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Serverless computing removes operational overhead: you write code and upload it to a platform (AWS Lambda, Google Cloud Functions, Azure Functions) without managing servers. The platform handles scaling automatically—one request or a million, the platform scales for you. You pay only for execution time, not idle capacity, making it cost-effective for variable workloads.
Serverless enables rapid development: focus on business logic without infrastructure concerns. Deployment is trivial: push code, it runs immediately. Scaling is automatic and instant. This makes serverless ideal for event-driven applications (process uploaded files, respond to API calls, react to database changes) and unpredictable workloads.
Serverless has limitations: execution time limits (typically 15-30 minutes), no direct file system access, cold starts (initial invocation is slow), and vendor lock-in. It's not ideal for long-running processes, complex state management, or applications requiring significant infrastructure customization. Hybrid approaches (some serverless, some traditional) are common.
Groovy Web uses serverless for event-driven AI workloads, such as processing documents or generating reports on-demand. Serverless is ideal for unpredictable AI inference workloads with cost-efficiency.
Our AI-First engineers build production systems using Serverless technology. Talk to us.
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