This article is the second part of Ibexlabs’ three-part Application Modernization series. While the first part delved into microservices basics, we expand on the benefits of serverless microservices in the second part. The article also highlights serverless microservices use cases and the difference between serverless microservices vs. containerized serverless microservices. 

Learning Objectives 

  1. The definition of serverless microservices.
  2. Understanding how serverless microservices work.
  3. Benefits of serverless microservices.
  4. Difference between serverless microservices and containerized serverless microservices.
  5. Real-world use case of containerized serverless microservices.

Serverless Microservices Architecture Explained

Serverless microservices architecture is when small segments of independent applications or microservices run on serverless compute environments. The advantage of a serverless computing environment is that organizations don’t have to deal with the hassle of managing servers. Serverless providers such as AWS, Google Cloud, etc., offer a pay-per-execution pricing model and take complete charge of server maintenance, scaling resources, fault tolerance, security measures, networking infrastructure, etc. As a result, developers can focus solely on writing code and developing backend applications without worrying about foundational computing resources. 

Serverless Microservices Architecture: Framework

Combining serverless computing with microservices is a powerful approach to building scalable and flexible applications. Let’s briefly look at how serverless microservices work.

After a developer writes the code for a microservices application, its functions are deployed to a serverless computing platform, such as AWS Lambda. Microservices communicate with each other through well-defined APIs and events, and this event-driven communication allows microservices to operate independently.

On the other hand, the serverless platform automatically scales resources to accommodate changes in workload. Serverless platforms also provide the tools for monitoring and observability. Developers can track performance metrics, diagnose issues, and optimize the system through logging, tracing, and analytics. For example, by leveraging AWS CloudWatch Logs or CloudWatch metrics, organizations can achieve critical log information, performance metrics, and application insights.

Benefits of Serverless Microservices

In addition to the commonly known benefits of serverless architecture, such as cost efficiency and flexibility, serverless microservices offer several advantages, especially in the case of complex and evolving applications. Let’s understand this better with the AWS computing platform services.

  • Granular scaling for running microservices

AWS’ serverless computing service, AWS Lambda, allows you to define and scale individual functions independently within a specific microservice based on event-driven triggers. This ensures efficient resource utilization and cost savings, particularly in scenarios where different microservices have varying demand levels.

  • Seamless developer experience in building applications

Serverless microservices offer seamless development and deployment experiences facilitated by various tools and practices. For example, AWS offers services such as the Serverless Application Model and the AWS Serverless Application Repository to simplify the process of building, testing, and deploying serverless microservices applications.

  • Unparalleled flexibility in data handling

When combined with serverless databases, serverless microservices represent a transformational approach to scalable applications. AWS offers serverless databases like Amazon Aurora Serverless and Amazon DocumentDB with serverless scaling. These database services complement serverless microservices, providing scalable and cost-efficient data storage solutions that automatically adjust to application needs.

  • Room for experimentation and prototyping

Serverless platforms provide a low-cost environment for experimentation compared to traditional server-based models. As a result, developers can quickly deploy serverless microservices without worrying about upfront infrastructure costs. Consequently, this enables rapid exploration and testing of new ideas or features.

  • Scalable backend for mobile and IoT

Serverless microservices are well-suited for scalable backends in mobile and Internet of Things (IoT) applications. They can efficiently handle sporadic requests from mobile and IoT devices without constantly maintaining a persistent server infrastructure.

Choosing Serverless Microservices

Although serverless microservices offer numerous benefits, evaluating your specific use case is essential before selecting an architecture. For instance, a traditional server will be the right choice if your microservices require continuous or long-running processing. Conversely, a pay-as-you-go serverless model might be redundant if your application has a consistently high and predictable workload.

Serverless microservices are especially well-suited for applications and development scenarios that involve event-driven and short-lived workloads. In event-driven scenarios, functions depend on events such as HTTP requests, database changes, or messages from a queue. As a result, a serverless microservices architecture allows for efficient handling of asynchronous tasks and quick responses to events.

Now, let’s analyze a scenario that demands the flexibility of serverless computing and the portability benefits of containerization. In this case, the best option is serverless containerized microservices. The primary distinction between serverless microservices and serverless containerized microservices lies in the packaging and deployment of the application.

Serverless microservices typically rely on function-as-a-service (FaaS) platforms like AWS Lambda. In contrast, serverless containerized microservices involve encapsulating entire microservices, including dependencies and runtime, into lightweight, portable containers, often managed by services like AWS Fargate. While both approaches offer automatic scaling and abstracted infrastructure management, containerized microservices provide a more comprehensive packaging solution, ensuring consistency across diverse environments.

Serverless Containerized Microservices: A Real-World Use Case

Let’s take a real-world use case to help you understand the unique value proposition of serverless containerized microservices.

Retail applications that handle dynamic pricing updates have the best use for serverless containerized microservices. Each pricing microservice is containerized using Docker and orchestrated by a serverless platform, such as AWS Fargate. The microservices, encapsulated in containers, are responsible for processing real-time data, applying pricing algorithms, and updating product prices accordingly.

The serverless nature of the architecture allows these containers to scale automatically based on fluctuating demand, ensuring responsiveness during peak shopping hours and cost efficiency during low periods of activity. The containerized microservices can be triggered by inventory changes or market trends, enabling the application to adapt dynamically to evolving market conditions. In short, serverless containerized microservices offer the utmost flexibility, scalability, and cost-effectiveness in the case of complex, event-driven workloads in retail or similar industries.


Serverless microservices are optimal for organizations with rapid scaling and fluctuating demand. Therefore, this model benefits startups and agile development teams, enabling efficient resource allocation and faster time-to-market.

However, if you are seeking the encapsulation benefits of containers while leveraging the automatic scaling of serverless platforms, serverless containerized microservices emerge as the optimal choice. For organizations looking for on-demand, right-sized compute capacity for containers, AWS Fargate is a great choice.

AWS Fargate excels in scenarios where containerized applications demand longer-running processes, as it helps orchestrate entire microservices encapsulated in containers.

Stay tuned to learn why AWS Fargate is well-suited for microservices or applications with complex dependencies.

If you want to deploy microservices using serverless functions, then Ibexlabs is the cloud specialist you need. Ibexlabs offers custom cloud consulting, migration, DevSecOps, and managed security services to meet all your cloud goals. Read our case studies here or contact us today.


What are serverless microservices?

Serverless microservices integrate serverless principles and microservices architecture for a more efficient and responsive computing environment, facilitating a modular and scalable development approach.

How does serverless microservices work?

Serverless microservices break down an application into discrete, independent units of function. These functions operate in a stateless manner and are deployed in a serverless computing environment, such as AWS Lambda.

What are the benefits of serverless microservices?

Serverless microservices enable fine-grained scalability, as functions are executed in response to specific events. This mitigates the need for continuous resource allocation. Serverless microservices architecture benefits agile startups or organizations with fluctuating, event-driven workloads.

What is the difference between serverless microservices and serverless containerized microservices?

Serverless microservices rely on function-as-a-service platforms like AWS Lambda. Serverless containerized microservices involve encapsulating microservices into portable containers, often managed by services like AWS Fargate. While Fargate is better suited for microservices, AWS Lambda is advantageous for serverless function scenarios.

Image by storyset on Freepik”>Photo credit – Freepik