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Former AppDynamics CMO Joins Unravel Data

Unravel Data announced the appointment of Steven Wastie as its CMO.

With more than 20 years of global marketing, product management and business development experience, Wastie assumes responsibility for building and scaling the marketing organization to support the strategic growth of the company.

Wastie previously served as CMO at AppDynamics during its hyper-growth phase and most recently as CMO at Origami Logic, a big data analytics company. He brings a strong background in building brand awareness and the keen ability to leverage marketing technology and data analytics to drive sustainable revenue results, build dynamic teams and lead organizations as they scale.

“Steven has a proven track record of implementing and scaling effective marketing strategies that combine his technical, analytical and creative skills to build results-driven marketing engines,” said Kunal Agarwal, CEO of Unravel. “His knowledge of the market is rooted in his deep enterprise experience and understanding of the highly specialized needs of organizations as they unlock the true potential of big data. Steven comes with the highest of recommendations from his peers, and we’re thrilled about the leadership, intense passion and the pivotal role he will play as we propel our efforts in delivering the most complete APM solution for big data applications.”

“The continued transformation of modern application architectures continues to present significant opportunities to innovate and disrupt. Unravel has come to market with the industry’s leading solution to not only provide visibility into how these applications are performing but to also provide granular insights and recommendations to auto-tune and auto-remediate issues proactively or as they occur. As a new generation of applications that depend on the big data stack are going into production, such as the Internet of Things (IoT), customer analytics, machine learning and fraud prevention, they require a different approach to deal with much higher data volumes, a much more distributed run-time and continuous deployment methodology,” stated Wastie. “Unravel has already experienced unprecedented customer validation very early on from leaders in the technology, healthcare and finance industries. I am humbled to join such a talented team and excited to help them drive continued growth and market leadership.”

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Former AppDynamics CMO Joins Unravel Data

Unravel Data announced the appointment of Steven Wastie as its CMO.

With more than 20 years of global marketing, product management and business development experience, Wastie assumes responsibility for building and scaling the marketing organization to support the strategic growth of the company.

Wastie previously served as CMO at AppDynamics during its hyper-growth phase and most recently as CMO at Origami Logic, a big data analytics company. He brings a strong background in building brand awareness and the keen ability to leverage marketing technology and data analytics to drive sustainable revenue results, build dynamic teams and lead organizations as they scale.

“Steven has a proven track record of implementing and scaling effective marketing strategies that combine his technical, analytical and creative skills to build results-driven marketing engines,” said Kunal Agarwal, CEO of Unravel. “His knowledge of the market is rooted in his deep enterprise experience and understanding of the highly specialized needs of organizations as they unlock the true potential of big data. Steven comes with the highest of recommendations from his peers, and we’re thrilled about the leadership, intense passion and the pivotal role he will play as we propel our efforts in delivering the most complete APM solution for big data applications.”

“The continued transformation of modern application architectures continues to present significant opportunities to innovate and disrupt. Unravel has come to market with the industry’s leading solution to not only provide visibility into how these applications are performing but to also provide granular insights and recommendations to auto-tune and auto-remediate issues proactively or as they occur. As a new generation of applications that depend on the big data stack are going into production, such as the Internet of Things (IoT), customer analytics, machine learning and fraud prevention, they require a different approach to deal with much higher data volumes, a much more distributed run-time and continuous deployment methodology,” stated Wastie. “Unravel has already experienced unprecedented customer validation very early on from leaders in the technology, healthcare and finance industries. I am humbled to join such a talented team and excited to help them drive continued growth and market leadership.”

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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.