Skip to main content

Infovista Announces User Experience Testing of OTT and 5G

Infovista announced new user experience testing solutions for the most resource intensive – and latency sensitive – OTT applications and interactive 5G services.

Combining various generic testing techniques, real live service traffic pattern emulations and machine learning (ML) algorithms, Infovista enables mobile operators to fully test not only their networks, but also the user experience of any native or OTT applications and services running over them. The Infovista user experience testing portfolio includes sQLEAR, Infovista’s VoLTE and VoNR voice quality testing solution, and new generic testing solutions for OTT voice services, OTT video streaming, and interactive services including e-gaming, remote drone control and video conferencing.

Operators can now test the user experience of high bandwidth, low latency 5G services such as e-gaming using Infovista’s new generic pattern profiling. By emulating the traffic patterns of highly interactive and intensive services, such as the First-Person Shooter (FPS) game genre (e.g. Counter-Strike), Infovista’s testing solutions validate if the network can deliver a great user experience for subscribers using this type of service. Real-time emulation of traffic based on adaptable network conditions enables gaming KPI measurements to be mapped to user experience scores on the service’s interactivity quality. This allows operators to determine both network readiness and any potential improvement actions needed to improve the end user experience.

Infovista’s new generic framework for OTT media testing solves the key challenge with testing OTT media today, namely that parameters such as how to login, or the layout and behavior of the application can change without any notice, and can differ between devices, platforms, countries and even networks. By providing user interface (UI) automation when setting up the tests, while the test methodology and KPIs remain generic, Infovista enables operators to test the generic framework regardless of what OTT media application/service is being used. This saves operators time when testing a multitude of OTT media applications and allows them to quickly test any new application with consistency and confidence.

Infovista now enables operators to generically test OTT voice and video streaming across the large variety of applications, codecs and clients by using a generic client to mimic the behavior of an OTT voice client (e.g. WhatsApp) and/or video streaming client (e.g. video on demand category like Netflix). Infovista’s voice quality ML-based predictor, sQLEAR, uses a generic OTT voice client design based on one of the most commonly used OTT voice apps, WhatsApp. This significantly reduces both cost and time to market of new OTT voice services.

Dr. Irina Cotanis, Technology Director, Network Testing at Infovista explains how using Infovista’s generic testing techniques enables operators to efficiently test user experience for all OTT apps running over their network, while reserving app specific testing for only those apps or services identified as requiring special care and attention: “If we look at the variety and diversity of popular OTT applications, we can see it is impossible to test them all. The most eloquent example is the most demanding and popular 5G service, mobile cloud gaming, for which the multitude and variety of game genres make it clear that there is no point even trying to optimize your network for all the different types of games. Thanks to the multitude of OTT apps and the ever-expanding range of devices, it’s simply not practical or financially viable to test every device, every OTT app and every interactive service. Instead, by testing the network against the key parameters of the most demanding and/or most commonly used OTT application/service, we can give operators the confidence they need to not just deliver a network capable of supporting less intensive and/or less common OTT apps and services, but make user experiences promises, safe in the knowledge that their network will deliver.”

Infovista’s TEMS Network Testing Portfolio enables network and services performance quality evaluation, troubleshooting and optimization by measuring and benchmarking end user experience. For Network Operators and Regulators, TEMS delivers the ability to walk test, drive test, and dynamically analyze service performance under real-life conditions—indoors, outdoors, and around the clock.

The Latest

While 87% of manufacturing leaders and technical specialists report that ROI from their AIOps initiatives has met or exceeded expectations, only 37% say they are fully prepared to operationalize AI at scale, according to The Future of IT Operations in the AI Era, a report from Riverbed ...

Many organizations rely on cloud-first architectures to aggregate, analyze, and act on their operational data ... However, not all environments are conducive to cloud-first architectures ... There are limitations to cloud-first architectures that render them ineffective in mission-critical situations where responsiveness, cost control, and data sovereignty are non-negotiable; these limitations include ...

