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AWS Lambda vs Azure Functions

AWS Lambda

AWS Lambda is a serverless computing service software that executes a code in response to the triggered events. It automatically manages all the computing resources for streamlining regular operations. AWS Lambda runs high-availability network infrastructure code (response to events from more than 150 natively integrated AWS and SaaS sources – all without any server management) and performs all computer resource management, including server and operating system maintenance, automated scaling and power provisioning, code and security patch deployment, code monitoring and logging.

Key Functionalities:

  • Develop custom services for the back-end

  • Extend, with custom logic, other AWS services

  • Absolutely Automated Administration Absolutely

Advantages of AWS Lambda:

  • Cheap

  • Quick

  • Stateless

  • Extensive API

  • Event-Driven Governance

  • Autoscale and cost-effective

  • VPC Support

  • Integrated with various AWS services

  • Better graphical view

Azure Functions

Azure Function is a serverless, compute-on-demand experience built by Microsoft that expands the existing Azure application platform with code deployment capabilities caused by events occurring on Azure or third-party services as well as on-site systems. Unlike AWS Lambda, Azure Functions offers multiple feature deployment options, such as One Drive, GitHub, Kudu Console, DropBox, Visual Studio, and Zip.

Key Features:

  • Easily schedule event-driven tasks across services

  • Expose Functions as HTTP API endpoints

  • Scale Functions based on customer demand

Advantages of Azure Function:

  • Great developer experience for C#

  • Multiple languages supported

  • Great debugging support

  • Easy Scalability

  • Can be used as a lightweight HTTPS service

  • Azure component events for Storage, services, etc

  • Event-driven

  • Webhooks

AWS Lambda VS Azure Functions

AWS Lambda

Azure Functions


AWS Lambda provides the support to upload the code in a zip file as well as writing the code in the console to create the function.

Azure Functions code support and writing approach is a little bit complex to implement but also at the same time it is more flexible.


PowerShell, Node.js, Go, Python, C#, Java, and Ruby code

C#, JavaScript, F#, Java, PowerShell, Python, TypeScript by transpiring them to JavaScript.


AWS Lambda works on a simple JSON and YAML input/output model. To develop a new function, all you would need is a package for deployment that needs to be executed. After executing this function, you need to deploy Amazon CloudWatch logs to keep a track of logs and streamline AWS X-ray tracking requests.

Azure Functions, we have triggers and bindings. If you use this, you can easily pull or push extra data while processing the query along with input and output bindings. These bindings are capable of offering better scalability with an extended cost of complexity in both APIs and configuration.


For AWS lambda deployment one needs to define maximum memory allocation approximately between 128 MB and 3 GB. The capacity of the CPU and the cost of operating the function are proportional to the memory allocated.

One size fits all- is true for all types of Azure functions. It has around 1.5GB of memory with low-profile virtual core functions. We can easily choose between different hosting platforms such as Windows and Linux.


The extensions help to integrate the already-in action tools with the Lambda environment. AppDynamics, Dynatrace, HashiCorp, Thundra, Lumigo, Splunk SignalFx, Datadog, Epsagon, AWS AppConfig, Check Point, New Relic, and Amazon CloudWatch Lambda Insights are available today as extensions.

Azure Portal, Non-.NET Languages, C# Class library using Visual Studio, C# Class Library using Visual Studio Code. Portal uses extension bundles

Functions Triggers and Types

Triggers in Lambda are used to make functions process data automatically. It can be considered as a Lambda resource that is configured to invoke functions for every lifecycle event or external request. Types: 1. API Gateway Event 2. S3 Event 3. DynamoDB Event

Azure functions are invoked by triggers. For each function, we have one trigger associated with it. The function triggers in a timely manner. Types: 1. Queue Trigger 2. HTTP Trigger 3. Event Hub Trigger 4. Timer Trigger 5. Blob Trigger 6. Generic Webhook 7. GitHub Webhook 8. Service Bus Trigger


AWS Lambda provides dynamic scaling applications allowing users to chain new features and also helps in incorporating custom serverless functions as a service. It also allows the user to perform external operations and a configurable timeout along with setting default action in case if it returns an error or takes more time than defined

In Azure Functions scaling is provided by Azure Function Scale Controller. This controller checks for all the queues in a timely manner and issues peek commands. Based on the messages received with these commands and also latencies of the same it will be deciding whether to use any additional virtual machines or not.

HTTP Trigger and Integration

Amazon introduced integration with Load balancing that may cost high and is efficient for high load scenarios. This comes on the basis of a per-hour pricing model where you can easily judge how to exactly use it. AWS only offers C# supported by .NET Core.

The Azure functions come with exceptional and extraordinary HTTP end-point functions for integration. There are no additional expenses added to its integration in order to develop a serverless API that reacts to webhooks using an HTTP trigger.

Identity and Access Management

It Regulate and provide access to AWS services safely through admin. Control of IAM administrators that can be validated using signed-in options and allowed (licensed) to use Lambda services. An AWS service- IAM can be used with no added expense.

You can add the security of apps and data at the frontend by supporting Azure identity and access management solutions. You can add security against various malicious logins that are risk-based with access rights, identity protection tools and more robust authentication alternatives.

Dependency Management

The AWS Lambda includes a range of modules, such as the Node.js and Python runtime AWS SDK. This is aimed to manage the dependencies in the implementation bundle of your function.

The Azure function supports all the injection and software, designing models. With these dependencies, you can achieve the inversion of control between classes. This injection in the Azure function is created using core .NET core dependency injection features.


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