EC2 vs Serverless. Cost Comparison for RESTful APIs


Two popular Amazon Web Services (AWS) options are Elastic Compute Cloud (EC2) and Serverless (AWS Lambda). Understanding the cost differences between these solutions is essential for making informed decisions. Considering performance, scalability, and management, let’s examine the costs of deploying a RESTful API using EC2 and Serverless. We will also look at real-world examples of companies that successfully implemented RESTful APIs using these solutions.

Executive Summary

This article provides a detailed comparison of Amazon EC2 and Serverless (AWS Lambda) for deploying RESTful APIs, discussing each solution's advantages, limitations, and cost differences. Using cases of Chronly, Stream, and CloudExpat, the article highlights the key factors to consider when choosing the right cloud infrastructure for your organization's needs.

EC2 and Serverless Overview

EC2: Amazon EC2 provides scalable virtual machines in the cloud, offering control over the infrastructure, including OS, security, and networking. EC2 instances can be scaled as needed.

Serverless (AWS Lambda): AWS Lambda is a serverless service for running code without managing servers. You pay only for computing time, and it scales automatically. Lambda suits event-driven architectures and microservices.

Cost Comparison

Feature Amazon EC2 AWS Lambda (Serverless)
Cost Pay for provisioned instances, even when idle Pay only for consumed compute time
Scalability Manual or auto-scaling with additional tools  Automatic scaling
Management Higher monitoring and maintenance overhead    Minimal management required
Limitations Overprovisioning risk, higher management costs  Cold start latency, limited execution time

Compute Costs

EC2: With EC2, you pay for provisioned instances, even when idle. Various instance types and sizes are available, but monitoring and optimization are necessary to minimize costs.

Serverless: Lambda charges only for consumed compute time, billed per 100 milliseconds. When idle, costs are minimal. AWS offers a free tier for Lambda.

Data Transfer Costs

EC2: EC2 data transfer costs depend on data volume. Data-intensive applications may incur high costs.

Serverless: Lambda charges for data transfer in and out of functions. However, data transfer costs can be minimal or free when communicating with other AWS services in the same region.

Storage Costs

EC2: EC2 storage costs relate to the Elastic Block Store (EBS) volumes. Costs depend on your application's storage requirements.

Serverless: Lambda provides free temporary storage. Persistent storage requires Amazon S3 or DynamoDB, which incur separate costs.

Management and Maintenance Costs

EC2: EC2 instances require ongoing monitoring, patching, and maintenance, increasing operational costs. Scaling may require manual intervention or additional tools.

Serverless: Lambda reduces management costs by handling operational tasks, allowing developers to focus on coding and delivering features.

Limitations and Challenges


  • Higher management overhead: EC2 instances require more monitoring, patching, and maintenance than serverless solutions.
  • Potential for overprovisioning: EC2 instances may result in wasted resources and increased costs if not optimally configured.


  • Cold start latency: Lambda functions may experience increased latency during a "cold start," which occurs when a new function instance is initiated.
  • Limited execution duration: Lambda functions have a maximum execution duration, which may not suit long-running tasks.

Real-world Examples: Chronly, Stream, and CloudExpat

This section will explore how three Pinely clients, Chronly, Stream, and CloudExpat, have successfully deployed RESTful APIs using EC2 and Serverless.

Chronly: AI-powered Workforce Management Tool

  • Challenges: Chronly faced the challenge of managing unpredictable workloads while maintaining cost efficiency. They also needed to ensure their development team could focus on core product features.
  • Solution: By adopting AWS Lambda (Serverless) to deploy their RESTful API, Chronly addressed these challenges through automatic scaling, pay-per-use pricing, and reduced management overhead. This decision simplified their development and maintenance processes, allowing the development team to focus on improving product features and functionality, resulting in faster iterations and a better user experience.

Stream: Digital Signage provider

  • Challenges: Stream required a versatile infrastructure to manage varied and ever-changing digital signage content while fulfilling client requirements.
  • Solution: Stream selected Amazon EC2 as the platform for deploying their RESTful API, thanks to its existing integrations with legacy POC systems from providers like NCR and others. This choice granted Stream the adaptability to tailor the foundational infrastructure, encompassing OS, security, and networking configurations. As a result, Stream was able to preserve a superior degree of control over its environment, guaranteeing that its digital signage content remained current and in line with client demands. Even though this strategy amplified their management and upkeep obligations, Stream invested in supplementary tools and expertise to tackle these challenges, ensuring that their infrastructure stayed dependable and secure.

