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Splunk Observability Cloud Available on AWS in Australia and New Zealand

Splunk announced Splunk Observability Cloud is now available in Australia and New Zealand (ANZ) via the Amazon Web Services (AWS) Asia Pacific (Sydney) Region.

With the Splunk Observability Cloud, DevOps, IT Operations and software development teams can answer any question about the performance and health of their applications, services and infrastructure with metrics, traces and logs - all data collected in real time, without sampling and at any scale. By providing services on AWS in ANZ, enterprises now have options to retain data closer to home with low latency, which is an important requirement for observability. This also helps Australian organizations meet compliance requirements associated with data residency.

“... Splunk Observability Cloud provides DevOps, IT Operations and software development teams with all the capabilities they need for observability in one integrated interface, enabling organizations to monitor and analyse their applications and infrastructure in real time." said Mark Troselj, Group VP of Australia and New Zealand, Splunk.

“AWS supports hundreds of thousands of organisations across Australia and New Zealand to continuously innovate, succeed, and grow globally,” said Sumal Karunanayake, Head of Partner Success, Amazon Web Services, Australia and New Zealand. “With Splunk Observability Cloud on AWS, local enterprises who are increasingly focused on user experience, app modernisation, and innovation, can quickly gain visibility of their technology infrastructure and IT applications, and accelerate improvements that support digital transformation – all with the data staying local
to Australia and New Zealand.”

The Splunk Observability Cloud brings together the world’s best-in-class solutions for infrastructure monitoring, application performance monitoring, real user monitoring, synthetic monitoring, log investigation and incident response. Backed by Splunk’s NoSample full-fidelity data ingestion, real-time streaming analytics and massive scalability, Splunk Observability Cloud delivers unprecedented capabilities for monitoring, troubleshooting and resolution of business-critical incidents. The full observability portfolio from Splunk includes Splunk Infrastructure Monitoring, Splunk APM, Splunk RUM, Splunk Synthetic Monitoring, Splunk Log Observer, Splunk IT Service Intelligence and Splunk On-Call.

Splunk announced the following new features to its unified security and observability platform:

- Splunk Log Observer Connect allows customers to visualize all their data in one place by combining the power of Splunk Cloud Platform, Splunk Enterprise and Splunk Observability Cloud, enabling site reliability engineers and DevOps engineers to access their metrics, traces, and Splunk Cloud or Splunk Enterprise logs in a single interface for faster, in-context debugging.

- Splunk Incident Intelligence, now in preview, helps DevOps teams investigate incidents and take action to ensure better system resilience by providing event correlation, incident response and on-call routing, collaboration, and automation - all within a unified workflow.

The Splunk Observability Cloud is optimized and designed to consume and manage OpenTelemetry data at scale enabling customers to unlock their data through open source standards. Splunk Observability Cloud is OpenTelemetry-native allowing customers to unify data ingestion without vendor lock-in and reduce resource consumption with the lightweight, open-source OpenTelemetry instrumentation.

As data volume and organizational complexities increase, Splunk wants to keep pricing simple and this bundle is designed to do that. With the Splunk Observability Cloud, Splunk is integrating these capabilities under one clear host-based pricing metric directly tied to the value DevOps, IT Operations and software development teams may gain.

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Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

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New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

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Splunk Observability Cloud Available on AWS in Australia and New Zealand

Splunk announced Splunk Observability Cloud is now available in Australia and New Zealand (ANZ) via the Amazon Web Services (AWS) Asia Pacific (Sydney) Region.

With the Splunk Observability Cloud, DevOps, IT Operations and software development teams can answer any question about the performance and health of their applications, services and infrastructure with metrics, traces and logs - all data collected in real time, without sampling and at any scale. By providing services on AWS in ANZ, enterprises now have options to retain data closer to home with low latency, which is an important requirement for observability. This also helps Australian organizations meet compliance requirements associated with data residency.

“... Splunk Observability Cloud provides DevOps, IT Operations and software development teams with all the capabilities they need for observability in one integrated interface, enabling organizations to monitor and analyse their applications and infrastructure in real time." said Mark Troselj, Group VP of Australia and New Zealand, Splunk.

“AWS supports hundreds of thousands of organisations across Australia and New Zealand to continuously innovate, succeed, and grow globally,” said Sumal Karunanayake, Head of Partner Success, Amazon Web Services, Australia and New Zealand. “With Splunk Observability Cloud on AWS, local enterprises who are increasingly focused on user experience, app modernisation, and innovation, can quickly gain visibility of their technology infrastructure and IT applications, and accelerate improvements that support digital transformation – all with the data staying local
to Australia and New Zealand.”

The Splunk Observability Cloud brings together the world’s best-in-class solutions for infrastructure monitoring, application performance monitoring, real user monitoring, synthetic monitoring, log investigation and incident response. Backed by Splunk’s NoSample full-fidelity data ingestion, real-time streaming analytics and massive scalability, Splunk Observability Cloud delivers unprecedented capabilities for monitoring, troubleshooting and resolution of business-critical incidents. The full observability portfolio from Splunk includes Splunk Infrastructure Monitoring, Splunk APM, Splunk RUM, Splunk Synthetic Monitoring, Splunk Log Observer, Splunk IT Service Intelligence and Splunk On-Call.

Splunk announced the following new features to its unified security and observability platform:

- Splunk Log Observer Connect allows customers to visualize all their data in one place by combining the power of Splunk Cloud Platform, Splunk Enterprise and Splunk Observability Cloud, enabling site reliability engineers and DevOps engineers to access their metrics, traces, and Splunk Cloud or Splunk Enterprise logs in a single interface for faster, in-context debugging.

- Splunk Incident Intelligence, now in preview, helps DevOps teams investigate incidents and take action to ensure better system resilience by providing event correlation, incident response and on-call routing, collaboration, and automation - all within a unified workflow.

The Splunk Observability Cloud is optimized and designed to consume and manage OpenTelemetry data at scale enabling customers to unlock their data through open source standards. Splunk Observability Cloud is OpenTelemetry-native allowing customers to unify data ingestion without vendor lock-in and reduce resource consumption with the lightweight, open-source OpenTelemetry instrumentation.

As data volume and organizational complexities increase, Splunk wants to keep pricing simple and this bundle is designed to do that. With the Splunk Observability Cloud, Splunk is integrating these capabilities under one clear host-based pricing metric directly tied to the value DevOps, IT Operations and software development teams may gain.

The Latest

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...