Introduction In the rapidly evolving landscape of cybersecurity, agentic AI telemetry emerges as a pivotal advancement, enabling organizations to harness AI agents for enhanced data processing and threat detection. This blog post delves into the insights from the CribbleCon Keynote titled “The Agentic AI Era,” where industry leaders from Cribble outlined their vision for an AI-first data engine. By integrating machine-generated and human-generated data, this approach provides semantic context essential for automated investigations, ensuring robust security and compliance in high-stakes environments. As data volumes explode due to AI workloads, legacy systems falter under the strain. Cribble’s suite—Stream, Edge, Lake, and Search—addresses these challenges, offering scalable solutions that prioritize human-in-the-loop oversight and predictable financial operations. This keynote highlights how agentic AI telemetry not only accelerates data handling but also fortifies cybersecurity postures against emerging threats. The Challenge of Exponential Data Growth in Cybersecurity Understanding the AI-Driven Data Surge The integration of AI agents into cybersecurity operations is transforming how organizations manage telemetry data. Traditional infrastructure, designed for keyword searches and human dashboards, is ill-equipped for the scale of agentic AI telemetry. Data growth rates, already at 30% compound annual growth pre-AI, are poised to accelerate dramatically as AI agents generate magnitudes more queries for troubleshooting and threat analysis. Leaders at Cribble emphasize that without intentional deployment, AI could lead to catastrophic errors, such as misclassifying sensitive data, resulting in audit failures or compliance breaches. For instance, in cybersecurity contexts, deploying AI without human validation risks exposing personally identifiable information (PII) or protected health information (PHI), violating standards like HIPAA or GDPR. Historical Parallels and the Need for New Infrastructure Drawing analogies to past technological shifts—like the PC revolution or mobile era—the keynote underscores that agentic AI telemetry represents an epochal change. Just as mobile infrastructure evolved to support real-time applications, cybersecurity telemetry must adapt to federated, open systems that access data across legacy databases, cloud warehouses, and data lakes without centralization. Cribble positions its data engine as the solution, built over seven years to handle this transition. This infrastructure ensures outcomes-focused operations, maximizing human productivity while mitigating risks associated with destructive AI decisions. Cribble’s AI-First Product Suite Stream and Edge: Optimizing Data in Motion Cribble Stream, a pioneering telemetry pipeline, decouples sources from destinations, allowing flexible routing, enrichment, and filtering of data. This is crucial for cybersecurity, where real-time data shaping prevents unauthorized access or leakage. Complementing Stream, Cribble Edge extends these capabilities to origination points, enabling edge processing to reduce central infrastructure loads. Features like centralized fleet management and version control ensure all agents remain updated—a common pain point in distributed cybersecurity environments. Recent enhancements include support for Windows 11, FIPS compliance, and Kubernetes explorer for deeper visibility. Lake and Lakehouse: Cost-Effective Storage and Analytics For data at rest, Cribble Lake offers inexpensive, secure storage with identity-based authorization, shifting from infrastructure-centric access controls. This aligns with cybersecurity best practices by enhancing data governance. The Lakehouse extension delivers sub-second queries over terabytes, separating storage and compute for scalability. In agentic AI telemetry scenarios, this high-performance layer supports rapid AI-driven analytics without escalating costs. Search: Federated Insights for Comprehensive Visibility Cribble Search provides a unified lens across disparate data stores, using familiar query interfaces like pipe-delimited syntax. This federation is vital for cybersecurity investigations, eliminating the need for users to navigate multiple tools. Integrated AI features, such as Copilot for generating queries in plain English, democratize access for novice and expert analysts alike. Search packs—bundles of pre-built knowledge—accelerate insights, while notebooks foster collaborative investigations in a virtual war room. AI Integration and Security