Developers are responsible for provisioning and managing the infrastructure, including servers, databases, and networking.
Scaling involves adding more servers or resources to accommodate increased demand. This process can be time-consuming and may result in over-provisioning during periods of low traffic.
Traditional servers are designed for continuous uptime, requiring redundancy and failover mechanisms to ensure availability.
Managing servers and their configurations can be complex, especially in large-scale applications.
Developers focus solely on code, with cloud providers handling server provisioning, scaling, and maintenance.
Serverless platforms automatically scale resources up or down based on usage, ensuring optimal performance and cost-efficiency.
Serverless functions are triggered by events, such as HTTP requests, database changes, or messages, making them highly responsive to real-time demands.
With serverless, you pay only for the actual compute resources used, making it cost-effective for variable workloads.
Serverless can be more cost-effective for applications with varying workloads, as you only pay for the resources consumed during execution.
Serverless platforms automatically handle scaling, ensuring that your application can handle traffic spikes without manual intervention.
With no server management, developers can focus on writing code and deploying applications more efficiently.
Serverless encourages a microservices approach, making it easier to build and deploy small, independent functions or services.
Serverless functions may experience slight delays during cold starts, as the platform initializes resources.
Adopting serverless often means relying on a specific cloud provider, which can lead to vendor lock-in.
Serverless platforms impose resource limits on functions, which may affect applications with high compute or memory requirements.
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