CloudExpat: Optimizing Cloud Infrastructure

  • Challenges: CloudExpat needed to embrace new technologies such as AWS Lambda and Serverless, fetch resources securely, and manage execution time for command execution.
  • Solution: CloudExpat utilized the Serverless Framework, AWS Services (including AWS Lambda), and other technologies to develop an economical solution. This approach allowed them to complete three out of five project scopes, enabling them to fetch AWS account resources, generate Terraform configurations, and deploy user changes. The completed scopes have laid the foundation for an AI model that provides cost-reduction insights, and as the remaining scopes are finalized, the project will progress towards optimizing cloud infrastructure and expenses.

Additional Use Cases

EC2 Use Cases:

  • Data-intensive applications: EC2 can be tailored to handle large data processing tasks, such as big data analytics and machine learning workloads.
  • Customizable environments: EC2 is suitable for applications that require specific OS, security, or networking configurations.
  • Customizable infrastructure: EC2 is suitable for content delivery platforms that require high levels of customization and control over their infrastructure to optimize performance and caching strategies.

Serverless Use Cases:

  • Event-driven architectures: Lambda is well-suited for applications that respond to events, such as IoT systems or real-time data processing pipelines.
  • Microservices: Lambda enables the development of lightweight, independent, and scalable microservices that can be easily integrated with other AWS services.
  • Real-time data processing pipeline: automatic scaling and event-driven architecture provide significant benefits for ingesting and analyzing data from various sources.

Cost-saving Strategies and Best Practices

When deploying RESTful APIs, EC2 instances can be combined with Amazon RDS for efficient database management. At the same time, Lambda functions can seamlessly integrate with Amazon API Gateway for effective API management and security. Such integrations allow organizations to build more comprehensive, efficient, cost-effective cloud solutions.

How can you optimize EC2 and Lambda costs?


  • Use Reserved Instances or Savings Plans for predictable workloads to save on long-term costs.
  • Leverage Auto Scaling Groups to automatically adjust the number of instances based on demand.
  • Implement proper monitoring and alerting to optimize instance usage and detect underutilized resources.


  • Package and optimize your function code to reduce the overall function size and improve performance.
  • Utilize Provisioned Concurrency to mitigate cold start latency for critical functions.
  • Monitor and fine-tune function timeouts and memory allocation to optimize resource usage and costs.

Security and Compliance Considerations

When choosing between EC2 and Lambda, it's essential to consider security and compliance requirements specific to your organization or industry. Both services offer features to help secure your infrastructure but differ in control and customization.

In the context of security features, EC2 provides options like Security Groups, Network ACLs, and Virtual Private Cloud (VPC) to ensure a secure and isolated environment. While handling most security aspects automatically, Lambda also supports custom authorizers, resource policies, and execution within a VPC for enhanced security.

EC2 allows more fine-grained control over security settings, such as firewalls, encryption, and networking configurations. This level of control is handy for organizations with strict security or regulatory requirements.

On the other hand, Lambda manages most security aspects for you, simplifying the security implementation process. However, it may not offer the same level of customization as EC2, which could be a limitation for some organizations.

When selecting a cloud infrastructure solution, consult your organization's security and compliance guidelines.

Further Reading

For more information and detailed documentation on Amazon EC2 and AWS Lambda, visit the following resources:


In summary, choosing between Amazon EC2 and Serverless (AWS Lambda) for deploying a RESTful API depends on your specific requirements, such as control, scalability, cost, and maintenance. EC2 provides more flexibility and control over the infrastructure, while Lambda offers automatic scaling and a pay-per-use model that can reduce costs.

Cases of Chronly, Stream, and CloudExpat demonstrate that both options can be successfully implemented for deploying RESTful APIs, depending on the organization's needs. By carefully evaluating your unique requirements, you can select the right cloud infrastructure solution to ensure your business’s success.

[NOTE] Diagrams that illustrate the architecture of a RESTful API deployed using EC2 and Lambda, highlighting components like load balancers, auto-scaling groups, databases, and API Gateway.

RESTful API Deployed Using EC2:

  1. API Gateway: Acts as the entry point for the RESTful API, handling client requests and directing them to the appropriate EC2 instances.
  2. Load Balancer: Distributes incoming API requests across multiple EC2 instances to balance the load and maintain high availability.
  3. Auto Scaling Group: Manages the number of EC2 instances running your API, automatically scaling the number of instances based on demand.
  4. EC2 Instances: Virtual machines running your API code, processing the incoming requests, and interacting with the database.
  5. Database: Stores the data required for your API, such as user information, product data, etc. You can use Amazon RDS, Amazon DynamoDB, or any other database service.

RESTful API Deployed Using Lambda:

  1. API Gateway: Acts as the entry point for the RESTful API, handling client requests and directing them to the appropriate Lambda functions.
  2. Lambda Functions: Serverless functions running your API code, processing incoming requests, and interacting with the database. These functions are automatically scaled by AWS based on demand.
  3. Database: Stores the data required for your API, such as user information, product data, etc. You can use Amazon RDS, Amazon DynamoDB, or any other database service.

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