AWS EC2 Vs Lambda: Everything you need to know

Lambda has gained massive acceptance since its release in November 2014 and has witnessed a healthy adoption over EC2 by many startups over a certain period. 

There is no doubt that it has evolved cloud computing and allowed businesses to leverage the ease of AWS environment over more advanced EC2. 

But when it comes to the enterprises it really matters which compute service they choose which will best suit their requirements. In this article, we will discern the comparison of Lambda vs EC2 from every perspective of their application to businesses. 

Let’s start by knowing what these services actually are and how they differ. 

What is AWS EC2?

An EC2 instance is a virtual machine on AWS cloud virtual environment. It stands for Elastic Compute Cloud. It is a web service where an AWS subscriber can request and provision a Compute virtual machine in the AWS cloud. AWS provides multiple instance types and pricing models for the business needs of the user. EC2 is a good example of IaaS (Infrastructure as a Service) where scalable infrastructure is provided for Businesses who want to host cloud-based applications without owning and managing the physical servers in their own data centres. 

AWS provides EC2 service in multiple regions so that users can launch the EC2 instances in locations that meet their requirements.

AWS EC2 currently supports a variety of operating systems including Amazon Linux, Ubuntu, Windows Server, Red Hat Enterprise Linux, SUSE Linux Enterprise Server, openSUSE Leap, Fedora, Fedora CoreOS, Debian, CentOS, Gentoo Linux, Oracle Linux, and FreeBSD.

What is AWS Lambda?

AWS Lambda is a zero-configuration & zero-administration compute service for backend components of an application for backend developers that executes the application code on AWS cloud with the fine-grained pricing structure. AWS Lambda runs on its own AWS compute fleet of Amazon EC2 instances across multiple availability zones in a region, with high availability, security performance and scalability of the AWS infrastructure.

Let’s dive into the comparison EC2 vs Lambda.

AWS EC2 instances should be used for applications or software that needs to handle many user requests. On the other hand, AWS Lambda can be an ideal choice for applications components with less traffic or on-demand computation needs as they just pay for several application components and their execution run-time.

For most periodic or very light workloads, Lambda is dramatically less expensive than even the smallest EC2 instances. Adopting with AWS Lambda effectively eliminates the need for traditional computing services and infrastructure. Lambda greatly reduces the cost and complexity of your IT operations, makes development times faster and scaling easier.

Setup and Management

Amazon EC2 requires sizable time to set up as it includes manual steps like logging into the VMs via SSH and manually installing Application/ DB servers, installing the development tools, cloning the code repos, etc. We can also use the predefined AMIs to get the images of Operating systems and open source tools.

In the case of AWS Lambda, the setup is not required as users can write/edit the code using the inline editor. Users are not required to provide any VM and the scaling is fully automated.


Usually, by using AWS EC2 instances businesses expect high availability and faster throughput with almost 0% downtime for their applications. When the user launches an EC2 instance, they have to select a Region that puts the selected instances closer to specific customers, for low latency or meeting the legal or other requirements that the business may have. By launching the instances in separate Availability Zones and hosting the applications on them, users can protect their applications from the failure of a single location.

When users launch an instance, they can optionally specify an Availability Zone in the Region that they are using. If not specified an Availability Zone, AWS selects a suitable Availability Zone automatically.

AWS Lambdas are available all the time but run as and when required. The scaling of resources happens automatically depending upon the requirements of the event triggers. Since the user pays only for the computation time, therefore it saves a lot of money.


Amazon EC2 is optimal for executing long-running tasks since different configurations EC2 instances are available depending upon the requirement. EC2 instances are a good solution when applications must be up and running 24x7.

AWS Lambda is a run-on-demand service. By default, the Lambda service remains inactive and gets activated only when an event is triggered. The Lambda service can run max up to 900 Seconds (15 minutes) and can only execute the workloads with a max memory requirement of 3000 MB.


