Virtana announced its expanded offering of Virtana Platform on Amazon Web Services (AWS) Marketplace.
Offering end user customers a unified SaaS platform on Marketplace, the solution leverages a "know before you go" approach with high-definition data collection on-premises, and delivers precision observability, reduces cloud costs, and de-risks public cloud migration to AWS.
Virtana Platform is designed to provide Global 2000 enterprises the precise data-driven ability to identify, de-risk, and prioritize workloads, accelerating the move of the right workloads at the right time in an optimized form to AWS. The migration-focused Software as a Service (SaaS) partner has a history of expertise in precisely understanding the existing customer application workloads that are candidates for migration.
With customers’ increasing need to de-risk and have precision visibility when migrating workloads to AWS, exacerbated by the pandemic, Virtana has fast-tracked Virtana Platform inclusion in AWS Marketplace — moving beyond cloud cost visibility to deliver a unified observability platform for hybrid cloud.
Ryan Broadwell, Global Director of ISVs at AWS, commented, “We look forward to seeing Virtana’s footprint expand in AWS Marketplace to support even more enterprise customers looking to optimize their move to the cloud and enable a strong digital transformation.”
Virtana chose to build its platform natively on AWS to ensure the highest levels of alignment as both services advance to meet ever-evolving customer requirements. This relationship with AWS and the SaaS platform availability give customers a unique artificial intelligence (AI)-powered roadmap for optimizing digital transformation and cloud enablement, along with true visibility throughout the digital transformation journey.
Kash Shaikh, President and CEO of Virtana, commented, “Data is the currency in this digital era, and it is time for customers to take it to the bank. We are proud of our growing relationship with AWS, supporting and enabling customers to know before they go to the cloud. Virtana’s SaaS platform (now available in AWS Marketplace) delivers a unique approach to observability that unifies AIOps, cloud cost optimization, and de-risks cloud migration using high-definition precision data insights.”
Shaikh added, “The combination of AWS best practices and our deep observability and insights are leading to stronger migration methodologies, reductions in cloud expenses, and acceleration of a more powerful digital transformation for our Global 2000 customers.”
As a member of AWS’ Advanced Technology Partner Program, Virtana is working with System Integrators (SI) aligned with AWS, leveraging their expertise and methodologies around migration. SIs are able to build Digital Transformation offerings built on capabilities of both platforms, delivering high-value, cost effective modernization strategies to the broader market. In turn, customers can meet their migration goals and business objectives, and get their move to cloud right the first time.
Virtana Platform is now available on AWS Marketplace and will continue to work to continue to deliver the best customer transformational journey through working with the Migration Acceleration Team, the SaaS Factory Team, individual product teams for Migration Evaluator, and the Business Case Analysis Team.
The Latest
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.
The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...