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AppDynamics Spring '17 Release Announced

AppDynamics, a Cisco company, announced its Spring ‘17 release, including the AppDynamics Developer Toolkit and major updates to Enterprise iQ and Business iQ.

The latest release empowers application teams to deliver impactful customer experiences faster while laying the foundation for unprecedented scale. Now, the entire business can quickly align around a single goal: continuously delivering high quality mobile and web applications faster than ever. AppDynamics customers can quickly build, deploy, measure and improve their customer experiences regardless of the environment.

“Today, the application is the business, creating immense pressure on organizations to deliver new experiences that ‘wow’ customers,” said Bhaskar Sunkara, CTO and Head of Product at AppDynamics. “And digital leaders continually raise the bar for what consumers expect from application experiences. With our new Developer Toolkit, companies can give their application teams the context of how their code impacts the business and deliver innovation like a digital leader.”

Introducing the AppDynamics Developer Toolkit

With the new Developer Toolkit, the AppDynamics Spring ‘17 release provides application teams application development lifecycle transparency, from the code to end-user experiences and the business outcomes. With this newfound visibility, every team member can see the impact their work has on the business in real time, and ultimately deliver better applications that create value for the organization. The new Developer Toolkit spans tools for build, test, analysis and continuous improvement:

Build: Support for new languages and development tools enable application developers to transform ideas into better apps faster.

- Go Support — Go’s (or Golang’s) popularity continues to rise because it’s powerful yet easy to understand and maintain. With AppDynamics for Go, application teams now have the patented Business Transaction (BT) detection and tracing for Go applications. They can now gain insight with reports on errors generated by bad requests, providing better end-to-end coverage across distributed application environments.

- Xamarin Support — Comprehensive support for Xamarin allows mobile application developers to embed AppDynamics in native iOS and Android mobile applications and monitor and drive application performance from a single code base.

- Android Studio Plugin — Developers can now automate the instrumentation process for Android applications, thereby reducing errors and making it easier for developers to deliver performant Android mobile apps.

Integration and Test: New extensions to BTs empower app teams to focus on the user journeys and code that move the needle the most, improving customer outcomes and speeding release velocity.

- Developer Mode Business Transactions — With new Developer Mode BTs, application teams now have deep-code diagnostics for specific Business Transactions in both pre-production and production environments enabling them to quickly address bottlenecks and remediate any issues found in testing.

- Live Mode Business Transactions — Live Mode BTs delivers faster and more accurate configuration by detecting and defining rules according to live application data to identify critical Business Transactions.

Automated Analysis: With new crash analysis tools, applications teams will spend less time on unplanned work and troubleshooting, and more time building new features that can impact the business.

- Smart Crash Alerts — When instrumenting new mobile applications, Smart Crash Alerts are set up by default to save time and effort post-instrumentation. Spend less time configuring alerts.

- Unique Crashes in Business iQ — New crash reports in Business iQ correlate app crashes to business metrics like conversion rates, revenue or anything else the business tracks. Now app teams have new visibility into crashes so they can prioritize fixing the issues that matter the most to the business.

Smarter Continuous Improvement with Business iQ: The AppDynamics Developer Toolkit provides intelligence into customer journeys so app teams know which updates will matter the most to customers and the business.

- Real User Insights — New session summary dashboards track individual customer sessions while capturing scrolls, taps and other gestures so developers and business leaders gain unparalleled insight into how customers experience applications.

- Mobile Scorecard — Major updates to the mobile scorecard show the metrics that matter, at a glance. The new mobile scorecard makes it easy to see crash rate, number of crashes, network request performance, and error rates for every mobile application at a glance.

Enterprise iQ and Business iQ Enhancements

The Spring ‘17 release also features updates to Enterprise iQ that provide powerful new capabilities and scale for modern enterprises including:

- License Management — Provides the flexibility required for DevOps environments by assigning licenses based on business unit. With powerful configuration rules and a simple to read dashboard, license keys can be easily assigned or reassigned so that teams never run out of licenses when they need it.

- Universal Agent — Deploying, upgrading, and maintaining agents is now significantly easier. A single package can now be deployed to any machine that requires monitoring, and the universal agent will coordinate with the AppDynamics controller to automatically deploy and configure it so teams spend less time configuring and more time innovating. Universal agent supports the Java and Machine agent types, with other agents expected to be supported in future releases.

- More Powerful Business iQ Metrics — Baselines become even more powerful with the Spring ‘17 release. By leveraging the power of the AppDynamics Query Language (ADQL) in Business iQ, application teams can build powerful dashboards and establish health rules faster than ever. Now application teams have even more intelligence into how application changes are impacting the business.

AppDynamics Spring '17 Release is available now.

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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 ...

