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Honeycomb Launches New Private Cloud Offering

Honeycomb announced a series of new product advancements: Honeycomb Private Cloud, Honeycomb Metrics, and Canvas, a part of Honeycomb Intelligence.

Together, these new capabilities bolster Honeycomb's enterprise portfolio, combining security, performance, and agentic experiences to help organizations deliver resilient software at scale.

With Honeycomb Private Cloud, organizations get a dedicated AWS infrastructure built to meet stringent security, data residency, and regulatory requirements—all without sacrificing performance or developer experience. By providing complete management over data and environment isolation, this offering is especially well-suited for customers in highly regulated industries like finance and healthcare, who need to confidently access the lighting-fast query performance and intuitive workflows that define Honeycomb's platform.

Customers are able to select self-managed or Honeycomb-managed options. Additionally, this new Bring Your Own Cloud (BYOC) option offers a cost-effective solution for organizations that want to keep their data in their own cloud accounts and control costs over time using their existing AWS discounts.

With the introduction of overhauled and improved Metrics, Honeycomb is expanding its observability platform to include native support for standard OpenTelemetry metrics. This builds on Honeycomb's longstanding support for custom metrics through events, giving teams a unified way to explore both high-level signals and detailed event data in one place.

With Metrics, users can now bring in gauges, counters, and histograms to track trends, monitor system health, and detect performance changes over time. All of this happens within the same intuitive Honeycomb experience. Unlike traditional monitoring tools that separate system data from application behavior, Honeycomb's unified model allows engineers to seamlessly connect what is happening in their infrastructure to why it is happening in their applications.

This new capability gives teams faster insights, deeper context, and a clearer path from detection to resolution, making it easier than ever to understand how their systems and users interact.

"Full time-series metrics are the industry standard for most developers and site reliability engineers," said Graham Siener, VP of Product at Honeycomb. "Our new Metrics capabilities meet customers where they are, combining open-standard metrics methodologies with our industry-leading tracing data to better determine the context around critical issues. The Honeycomb Intelligence platform, which includes our improved Metrics, is purpose-built for teams of every size and provides a platform for success that organizations can use to navigate their AI journey."

Also launching for General Availability is Canvas, Honeycomb's AI-guided dashboard that blends natural language investigation with interactive notebooks for collaborative debugging.

With Canvas, engineers can ask questions in plain English and watch as Honeycomb autonomously explores telemetry data, surfaces anomalies, and visualizes findings in real time. Canvas runs multiple queries, comparisons, and BubbleUp analyses automatically, producing dynamic charts and trace visualizations that evolve as the investigation progresses.

As part of Honeycomb Intelligence, Canvas works with MCP Server and Anomaly Detection, bringing AI-driven investigation directly into the developer workflow rather than bolting it on as an afterthought. With these new offerings, Honeycomb further extends its leadership in helping enterprises achieve faster resolution, tighter control, and deeper understanding across distributed systems.

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Honeycomb Launches New Private Cloud Offering

Honeycomb announced a series of new product advancements: Honeycomb Private Cloud, Honeycomb Metrics, and Canvas, a part of Honeycomb Intelligence.

Together, these new capabilities bolster Honeycomb's enterprise portfolio, combining security, performance, and agentic experiences to help organizations deliver resilient software at scale.

With Honeycomb Private Cloud, organizations get a dedicated AWS infrastructure built to meet stringent security, data residency, and regulatory requirements—all without sacrificing performance or developer experience. By providing complete management over data and environment isolation, this offering is especially well-suited for customers in highly regulated industries like finance and healthcare, who need to confidently access the lighting-fast query performance and intuitive workflows that define Honeycomb's platform.

Customers are able to select self-managed or Honeycomb-managed options. Additionally, this new Bring Your Own Cloud (BYOC) option offers a cost-effective solution for organizations that want to keep their data in their own cloud accounts and control costs over time using their existing AWS discounts.

With the introduction of overhauled and improved Metrics, Honeycomb is expanding its observability platform to include native support for standard OpenTelemetry metrics. This builds on Honeycomb's longstanding support for custom metrics through events, giving teams a unified way to explore both high-level signals and detailed event data in one place.

With Metrics, users can now bring in gauges, counters, and histograms to track trends, monitor system health, and detect performance changes over time. All of this happens within the same intuitive Honeycomb experience. Unlike traditional monitoring tools that separate system data from application behavior, Honeycomb's unified model allows engineers to seamlessly connect what is happening in their infrastructure to why it is happening in their applications.

This new capability gives teams faster insights, deeper context, and a clearer path from detection to resolution, making it easier than ever to understand how their systems and users interact.

"Full time-series metrics are the industry standard for most developers and site reliability engineers," said Graham Siener, VP of Product at Honeycomb. "Our new Metrics capabilities meet customers where they are, combining open-standard metrics methodologies with our industry-leading tracing data to better determine the context around critical issues. The Honeycomb Intelligence platform, which includes our improved Metrics, is purpose-built for teams of every size and provides a platform for success that organizations can use to navigate their AI journey."

Also launching for General Availability is Canvas, Honeycomb's AI-guided dashboard that blends natural language investigation with interactive notebooks for collaborative debugging.

With Canvas, engineers can ask questions in plain English and watch as Honeycomb autonomously explores telemetry data, surfaces anomalies, and visualizes findings in real time. Canvas runs multiple queries, comparisons, and BubbleUp analyses automatically, producing dynamic charts and trace visualizations that evolve as the investigation progresses.

As part of Honeycomb Intelligence, Canvas works with MCP Server and Anomaly Detection, bringing AI-driven investigation directly into the developer workflow rather than bolting it on as an afterthought. With these new offerings, Honeycomb further extends its leadership in helping enterprises achieve faster resolution, tighter control, and deeper understanding across distributed systems.

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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 ...

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 ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...