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Splunk Now Available on Microsoft Azure

Splunk announced the general availability of its enterprise security, observability and platform offerings on Microsoft Azure.

In partnering with Microsoft Corp., Splunk empowers organizations to scale their digital transformation on Azure with unified solutions that accelerate innovation and strengthen security.

"Splunk's strategic partnership with Microsoft to build Splunk natively on Azure demonstrates our commitment to advancing digital resilience to help our customers and partners remain secure and up and running at every step of their cloud journey,” said Tom Casey, Senior Vice President, Splunk Products & Technology Group. “Together, Splunk and Microsoft are integrating enterprise data to strengthen digital resilience and deliver superior hybrid-cloud solutions, both natively and on-premises, that help organizations achieve their digital transformation strategy. Today’s news emphasizes Splunk’s dedication to meeting our customers where they are, and we are pleased to now offer even more flexibility on the trusted Microsoft Azure platform.”

Built natively on Microsoft Azure and powered by Splunk AI, the availability of Splunk Cloud Platform, Splunk Enterprise Security, and Splunk IT Service Intelligence enhances the agility and flexibility of Splunk’s software-as-a-service (SaaS) offerings by enabling comprehensive visibility, rapid detection and investigation, and optimized response. With Splunk on Microsoft Azure, customers and partners can leverage powerful data insights to accelerate innovation, strengthen security postures and optimize infrastructure and application performance.

Existing Splunk customers can choose to migrate on-premises or self-managed cloud deployments to Microsoft Azure, ensuring enhanced security and reliability by delegating the management and deployment of their Splunk infrastructure to Azure. This transition frees up internal resources to focus on mission-critical initiatives rather than managing self-hosted Splunk deployments. With access to the SaaS offerings of Splunk, organizations will be able to unlock cloud value and drive security and observability outcomes from within their Azure environment. Customers with a Microsoft Azure Consumption Commitment (MACC) can utilize their commitment toward Splunk.

Benefits of Splunk deployment on Azure include:

- Simpler administration: Splunk will manage the IT backend for customers’ Splunk deployments, allowing customer teams to act on data insights and explore and implement new use cases.

- Fewer infrastructure requirements: Splunk-provisioned and managed infrastructure delivers a turnkey, cloud-based and scalable data analytics solution.

- Lower total cost of ownership (TCO): Existing Azure customers save on administrative costs and overhead costs, as well as the costs associated with managing private data centers or public cloud infrastructures. They can also avoid egress and ingress costs.

- Improved security: Customers will benefit from consistent Splunk releases to enhance security.

“Accelerating the outcomes and opportunity of AI is essential to meeting the needs of customers across the globe,” said Deb Cupp, President, Microsoft Americas. “Splunk and Microsoft share a commitment to help organizations succeed in the AI era. Our partnership empowers rapid innovation that supports our joint customers’ journey to expedite digital resilience and drive success.”

“The Splunk and Microsoft alliance helps large organizations with complex IT stacks scale their AI transformation efforts and deliver visibility across data sources to ensure enterprise resiliency,” said Michelle Abraham, Research Director, Security and Trust, IDC. “As trusted innovators, Splunk and Microsoft provide customers with the ability to unlock value by simplifying infrastructure requirements, improving security, and decreasing the total cost of ownership.”

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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 ...

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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 ...

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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.

Splunk Now Available on Microsoft Azure

Splunk announced the general availability of its enterprise security, observability and platform offerings on Microsoft Azure.

In partnering with Microsoft Corp., Splunk empowers organizations to scale their digital transformation on Azure with unified solutions that accelerate innovation and strengthen security.

"Splunk's strategic partnership with Microsoft to build Splunk natively on Azure demonstrates our commitment to advancing digital resilience to help our customers and partners remain secure and up and running at every step of their cloud journey,” said Tom Casey, Senior Vice President, Splunk Products & Technology Group. “Together, Splunk and Microsoft are integrating enterprise data to strengthen digital resilience and deliver superior hybrid-cloud solutions, both natively and on-premises, that help organizations achieve their digital transformation strategy. Today’s news emphasizes Splunk’s dedication to meeting our customers where they are, and we are pleased to now offer even more flexibility on the trusted Microsoft Azure platform.”

Built natively on Microsoft Azure and powered by Splunk AI, the availability of Splunk Cloud Platform, Splunk Enterprise Security, and Splunk IT Service Intelligence enhances the agility and flexibility of Splunk’s software-as-a-service (SaaS) offerings by enabling comprehensive visibility, rapid detection and investigation, and optimized response. With Splunk on Microsoft Azure, customers and partners can leverage powerful data insights to accelerate innovation, strengthen security postures and optimize infrastructure and application performance.

Existing Splunk customers can choose to migrate on-premises or self-managed cloud deployments to Microsoft Azure, ensuring enhanced security and reliability by delegating the management and deployment of their Splunk infrastructure to Azure. This transition frees up internal resources to focus on mission-critical initiatives rather than managing self-hosted Splunk deployments. With access to the SaaS offerings of Splunk, organizations will be able to unlock cloud value and drive security and observability outcomes from within their Azure environment. Customers with a Microsoft Azure Consumption Commitment (MACC) can utilize their commitment toward Splunk.

Benefits of Splunk deployment on Azure include:

- Simpler administration: Splunk will manage the IT backend for customers’ Splunk deployments, allowing customer teams to act on data insights and explore and implement new use cases.

- Fewer infrastructure requirements: Splunk-provisioned and managed infrastructure delivers a turnkey, cloud-based and scalable data analytics solution.

- Lower total cost of ownership (TCO): Existing Azure customers save on administrative costs and overhead costs, as well as the costs associated with managing private data centers or public cloud infrastructures. They can also avoid egress and ingress costs.

- Improved security: Customers will benefit from consistent Splunk releases to enhance security.

“Accelerating the outcomes and opportunity of AI is essential to meeting the needs of customers across the globe,” said Deb Cupp, President, Microsoft Americas. “Splunk and Microsoft share a commitment to help organizations succeed in the AI era. Our partnership empowers rapid innovation that supports our joint customers’ journey to expedite digital resilience and drive success.”

“The Splunk and Microsoft alliance helps large organizations with complex IT stacks scale their AI transformation efforts and deliver visibility across data sources to ensure enterprise resiliency,” said Michelle Abraham, Research Director, Security and Trust, IDC. “As trusted innovators, Splunk and Microsoft provide customers with the ability to unlock value by simplifying infrastructure requirements, improving security, and decreasing the total cost of ownership.”

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.