•  


GitHub - syedhassaanahmed/azure-event-driven-data-pipeline: Building event-driven data ingestion pipelines in Azure
Skip to content

syedhassaanahmed/azure-event-driven-data-pipeline

Repository files navigation

azure-event-driven-data-pipeline

Build Status

Problem

A large retailer with many source systems, wants a single source of truth of their data and be able to send updates to their consumers whenever this data is changed. They want to support an unpredictable load, with a max spike of 1500 req/sec.

Architecture

Deployment

Deploy to Azure

The entire deployment can be orchestrated using ARM template azuredeploy.json .

To deploy using Azure CLI ;

az group deployment create -g <RESOURCE_GROUP> --template-file azuredeploy.json

Once the deployment is complete, the only manual step is to copy ConsumerReceiveFunc URL from the Azure portal and paste it multiple times (pipe | delimited) in ConsumerEgressFunc -> App Settings -> CONSUMERS .

Running load tests

We perform the load tests using Azure Container Instances . After creating resources using the above ARM template, run the following load testing script;

./generate-load.sh <RESOURCE_GROUP> <CONTAINER_NAME> https://http-ingress-func.azurewebsites.net/api/HttpIngressFunc?code=<FUNCTION_KEY>

Here is how to stream logs from the container;

az container attach -g <RESOURCE_GROUP> -n <CONTAINER_NAME>

Measuring Cosmos DB RUs using Application Insights

When we upsert into Cosmos DB, we log the Request Units consumed in Application Insights . The following Kusto query renders a timechart of RUs consumed in the last 10 minutes, aggregated on 10 seconds.

customMetrics
| 
where
 timestamp
 >
 ago(10m)
    
and
 name 
==
 "
product_RU
"

| summarize 
avg
(value) by bin(
timestamp
, 10s)
| render timechart

Resources

Choose between Azure services that deliver messages

Choose between Flow, Logic Apps, Functions, and WebJobs

Durable Functions overview

Understanding Serverless Cold Start

Azure Function Apps: Performance Considerations

Processing 100,000 Events Per Second on Azure Functions

Choose the right data store

Modeling document data for NoSQL databases

A fast, serverless, big data pipeline powered by a single Azure Function

Load testing with Azure Container Instances and wrk

- "漢字路" 한글한자자동변환 서비스는 교육부 고전문헌국역지원사업의 지원으로 구축되었습니다.
- "漢字路" 한글한자자동변환 서비스는 전통문화연구회 "울산대학교한국어처리연구실 옥철영(IT융합전공)교수팀"에서 개발한 한글한자자동변환기를 바탕하여 지속적으로 공동 연구 개발하고 있는 서비스입니다.
- 현재 고유명사(인명, 지명등)을 비롯한 여러 변환오류가 있으며 이를 해결하고자 많은 연구 개발을 진행하고자 하고 있습니다. 이를 인지하시고 다른 곳에서 인용시 한자 변환 결과를 한번 더 검토하시고 사용해 주시기 바랍니다.
- 변환오류 및 건의,문의사항은 juntong@juntong.or.kr로 메일로 보내주시면 감사하겠습니다. .
Copyright ⓒ 2020 By '전통문화연구회(傳統文化硏究會)' All Rights reserved.
 한국   대만   중국   일본