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Observe Releases Kubernetes Explorer

Observe announced the launch of Kubernetes Explorer, a new addition to its observability platform designed to simplify visualizing and troubleshooting for cloud-native environments.

Kubernetes Explorer enables DevOps teams, Site Reliability Engineers (SREs) and software engineers to easily understand disparate Kubernetes components, detect issues quickly, uncover root causes and resolve them faster than ever before.

Observe unifyies fragmented data across metrics, traces, and logs, providing insights that span applications, the Kubernetes platform, and cloud-native infrastructure.

"Kubernetes Explorer represents a leap forward in observability for cloud-native environments," said Jeremy Burton, CEO of Observe. "By leveraging Kubernetes Explorer and AI capabilities, we're enabling teams to cut through the complexity of Kubernetes and quickly pinpoint and resolve issues that would otherwise take much longer to troubleshoot."

Observe's AI Investigator tightly integrates with Kubernetes Explorer to create custom, incident-specific visualizations and suggestions, providing on-call engineers with an expert Kubernetes assistant while troubleshooting. Observe launched its new AI Investigator – based on an agentic AI approach – last month as part of its most significant product update to date, along with $145 million in Series B funding.

Additional Kubernetes Explorer features include:

- Kubernetes Hindsight: Provides historical visibility so teams can do retrospective analysis and performance optimization in ephemeral container environments.

- Cluster Optimization: Offers a visual map of workload distribution across the Kubernetes cluster, enabling quick identification of underutilized capacity and optimization of resources. This capability is crucial as the latest CNCF cloud-native FinOps survey found half of organizations overspend on Kubernetes infrastructure, primarily due to over-provisioning.

- Resource Descriptors: Delivers comprehensive visibility into full YAML configurations of Kubernetes resources, maintaining deployment descriptor history for easy version comparison.

Kubernetes Explorer is available to all Observe customers at no additional cost, reinforcing the company's commitment to providing comprehensive observability solutions without hidden fees.

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Observe Releases Kubernetes Explorer

Observe announced the launch of Kubernetes Explorer, a new addition to its observability platform designed to simplify visualizing and troubleshooting for cloud-native environments.

Kubernetes Explorer enables DevOps teams, Site Reliability Engineers (SREs) and software engineers to easily understand disparate Kubernetes components, detect issues quickly, uncover root causes and resolve them faster than ever before.

Observe unifyies fragmented data across metrics, traces, and logs, providing insights that span applications, the Kubernetes platform, and cloud-native infrastructure.

"Kubernetes Explorer represents a leap forward in observability for cloud-native environments," said Jeremy Burton, CEO of Observe. "By leveraging Kubernetes Explorer and AI capabilities, we're enabling teams to cut through the complexity of Kubernetes and quickly pinpoint and resolve issues that would otherwise take much longer to troubleshoot."

Observe's AI Investigator tightly integrates with Kubernetes Explorer to create custom, incident-specific visualizations and suggestions, providing on-call engineers with an expert Kubernetes assistant while troubleshooting. Observe launched its new AI Investigator – based on an agentic AI approach – last month as part of its most significant product update to date, along with $145 million in Series B funding.

Additional Kubernetes Explorer features include:

- Kubernetes Hindsight: Provides historical visibility so teams can do retrospective analysis and performance optimization in ephemeral container environments.

- Cluster Optimization: Offers a visual map of workload distribution across the Kubernetes cluster, enabling quick identification of underutilized capacity and optimization of resources. This capability is crucial as the latest CNCF cloud-native FinOps survey found half of organizations overspend on Kubernetes infrastructure, primarily due to over-provisioning.

- Resource Descriptors: Delivers comprehensive visibility into full YAML configurations of Kubernetes resources, maintaining deployment descriptor history for easy version comparison.

Kubernetes Explorer is available to all Observe customers at no additional cost, reinforcing the company's commitment to providing comprehensive observability solutions without hidden fees.

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For years, infrastructure teams have treated compute as a relatively stable input. Capacity was provisioned, costs were forecasted, and performance expectations were set based on the assumption that identical resources behaved identically. That mental model is starting to break down. AI infrastructure is no longer behaving like static cloud capacity. It is increasingly behaving like a market ...

Resilience can no longer be defined by how quickly an organization recovers from an incident or disruption. The effectiveness of any resilience strategy is dependent on its ability to anticipate change, operate under continuous stress, and adapt confidently amid uncertainty ...

Mobile users are less tolerant of app instability than ever before. According to a new report from Luciq, No Margin for Error: What Mobile Users Expect and What Mobile Leaders Must Deliver in 2026, even minor performance issues now result in immediate abandonment, lost purchases, and long-term brand impact ...

Artificial intelligence (AI) has become the dominant force shaping enterprise data strategies. Boards expect progress. Executives expect returns. And data leaders are under pressure to prove that their organizations are "AI-ready" ...

Agentic AI is a major buzzword for 2026. Many tech companies are making bold promises about this technology, but many aren't grounded in reality, at least not yet. This coming year will likely be shaped by reality checks for IT teams, and progress will only come from a focus on strong foundations and disciplined execution ...

AI systems are still prone to hallucinations and misjudgments ... To build the trust needed for adoption, AI must be paired with human-in-the-loop (HITL) oversight, or checkpoints where humans verify, guide, and decide what actions are taken. The balance between autonomy and accountability is what will allow AI to deliver on its promise without sacrificing human trust ...

More data center leaders are reducing their reliance on utility grids by investing in onsite power for rapidly scaling data centers, according to the Data Center Power Report from Bloom Energy ...

In MEAN TIME TO INSIGHT Episode 21, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses AI-driven NetOps ... 

Enterprise IT has become increasingly complex and fragmented. Organizations are juggling dozens — sometimes hundreds — of different tools for endpoint management, security, app delivery, and employee experience. Each one needs its own license, its own maintenance, and its own integration. The result is a patchwork of overlapping tools, data stuck in silos, security vulnerabilities, and IT teams are spending more time managing software than actually getting work done ...

2025 was the year everybody finally saw the cracks in the foundation. If you were running production workloads, you probably lived through at least one outage you could not explain to your executives without pulling up a diagram and a whiteboard ...