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SOASTA Partners with Kony on Mobile App Performance

Kony and SOASTA announced a partnership that combines both companies’ capabilities to optimize the performance of enterprise mobile apps across the mobile application development lifecycle.

Through this partnership, Kony and SOASTA will work together to integrate their technologies and combine their expertise to deliver a comprehensive, integrated mobile solution across the DevOps lifecycle for customers. As a result, from prototype to production, mobile apps built on the Kony Mobility Platform can be tested, monitored, measured, analyzed and optimized for peak performance with SOASTA’s TouchTest, CloudTest and mPulse solutions for an integrated Mobile DevOps solution.

According to industry analyst firm Gartner, “The need for automation in mobile application testing is high, and is being driven by agile development practices and a desire to drive quality and features based on user analytics. This pace, combined with a broad and changing device ecosystem, creates a test explosion that without automation will end up crushing all but the most trivial application efforts.” (Gartner, Market Guide for Mobile Application Testing, 3 December 2014)

The Kony Mobility Platform is an open and standards-based, integrated platform that supports the entire application software development lifecycle (SDLC), and empowers enterprises to quickly design, build, deploy and manage multi-edge app experiences. The combined Kony and SOASTA offering delivers an expanded, comprehensive new generation mobile DevOps lifecycle support, including design prototyping, rapid development, functional test automation, back-end integration, deployment, user monitoring and advanced mobile real-time analytics. No other vendor is offering this kind of comprehensive solution. This underscores SOASTA and Kony’s commitment to providing the highest level of mobile developer support, helping enterprise companies align business and IT, while also keeping the rapidly growing mobile user population productive on their systems.

DevOps is a software development method that stresses communication, collaboration, integration, automation and measurement of cooperation between software developers and other information-technology (IT) professionals. DevOps acknowledges the interdependence of software development, quality assurance and IT operations and aims to help an organization rapidly produce software products and services and to improve operations performance.

“In the rapidly growing world of mobile, user experience and application performance are fundamental to enterprise mobile application adoption and success,” said Thomas E. Hogan, CEO, Kony, Inc. “By adding performance analytics and testing solutions to our market-leading enterprise mobility platform, we will empower developers and DevOps teams with the best platform for creating mobile applications at any scale, with the best performance and experience.”

With the integration of Kony and SOASTA, the following new capabilities will be offered to customers:

- Mobile test automation eliminates manual testing delays and accelerates time-to-market, with the SOASTA TouchTest offering

- Continuous performance testing at speed and scale through SOASTA’s patented CloudTest federates millions of cloud-based servers from every major cloud provider

- Access to hundreds of real mobile devices through the cloud for testing at every phase of mobile development, with SOASTA Mobile Device Cloud

- Real User Monitoring (RUM) validates each user experience in real time and correlate real user activity to business metrics through performance analytics, with SOASTA mPulse

“Enterprise mobile application developers will hugely benefit from the partnership between SOASTA and Kony, with the best end-to-end solution to create apps that will perform at the most optimal level,” said Tom Lounibos, CEO, SOASTA. “SOASTA customers are committed to providing the highest level of user experience. Now, Kony customers can also rely on the same market-leading performance analytics to optimize their mobile and Web platforms.

Key benefits of the new end-to-end DevOps platform:

Agility

- Continuous test integration and agile delivery enables the business to respond to market and competitive change

- Reuse code and backend APIs across apps, digital channels and form factors

- Leverage the cloud to instantly build, provision, test and scale mobile apps and infrastructure

- Keep up with the rapid pace of new devices, versions, OSs and form factors as they are released

Usability

- Use powerful analytics to drive insights, iteration and perfect the UX/UI

- Accelerate performance by analyzing all the real user data in real time in a single pane for quick and accurate insights

- Create visually rich, device-exploiting apps in record time using collaborative WYSIWYM (“what you see is what you get”) design tools

Certainty

- Guarantee compatibility across a constantly changing device landscape with unmatched 30-day service level agreement (SLA) on new OS updates

- Ensure a mobile app scales in line with the growth of your customers and business

- Define smart, context-aware policies to secure your enterprise apps and ensure data integrity and availability

- Reuse, Integrate and extend high-value LOB processes to mobile users with powerful backend mobile infrastructure

Efficiency

- Ability to automate functional test cases against a variety of devices and form factors

- Significantly reduce quality assurance cycles

- Create proactive testing plans letting enterprises know of problems before their customers do

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.

