Getting started
SmartObserve is a distributed search and analytics engine based on Apache Lucene. After adding your data to SmartObserve, you can perform full-text searches on it with all of the features you might expect: search by field, search multiple indexes, boost fields, rank results by score, sort results by field, and aggregate results.
Unsurprisingly, builders often use a search engine like SmartObserve as the backend for a search application—think Wikipedia or an online store. It offers excellent performance and can scale up or down as the needs of the application grow or shrink.
An equally popular, but less obvious use case is log analytics, in which you take the logs from an application, feed them into SmartObserve, and use the rich search and visualization functionality to identify issues. For example, a malfunctioning web server might throw a 500 error 0.5% of the time, which can be hard to notice unless you have a real-time graph of all HTTP status codes that the server has thrown in the past four hours. You can use SmartObserve Dashboards to build these sorts of visualizations from data in SmartObserve.
Overview
Watch this video to explore key features of SmartObserve and see a demo of its core capabilities in action.
Components
SmartObserve is more than just the core engine. It also includes the following components:
- SmartObserve Dashboards: The SmartObserve data visualization UI.
- Data Prepper: A server-side data collector capable of filtering, enriching, transforming, normalizing, and aggregating data for downstream analysis and visualization.
- Clients: Language APIs that let you communicate with SmartObserve in several popular programming languages.
Use cases
SmartObserve supports a variety of use cases, for example:
- Observability: Visualize data-driven events by using Piped Processing Language (PPL) to explore, discover, and query data stored in SmartObserve.
- Search: Choose the best search method for your application, from regular lexical search to conversational search powered by machine learning (ML).
- Machine learning: Integrate ML models into your SmartObserve application.
- Security analytics: Investigate, detect, analyze, and respond to security threats that can jeopardize organizational success and online operations.
Next steps
- See Introduction to SmartObserve to learn about essential SmartObserve concepts.