- Applications workloads are unpredictable
- Overestimate => Pay for unnecessary compute resources
- Underestimate => Poor user experience
- Ideally => Use extra instance only when it's needed and shut down when it's not.
- 📝 Four common computing patterns you'll see for web applications in cloud
- On and Off
- |||||....|||||......
- E.g.: batch processing.
- Growing fast
- |.||.|||.||||.|||||.||||||
- Often growing start-ups.
- Unpredictable bursting
- |..|..|||||||||..|.|
- Predictable bursting
- |.|.||||.|.|.||||.|.|
- E.g. during black friday for a e-commerce site.
- On and Off
- Distribute applications across multiple instances to provide redundancy + performance.
- A load balancer is needed to distribute.
- Primary advantage of the cloud is elastic scaling.
- Ability to use as much capacity as you need, scale out if load increases, scale in when the extra capacity is not needed.
- Supported in many Azure Services
- IaaS: Azure Virtual Machine Scale Sets (identical VMs in same set)
- PaaS: Azure App Service
- Or event database services such as Cosmos DB
- Auto-scale metrics
- Supported in all pricing plans of App Service.
- Autoscale can be triggered based on metrics or at scheduled date and time.
- Metrics are aggregated over all instances of the plan
- E.g.
CpuPercentage,MemoryPercentage,BytesRecieved,BytesSent,HttpQueueLength,DiskQueueLength(read+writes queued on storage)
- ❗ Basic plan does not include AutoScaling