VMware announced its intent to acquire Avi Networks, a provider of multi-cloud application delivery services.
Avi Networks will further enable VMware to bring the public cloud experience to the entire data center — automated, highly scalable, and intrinsically more secure with the ability to deploy applications with a single click, upon close of the acquisition.
Leveraging a common architectural foundation, VMware and Avi Networks will be able to deliver a complete software-defined networking stack from L2-7 built for the modern multi-cloud era after the deal closes.
“VMware is committed to making the data center operate as simply and easily as it does in the public cloud, and the addition of Avi Networks to the growing VMware networking and security portfolio will bring us one step closer to this goal after the acquisition closes,” said Tom Gillis, SVP and GM, networking and security business unit, VMware. “This acquisition will further advance our Virtual Cloud Network vision, where a software-defined distributed network architecture spans all infrastructure and ties all pieces together with the automation and programmability found in the public cloud. Combining Avi Networks with VMware NSX will further enable organizations to respond to new opportunities and threats, create new business models, and deliver services to all applications and data, wherever they are located.”
“Unlike existing ADC solutions, Avi Networks’ distributed ADC is designed for modern data center and public cloud deployments, with an architecture that mirrors cloud principles,” said Amit Pandey, CEO, Avi Networks. “Upon close, customers will be able to benefit from a full set of software-defined L2-7 application networking and security services, on-demand elasticity, real time insights, simplified troubleshooting, and developer self-service.”
Upon close with Avi Networks, VMware will offer both built-in load balancing capabilities as part of VMware NSX Data Center, and an advanced, standalone ADC. The Avi platform enables organizations to overcome the complexity and rigidness of legacy systems and ADC appliances with modern, software-defined application services.
Avi Networks’ key differentiators include:
- Automation driven by closed-loop analytics, template-driven configuration, and integration with management products
- Advanced analytics and insights for performance monitoring and troubleshooting
- Ability to deploy across on-premises and multiple cloud environments
- Elasticity and on-demand scalability
- Intrinsic security
The Avi platform provides a Software Load Balancer, Intelligent Web Application Firewall (iWAF), Advanced Analytics and Monitoring and a Universal Service Mesh to help enable a fast, scalable, and more intrinsically secure application experience. Avi’s central control plane and distributed data plane deliver application services as a dynamic, multi-cloud fabric which intelligently automates decisions and provides unprecedented application analytics and on-demand elasticity. Avi customers can dispatch services such as load balancing and web application firewall to any application using one centralized interface. Avi technology runs across private and public clouds, and supports applications running on VMs, containers and bare metal.
The transaction is expected to close in VMware's fiscal Q2 FY2020, subject to customary closing conditions, including regulatory approvals. This acquisition is not expected to have a material impact on fiscal 2020 operating results.
The Latest
In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...
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 ...