Azure event grid

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This document discusses several Azure serverless services for building event-driven applications at massive scale including Event Hubs for high-volume data streams, Service Bus for critical workflows, Event Grid for business logic triggered by events, and IoT Hub. It highlights key capabilities like near real-time processing, high reliability, and massive throughput of these services.

Software

Event Hubs
• “Point in time” data
• Fast pull
• Replay / strict ordering
• Big data streams

Event Hubs
• “Point in time” data
• Fast pull
• Replay / strict ordering
• Big data streams
Service Bus
• Queue for critical items
• Routing
• Workflow
• Transactional

Event Hubs
• “Point in time” data
• Fast pull
• Replay / strict ordering
• Big data streams
Event Grid
• Business logic
• Push, not poll
• Handlers
• Ordering
Service Bus
• Queue for critical items
• Routing
• Workflow
• Transactional

IoT Hub
Blob Storage
Resource Groups
Azure Subscriptions
Event Hubs
Custom Topics
Storage (GPv2)
Azure Functions
Logic Apps
Azure Automation
WebHooks
Event Hubs

High reliabilityNear real-time Massive scale-out

Sub-second end-to-end latency in the 99th percentile
99.99% availability
10,000,000 events per second per region
100,000,000 subscriptions per region
50 ms publisher latency
24 hour retry with exponential back off for events not delivered
Transparent regional failover

 Events
 Event Publishers
 Topics
 Event Subscriptions
 Event Handlers

Storage (GPv2) Azure Functions
Logic Apps

Customer ApplicationCustom Topics
Customer Application

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The U.S. Geological Survey (USGS) has made substantial investments in meeting evolving scientific, technical, and policy driven demands on storing, managing, and delivering data. As these demands continue to grow in complexity and scale, the USGS must continue to explore innovative solutions to improve its management, curation, sharing, delivering, and preservation approaches for large-scale research data. Supporting these needs, the USGS has partnered with the University of Chicago-Globus to research and develop advanced repository components and workflows leveraging its current investment in Globus. The primary outcome of this partnership includes the development of a prototype enterprise repository, driven by USGS Data Release requirements, through exploration and implementation of the entire suite of the Globus platform offerings, including Globus Flow, Globus Auth, Globus Transfer, and Globus Search. This presentation will provide insights into this research partnership, introduce the unique requirements and challenges being addressed and provide relevant project progress.

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Exploring Innovations in Data Repository Solutions - Insights from the U.S. G...

Azure event grid

2. Azure Serverless application platform

5. https://www.reactivemanifesto.org/

8. Event Hubs • “Point in time” data • Fast pull • Replay / strict ordering • Big data streams

9. Event Hubs • “Point in time” data • Fast pull • Replay / strict ordering • Big data streams Service Bus • Queue for critical items • Routing • Workflow • Transactional

10. Event Hubs • “Point in time” data • Fast pull • Replay / strict ordering • Big data streams Event Grid • Business logic • Push, not poll • Handlers • Ordering Service Bus • Queue for critical items • Routing • Workflow • Transactional

11.

12. IoT Hub Blob Storage Resource Groups Azure Subscriptions Event Hubs Custom Topics Storage (GPv2) Azure Functions Logic Apps Azure Automation WebHooks Event Hubs

13.

14. High reliabilityNear real-time Massive scale-out

15. Sub-second end-to-end latency in the 99th percentile 99.99% availability 10,000,000 events per second per region 100,000,000 subscriptions per region 50 ms publisher latency 24 hour retry with exponential back off for events not delivered Transparent regional failover

16.  Events  Event Publishers  Topics  Event Subscriptions  Event Handlers

17. Storage (GPv2) Azure Functions

18. Storage (GPv2) Azure Functions Logic Apps

19. Customer ApplicationCustom Topics Customer Application

Azure event grid

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