My $8,000 Serverless Mistake
summary
Background jobs move to Azure Functions using queues, hit memory limits, upgrade to EP2 (7 GB) and autoscale to 25 instances, and the month ends with roughly $8,000 of charges. The functions successfully clear the backlog but create unexpected database load and API rate‑limit failures. The hard specifics are what matters: consumption pricing plus unbounded scaling costs, memory/profile choices, instance limits, and mitigations like throttling, batching, sizing, or moving heavy work off serverless. Monitor budgets and cost analysis.
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chapters (12)
- 0:00Welcome
- 1:25Serverless golden solution
- 3:09Background jobs to Azure Functions
- 4:35Serverless architecture promise
- 6:01Hosting versus serverless costs
- 8:31Serverless triggers and actions
- 9:54Where serverless excels and where it fails
- 12:21Serverless scale limits
- 13:23High memory premium pricing
- 17:34Back pressure mistake
- 19:01Avoiding nail problem
- 19:44Key takeaways
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