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AppDynamics Introduces Transaction Analytics

AppDynamics 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.

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:

- Comprehensive business intelligence extraction from live application data without any changes to application or the underlying infrastructure

- Interactive visualizations seamlessly slice and dice data for fast and robust analysis

- Robust search capabilities provide the ability to quickly and easily zero in on any specific transaction or log

- Provides full coverage and comprehensive visibility across the application environment

- Powerful cross-platform integration auto-correlates performance metrics and reports

- Infinitely scalable data stores support the needs of today’s large, complex enterprise environments

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AppDynamics Introduces Transaction Analytics

AppDynamics 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.

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:

- Comprehensive business intelligence extraction from live application data without any changes to application or the underlying infrastructure

- Interactive visualizations seamlessly slice and dice data for fast and robust analysis

- Robust search capabilities provide the ability to quickly and easily zero in on any specific transaction or log

- Provides full coverage and comprehensive visibility across the application environment

- Powerful cross-platform integration auto-correlates performance metrics and reports

- Infinitely scalable data stores support the needs of today’s large, complex enterprise environments

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...