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Appnomic Launches AppsOne 4.0 in US Market

Appnomic Systems, a provider of automated enterprise and Cloud IT performance management solutions, released 4.0 of its AppsOne solution.

AppsOne 4.0 is an Application Behavior Learning (ABL) solution designed to leverage real-time application usage patterns in a three-dimensional (3D) performance management model.

Diverse software application architectures and disparate data sources in today’s complex IT ecosystems are introducing multiple potential performance break points. There is a need for new methods to analyze the complex and massive volumes of performance data from Cloud and hybrid IT productions systems. The AppsOne 3D metrics model of monitoring application performance effectively analyzes diverse and massive amounts of application and infrastructure operations data to optimize performance and end user productivity.

“Now that Appnomic has proven AppsOne’s success at top banks, online portals, SaaS, and enterprise clients in India, we are pleased to announce, for the first time, our latest product release in the US market,” said Ray Solnik, president of Appnomic Systems, Inc.

With AppsOne 4.0, Appnomic is bringing to its customers:

- 3D real time performance analytics: AppsOne 4.0 analyzes metrics across three key dimensions of application performance: 1) real end user transaction response time, 2) infrastructure components, and 3) application usage patterns. The usage patterns set the foundation for a new approach to application operations management. They correlate the other two dimensions to enable innovative approaches to a variety of application stack operations like: Early Warning Alerts of impending application issues, preventative infrastructure configuration changes, capacity planning, reducing transaction response times, and more.

- End User Monitoring (EUM) for all types of applications: AppsOne 4.0 can capture metrics with JavaScript injection, network monitoring methods or an agent based approach depending on the IT operations objective or architecture. AppsOne 4.0 EUM may be used for http and non-http transaction types as is often necessary for hybrid environments.

- Automated Forensics: Automated deep dive diagnostics information is now collected with every Early Warning Alert to enable faster root cause analysis (RCA) as well as to automate remediation workflow. System administrators can also plug in their diagnostics scripts to collect custom system state data at the time of the alert.

- Support for SAP applications: AppsOne 4.0 customers can monitor the performance of SAP transactions in real time. These include transactions executed via web, ABAP interface and batch jobs. SAP operations support professionals can now benefit from Early Warning Alerts and can use application usage pattern insights to manage capacity for transaction growth.

AppsOne 4.0 service provider clients can use AppsOne EUM to better serve remote customers with quicker root cause analysis for remote user complaints of frustrating, slow transaction experience.

In addition, service provider partners can benchmark an application stack’s performance behavior before migrating the application from an enterprise data center environment to a Cloud environment.

As a result, enterprise clients of Appnomic service provider partners will have a high degree of confidence in final results and enable the service provider to commit to an application migration service level agreement (SLA). Both of these use cases allow enterprises to accelerate migration to the Cloud.

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Appnomic Launches AppsOne 4.0 in US Market

Appnomic Systems, a provider of automated enterprise and Cloud IT performance management solutions, released 4.0 of its AppsOne solution.

AppsOne 4.0 is an Application Behavior Learning (ABL) solution designed to leverage real-time application usage patterns in a three-dimensional (3D) performance management model.

Diverse software application architectures and disparate data sources in today’s complex IT ecosystems are introducing multiple potential performance break points. There is a need for new methods to analyze the complex and massive volumes of performance data from Cloud and hybrid IT productions systems. The AppsOne 3D metrics model of monitoring application performance effectively analyzes diverse and massive amounts of application and infrastructure operations data to optimize performance and end user productivity.

“Now that Appnomic has proven AppsOne’s success at top banks, online portals, SaaS, and enterprise clients in India, we are pleased to announce, for the first time, our latest product release in the US market,” said Ray Solnik, president of Appnomic Systems, Inc.

With AppsOne 4.0, Appnomic is bringing to its customers:

- 3D real time performance analytics: AppsOne 4.0 analyzes metrics across three key dimensions of application performance: 1) real end user transaction response time, 2) infrastructure components, and 3) application usage patterns. The usage patterns set the foundation for a new approach to application operations management. They correlate the other two dimensions to enable innovative approaches to a variety of application stack operations like: Early Warning Alerts of impending application issues, preventative infrastructure configuration changes, capacity planning, reducing transaction response times, and more.

- End User Monitoring (EUM) for all types of applications: AppsOne 4.0 can capture metrics with JavaScript injection, network monitoring methods or an agent based approach depending on the IT operations objective or architecture. AppsOne 4.0 EUM may be used for http and non-http transaction types as is often necessary for hybrid environments.

- Automated Forensics: Automated deep dive diagnostics information is now collected with every Early Warning Alert to enable faster root cause analysis (RCA) as well as to automate remediation workflow. System administrators can also plug in their diagnostics scripts to collect custom system state data at the time of the alert.

- Support for SAP applications: AppsOne 4.0 customers can monitor the performance of SAP transactions in real time. These include transactions executed via web, ABAP interface and batch jobs. SAP operations support professionals can now benefit from Early Warning Alerts and can use application usage pattern insights to manage capacity for transaction growth.

AppsOne 4.0 service provider clients can use AppsOne EUM to better serve remote customers with quicker root cause analysis for remote user complaints of frustrating, slow transaction experience.

In addition, service provider partners can benchmark an application stack’s performance behavior before migrating the application from an enterprise data center environment to a Cloud environment.

As a result, enterprise clients of Appnomic service provider partners will have a high degree of confidence in final results and enable the service provider to commit to an application migration service level agreement (SLA). Both of these use cases allow enterprises to accelerate migration to the Cloud.

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In MEAN TIME TO INSIGHT Episode 14, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud network observability... 

While companies adopt AI at a record pace, they also face the challenge of finding a smart and scalable way to manage its rapidly growing costs. This requires balancing the massive possibilities inherent in AI with the need to control cloud costs, aim for long-term profitability and optimize spending ...

Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

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