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Splunk Cloud Provides International Availability on AWS

Splunk Cloud is generally available internationally through nine Amazon Web Services’ (AWS) global regions and will be available soon in AWS GovCloud for US government agencies, contractors and businesses.

Splunk Cloud is as an enterprise-ready cloud service with a 100 percent uptime service level agreement (SLA). Splunk Cloud offers enterprise scalability of 10+ Terabytes per day. Experience the power of Splunk Cloud first-hand today through the free Splunk Online Sandbox.

“Splunk is a long term, innovative AWS Technology Partner and we are excited to see them extend their reach to new geographies,” said Terry Wise, vice president of worldwide partner ecosystem, Amazon Web Services, Inc. “By ‘going-global’ on AWS, Splunk is able to serve the needs of organizations worldwide, including those moving mission-critical production workloads to the cloud. We are excited to see Splunk’s global footprint increase as we launch more AWS regions around the world.”

“As organizations make a seminal shift to the cloud, we are pleased to extend Splunk Cloud internationally with AWS,” said Marc Olesen, SVP and GM of Cloud Solutions, Splunk. “Organizations in countries around the world can now take advantage of centralized visibility across cloud, on-premises and hybrid environments with all the benefits of software-as-a-service (SaaS).”

Splunk Cloud includes access to all features of the Splunk Enterprise platform, including apps, APIs, alerting and role-based access controls.

Key features and benefits of Splunk Cloud include:

- Instant: Instant trials through an online sandbox and rapid conversion from proof-of-concept to production.

- Secure: SOC2 Type 2 certification with dedicated environments for every customer.

- Reliable: 100 percent uptime SLA and 10+ TB/day scalability.

- Hybrid: Centralized visibility across Splunk Cloud (SaaS) and Splunk Enterprise (software) deployments.

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.

Splunk Cloud Provides International Availability on AWS

Splunk Cloud is generally available internationally through nine Amazon Web Services’ (AWS) global regions and will be available soon in AWS GovCloud for US government agencies, contractors and businesses.

Splunk Cloud is as an enterprise-ready cloud service with a 100 percent uptime service level agreement (SLA). Splunk Cloud offers enterprise scalability of 10+ Terabytes per day. Experience the power of Splunk Cloud first-hand today through the free Splunk Online Sandbox.

“Splunk is a long term, innovative AWS Technology Partner and we are excited to see them extend their reach to new geographies,” said Terry Wise, vice president of worldwide partner ecosystem, Amazon Web Services, Inc. “By ‘going-global’ on AWS, Splunk is able to serve the needs of organizations worldwide, including those moving mission-critical production workloads to the cloud. We are excited to see Splunk’s global footprint increase as we launch more AWS regions around the world.”

“As organizations make a seminal shift to the cloud, we are pleased to extend Splunk Cloud internationally with AWS,” said Marc Olesen, SVP and GM of Cloud Solutions, Splunk. “Organizations in countries around the world can now take advantage of centralized visibility across cloud, on-premises and hybrid environments with all the benefits of software-as-a-service (SaaS).”

Splunk Cloud includes access to all features of the Splunk Enterprise platform, including apps, APIs, alerting and role-based access controls.

Key features and benefits of Splunk Cloud include:

- Instant: Instant trials through an online sandbox and rapid conversion from proof-of-concept to production.

- Secure: SOC2 Type 2 certification with dedicated environments for every customer.

- Reliable: 100 percent uptime SLA and 10+ TB/day scalability.

- Hybrid: Centralized visibility across Splunk Cloud (SaaS) and Splunk Enterprise (software) deployments.

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.