AWS follows a shared responsibility model between AWS and their Customers. Multiple security features are in place at different levels.

AWS Key-value pairs: AWS uses public-key cryptography to secure the login information for the EC2 instances.

Security groups: Security groups act as a firewall for associated instances, controlling both inbound and outbound traffic at the instance level. Users can add rules to a security group that enable them to connect to the instance from the IP address using SSH. Users can also add rules that allow inbound and outbound HTTP and HTTPS access from anywhere.

IAM policies are used to provide the permissions to create or modify Amazon EC2 resources or perform tasks using the Amazon EC2 API.

Use Cases

EC2 Usecases

Various Organizations use EC2 instances for various purposes. Many businesses use EC2 VMs to run production loads and for experimental and proof of concept work. Additionally, EC2 allows us to deploy resources and restrict IAM roles and access policies in an agile manner as many organizations work with freelancers, contractors and third parties.

AWS EC2 instances are widely used for web and app development and to host websites and web applications on both production and development servers.

In DevOps teams, a fleet of reserved EC2 instances is used as Docker containers to host backend services and CD/CI pipelines using Kubernetes.

Data Science teams also use EC2 instances to run Jupytor notebooks to do feature exploration on pre-loaded data and sometimes spot instances to support ad-hoc feature generation and model training. Data team uses the spot instances to run backfill jobs whenever needed.

EC2 also provides auto-scalability, which is very important in managing high burst in web traffic on your application.

Lamda Usecases

AWS Lambda service allows developers to run their code without setting up and manage servers, this is called “serverless computing. In Lambda the resource scaling is automatically managed by AWS based upon the computing requirements of the code which is sent for execution. Most of the popular languages are been supported out of the box as mentioned below:

  • Java
  • Python
  • Node.js
  • C#
  • Go and
  • PowerShell

Below are the popular use-cases for AWS lambda service:

File processing - AWS Lambda service can be invoked by other AWS services like S3, Kinesis, etc. The Lambda function code can read and manipulate the objects from other AWS sources like S3, EFS, and then save them in another Storage location.

Data and Analytics - Lambda service can read data from Databases, Data Streams and events and are used to trigger the next steps or generate custom metrics by aggregating raw data.

Websites - AWS lambda is used widely to be configured as an API endpoint that receives the web requests and can do request processing for web clients.


AWS permits Free Tier for AWS EC2 instances including 750 hours of Linux and Windows t2.micro instances each month for one year. To stay within the AWS EC2 Free Tier, use only EC2 Micro instances. AWS allows Per-Second billing for EC2 servers, and the user pays for only what they use. It takes the cost of unused minutes and seconds in an hour off of the bill, so businesses can focus on improving their applications instead of maximizing usage to the hour.

With On-Demand instances, users can pay for the compute capacity by the hour or the second depending on which instances run. No longer-term commitments or upfront payments are needed. Users can increase or decrease the compute capacity depending on the demands of the application and only pay the specified per hourly rates for the instance in use.

Reserved Instances provide a significant discount (up to 75%) compared to On-Demand instance pricing. In addition, when Reserved Instances are assigned to a specific Availability Zone, they provide a capacity reservation, giving users additional confidence with the ability to launch instances as and when required.


AWS EC2 and Lambda cater to different requirements and use cases. If there's a need to use the customised tools for Development, Server setups and specific hardware resources (in terms of CPU cores, Memory size and IOPS) then Amazon EC2 offers better flexibility. EC2 offers per-second billing as long as VM is running.

On the other hand, if a user wants a fully managed event-driven service then the use of AWS Lambda is recommended. It offers computation time billing.

Curated by-

Ms. Mahima Garg

She is a technology enthusiast and an author who is passionate about ideation, planning, implementing, integrating, and managing business processes for business growth. This led her and the team to build a Global IT Certification and Preparation Platform for professionals which help them get certified and enhance their career growth. With 20+ years of experience in IT and Management, she believes to impart what she has learned in her exciting career.

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