Azure Event Hubs

Observability for Event Stream Processing with Azure Functions, Event Hubs, and Application Insights

May 13, 2021 May 13, 2021 05/13/21

Shervyna Ruan

With distributed tracing handled by Azure Functions, Azure Event Hubs, and Azure Application Insights behind the scenes, Azure Application Insights provides useful monitoring visualizations of the system that helped us easily understand system performances and troubleshoot failures.

Social Stream Pipeline on Databricks with auto-scaling and CI/CD using Travis

December 12, 2018 Dec 12, 2018 12/12/18

Mor Shemesh

This code story describes CSE's work with ZenCity to create a data pipeline on Azure Databricks supported by a CI/CD pipeline on TravisCI. The aim of the collaboration was to create a pipeline capable of processing a stream of social posts, analyzing them, and identifying trends.

Azure Event Hub Ingestion at Scale with Python and Kubernetes

January 24, 2018 Jan 24, 2018 01/24/18

Tomer Rosenthal

We created a solution to ingest Azure Event Hubs events at scale using Python and Kubernetes.

Working with Spatial Data in Table Storage

November 2, 2015 Nov 2, 2015 11/2/15

Beat Schwegler

Implementing spatial capabilities by mapping entities to unique grid numbers in large-scale cloud-based table storage, like Microsoft Azure Table Storage.

Real-time Maps with Event Hubs and SignalR Using Leaflet

August 26, 2015 Aug 26, 2015 08/26/15

Michael Lanzetta

Building a website map to visualize real-time geographic data from mobile apps with Event Hubs and SignalR using Leaflet.

Processing Time Series Data with HDInsight Storm

July 21, 2015 Jul 21, 2015 07/21/15

Tim Park

At Microsoft, we are working with a number of car manufacturers on processing telemetry streams. One of the key business scenarios for the incoming real-time car telemetry is to offer real-time driver risk scoring for end user driving guidance applications, fleet administration, and usage-based insurance scenarios.

CSE Developer Blog

Azure Event Hubs - CSE Developer Blog

Observability for Event Stream Processing with Azure Functions, Event Hubs, and Application Insights

Social Stream Pipeline on Databricks with auto-scaling and CI/CD using Travis

Azure Event Hub Ingestion at Scale with Python and Kubernetes

Working with Spatial Data in Table Storage

Real-time Maps with Event Hubs and SignalR Using Leaflet

Processing Time Series Data with HDInsight Storm

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