Operations | Monitoring | ITSM | DevOps | Cloud

Join us to chat about the latest Cribl Packs release, how AI comes into play, and a demo to see it all in action.

Clint Sharp demonstrates how Cribl Search leverages AI to streamline incident investigation. Starting from a Slack channel, the AI builds an interactive notebook, analyzes order processing logs, and identifies suspicious traffic spikes. It connects high CPU usage to a recent Jenkins deployment, hypothesizing a supply chain attack, and ultimately recommends a rollback. This isn't a far off concept. It is the future of operations arriving right now.

Clint Sharp explains why a common model like OCSF is critical for the future of AI. Agents need standardized data to analyze information effectively on your behalf. He contrasts the traditional manual workflow of checking Slack, tickets, and wikis while asking colleagues with a future where AI fuses this human context with machine data. Instead of just search results, AI agents will hand you examined hypotheses so you know exactly where to take your investigation.

Clint Sharp explains why traditional schema-on-read systems cannot handle the query loads of the future. Agentic telemetry requires a 360-degree view, but structuring data only when you read it is too slow for AI-driven workloads. The solution is using LLMs to drive the cost of building parsers to near zero. Tools like Copilot Editor allow teams to map data to OCSF instantly, effectively building factories of parsers to handle the scale of agentic AI.

Cribl Notebooks aims to streamline the investigation process by bringing everything into a single interactive interface. It functions as a virtual war room where teams can collaborate in real time. You can view AI queries and code alongside charts without switching between scattered tabs or workstations. This persistence makes it easier to document the root cause and share the story behind the data.

Get visibility into your AWS WAF logs — without shipping data to a SIEM or building dashboards from scratch. In this video, we walk through the Cribl Search Pack for AWS WAF, letting you search and visualize WAF logs directly in Amazon S3 using search-in-place.

Chris Ebley from Blackwood explains why FedRAMP In Process is a major milestone. It gives federal teams confidence that the product can handle sensitive data, meets strict security controls, and comes from a company committed to operating at the maturity level the government expects. This opens new go to market opportunities and makes it easier for agencies to move forward with Cribl.

CMO Abby Strong explains how Cribl Lake is built for the real demands of modern AI. You get fast storage for high performance workloads and efficient architecture that scales without blowing up your budget. A smarter foundation for the AI era.

Clint Sharp breaks down the shift from traditional observability to AI ready telemetry. Agents need well formed fields, consistent schemas, and predictable data models. If your environment is full of unstructured logs, agents will give inconsistent answers. The work starts now so your AI future can actually deliver value later.

Clint Sharp explains why data is growing at a 30% CAGR while budgets stay flat. Teams are already running infrastructure at 80 to 90% capacity, and AI agents multiply query volume by ten or fifty. What got you to 2025 will not get you to 2035. You need a new approach to handle AI scale without blowing up cost.

Glenn Block explains how the new Cloudflare source and R2 destination in Cribl Stream lets you ingest WAF, DNS, and Zero Trust logs for full visibility and real time intelligence. Better security, better performance, and lower cost for modern IT and security teams.

Telemetry growth is about to hit a new level in 2026. Nick Heudecker from Cribl walks through our new predictions report and explains why observability costs are set to surge again, with more than a third of enterprises spending at least 15 % of their IT budgets on telemetry alone. He also shares how agentic AI adds new risk to the data pipeline, why most AI workloads will struggle to scale, and how platform shifts and market forces will reshape the data landscape.

Cribl Guard uses an always running AI agent to spot sensitive data as it moves through your environment and recommend the right protections in real time. In this demo, you will see how the agent samples live events, identifies patterns like credentials and credit cards, and turns them into one click fixes that keep your destinations safe. Faster detection, smarter rule recommendations, and instant mitigation. This is what modern data protection looks like.