Operations | Monitoring | ITSM | DevOps | Cloud

The countdown to is on and we’re giving you an exclusive first look at the expert insights, innovative solutions, and success stories you’ll see on the big stage. Join us as we chat with Chris McNab, Founder of AlphaSOC, a security startup that processes network telemetry to uncover infected hosts, emerging threats, and targeted attacks.

When enterprises run dozens of monitoring and observability tools, performance gaps almost always emerge. By applying the BigPanda Observability Scorecard, our customers consistently see their tool portfolio fall into three groups: In some cases, removing bottom-tier tools can reduce portfolio complexity by double digits while cutting operational noise by as much as 35-40%. This simplification reduces costs while creating a leaner, more reliable monitoring environment that strengthens service availability and operational efficiency.

Choosing the right observability tools is critical so ensure your teams get actionable insights. In this video, we explore how to evaluate observability platforms based on their ability to detect anomalies, link causes, and trigger effective responses.

Uptrace is your single source of truth for monitoring, understanding, and optimizing complex distributed systems. Proven in production for over five years and trusted by more than a thousand installations worldwide, it lets you see your system like never before. What makes the difference is that Uptrace is pure OpenTelemetry, built natively from day one. This isn't a translation layer—it's a direct connection that eliminates friction and ensures zero vendor lock-in. Your homepage serves as your command center, providing complete visibility across your stack at a glance.

In this video, you’ll learn how to scrape Prometheus endpoints with the OpenTelemetry Collector’s Prometheus receiver and send metrics to Splunk Observability Cloud. We’ll walk through configuring three common data sources (a Python Flask app, node_exporter for host metrics, and the NGINX Prometheus exporter), show how to enrich metrics with resource attributes, and build simple charts in Splunk Observability Cloud. You’ll see how centralized scraping and consistent tagging make it easy to manage and visualize Prometheus metrics in Splunk Observability Cloud.

You can give AI agents everywhere fingers & eyes into your tool or service, by implementing an MCP (Model Context Protocol) server. It’s a great idea! It’s also a new kind of design and engineering. Jessica describes how it’s different from implementing an API or a GUI, and why it’s more exciting than either.

Manual hunts for sensitive data are slow, error-prone, and expensive. Cribl Guard combines advanced AI with a human-in-the-loop control point to spot sensitive data, such as credit card, passport, and Social Security numbers, as it flows through Cribl Stream. Whether you’re fully cloud or hybrid, Cribl Guard puts you firmly in control of every piece of sensitive information that crosses your pipes.

LLM observability is broken There are too many new libraries floating around, but they don't follow accurately the OpenTelemetry conventions. OTel isn’t perfect for LLMs yet—but extending a proven standard beats inventing another one. Why not use the same standard (OTel) which works so well for rest of the apps, and just work on top of it? This is what I was ranting with Pranav Raj S, co-founder at Chatwoot and we thought there must be other folks facing similar issues.

Uptrace is your single source of truth for monitoring, understanding, and optimizing complex distributed systems. Proven in production for over five years and trusted by more than a thousand installations worldwide, it lets you see your system like never before. What makes the difference is that Uptrace is pure OpenTelemetry, built natively from day one. This isn't a translation layer—it's a direct connection that eliminates friction and ensures zero vendor lock-in. Your homepage serves as your command center, providing complete visibility across your stack at a glance.

Watch how AI is reshaping observability for the years ahead. In this fireside chat, Logz.io founders Tomer Levy and Asaf Yigal reveal how the most innovative AI-first companies are breaking free from dashboards, avoiding common RFP mistakes, and building future-ready stacks. You’ll see: Watch and learn how autonomous AI eliminates noise, slashes costs, and gives engineering teams back their velocity.

In this video, we discuss handling both old and new systems in IT environments. From legacy SNMP setups to modern telemetry, most organizations juggle multiple data sources, which can make observability feel overwhelming. We explore how to combine logs, metrics, and flow data into one system that provides actionable insights. You’ll see practical examples of simplifying scattered tools and making sense of complex, disparate information. Understanding how these different types of data work together is key to getting observability right.

Did you miss Honeycomb's Observability Day San Francisco? Here are some highlights of the day.

Valkey OSS Developer Advocate Roberto Luna Rojas shares why open source matters to him - and the world.

Canvas is an AI-guided workspace inside Honeycomb that combines an AI assistant with an interactive notebook for visualizing query results and traces. You can ask a natural language question about your data and Canvas will immediately start exploring your traces, through multiple queries and other tools, to find the right next steps. Instead of having to write each query yourself, Canvas automatically proposes relational queries, comparisons, and visualizations that explain why an SLO fired or what changed after a deploy.

In this episode of Pastries with SREs, we dig into Limitless Observability with a sweet side of unified observability strategy. If you're tired of siloed tools, fractured data, and swivel-chair investigations, this one’s for you. We explore: Why are silos still the norm in modern observability? What’s the true cost of inefficiencies across logs, metrics, and traces? How can SREs, IT operations, and dev teams shift to a no-compromise, unified observability model?

Modern teams face a persistent challenge: knowing when something goes wrong before their customers do. With architectures sprawling across dozens or hundreds of services, creating comprehensive alerting becomes an overwhelming task. You're left playing whack-a-mole with manual alert configurations, often missing critical issues or drowning in false positives. Today, we're excited to announce our solution to this challenge: Anomaly Detection (currently in alpha), Honeycomb's proactive approach to understanding and acting on service health.

In the months since we launched our public beta, we’ve been hard at work making Honeycomb MCP more useful and capable for agents and human operators alike. Our goal with this project has been, from the start, to allow AI to engage in the same kind of investigatory loops that we guide users towards. Many of the new features are designed expressly with this in mind, the most exciting of which is BubbleUp, now available in.

Did you know you can define a calculated field in your Honeycomb queries? You can, and with the power of Honeycomb AI you can ask it to write the calculated field definition for you. Find out how in this short video.

Join Dell Technologies, TekStream Solutions, and Grafana Labs for a candid panel on scalining observability. Learn how enterprise teams scale observability, balance centralized vs. decentralized models, and accelerate adoption. The panel explores challenges with culture, governance, tool sprawl, and how AI is reshaping monitoring and incident response.

In Grafana’s 3rd annual Observability Survey, over 1,000 engineers and leaders shared their challenges — tool sprawl, complexity, rising costs, and nonstop alerts — and their hopes for how AI can help.

#shorts #cloudcomputing #aws #costoptimization #kubernetes

From AWS to Zendesk, and across all teams, Ove at CLAAS explains a variety of approaches that go beyond traditional app monitoring. By focusing on the data itself, one can deliver deeper insights and a fuller understanding of your entire system.

Technology moves quickly and while the spotlight has shifted to dynamic, cloud-based systems, many organizations have legacy applications and infrastructure that they must maintain. In this fireside chat, Datadog’s Matt Moore (Principal Observability Strategist) will host James Flores (Enterprise Systems Engineer) at Australian Community Media to discuss their journey of modernization and bridging legacy systems with the cloud using a bit of ingenuity and observability.

Valkey OSS Developer Advocate Roberto Luna Rojas explains what a Vector is, how Valkey (and Vector) search works, and gives us an example using an interesting combination of music tastes.