Cribl, a San Francisco-based company, is focused on helping organizations gather and analyze their data for better observability in IT operations and security. The company’s core offering is its data engine platform, which includes products like Cribl Stream for routing and processing data streams, Cribl Search for querying large datasets without moving the data, Cribl Edge for lightweight data collection, and Cribl Lake for storing and managing data on Amazon S3.
According to Clint Sharp, Cribl’s CEO, the company has repositioned itself as the “data engine for IT and security” to reflect its evolution into a multi-product company. Cribl aims to make it easier for enterprises of all sizes to obtain, store, and analyze data, positioning itself as more than just an observability provider in the competitive data observability market.
While Cribl does not directly compete with large data platform vendors like Snowflake or Databricks, it focuses on enabling data for IT and security teams within enterprises. These teams often deal with loosely structured or unstructured log data, which other data platforms may not handle well. Cribl helps customers route heterogeneous data to destinations like Splunk or Elasticsearch and enables searching large datasets without moving them, making it suitable for security, observability, and analytics on messy technical data streams.
It’s important to note that Cribl is not a fully featured monitoring or observability solution. Instead, it helps organizations get their data into technologies like Splunk or Datadog for analysis. The company complements existing solutions in the space by facilitating data ingestion, processing, and management.
In its latest development, Cribl has introduced an AI copilot to assist its users. The AI copilot utilizes a Retrieval Augmented Generation (RAG) approach, combining a vector database with a large language model (LLM). This copilot allows users to interact with Cribl’s products using natural language, enabling tasks like generating data pipelines, searching logs, charting errors over time, and creating dashboards. The AI copilot underwent extensive development to ensure accuracy and meet the technical requirements of Cribl’s users.
Overall, Cribl’s data engine platform and AI copilot aim to empower organizations with the tools they need to efficiently manage and make sense of their data. By providing solutions for data routing, processing, storage, and analysis, Cribl enables IT and security teams to improve observability, streamline operations, and make data-driven decisions.