What's New In Graylog V7.0
Check out the new exciting features added to Graylog V7.0 Seth Goldhammer VP of Product and Ed Metcalf VP of Product Marketing walk you through the new features!
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The latest News and Information on Log Management, Log Analytics and related technologies.
Graylog MCP Integration: Real-Time LLM Access to Your Data
Graylog V7.0 supports integration with the Model Context Protocol (MCP), which allows large language models (LLMs) to access and interact with Graylog data and workflows in real time. Graylog exposes an MCP-compatible endpoint for LLM clients, such as Claude and LM Studio. MCP integration allows Graylog users to interact with their data through LLMs. With MCP, an LLM can connect directly to Graylog as a remote tool interface, performing queries, retrieving system information, and assisting with common administrative or investigative tasks. This capability may make it possible to.
Introducing the Splunk Technology Add on for Ollama Illuminating Shadow AI Deployments
Without strong visibility and governance, local LLMs risk replicating the fragmented, unsupervised sprawl once seen in shadow IT, complicating security postures and making it difficult for organizations to ensure proper oversight and compliance as these powerful AI tools become embedded in daily workflows. To address this challenge, The Splunk Threat Research Team has released the Splunk Technology Add-on for Ollama that provides comprehensive monitoring and observability capabilities specifically designed for local LLM deployments.
MCP Explained: Conversational AI for Graylog
Model Context Protocol (MCP) gives large language models (LLMs) a secure way to interact with your Graylog data and workflows. Instead of writing complex queries, you can ask questions in plain English, such as: Analysts gain speed, administrators maintain control, and security stays intact.
Use Grok parsing to extract fields from logs | Datadog Tips & Tricks
When your logs don’t follow a standard format, it can be difficult to extract valuable information, like key-value pairs and nested JSON objects. Grok parsing lets you define flexible patterns that match unstructured log data so you can extract specific fields to query, filter, and visualize. In this video, you’ll learn how to: By refining your Grok parsers, you can make your logs more useful for analytics, dashboards, or alerts, and get even more value from your logs.
Pastries with SREs: No compromises on cost-effective observability or donuts.
In this episode of Pastries and SREs, we dig into how vendor lock-in and sky-high observability costs are forcing teams to choose between coverage and budget, AND why you shouldn’t have to settle. With donuts in hand, we explore how to take back control of your observability strategy by making it cost-effective, comprehensive, and flexible.
Investigating SIEM Incidents with Logz.io
A short demo showing how Logz.io, powered by the AI Agent, helps investigate security incidents by analyzing and correlating data. The AI Agent uses natural language to: Query and correlate SIEM questions with related logs Detect anomalies and highlight unusual activity Summarize findings to speed up root cause analysis Provide recommended actions This video demonstrates a practical SIEM use case for the AI Agent inside Logz.io.
Conquer Complexity, Accelerate Resolution with the AI Troubleshooting Agent in Splunk Observability Cloud
The digital landscape has transformed dramatically, and with it, the demands on our systems have grown exponentially. Traditional monitoring tools struggle to provide sufficient insight into complex, distributed, cloud-native environments. Observability is the answer, moving beyond merely knowing "what" is happening to understanding "why" it's happening, and its impact on user experience and business outcomes.
What is Active Telemetry
Active Telemetry is the evolution in how organizations collect, process, and use observability data. In traditional observability, telemetry is passive: systems emit logs, metrics, and traces that are stored and visualized after the fact. This model worked when systems were simpler and changes were predictable. But in today’s world with distributed microservices, Kubernetes, and AI workloads, passive telemetry can’t keep up. Active Telemetry changes that.
Using Sentry Logs to Debug a Dynamic Sampling Issue
Some of the team at Sentry spent this past quarter fixing bugs, more than 800 to be exact. Among them was a complex issue causing transaction spikes in our own Sentry project. Using Sentry Logs, we were able to investigate, trace the root cause, and resolve the problem.