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Splunk Announces Improved OpenTelemetry Experience

Splunk announced new innovations to deliver a seamless OpenTelemetry experience that offers organizations flexibility, customization, and freedom from vendor lock-in with no manual setup. 

With the introduction of these new capabilities, Splunk provides a more intuitive, simplified OpenTelemetry experience – ensuring organizations can seamlessly integrate open-source observability into their software delivery and build a leading observability practice.

Recognizing the great advantages of OpenTelemetry, Splunk made it the foundation of its Splunk Observability Cloud solution and continued to innovate to ensure organizations benefit from the framework's vendor-neutral telemetry with unmatched ease of use. These new solutions include Service Inventory, enhanced capabilities for Kubernetes troubleshooting, and expanded support for automatic setup of OpenTelemetry instrumentation for applications.

Service Inventory addresses the operational challenges of large-scale observability building on infrastructure inventory, automatic discovery and automatic configuration. This new capability:

  • Provides end-to-end visibility – Automatically detects all third-party applications, like databases and message queues.
  • Guides users through configuration – Provides step-by-step recommendations for seamless OpenTelemetry setup.
  • Identifies and resolves visibility gaps – Highlights missing instrumentation, allowing enterprises to proactively address blind spots across their infrastructure.  

"Splunk customers benefit from OpenTelemetry's full power, with a frictionless experience that ensures complete visibility, so they can attain flexibility and ownership of their data," said Morgan McLean, OpenTelemetry Co-founder and Senior Director of Product Management at Splunk, a Cisco company. "OpenTelemetry should be effortless to use, and Splunk is committed to making that a reality with the introduction of Service Inventory and expanded automation. These enhancements give customers the power to build a leading observability practice with the ability to instrument and monitor their environments without the complexity of manual configuration."

Splunk enhanced its Kubernetes monitoring and troubleshooting capabilities to further enrich visibility and empower teams to quickly detect and resolve issues within Kubernetes clusters, reducing downtime and improving performance.

Further strengthening Splunk's OpenTelemetry offering, the company is rolling out OpenTelemetry Python 2.0 and Node.js 3.0, delivering greater flexibility and improved performance for cloud-native applications.

"OpenTelemetry is rapidly becoming the industry standard for building an effective observability practice, but complex instrumentation remains a significant barrier. Splunk's latest innovations have the potential to make its adoption more seamless than ever," said Archana Venkatraman, Senior Research Director, Cloud Data Management, IDC Europe. "Cloud-native and Kubernetes strategies are becoming mainstream, requiring enterprise-grade management. Amid this, by automating instrumentation and deepening Kubernetes troubleshooting, Splunk continues to make OpenTelemetry a practical and powerful solution for digital enterprises."

As part of Cisco, Splunk continues to champion OpenTelemetry adoption. Cisco ThousandEyes and Splunk AppDynamics natively support OpenTelemetry, enabling a seamless observability experience across the entire IT stack. As the first assurance solution to support OpenTelemetry, Cisco ThousandEyes allows customers to infer correlations between digital experience health and observability metrics for end-to-end visibility that helps solve problems quicker, and get services restored and running faster. Splunk AppDynamics provides an OpenTelemetry-compatible backend to ingest trace data using OpenTelemetry components and leverages Splunk AppDynamics agents to produce OpenTelemetry data for easy consumption by Splunk Observability Cloud.

Service Inventory is available globally for all Splunk Observability Cloud customers.

Kubernetes troubleshooting enhancements and expanded OpenTelemetry language support are available globally.

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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 ...

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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 ...

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Splunk Announces Improved OpenTelemetry Experience

Splunk announced new innovations to deliver a seamless OpenTelemetry experience that offers organizations flexibility, customization, and freedom from vendor lock-in with no manual setup. 

With the introduction of these new capabilities, Splunk provides a more intuitive, simplified OpenTelemetry experience – ensuring organizations can seamlessly integrate open-source observability into their software delivery and build a leading observability practice.

Recognizing the great advantages of OpenTelemetry, Splunk made it the foundation of its Splunk Observability Cloud solution and continued to innovate to ensure organizations benefit from the framework's vendor-neutral telemetry with unmatched ease of use. These new solutions include Service Inventory, enhanced capabilities for Kubernetes troubleshooting, and expanded support for automatic setup of OpenTelemetry instrumentation for applications.

Service Inventory addresses the operational challenges of large-scale observability building on infrastructure inventory, automatic discovery and automatic configuration. This new capability:

  • Provides end-to-end visibility – Automatically detects all third-party applications, like databases and message queues.
  • Guides users through configuration – Provides step-by-step recommendations for seamless OpenTelemetry setup.
  • Identifies and resolves visibility gaps – Highlights missing instrumentation, allowing enterprises to proactively address blind spots across their infrastructure.  

"Splunk customers benefit from OpenTelemetry's full power, with a frictionless experience that ensures complete visibility, so they can attain flexibility and ownership of their data," said Morgan McLean, OpenTelemetry Co-founder and Senior Director of Product Management at Splunk, a Cisco company. "OpenTelemetry should be effortless to use, and Splunk is committed to making that a reality with the introduction of Service Inventory and expanded automation. These enhancements give customers the power to build a leading observability practice with the ability to instrument and monitor their environments without the complexity of manual configuration."

Splunk enhanced its Kubernetes monitoring and troubleshooting capabilities to further enrich visibility and empower teams to quickly detect and resolve issues within Kubernetes clusters, reducing downtime and improving performance.

Further strengthening Splunk's OpenTelemetry offering, the company is rolling out OpenTelemetry Python 2.0 and Node.js 3.0, delivering greater flexibility and improved performance for cloud-native applications.

"OpenTelemetry is rapidly becoming the industry standard for building an effective observability practice, but complex instrumentation remains a significant barrier. Splunk's latest innovations have the potential to make its adoption more seamless than ever," said Archana Venkatraman, Senior Research Director, Cloud Data Management, IDC Europe. "Cloud-native and Kubernetes strategies are becoming mainstream, requiring enterprise-grade management. Amid this, by automating instrumentation and deepening Kubernetes troubleshooting, Splunk continues to make OpenTelemetry a practical and powerful solution for digital enterprises."

As part of Cisco, Splunk continues to champion OpenTelemetry adoption. Cisco ThousandEyes and Splunk AppDynamics natively support OpenTelemetry, enabling a seamless observability experience across the entire IT stack. As the first assurance solution to support OpenTelemetry, Cisco ThousandEyes allows customers to infer correlations between digital experience health and observability metrics for end-to-end visibility that helps solve problems quicker, and get services restored and running faster. Splunk AppDynamics provides an OpenTelemetry-compatible backend to ingest trace data using OpenTelemetry components and leverages Splunk AppDynamics agents to produce OpenTelemetry data for easy consumption by Splunk Observability Cloud.

Service Inventory is available globally for all Splunk Observability Cloud customers.

Kubernetes troubleshooting enhancements and expanded OpenTelemetry language support are available globally.

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 ...