Serverless computing has transformed how developers approach application deployment and infrastructure management. No longer do development teams need to divide their time between writing code and maintaining server infrastructure. Instead, cloud service providers handle the servers, allowing developers to focus solely on their code. But when should you embrace serverless, and when might traditional approaches be more suitable?
Despite its name, serverless computing doesn’t actually eliminate servers. Rather, it abstracts them away from the development process. The concept was pioneered by Google with their App Engine release in 2008, but it gained substantial momentum when Amazon launched AWS Lambda in 2014. Since then, the serverless market has expanded dramatically, with projections suggesting continued robust growth through 2025 and beyond.
In a serverless model, developers upload code in the form of functions, and cloud providers like AWS, Microsoft Azure, or Google Cloud handle all the underlying infrastructure—automatically scaling resources up or down based on demand. You pay only for the exact compute time you use, often down to the millisecond.
Serverless architecture excels for applications that respond to events rather than maintaining continuous operation. These might include processing uploads, handling API requests, or responding to database changes. Because serverless functions can instantly spin up in response to triggers and then shut down when idle, they’re perfect for sporadic workloads with unpredictable traffic patterns.
For example, an e-commerce site might use serverless functions to process image uploads for product listings, generate thumbnails, and update inventory after purchases—all without maintaining constantly running servers.
If you’re building applications using a microservices architecture, serverless provides a natural fit. Each microservice can be implemented as a separate function, allowing teams to develop, deploy, and scale components independently. This approach enables faster development cycles and more efficient resource utilisation.
Many New Zealand businesses have found success using serverless for microservices that handle specific business functions like payment processing, notification systems, or data validation.
For startups and innovation teams looking to validate ideas quickly, serverless reduces the time from concept to working prototype. Without server provisioning or infrastructure management, developers can focus exclusively on business logic and user experience.
This speed advantage is particularly valuable in competitive markets where being first can make all the difference. Several Kiwi tech startups have leveraged serverless to rapidly test market assumptions before committing to larger infrastructure investments.
Serverless functions typically have execution time limits—for instance, AWS Lambda functions can run for a maximum of 15 minutes. Applications requiring continuous processing or long-running operations might not be suitable for a purely serverless approach.
Data analytics pipelines, machine learning training jobs, or video transcoding services often need extended processing time and might be better served by container-based services or traditional virtual machines.
While serverless can scale impressively for variable workloads, applications with steady, predictable, high-volume traffic might actually be more cost-effective on traditional infrastructure. The pay-per-use model becomes less advantageous when your functions are constantly running.
Many organisations adopt a hybrid approach, using serverless for bursty, variable components while maintaining traditional infrastructure for steady-state operations.
Serverless platforms can experience “cold starts”—brief delays when a function is invoked after being idle. While cloud providers continue to improve this aspect, applications requiring consistent, millisecond-level response times might face challenges in a serverless environment.
This concern is particularly relevant for financial trading platforms, online gaming servers, or real-time bidding systems where even slight delays can impact outcomes.
When transitioning to serverless, consider starting with a pilot project in a low-risk area of your application. This approach allows your team to learn the new paradigm without endangering critical business functions.
Build observability into your serverless applications from day one. Since the infrastructure is abstracted away, comprehensive logging and monitoring become even more essential for troubleshooting and optimisation.
Security practices must evolve for serverless environments. The principle of least privilege becomes especially important—each function should have only the specific permissions it needs to perform its task, nothing more.
Serverless doesn’t eliminate complexity; it shifts it. While server management disappears, developers must now contend with different challenges: managing numerous small functions, handling cold starts, and orchestrating distributed components.
The serverless approach continues to mature, with providers addressing initial limitations through improved tooling, longer execution times, and better integration options. As the ecosystem evolves, the range of suitable use cases expands accordingly.
Serverless computing offers compelling advantages in agility, scalability, and reduced operational overhead. By understanding its strengths and limitations, you can make informed decisions about where it fits within your technology strategy. The most successful organisations often adopt pragmatic, mixed approaches—leveraging serverless where it shines while using alternative computing models where they make more sense.
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