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Infovista Partners with VMware

Infovista announced that it is partnering with VMware to enable deployment of its Ativa™ Automated Assurance and Operations suite on the VMware Tanzu platform.

This enables Communication Service Providers (CSPs) to accelerate their digital transformation by deploying Ativa, seamlessly across any combination of multi-cloud environments.

Officially validated as Partner Ready for VMWare Tanzu and listed on the VMWare Marketplace, Infovista has tested and verified the interoperability of Ativa with VMware Tanzu Kubernetes Grid and can fully manage customer support requests for Ativa and its solution deployments.

Designed to address the complexity of modern network and service operations, Ativa replaces siloed, fragmented, domain-oriented OSS and assurance systems that focus on multiple disparate domains such as subscriber, service, network, or infrastructure with a single cloud-native suite of automated operations and assurance applications.

CSPs use Infovista Ativa for a wide range of use cases, with its pre-configured use-case based solutions spanning monitoring and troubleshooting for mobile, 5G standalone, IoT, fixed and enterprise connectivity services; customer and device analytics; and the 360° assurance family of solutions that enable horizontally and vertically correlated, real-time, automated service assurance.

“The ‘cloud’ doesn’t automatically equate to agility, flexibility and scalability; it’s about having the right systems in place – which are cloud-native by design – to enable you to unlock the power of whatever cloud architecture you have to drive your own digital transformation,” said Yann Le Helloco, Chief Technology Officer, Infovista. “This requires the ability to combine previously siloed data with powerful automation to create a single source of truth that gives you 360° visibility, interoperability and predictive automation in a multi-cloud environment. By validating Infovista Ativa for VMware Tanzu, we are ensuring that enterprises and operators can realize the full benefits of their cloudified network.”

Deployable on private, public and hybrid clouds, virtualized datacenters and bare metal, Infovista Ativa is powered by the network lifecycle automation (NLA) Cloud Platform, which provides the building blocks for Infovista’s NLA solutions. These automate processes and tasks that span traditionally siloed systems, not only within operations but across every phase of the network lifecycle. Ativa lays the foundations for CSPs and enterprises to cost-effectively and seamlessly expand to NLA solutions that extend beyond operations, such as Smart CAPEX for ROI-optimized planning decision-making enriched by live operational intelligence.

Infovista Ativa is underpinned by an open, cloud-native platform utilizing industry standard Open APIs and software development kits (SDKs) that allow customers and partners to extend the available catalog of pre-configured Infovista solutions and build their own applications and use cases.

The Infovista Ativa suite of applications can be deployed independently or in combination, and include:

- Ativa Net for cross-domain visibility of network resources and infrastructure performance. It correlates network services, VNFs and infrastructure for rapid troubleshooting

- Ativa App for cross-domain visibility of subscriber-facing and resource-facing services. It proactively monitors and troubleshoots QoS and enterprise SLAs across wireless and wireline

- Ativa Experience for cross-domain visibility of perceived subscriber experience, including deep packet analysis

- Ativa Automated Ops for automated AI/ML-driven predictive analytics; network and service orchestrator interoperability; zero-touch resource configuration; NOC/SOC workflow automation; and active testing and validation

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.

Infovista Partners with VMware

Infovista announced that it is partnering with VMware to enable deployment of its Ativa™ Automated Assurance and Operations suite on the VMware Tanzu platform.

This enables Communication Service Providers (CSPs) to accelerate their digital transformation by deploying Ativa, seamlessly across any combination of multi-cloud environments.

Officially validated as Partner Ready for VMWare Tanzu and listed on the VMWare Marketplace, Infovista has tested and verified the interoperability of Ativa with VMware Tanzu Kubernetes Grid and can fully manage customer support requests for Ativa and its solution deployments.

Designed to address the complexity of modern network and service operations, Ativa replaces siloed, fragmented, domain-oriented OSS and assurance systems that focus on multiple disparate domains such as subscriber, service, network, or infrastructure with a single cloud-native suite of automated operations and assurance applications.

CSPs use Infovista Ativa for a wide range of use cases, with its pre-configured use-case based solutions spanning monitoring and troubleshooting for mobile, 5G standalone, IoT, fixed and enterprise connectivity services; customer and device analytics; and the 360° assurance family of solutions that enable horizontally and vertically correlated, real-time, automated service assurance.

“The ‘cloud’ doesn’t automatically equate to agility, flexibility and scalability; it’s about having the right systems in place – which are cloud-native by design – to enable you to unlock the power of whatever cloud architecture you have to drive your own digital transformation,” said Yann Le Helloco, Chief Technology Officer, Infovista. “This requires the ability to combine previously siloed data with powerful automation to create a single source of truth that gives you 360° visibility, interoperability and predictive automation in a multi-cloud environment. By validating Infovista Ativa for VMware Tanzu, we are ensuring that enterprises and operators can realize the full benefits of their cloudified network.”

Deployable on private, public and hybrid clouds, virtualized datacenters and bare metal, Infovista Ativa is powered by the network lifecycle automation (NLA) Cloud Platform, which provides the building blocks for Infovista’s NLA solutions. These automate processes and tasks that span traditionally siloed systems, not only within operations but across every phase of the network lifecycle. Ativa lays the foundations for CSPs and enterprises to cost-effectively and seamlessly expand to NLA solutions that extend beyond operations, such as Smart CAPEX for ROI-optimized planning decision-making enriched by live operational intelligence.

Infovista Ativa is underpinned by an open, cloud-native platform utilizing industry standard Open APIs and software development kits (SDKs) that allow customers and partners to extend the available catalog of pre-configured Infovista solutions and build their own applications and use cases.

The Infovista Ativa suite of applications can be deployed independently or in combination, and include:

- Ativa Net for cross-domain visibility of network resources and infrastructure performance. It correlates network services, VNFs and infrastructure for rapid troubleshooting

- Ativa App for cross-domain visibility of subscriber-facing and resource-facing services. It proactively monitors and troubleshoots QoS and enterprise SLAs across wireless and wireline

- Ativa Experience for cross-domain visibility of perceived subscriber experience, including deep packet analysis

- Ativa Automated Ops for automated AI/ML-driven predictive analytics; network and service orchestrator interoperability; zero-touch resource configuration; NOC/SOC workflow automation; and active testing and validation

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.