azure_event_hubs

Azure Event Hubs

Azure Event Hubs, introduced in 2014, is a big data streaming platform and event ingestion service. It provides reliable data capture from multiple sources and integrates seamlessly with databases and analytics services like Azure Cosmos DB and Azure Synapse Analytics.

https://learn.microsoft.com/en-us/azure/event-hubs

TLDR: Azure Event Hubs, introduced in 2014, is a scalable event streaming platform and data ingestion service designed to handle millions of events per second. It enables real-time data collection, processing, and analytics from various sources such as IoT devices, applications, and cloud services.

https://learn.microsoft.com/en-us/azure/event-hubs/event-hubs-overview

Azure Event Hubs supports the ingestion of both structured and unstructured data, making it versatile for a range of use cases, including log analytics, telemetry data streaming, financial transaction tracking, and clickstream analysis. Its flexible architecture allows seamless integration with downstream data storage and Big Data Analytics systems.

https://learn.microsoft.com/en-us/azure/event-hubs/event-hubs-about

The platform uses a partitioned consumer model to enable horizontal scaling and high availability. Partitions allow parallel processing of data streams, ensuring that large volumes of data can be ingested and processed without bottlenecks or performance degradation.

https://learn.microsoft.com/en-us/azure/event-hubs/event-hubs-features

Azure Event Hubs integrates seamlessly with popular processing frameworks such as Apache Spark, Apache Flink, and Azure Stream Analytics, enabling real-time data processing and Data Visualization. These integrations make it a critical component of modern Big Data pipelines.

https://learn.microsoft.com/en-us/azure/event-hubs/event-hubs-stream-analytics-integration

The service supports a range of data ingestion protocols, including AMQP, Kafka Protocol, and REST APIs. This flexibility ensures compatibility with existing systems and simplifies integration into diverse architectures, especially those involving NoSQL Databases and data pipelines.

https://learn.microsoft.com/en-us/azure/event-hubs/event-hubs-kafka-protocol-overview

Security is a core feature of Azure Event Hubs, offering encryption in transit and at rest, role-based access control via Azure Active Directory, and network-level security using private endpoints and virtual networks.

https://learn.microsoft.com/en-us/azure/event-hubs/event-hubs-security-features

The service provides reliable data retention capabilities, allowing event streams to be stored for up to 90 days. This ensures that consumers can replay events or perform batch analytics on historical data without impacting the system's performance, supporting applications in Time Series Analysis and Anomaly Detection.

https://learn.microsoft.com/en-us/azure/event-hubs/event-hubs-retention-policy

Azure Event Hubs supports auto-scaling, enabling the system to dynamically adjust throughput units based on data volume. This ensures cost efficiency while maintaining optimal performance during peak loads, especially in high-demand Data Engineering workflows.

https://learn.microsoft.com/en-us/azure/event-hubs/event-hubs-scalability

Monitoring and diagnostics are simplified with tools like Azure Monitor and Log Analytics, which provide metrics and logs to track event ingestion, processing, and throughput. These insights help optimize the pipeline and ensure reliability, making it suitable for Model Monitoring and other MLOps (Machine Learning Operations) tasks.

https://learn.microsoft.com/en-us/azure/event-hubs/event-hubs-metrics-available

Widely adopted across industries, Azure Event Hubs is a powerful solution for real-time data ingestion and processing. It empowers organizations to build robust data pipelines for analytics, decision-making, and insights generation in fields like e-commerce, healthcare, and Artificial Intelligence (AI).

https://learn.microsoft.com/en-us/azure/event-hubs/event-hubs-overview

azure_event_hubs.txt · Last modified: 2025/02/01 07:16 by 127.0.0.1

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