- Lab
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Libraries: If you want this lab, consider one of these libraries.
Choose and Implement the Right Azure Compute Service
This challenge lab puts you in charge of a real deployment decision: three workloads at your company need to move to Azure. You will consider a legacy Windows dependency, a bursty IoT ingestion pipeline, and a low-maintenance internal dashboard, then deploy the right service for each one based on its actual constraints. Automated assertions check the final state of your environment against every requirement, so the lab isn't marked complete until your choices hold up.
Lab Info
Table of Contents
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Challenge
Select and deploy the compute service for the order-processing workload
Evaluate a workload with a legacy, OS-level dependency and deploy the Azure compute service that can support it without unnecessary overhead.
Deploy a Virtual machine named
vm-order-api, with asizeofStandard_B2s. -
Challenge
Select and deploy the compute service for the IoT telemetry workload
Evaluate a bursty, event-driven workload and deploy a compute service that can start quickly and run independently of the ingestion layer.
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Challenge
Select and deploy the compute service for the dashboard workload
Evaluate a low-traffic internal workload and deploy a compute service that avoids ongoing operating system maintenance.
Create an App Service Plan named
plan-dashboard. -
Challenge
Configure observability and document your architectural decisions
Configure monitoring across the deployed workloads and document the reasoning behind each compute service selection.
Create a Metric Alert named
dashboard-high-cpu.
Real skill practice before real-world application
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On average, you retain 75% more of your learning if you take time to practice. Hands-on labs set you up for success to make those skills stick.