For years, cybersecurity was built around a simple assumption: protect the physical network and trust everything inside it. That model made sense when employees worked in offices, applications lived in data centers, and devices rarely left the building. Today's reality is fluid: people work from everywhere, applications run across multiple clouds, and AI-driven agents are beginning to act on behalf of users. But while the old perimeter dissolved, a new one quietly emerged ...

For years, infrastructure teams have treated compute as a relatively stable input. Capacity was provisioned, costs were forecasted, and performance expectations were set based on the assumption that identical resources behaved identically. That mental model is starting to break down. AI infrastructure is no longer behaving like static cloud capacity. It is increasingly behaving like a market ...

Resilience can no longer be defined by how quickly an organization recovers from an incident or disruption. The effectiveness of any resilience strategy is dependent on its ability to anticipate change, operate under continuous stress, and adapt confidently amid uncertainty ...

Mobile users are less tolerant of app instability than ever before. According to a new report from Luciq, No Margin for Error: What Mobile Users Expect and What Mobile Leaders Must Deliver in 2026, even minor performance issues now result in immediate abandonment, lost purchases, and long-term brand impact ...

Artificial intelligence (AI) has become the dominant force shaping enterprise data strategies. Boards expect progress. Executives expect returns. And data leaders are under pressure to prove that their organizations are "AI-ready" ...

Agentic AI is a major buzzword for 2026. Many tech companies are making bold promises about this technology, but many aren't grounded in reality, at least not yet. This coming year will likely be shaped by reality checks for IT teams, and progress will only come from a focus on strong foundations and disciplined execution ...

AI systems are still prone to hallucinations and misjudgments ... To build the trust needed for adoption, AI must be paired with human-in-the-loop (HITL) oversight, or checkpoints where humans verify, guide, and decide what actions are taken. The balance between autonomy and accountability is what will allow AI to deliver on its promise without sacrificing human trust ...

More data center leaders are reducing their reliance on utility grids by investing in onsite power for rapidly scaling data centers, according to the Data Center Power Report from Bloom Energy ...

Infovista Announces User Experience Testing of OTT and 5G

Infovista announced new user experience testing solutions for the most resource intensive – and latency sensitive – OTT applications and interactive 5G services.

Combining various generic testing techniques, real live service traffic pattern emulations and machine learning (ML) algorithms, Infovista enables mobile operators to fully test not only their networks, but also the user experience of any native or OTT applications and services running over them. The Infovista user experience testing portfolio includes sQLEAR, Infovista’s VoLTE and VoNR voice quality testing solution, and new generic testing solutions for OTT voice services, OTT video streaming, and interactive services including e-gaming, remote drone control and video conferencing.

Operators can now test the user experience of high bandwidth, low latency 5G services such as e-gaming using Infovista’s new generic pattern profiling. By emulating the traffic patterns of highly interactive and intensive services, such as the First-Person Shooter (FPS) game genre (e.g. Counter-Strike), Infovista’s testing solutions validate if the network can deliver a great user experience for subscribers using this type of service. Real-time emulation of traffic based on adaptable network conditions enables gaming KPI measurements to be mapped to user experience scores on the service’s interactivity quality. This allows operators to determine both network readiness and any potential improvement actions needed to improve the end user experience.

Infovista’s new generic framework for OTT media testing solves the key challenge with testing OTT media today, namely that parameters such as how to login, or the layout and behavior of the application can change without any notice, and can differ between devices, platforms, countries and even networks. By providing user interface (UI) automation when setting up the tests, while the test methodology and KPIs remain generic, Infovista enables operators to test the generic framework regardless of what OTT media application/service is being used. This saves operators time when testing a multitude of OTT media applications and allows them to quickly test any new application with consistency and confidence.

Infovista now enables operators to generically test OTT voice and video streaming across the large variety of applications, codecs and clients by using a generic client to mimic the behavior of an OTT voice client (e.g. WhatsApp) and/or video streaming client (e.g. video on demand category like Netflix). Infovista’s voice quality ML-based predictor, sQLEAR, uses a generic OTT voice client design based on one of the most commonly used OTT voice apps, WhatsApp. This significantly reduces both cost and time to market of new OTT voice services.