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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.

AppDynamics Spring '17 Release Announced

AppDynamics, a Cisco company, announced its Spring ‘17 release, including the AppDynamics Developer Toolkit and major updates to Enterprise iQ and Business iQ.

The latest release empowers application teams to deliver impactful customer experiences faster while laying the foundation for unprecedented scale. Now, the entire business can quickly align around a single goal: continuously delivering high quality mobile and web applications faster than ever. AppDynamics customers can quickly build, deploy, measure and improve their customer experiences regardless of the environment.

“Today, the application is the business, creating immense pressure on organizations to deliver new experiences that ‘wow’ customers,” said Bhaskar Sunkara, CTO and Head of Product at AppDynamics. “And digital leaders continually raise the bar for what consumers expect from application experiences. With our new Developer Toolkit, companies can give their application teams the context of how their code impacts the business and deliver innovation like a digital leader.”

Introducing the AppDynamics Developer Toolkit

With the new Developer Toolkit, the AppDynamics Spring ‘17 release provides application teams application development lifecycle transparency, from the code to end-user experiences and the business outcomes. With this newfound visibility, every team member can see the impact their work has on the business in real time, and ultimately deliver better applications that create value for the organization. The new Developer Toolkit spans tools for build, test, analysis and continuous improvement:

Build: Support for new languages and development tools enable application developers to transform ideas into better apps faster.

- Go Support — Go’s (or Golang’s) popularity continues to rise because it’s powerful yet easy to understand and maintain. With AppDynamics for Go, application teams now have the patented Business Transaction (BT) detection and tracing for Go applications. They can now gain insight with reports on errors generated by bad requests, providing better end-to-end coverage across distributed application environments.

- Xamarin Support — Comprehensive support for Xamarin allows mobile application developers to embed AppDynamics in native iOS and Android mobile applications and monitor and drive application performance from a single code base.

- Android Studio Plugin — Developers can now automate the instrumentation process for Android applications, thereby reducing errors and making it easier for developers to deliver performant Android mobile apps.

Integration and Test: New extensions to BTs empower app teams to focus on the user journeys and code that move the needle the most, improving customer outcomes and speeding release velocity.

- Developer Mode Business Transactions — With new Developer Mode BTs, application teams now have deep-code diagnostics for specific Business Transactions in both pre-production and production environments enabling them to quickly address bottlenecks and remediate any issues found in testing.

- Live Mode Business Transactions — Live Mode BTs delivers faster and more accurate configuration by detecting and defining rules according to live application data to identify critical Business Transactions.

Automated Analysis: With new crash analysis tools, applications teams will spend less time on unplanned work and troubleshooting, and more time building new features that can impact the business.

- Smart Crash Alerts — When instrumenting new mobile applications, Smart Crash Alerts are set up by default to save time and effort post-instrumentation. Spend less time configuring alerts.

- Unique Crashes in Business iQ — New crash reports in Business iQ correlate app crashes to business metrics like conversion rates, revenue or anything else the business tracks. Now app teams have new visibility into crashes so they can prioritize fixing the issues that matter the most to the business.

Smarter Continuous Improvement with Business iQ: The AppDynamics Developer Toolkit provides intelligence into customer journeys so app teams know which updates will matter the most to customers and the business.

- Real User Insights — New session summary dashboards track individual customer sessions while capturing scrolls, taps and other gestures so developers and business leaders gain unparalleled insight into how customers experience applications.

- Mobile Scorecard — Major updates to the mobile scorecard show the metrics that matter, at a glance. The new mobile scorecard makes it easy to see crash rate, number of crashes, network request performance, and error rates for every mobile application at a glance.

Enterprise iQ and Business iQ Enhancements

The Spring ‘17 release also features updates to Enterprise iQ that provide powerful new capabilities and scale for modern enterprises including:

- License Management — Provides the flexibility required for DevOps environments by assigning licenses based on business unit. With powerful configuration rules and a simple to read dashboard, license keys can be easily assigned or reassigned so that teams never run out of licenses when they need it.

- Universal Agent — Deploying, upgrading, and maintaining agents is now significantly easier. A single package can now be deployed to any machine that requires monitoring, and the universal agent will coordinate with the AppDynamics controller to automatically deploy and configure it so teams spend less time configuring and more time innovating. Universal agent supports the Java and Machine agent types, with other agents expected to be supported in future releases.

- More Powerful Business iQ Metrics — Baselines become even more powerful with the Spring ‘17 release. By leveraging the power of the AppDynamics Query Language (ADQL) in Business iQ, application teams can build powerful dashboards and establish health rules faster than ever. Now application teams have even more intelligence into how application changes are impacting the business.

AppDynamics Spring '17 Release is available now.

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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.