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Cribl Stream is a vendor-agnostic observability pipeline that gives you the flexibility to collect, reduce, enrich, normalize, and route data from any source to any destination within your existing data infrastructure.
Vodafone Case Study
Vodafone Dials up Business Insights with Cribl Stream
Cribl Edge provides an intelligent, highly scalable edge-based data collection system for logs, metrics, and application data.
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Cribl Search turns the traditional search process on its head, allowing users to search data in place without having to collect/store first.
The Cribl.Cloud platform gets you up and running fast without the hassle of running infrastructure.
Cribl.Cloud Solution Brief
The fastest and easiest way to realize the value of an observability ecosystem.
AppScope gives operators the visibility they need into application behavior, metrics and events with no configuration and no agent required.
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Cribl Corporate Overview
Cribl makes open observability a reality, giving you the freedom and flexibility to make choices instead of compromises.
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How do you get the data out of your infrastructure and applications in order to properly observe, monitor, and secure their running states while minimizing overlap, wasted resources, and cost?
Many business folks need a broad category of tools in all their environments to solve challenges such as up and down monitoring, metrics, a time series database (TSDB), log analytics, event streaming, security information and event management (SIEM), user behavior analytics (UBA), and data lakes. The answer to the proposed question to solve these hurdles is using an observability pipeline.
This book introduces you to the concept of observability pipelines, which help slash costs, improve performance, and get the right data, to the right destinations, in the right formats, at the right time. Observability is the practice of interrogating your environment without knowing in advance the questions you need to ask. That means making choices and living with the consequences. These choices almost always present tradeoffs. More data means more money. Standardizing on one platform limits flexibility, and dropping data may limit what you can learn from your environment.
Peruse the chapters in this book to see how implementing an observability pipeline can keep you learning limitlessly from your environment.