> For the complete documentation index, see [llms.txt](https://rcofinance.gitbook.io/whitepaper/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://rcofinance.gitbook.io/whitepaper/ai-powered-robo-advisor/real-time-data-infrastructure-and-processing.md). # Real-Time Data Infrastructure and Processing ### Real-Time Data Infrastructure and Processing #### Kafka-Based Streaming Architecture Our real-time data processing infrastructure handles massive volumes of market data with enterprise-grade reliability and performance. **Three-Broker Kafka Cluster:** * **High Availability**: Redundant brokers ensure no data loss during hardware failures * **Scalability**: Can process millions of messages per second with linear scaling * **Fault Tolerance**: Automatic failover and data replication across brokers * **Low Latency**: Sub-millisecond message processing for time-sensitive trading data **Data Stream Management:** * **Market Data Feeds**: Real-time price, volume, and order book data from multiple exchanges * **News Feeds**: Instant processing of breaking news and market announcements * **Social Media Streams**: Real-time sentiment data from social media platforms * **Economic Data**: Immediate processing of economic indicators and central bank announcements --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://rcofinance.gitbook.io/whitepaper/ai-powered-robo-advisor/real-time-data-infrastructure-and-processing.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.