Serverless computing has become an increasingly popular approach for deploying applications and services in the cloud. It offers a number of potential benefits but also comes with some drawbacks to consider. In this article, I will examine the key pros and cons of serverless computing to help you determine if it is the right approach for your needs.
What is Serverless Computing?
Before diving into the pros and cons, it’s important to have a clear understanding of what serverless computing is and how it works.
Serverless computing is a cloud computing execution model where the cloud provider dynamically manages the allocation and provisioning of servers. With serverless, the code is run on-demand in ephemeral containers that are event-triggered and fully managed by a cloud provider.
Key characteristics of serverless computing include:
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No server management – The cloud provider completely handles server provisioning, scaling, availability and capacity planning. Developers don’t have to worry about infrastructure at all.
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Event-driven scaling – The code is run only when triggered by an event such as an HTTP request, database change or API call. It automatically scales up and down based on usage.
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Ephemeral compute – The code runs in temporary containers that can scale up and down rapidly based on workload. You only pay for the compute time used.
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Granular billing – Usage is metered in milliseconds and billed based on compute time consumed per execution. There is no charge when code is not running.
Some common examples of serverless computing services are AWS Lambda, Google Cloud Functions and Azure Functions. Serverless is commonly used to build microservices architectures.
Pros of Serverless Computing
Cost Savings
One of the biggest advantages of serverless is significant cost savings compared to traditional always-on servers and virtual machines. With serverless, you only pay for the exact amount of compute time used to execute your code. There is no charge when your code is not running. This can amount to massive savings, especially for workloads that are event-driven, infrequent or intermittent.
Automatic Scaling
Serverless applications automatically scale up and down based on usage, eliminating the need to provision and manage infrastructure. This auto-scaling is seamless, rapid, and has virtually unlimited capacity since it is handled by the cloud provider’s robust infrastructure. This makes serverless ideal for applications with variable workloads and traffic spikes.
Faster Development
By removing the need to manage servers, serverless enables faster development cycles. Developers can focus on writing and deploying code without all the overhead of server ops. Code can be deployed in seconds via event triggers instead of manually managing servers. This increased productivity can accelerate time to market.
Flexibility
Serverless provides immense flexibility since your application can scale down to zero when not in use. Traditional servers still incur costs even when idle. With serverless, you only pay for exactly what you use. This flexible consumption model is ideal for event-driven workloads.
Cons of Serverless Computing
Vendor Lock-in
The biggest downside of serverless is often vendor lock-in. Once you build your application on a specific vendor’s serverless platform, it can be extremely difficult to switch providers later. This is because serverless offerings differ substantially between vendors. Portability is limited.
Cold Starts
When a serverless function is triggered after being idle, it leads to cold starts where the container hosting the code needs to be initialized. This can mean slower response times for the first invocation until the container is warmed up. Cold starts can impact latency-sensitive applications.
Monitoring and Debugging
Monitoring and debugging serverless applications can be challenging since the code is run in ephemeral containers that rapidly scale up and down. Log aggregation and tracking issues across distributed executions requires more observability tooling.
State Management
Maintaining state is difficult with serverless functions since they are meant to be stateless for rapid scaling. Storing state such as user sessions requires additional services like datastores. Vendor services like AWS Step Functions help manage state.
Architectural Complexity
For larger applications with many interconnected services and functions, architectural complexity can grow quickly. Serverless code needs to be structured and managed properly to avoid creating a tangled architecture that is hard to understand and maintain.
In summary, while serverless offers major benefits like reduced costs and faster development, there are also notable downsides like vendor lock-in and state management challenges. As with any technology, it is vital to assess if serverless aligns with your specific workload, use case and application architecture. The pros and cons outlined above provide a starting point for evaluating if serverless computing is the right choice.