SOASTA Partners with Kony on Mobile App Performance

Kony and SOASTA announced a partnership that combines both companies’ capabilities to optimize the performance of enterprise mobile apps across the mobile application development lifecycle.

Through this partnership, Kony and SOASTA will work together to integrate their technologies and combine their expertise to deliver a comprehensive, integrated mobile solution across the DevOps lifecycle for customers. As a result, from prototype to production, mobile apps built on the Kony Mobility Platform can be tested, monitored, measured, analyzed and optimized for peak performance with SOASTA’s TouchTest, CloudTest and mPulse solutions for an integrated Mobile DevOps solution.

According to industry analyst firm Gartner, “The need for automation in mobile application testing is high, and is being driven by agile development practices and a desire to drive quality and features based on user analytics. This pace, combined with a broad and changing device ecosystem, creates a test explosion that without automation will end up crushing all but the most trivial application efforts.” (Gartner, Market Guide for Mobile Application Testing, 3 December 2014)

The Kony Mobility Platform is an open and standards-based, integrated platform that supports the entire application software development lifecycle (SDLC), and empowers enterprises to quickly design, build, deploy and manage multi-edge app experiences. The combined Kony and SOASTA offering delivers an expanded, comprehensive new generation mobile DevOps lifecycle support, including design prototyping, rapid development, functional test automation, back-end integration, deployment, user monitoring and advanced mobile real-time analytics. No other vendor is offering this kind of comprehensive solution. This underscores SOASTA and Kony’s commitment to providing the highest level of mobile developer support, helping enterprise companies align business and IT, while also keeping the rapidly growing mobile user population productive on their systems.

DevOps is a software development method that stresses communication, collaboration, integration, automation and measurement of cooperation between software developers and other information-technology (IT) professionals. DevOps acknowledges the interdependence of software development, quality assurance and IT operations and aims to help an organization rapidly produce software products and services and to improve operations performance.

“In the rapidly growing world of mobile, user experience and application performance are fundamental to enterprise mobile application adoption and success,” said Thomas E. Hogan, CEO, Kony, Inc. “By adding performance analytics and testing solutions to our market-leading enterprise mobility platform, we will empower developers and DevOps teams with the best platform for creating mobile applications at any scale, with the best performance and experience.”

With the integration of Kony and SOASTA, the following new capabilities will be offered to customers:

- Mobile test automation eliminates manual testing delays and accelerates time-to-market, with the SOASTA TouchTest offering

- Continuous performance testing at speed and scale through SOASTA’s patented CloudTest federates millions of cloud-based servers from every major cloud provider

- Access to hundreds of real mobile devices through the cloud for testing at every phase of mobile development, with SOASTA Mobile Device Cloud

- Real User Monitoring (RUM) validates each user experience in real time and correlate real user activity to business metrics through performance analytics, with SOASTA mPulse

“Enterprise mobile application developers will hugely benefit from the partnership between SOASTA and Kony, with the best end-to-end solution to create apps that will perform at the most optimal level,” said Tom Lounibos, CEO, SOASTA. “SOASTA customers are committed to providing the highest level of user experience. Now, Kony customers can also rely on the same market-leading performance analytics to optimize their mobile and Web platforms.

Key benefits of the new end-to-end DevOps platform:

Agility

- Continuous test integration and agile delivery enables the business to respond to market and competitive change

- Reuse code and backend APIs across apps, digital channels and form factors

- Leverage the cloud to instantly build, provision, test and scale mobile apps and infrastructure

- Keep up with the rapid pace of new devices, versions, OSs and form factors as they are released

Usability

- Use powerful analytics to drive insights, iteration and perfect the UX/UI

- Accelerate performance by analyzing all the real user data in real time in a single pane for quick and accurate insights

- Create visually rich, device-exploiting apps in record time using collaborative WYSIWYM (“what you see is what you get”) design tools

Certainty

- Guarantee compatibility across a constantly changing device landscape with unmatched 30-day service level agreement (SLA) on new OS updates

- Ensure a mobile app scales in line with the growth of your customers and business

- Define smart, context-aware policies to secure your enterprise apps and ensure data integrity and availability

- Reuse, Integrate and extend high-value LOB processes to mobile users with powerful backend mobile infrastructure

Efficiency

- Ability to automate functional test cases against a variety of devices and form factors

- Significantly reduce quality assurance cycles

- Create proactive testing plans letting enterprises know of problems before their customers do

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.