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Turbonomic Supports Applications on MS Azure

Turbonomic announced new features to continuously assure application performance at the lowest cost for applications running on Microsoft Azure.

Customers are increasingly designing, building, and managing mission critical applications using Azure’s rich set of Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) offerings. Optimizing the millions of combinations of configurations at scale is complex. Turbonomic, a Microsoft Certified Partner, is the platform of choice for many of the Fortune 1000 enterprises implementing cloud strategies.

The latest Turbonomic platform enhancements help customers accelerate their efforts through:

- Performance Optimization for Azure Reserved Instances: Turbonomic can now make scaling decisions that assure the optimal use of Microsoft Azure Reserved Instances (RI), maximizing RI coverage and utilization while assuring application and virtual machine performance.

- Enterprise Agreement Tailored Pricing: Turbonomic now discovers Azure Enterprise Agreement (EA) subscriptions and captures negotiated discounts so that customers have a more accurate and custom pricing view of the Azure estate that is supporting their modern applications.

- Planning for Migration to Microsoft Azure SQL Database Managed Instance: Turbonomic is providing customers with a roadmap for migration to Azure SQL Database Managed Instance, thereby allowing them to unlock innovation with the SQL Server PaaS offering, help modernize older SQL Server workloads and avoid penalties associated with SQL Server 2008 (R2) end of support. The Azure PaaS migration planning adds to the platform’s existing ability to model the migration of on-premises SQL workloads into Azure Virtual Machines service.

“Turbonomic enables businesses to intelligently migrate workloads to Azure and, once there, continuously optimize their experience and investment. Intelligent automation helps maximize customers’ investment in Azure no matter where they are on their migration path,” said Jeremy Winter, Partner Director, Azure Management at Microsoft Corp.

“As Microsoft continues delivering more value for customers by growing the Azure catalog, so does the skill set needed to manage those offerings. It’s more critical than ever that organizations leverage automated software and systems in order to continuously and automatically assure application performance, cost effectively, while enforcing policy compliance,” said Charles Crouchman, CTO at Turbonomic.

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Turbonomic Supports Applications on MS Azure

Turbonomic announced new features to continuously assure application performance at the lowest cost for applications running on Microsoft Azure.

Customers are increasingly designing, building, and managing mission critical applications using Azure’s rich set of Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) offerings. Optimizing the millions of combinations of configurations at scale is complex. Turbonomic, a Microsoft Certified Partner, is the platform of choice for many of the Fortune 1000 enterprises implementing cloud strategies.

The latest Turbonomic platform enhancements help customers accelerate their efforts through:

- Performance Optimization for Azure Reserved Instances: Turbonomic can now make scaling decisions that assure the optimal use of Microsoft Azure Reserved Instances (RI), maximizing RI coverage and utilization while assuring application and virtual machine performance.

- Enterprise Agreement Tailored Pricing: Turbonomic now discovers Azure Enterprise Agreement (EA) subscriptions and captures negotiated discounts so that customers have a more accurate and custom pricing view of the Azure estate that is supporting their modern applications.

- Planning for Migration to Microsoft Azure SQL Database Managed Instance: Turbonomic is providing customers with a roadmap for migration to Azure SQL Database Managed Instance, thereby allowing them to unlock innovation with the SQL Server PaaS offering, help modernize older SQL Server workloads and avoid penalties associated with SQL Server 2008 (R2) end of support. The Azure PaaS migration planning adds to the platform’s existing ability to model the migration of on-premises SQL workloads into Azure Virtual Machines service.

“Turbonomic enables businesses to intelligently migrate workloads to Azure and, once there, continuously optimize their experience and investment. Intelligent automation helps maximize customers’ investment in Azure no matter where they are on their migration path,” said Jeremy Winter, Partner Director, Azure Management at Microsoft Corp.

“As Microsoft continues delivering more value for customers by growing the Azure catalog, so does the skill set needed to manage those offerings. It’s more critical than ever that organizations leverage automated software and systems in order to continuously and automatically assure application performance, cost effectively, while enforcing policy compliance,” said Charles Crouchman, CTO at Turbonomic.

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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 ...