ultimately, revenue. It is a true big data analytics platform that enables stakeholders to instantly analyze transactions, manage performance, and determine current and potential impact across the business in real time.

Application Analytics captures raw business data from every line of code in all layers of an application and across every single node, without requiring code changes or additional infrastructure. There is no need for coding, as is required to collect data from log files. And unlike data warehousing, which can only provide historical snapshots of completed transactions, Application Analytics provides an up-to-the-minute, real-time view into transactions that are in flight.

The solution is easy to deploy and massively scalable, capable of handling a trillion metrics daily.

“Application Analytics addresses the biggest data challenges enterprises face today — volume, velocity, and variety,” said Jyoti Bansal, founder and CEO of AppDynamics. “Huge volumes of data are being generated at blinding speed, and it’s coming from every direction — the cloud, different devices, and complex application infrastructures. But it’s just so much noise if it can’t be efficiently harvested and parsed. That’s what Application Analytics does. With the lens of business context, no matter how fast the data comes at you, it quickly makes sense, and gives a basis for smart, insightful decision-making.”

With a solution that is easy to deploy and massively scalable, and capable of handling a trillion metrics daily, Application Analytics enables IT operations to gain intelligence faster than ever before, seeing errors, slowdowns, and outages in real time. Armed with this data, business and IT can collaborate and act quickly to minimize business impact. At the same time, the data it captures can be used to engage those users who have been negatively impacted to mitigate any negative brand impact.

“The challenge to date has been the abundance of solutions for unstructured data analysis, which still require the application to log the correct and relevant data from within the application. This requires a specific type of maturity within an organization, such as developers logging relevant metrics as defined by the business stakeholders or product management professionals,” said Jonah Kowall, Research VP at Gartner. “Alternate approaches have begun to emerge from leading APM providers, which leverage the solution's placement (and viewpoint from) within the application; hence they are able to automatically extract business logic demonstrated in transactional execution. The coupling of this context with detailed information about end-user experience and user interactions with applications themselves, provides a rich set of data that requires no development resources as long as the applications are built on modern technology.”

Application Analytics Use Cases

- Business impact analysis. Quantify the dollars-and-cents impact of stalls and outages, and identify and communicate with impacted customers to recover their business and preserve a positive brand perception.

- Business operations monitoring. Pinpoint where in the process a transaction is stuck, and know how to resolve it.

- Performance analytics. Identify poor-performing transactions and understand the cause in order to prioritize IT investments.

- Customer analytics. Understand user behavior and usage trends to optimize user engagement and conversions.

- SLA management. Real-time reporting on service level agreement performance.

AppDynamics Application Analytics, which completed its beta as “Transaction Analytics,” will be available with the Fall 2014 Release.

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AppDynamics Introduces Application Analytics

AppDynamics announced AppDynamics Application Analytics, a powerful new solution that provides real-time IT operations and business operations intelligence from across distributed application environments.

Application Analytics automatically collects meaningful data in its business context from the entire application stack, no matter how complex or distributed. This data with business context enables IT not only to manage IT operations, but also to provide business units with vital metrics they can use to optimize user engagement, conversion, and ultimately, revenue. It is a true big data analytics platform that enables stakeholders to instantly analyze transactions, manage performance, and determine current and potential impact across the business in real time.

Application Analytics captures raw business data from every line of code in all layers of an application and across every single node, without requiring code changes or additional infrastructure. There is no need for coding, as is required to collect data from log files. And unlike data warehousing, which can only provide historical snapshots of completed transactions, Application Analytics provides an up-to-the-minute, real-time view into transactions that are in flight.

The solution is easy to deploy and massively scalable, capable of handling a trillion metrics daily.

“Application Analytics addresses the biggest data challenges enterprises face today — volume, velocity, and variety,” said Jyoti Bansal, founder and CEO of AppDynamics. “Huge volumes of data are being generated at blinding speed, and it’s coming from every direction — the cloud, different devices, and complex application infrastructures. But it’s just so much noise if it can’t be efficiently harvested and parsed. That’s what Application Analytics does. With the lens of business context, no matter how fast the data comes at you, it quickly makes sense, and gives a basis for smart, insightful decision-making.”

With a solution that is easy to deploy and massively scalable, and capable of handling a trillion metrics daily, Application Analytics enables IT operations to gain intelligence faster than ever before, seeing errors, slowdowns, and outages in real time. Armed with this data, business and IT can collaborate and act quickly to minimize business impact. At the same time, the data it captures can be used to engage those users who have been negatively impacted to mitigate any negative brand impact.

“The challenge to date has been the abundance of solutions for unstructured data analysis, which still require the application to log the correct and relevant data from within the application. This requires a specific type of maturity within an organization, such as developers logging relevant metrics as defined by the business stakeholders or product management professionals,” said Jonah Kowall, Research VP at Gartner. “Alternate approaches have begun to emerge from leading APM providers, which leverage the solution's placement (and viewpoint from) within the application; hence they are able to automatically extract business logic demonstrated in transactional execution. The coupling of this context with detailed information about end-user experience and user interactions with applications themselves, provides a rich set of data that requires no development resources as long as the applications are built on modern technology.”

Application Analytics Use Cases

- Business impact analysis. Quantify the dollars-and-cents impact of stalls and outages, and identify and communicate with impacted customers to recover their business and preserve a positive brand perception.

- Business operations monitoring. Pinpoint where in the process a transaction is stuck, and know how to resolve it.

- Performance analytics. Identify poor-performing transactions and understand the cause in order to prioritize IT investments.

- Customer analytics. Understand user behavior and usage trends to optimize user engagement and conversions.

- SLA management. Real-time reporting on service level agreement performance.

AppDynamics Application Analytics, which completed its beta as “Transaction Analytics,” will be available with the Fall 2014 Release.

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Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

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Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...

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