Dr. Irina Cotanis, Technology Director, Network Testing at Infovista explains how using Infovista’s generic testing techniques enables operators to efficiently test user experience for all OTT apps running over their network, while reserving app specific testing for only those apps or services identified as requiring special care and attention: “If we look at the variety and diversity of popular OTT applications, we can see it is impossible to test them all. The most eloquent example is the most demanding and popular 5G service, mobile cloud gaming, for which the multitude and variety of game genres make it clear that there is no point even trying to optimize your network for all the different types of games. Thanks to the multitude of OTT apps and the ever-expanding range of devices, it’s simply not practical or financially viable to test every device, every OTT app and every interactive service. Instead, by testing the network against the key parameters of the most demanding and/or most commonly used OTT application/service, we can give operators the confidence they need to not just deliver a network capable of supporting less intensive and/or less common OTT apps and services, but make user experiences promises, safe in the knowledge that their network will deliver.”

Infovista’s TEMS Network Testing Portfolio enables network and services performance quality evaluation, troubleshooting and optimization by measuring and benchmarking end user experience. For Network Operators and Regulators, TEMS delivers the ability to walk test, drive test, and dynamically analyze service performance under real-life conditions—indoors, outdoors, and around the clock.

The Latest

While 87% of manufacturing leaders and technical specialists report that ROI from their AIOps initiatives has met or exceeded expectations, only 37% say they are fully prepared to operationalize AI at scale, according to The Future of IT Operations in the AI Era, a report from Riverbed ...

Many organizations rely on cloud-first architectures to aggregate, analyze, and act on their operational data ... However, not all environments are conducive to cloud-first architectures ... There are limitations to cloud-first architectures that render them ineffective in mission-critical situations where responsiveness, cost control, and data sovereignty are non-negotiable; these limitations include ...

For years, cybersecurity was built around a simple assumption: protect the physical network and trust everything inside it. That model made sense when employees worked in offices, applications lived in data centers, and devices rarely left the building. Today's reality is fluid: people work from everywhere, applications run across multiple clouds, and AI-driven agents are beginning to act on behalf of users. But while the old perimeter dissolved, a new one quietly emerged ...

For years, infrastructure teams have treated compute as a relatively stable input. Capacity was provisioned, costs were forecasted, and performance expectations were set based on the assumption that identical resources behaved identically. That mental model is starting to break down. AI infrastructure is no longer behaving like static cloud capacity. It is increasingly behaving like a market ...

Resilience can no longer be defined by how quickly an organization recovers from an incident or disruption. The effectiveness of any resilience strategy is dependent on its ability to anticipate change, operate under continuous stress, and adapt confidently amid uncertainty ...

Mobile users are less tolerant of app instability than ever before. According to a new report from Luciq, No Margin for Error: What Mobile Users Expect and What Mobile Leaders Must Deliver in 2026, even minor performance issues now result in immediate abandonment, lost purchases, and long-term brand impact ...

Artificial intelligence (AI) has become the dominant force shaping enterprise data strategies. Boards expect progress. Executives expect returns. And data leaders are under pressure to prove that their organizations are "AI-ready" ...

Agentic AI is a major buzzword for 2026. Many tech companies are making bold promises about this technology, but many aren't grounded in reality, at least not yet. This coming year will likely be shaped by reality checks for IT teams, and progress will only come from a focus on strong foundations and disciplined execution ...

AI systems are still prone to hallucinations and misjudgments ... To build the trust needed for adoption, AI must be paired with human-in-the-loop (HITL) oversight, or checkpoints where humans verify, guide, and decide what actions are taken. The balance between autonomy and accountability is what will allow AI to deliver on its promise without sacrificing human trust ...

More data center leaders are reducing their reliance on utility grids by investing in onsite power for rapidly scaling data centers, according to the Data Center Power Report from Bloom Energy ...