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Apica and AppDynamics Partner on Performance Testing of Web Apps

Per aq new partnership, AppDynamics’ real-time application monitoring will now be integrated with Apica LoadTest, Apica ProxySniffer and Apica WebPerformance to bring enhanced visibility and analytics to the testing and monitoring of today’s most complex web, cloud and mobile applications.

This integration will provide up to 10 times more visibility into distributed applications and enable 90 percent faster root cause analysis while deploying in minutes — everything that IT ops and dev teams require to optimize performance in today’s revenue-critical applications.

“Companies today cannot afford performance problems to be anywhere in their applications,” says Sven Hammar, CEO of Apica. “Users expect a fast and reliable web, cloud, and mobile experience. Every second delay can cost businesses valuable customers and revenue. Together with AppDynamics, we’re providing users with best-of-breed solutions to ensure uptime and availability for revenue-critical applications. They’ll have the most complete understanding available of the metrics that are powering or causing problems for their applications so they can take measures to improve performance.”

Performance testing, both as part of the development process as well as in the production environment, ensures that problems are quickly identified and resolved. Apica LoadTest, Apica ProxySniffer, and Apica WebPerformance reveal exactly how an application is performing from the end-user perspective. Now with the integration of AppDynamics, users can get a detailed inside view, down to the code level, of the path of a transaction and see exactly what is behind the performance metrics like availability and response times. This will enable businesses to isolate and address performance problems more quickly, before they can impact reputation or profits.

DevOps can access the Apica portals directly from a web browser. The architectural configuration can be adjusted from day-to-day operations to plan for extreme peaks of traffic as necessary. The same scripts can be used in both Apica LoadTest for performance and stress testing and Apica WebPerformance to measure end-user response times 24x7 for service assurance. Performance trends can be measured and analyzed over time from over 90 locations worldwide. The portals provide automatic alerts if there is any service degradation.

“Apica WebPerformance, Apica ProxySniffer and Apica LoadTest offer customers deep insight into the speed and capabilities of their web applications,” says Jyoti Bansal, Founder and CEO of AppDynamics. “IT operations teams love the production-ready capability of AppDynamics. Now through our partnership with Apica, they will be able to leverage that same visibility and root cause analysis to validate and tune new releases. Our integration with Apica will give businesses a new level of application performance insight.”

The integration of Apica and AppDynamics give DevOps staff an efficient way to correlate the view from the outside – from the end-user perspective – with the view from the inside, down to code level. Together, these two views provide the most complete snapshot of performance for supporting business processes and protecting revenues and brands.

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 ...

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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.

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 ...

Apica and AppDynamics Partner on Performance Testing of Web Apps

Per aq new partnership, AppDynamics’ real-time application monitoring will now be integrated with Apica LoadTest, Apica ProxySniffer and Apica WebPerformance to bring enhanced visibility and analytics to the testing and monitoring of today’s most complex web, cloud and mobile applications.

This integration will provide up to 10 times more visibility into distributed applications and enable 90 percent faster root cause analysis while deploying in minutes — everything that IT ops and dev teams require to optimize performance in today’s revenue-critical applications.

“Companies today cannot afford performance problems to be anywhere in their applications,” says Sven Hammar, CEO of Apica. “Users expect a fast and reliable web, cloud, and mobile experience. Every second delay can cost businesses valuable customers and revenue. Together with AppDynamics, we’re providing users with best-of-breed solutions to ensure uptime and availability for revenue-critical applications. They’ll have the most complete understanding available of the metrics that are powering or causing problems for their applications so they can take measures to improve performance.”

Performance testing, both as part of the development process as well as in the production environment, ensures that problems are quickly identified and resolved. Apica LoadTest, Apica ProxySniffer, and Apica WebPerformance reveal exactly how an application is performing from the end-user perspective. Now with the integration of AppDynamics, users can get a detailed inside view, down to the code level, of the path of a transaction and see exactly what is behind the performance metrics like availability and response times. This will enable businesses to isolate and address performance problems more quickly, before they can impact reputation or profits.

DevOps can access the Apica portals directly from a web browser. The architectural configuration can be adjusted from day-to-day operations to plan for extreme peaks of traffic as necessary. The same scripts can be used in both Apica LoadTest for performance and stress testing and Apica WebPerformance to measure end-user response times 24x7 for service assurance. Performance trends can be measured and analyzed over time from over 90 locations worldwide. The portals provide automatic alerts if there is any service degradation.

“Apica WebPerformance, Apica ProxySniffer and Apica LoadTest offer customers deep insight into the speed and capabilities of their web applications,” says Jyoti Bansal, Founder and CEO of AppDynamics. “IT operations teams love the production-ready capability of AppDynamics. Now through our partnership with Apica, they will be able to leverage that same visibility and root cause analysis to validate and tune new releases. Our integration with Apica will give businesses a new level of application performance insight.”

The integration of Apica and AppDynamics give DevOps staff an efficient way to correlate the view from the outside – from the end-user perspective – with the view from the inside, down to code level. Together, these two views provide the most complete snapshot of performance for supporting business processes and protecting revenues and brands.

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 ...