Enhancements Co-Pilot Editor: Accelerating Configurations Launched earlier this year, the Co-Pilot Editor has seen rapid adoption, with hundreds of users creating thousands of pipelines weekly. It provides real-time feedback and human review, ensuring accuracy in data transformations critical for cybersecurity compliance. Cribble Guard: Real-Time Data Protection A standout innovation, Cribble Guard employs AI-powered rules to mask sensitive information like PII, PHI, and credentials in transit. With over 200 out-of-the-box rules and an agentic background detection system, it continuously scans for patterns, recommending refinements. In a live demonstration, Guard redacted emails and tokens in seconds, demonstrating its efficacy in preventing data breaches. This tool turns cybersecurity risks into resilience, supporting standards such as PCI and GDPR. Human-in-the-Loop Philosophy Cribble’s approach maintains human oversight in high-stakes decisions, avoiding autonomous errors. For investigations, AI assists by running multiple hypotheses, where error costs are minimal, enhancing efficiency without compromising security. Future Directions: Scaling for Agentic AI Upcoming Features and Integrations Cribble is expanding with Mac OS support for Edge, scaling to 500,000 nodes, and Outpost for restricted environments. Stream enhancements include optimized persistent queuing and integrations with Microsoft, Cloudflare, and others. Search will federate to additional platforms like Snowflake and Azure Data Explorer, improving performance to handle 10-100x query loads from AI agents. Monitoring and alerting will automate insights, reducing manual investigations. Cribble Cloud: Modern Architecture for Global Operations Cribble Cloud offers tiered storage, elastic resources, and distributed data planes, eliminating noisy neighbors and ensuring geographic flexibility. Features like Cribble as Code (via APIs, SDKs, and Terraform) enable programmatic deployments, while FinOps Center provides cost projections for predictable budgeting. Achieving FedRAMP in-process designation underscores its security rigor, complementing SOC 2, PCI, and HIPAA compliance. Notebooks: Collaborative Intelligence Notebooks transform investigations by integrating AI queries, code, charts, and context in real-time. A demonstration illustrated identifying credential theft from a malicious NPM package, summarizing findings for quick action. Preparing for the Agentic AI Era in Cybersecurity The fusion of machine and human data in agentic AI telemetry provides a 360-degree view, enabling automated root-cause analysis. Cribble’s open, federated platform differentiates it by supporting diverse agents while ensuring deterministic query translations for superior accuracy. As AI rewires workflows, organizations must adopt AI-first infrastructure to thrive. Resistance to this shift risks obsolescence, but intentional implementation—prioritizing security and human control—promises 10x productivity gains. For further reading on AI in cybersecurity, explore resources from authoritative sources such as the National Institute of Standards and Technology (NIST) on risk management frameworks and Gartner’s hype cycle for emerging technologies. This post, derived from the CribbleCon Keynote, illustrates how agentic AI telemetry is not a distant future but an immediate opportunity to bolster cybersecurity resilience. Key Takeaways Agentic AI telemetry revolutionizes cybersecurity by combining machine-generated and human-generated data for better threat detection. Cribble’s suite, including Stream, Edge, Lake, and Search, enhances data processing and simplifies real-time analytics for growing data volumes. The Co-Pilot Editor and Cribble Guard provide robust tools for data transformation and real-time protection against sensitive data breaches. The integration of AI with human oversight ensures accurate decision-making and compliance, preventing catastrophic errors in sensitive data management. Cribble’s open platform supports organizations in adapting to an AI-first infrastructure, promoting efficiency and security in cybersecurity operations. About SIEMtune Cribl Search Integration: Real-Time Insights with Cribl Edge Understanding Devo Gov Cloud Limitations Cribl Edge with Splunk: Integration Guide Cribl Edge Log Collection: Mastering File Monitor and Exec Sources The post Agentic AI Telemetry: Revolutionizing Data Infrastructure in the Cybersecurity Era appeared first on SIEMTune | SIEM Optimization & Cybersecurity Engineering for U.S. Enterprises.
