Serverless computing has emerged as one of the most talked-about trends in software architecture. For companies building custom applications, serverless promises rapid scalability, reduced operational complexity, and lower costs, but it’s not without its trade-offs.
Let’s explore what serverless computing really means, and weigh the advantages and limitations it presents for businesses building custom software solutions.
What Is Serverless Computing?
Despite the name, “serverless” doesn’t mean there are no servers. Instead, it refers to a cloud computing model where infrastructure management is abstracted away. Developers write and deploy code in small, event-driven functions, and the cloud provider (like AWS Lambda, Azure Functions, or Google Cloud Functions) automatically handles provisioning, scaling, and maintenance.
This architecture eliminates the need to manually manage servers or containers, allowing teams to focus purely on building features and delivering value.
Pros of Serverless Computing for Custom Application
1. Reduced Infrastructure Management
One of the biggest advantages is operational simplicity. With serverless, developers no longer have to manage servers, patch systems, or handle scaling configurations. Everything is managed by the cloud provider, freeing teams to spend more time coding and less time maintaining environments.
This is particularly useful for custom applications built from scratch, where the development team needs to move fast without being bogged down by DevOps overhead.
2. Automatic Scalability
Serverless platforms automatically scale based on demand. When your application experiences a spike in traffic — for example, during a product launch or seasonal surge — new function instances are spun up instantly. When demand drops, resources are scaled back down.
For startups or growing businesses, this on-demand elasticity means they never pay for idle capacity or worry about over-provisioning.
3. Pay-Per-Use Pricing
Unlike traditional server hosting models where you pay for uptime or reserved instances, serverless billing is based solely on execution time and resource usage.
This model can offer significant savings for applications with variable workloads, such as analytics dashboards, data pipelines, or event-driven integrations.
For many of Delta Systems’ clients developing custom business tools or API endpoints, serverless can be an efficient way to deploy lightweight, infrequently accessed functions without maintaining full-time servers.
4. Faster Development and Deployment
With no servers to configure or maintain, developers can deploy code updates in seconds. Serverless architectures naturally align with CI/CD pipelines, allowing continuous iteration and faster release cycles.
This agility supports rapid prototyping, where new features can be tested and refined quickly, a key advantage for businesses creating tailor-made digital tools to fit evolving workflows.
5. High Availability and Fault Tolerance
Serverless functions are inherently distributed across multiple availability zones. Cloud providers ensure high uptime and automatically handle failures and restarts.
For applications that need consistent performance without investing in complex failover systems, this reliability is a major plus.
Cons of Serverless Computing for Custom Applications
1. Cold Start Latency
When a serverless function hasn’t been called in a while, it enters a “cold” state. The next time it’s triggered, there can be a brief delay known as a cold start while the environment initializes.
For latency-sensitive applications such as real-time APIs or chat systems, this can affect user experience. Techniques like function “warming” or keeping containers hot can help, but they add complexity.
2. Limited Execution Time and Resources
Serverless functions are designed for short, stateless operations. Providers often cap execution times (e.g., AWS Lambda’s 15-minute limit) and restrict memory or CPU allocation.
This makes serverless less suitable for long-running tasks like video processing, complex data analysis, or continuous background operational, areas where traditional microservices or containerized architectures shine.
3. Complex Debugging and Monitoring
Because serverless environments are fully managed and distributed, debugging becomes more challenging. Developers can’t access the underlying infrastructure or logs in real time, and tracing function dependencies across events can be difficult.
This complexity increases when multiple serverless functions interact with other cloud services, requiring advanced observability tools to maintain visibility.
4. Vendor Lock-In
Each cloud provider implements its own set of serverless standards, APIs, and event triggers.
Migrating from AWS Lambda to Azure Functions or Google Cloud Functions often requires rewriting portions of the codebase.
For businesses that want flexibility or a multi-cloud strategy, this dependency can create long-term constraints unless mitigated through container-based wrappers or open-source frameworks like Knative.
5. Unpredictable Costs for Heavy Workloads
While serverless is cost-effective for low or fluctuating workloads, high-traffic applications may find costs harder to predict or control.
Each function invocation adds to the bill, and as usage grows, expenses can scale unexpectedly compared to fixed-rate server hosting.
Budget-conscious teams should closely monitor usage patterns and employ cost-tracking tools to avoid surprises.
When Serverless Makes Sense and When It Doesn’t
Ideal Use Cases for Serverless:
- Event-driven systems (e.g., file uploads, email triggers, IoT)
- APIs or microservices with irregular traffic
- Prototypes, proofs of concept, and MVPs
- Data transformation or automation tasks
Better Alternatives:
- Applications requiring long processing times or heavy compute
- Systems needing persistent connections (e.g., WebSockets)
- Workloads where vendor independence is a top priority
How Delta Systems Approaches Serverless Architecture
At Delta Systems, we don’t believe in one-size-fits-all solutions. Our software engineers evaluate each client’s application goals, data requirements, and performance expectations before recommending the right architecture.
For some projects, a hybrid model that combines serverless functions with containerized or traditional components delivers the best of both worlds. This approach ensures scalability and cost efficiency without sacrificing reliability or control.
Serverless computing offers incredible agility for custom applications, enabling faster releases, lower overhead, and seamless scaling. However, understanding its limitations and trade-offs is crucial before adopting it as your default architecture.
If your organization is exploring whether serverless is the right fit for your next custom software project, Delta Systems can help you assess your options and design a solution that balances performance, scalability, and cost-efficiency.
Contact Delta Systems today to discuss your application architecture strategy.