Case Study: How Serverless Computing Saved a Startup Thousands on Cloud Costs

In the realm of cloud computing, managing costs while maintaining efficiency is a constant challenge for startups. Imagine running a fleet of taxis that need to be ready 24/7, even if there are no passengers. This is similar to traditional cloud computing, where servers are always on, racking up bills regardless of usage. Now, picture a different model—one where taxis are dispatched only when there's a passenger. This is the essence of serverless computing. In this case study, we explore how a startup transformed their cloud strategy, significantly cutting costs by moving to a serverless architecture.

Serverless vs Servers

The Challenge

Our client, a growing startup, was using a Kubernetes cluster to manage their microservices. While Kubernetes offered excellent scalability and orchestration, it required maintaining always-on servers. This setup was akin to keeping a fleet of idle taxis, incurring high costs even during off-peak hours. The startup's monthly cloud computing bill was hitting $5,000, a significant expense for their budget.

The Solution: Serverless Architecture

We proposed a shift to serverless computing. Serverless is like a pay-as-you-go taxi service: you only pay when the service is being used. For tasks such as sending SMS, emails, and notifications, serverless is particularly effective. These tasks are like short taxi rides—they don't take long, and you don't need the taxi waiting around for the next trip.

  1. SMS and Email Services: These services are perfect for serverless functions. They don't require long computational times and can handle bursty traffic efficiently. AWS Lambda, Google Cloud Functions, and Azure Functions can process these tasks on-demand, reducing idle time costs.
  2. Notification Services: Similar to SMS and email, notifications are event-driven. Serverless can scale automatically to meet the demand when notifications are sent out, ensuring you're only billed for the compute time used during these events.
  3. Microservices: Many microservices don't need to run continuously. By migrating these to serverless, the startup could run their services only when needed. For instance, a user authentication service that only needs to run when users log in can be executed on-demand, reducing constant overhead.

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Migration from Kubernetes to Serverless

AI Suzana

Kubernetes is excellent for certain use cases, such as applications requiring persistent connections or complex orchestration of multiple services that need to run continuously. However, in this case, the startup's usage pattern revealed that many of their services could benefit from a serverless approach. The migration process involved:

  1. Assessment: We evaluated which microservices could be moved to a serverless environment. Services with sporadic usage and those that did not require persistent connections were prime candidates.
  2. Planning: A phased migration plan ensured minimal disruption. Services were gradually moved, starting with the least critical to monitor performance and cost savings.
  3. Implementation: Using AWS Lambda and API Gateway, we redeployed the selected services. For example, their user authentication and notification systems were transitioned first, leveraging the event-driven nature of serverless.
  4. Optimization: Post-migration, we optimized the configurations to ensure maximum cost efficiency without sacrificing performance.
  5. Bug Hunt: There were no major issues during the migration, the company already had a robust monitoring system in place, and their api was stateless which made the migration process smooth.
  6. Monitoring: Constant monitoring post-migration ensured that the services were running smoothly and that the cost savings were being realized.


The shift to serverless architecture led to dramatic cost savings. The startup's monthly cloud bill dropped from $5,000 to a range of $400-$600. This reduction is akin to switching from owning an idle taxi fleet to using a taxi service only when needed. The savings enabled the startup to reallocate funds to other critical areas such as development and marketing, fostering further growth.

Serverless computing proved to be a game-changer for this startup. By eliminating the need for always-on servers, they were able to significantly cut their cloud computing costs. This case study highlights the potential of serverless to transform how startups manage their infrastructure costs. While serverless isn't a one-size-fits-all solution, it offers substantial benefits for services with variable workloads.

For startups looking to optimize their cloud spending, evaluating the potential of serverless architecture could be a step in the right direction. As demonstrated, the cost savings can be substantial, allowing businesses to invest more in innovation and growth. By strategically leveraging serverless, startups can navigate the competitive landscape with greater financial agility and technical efficiency.

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