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AWS Auto Scaling VS AWS Lambda

Compare AWS Auto Scaling VS AWS Lambda and see what are their differences

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AWS Auto Scaling logo AWS Auto Scaling

Learn how AWS Auto Scaling monitors your applications and automatically adjusts capacity to maintain steady, predictable performance at the lowest possible cost.

AWS Lambda logo AWS Lambda

Automatic, event-driven compute service
  • AWS Auto Scaling Landing page
    Landing page //
    2023-02-26
  • AWS Lambda Landing page
    Landing page //
    2023-04-29

AWS Auto Scaling features and specs

  • Cost Efficiency
    AWS Auto Scaling helps reduce costs by automatically adjusting the number of running instances based on demand, ensuring that you only pay for what you use.
  • Improved Availability
    It enhances application availability by ensuring that applications always have the correct number of resources running to handle current workload demands.
  • Scalability
    AWS Auto Scaling enables applications to scale seamlessly both vertically and horizontally, accommodating both predictable and unpredictable workload patterns.
  • Load Balancing Integration
    Easily integrates with AWS Elastic Load Balancing, automatically distributing incoming application traffic across multiple targets such as Amazon EC2 instances.
  • Deploy Management
    Facilitates management of deployment processes by automatically scaling resources during deployments or updates to minimize service disruption.

Possible disadvantages of AWS Auto Scaling

  • Complexity
    Setting up and managing Auto Scaling can become complex, requiring careful planning to properly configure scaling policies and thresholds.
  • Latency in Scale Up
    There can be a delay in acquiring new resources when scaling up, as launching and configuring new instances takes some time.
  • Cost Management
    While cost management is an advantage, improperly configured auto scaling can lead to unexpected costs if there are spikes in demand.
  • Monitoring Requirements
    Constant monitoring and adjustments may be needed to ensure auto scaling policies align with business needs and performance metrics.
  • Learning Curve
    For newcomers, there can be a steep learning curve involved in understanding and effectively leveraging AWS Auto Scaling and related services.

AWS Lambda features and specs

  • Scalability
    AWS Lambda automatically scales your application by running your code in response to each trigger. This means no manual intervention is required to handle varying levels of traffic.
  • Cost-effectiveness
    You only pay for the compute time you consume. Billing is metered in increments of 100 milliseconds and you are not charged when your code is not running.
  • Reduced Operations Overhead
    AWS Lambda abstracts the infrastructure management layer, so there is no need to manage or provision servers. This allows you to focus more on writing code for your applications.
  • Flexibility
    Supports multiple programming languages such as Python, Node.js, Ruby, Java, Go, and .NET, which allows you to use the language you are most comfortable with.
  • Integration with Other AWS Services
    Seamlessly integrates with many other AWS services such as S3, DynamoDB, RDS, SNS, and more, making it versatile and highly functional.
  • Automatic Scaling and Load Balancing
    Handles thousands of concurrent requests without managing the scaling yourself, making it suitable for applications requiring high availability and reliability.

Possible disadvantages of AWS Lambda

  • Cold Start Latency
    The first request to a Lambda function after it has been idle for a certain period can take longer to execute. This is referred to as a 'cold start' and can impact performance.
  • Resource Limits
    Lambda has defined limits, such as a maximum execution timeout of 15 minutes, memory allocation ranging from 128 MB to 10,240 MB, and temporary storage up to 512 MB.
  • Vendor Lock-in
    Using AWS Lambda ties you into the AWS ecosystem, making it difficult to migrate to another cloud provider or an on-premises solution without significant modifications to your application.
  • Complexity of Debugging
    Debugging and monitoring distributed, serverless applications can be more complex compared to traditional applications due to the lack of direct access to the underlying infrastructure.
  • Cold Start Issues with VPC
    When Lambda functions are configured to access resources within a Virtual Private Cloud (VPC), the cold start latency can be exacerbated due to additional VPC networking overhead.
  • Limited Execution Control
    AWS Lambda is designed for stateless, short-running tasks and may not be suitable for long-running processes or tasks requiring complex orchestration.

Analysis of AWS Lambda

Overall verdict

  • AWS Lambda is a strong choice for developers looking for scalable, event-driven applications with minimal management overhead. It is particularly beneficial for applications that experience intermittent traffic or unpredictable workloads.

Why this product is good

  • AWS Lambda is a popular serverless computing service because it allows users to run code without provisioning or managing servers. It automatically scales applications by running code in response to triggers such as HTTP requests, changes in data, or system events. This can significantly reduce operational overhead and costs, as you only pay for the compute time you consume.

Recommended for

  • Developers building microservices or serverless applications.
  • Companies looking to reduce infrastructure management.
  • Startups wanting to quickly deploy applications with limited operational costs.
  • Organizations needing to integrate with other AWS services for a comprehensive solution.
  • Projects with unpredictable or variable workloads that require automatic scaling.

AWS Auto Scaling videos

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AWS Lambda videos

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AWS Lambda Vs EC2 | Serverless Vs EC2 | EC2 Alternatives

More videos:

  • Tutorial - AWS Lambda Tutorial | AWS Tutorial for Beginners | Intro to AWS Lambda | AWS Training | Edureka
  • Tutorial - AWS Lambda | What is AWS Lambda | AWS Lambda Tutorial for Beginners | Intellipaat

Category Popularity

0-100% (relative to AWS Auto Scaling and AWS Lambda)

AWS Auto Scaling

AWS Lambda

Development
100 100%
Development
0% 0
Cloud Computing
0 0%
Cloud Computing
100% 100
Diagnostics Software
100 100%
Diagnostics Software
0% 0
Cloud Hosting
0 0%
Cloud Hosting
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare AWS Auto Scaling and AWS Lambda

AWS Auto Scaling Reviews

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AWS Lambda Reviews

Top 7 Firebase Alternatives for App Development in 2024
AWS Lambda is suitable for applications with varying workloads and those already using the AWS ecosystem.
Source: signoz.io

Social recommendations and mentions

Based on our record, AWS Lambda seems to be a lot more popular than AWS Auto Scaling. While we know about 287 links to AWS Lambda, we've tracked only 13 mentions of AWS Auto Scaling. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

AWS Auto Scaling mentions (13)

  • Optimizing AWS Costs for AI Development in 2025
    Autoscaling is your best friend: Use Amazon SageMaker's Autoscaling or an autoscaling group with your EC2 inference instances. Configure it to scale based on a metric like CPU or GPU utilization. - Source: dev.to / about 2 months ago
  • Scalability: Explained
    This is a strategy mainly used in cloud environments, where resources are automatically scaled up or down based on real-time incoming traffic. AWS Auto Scaling helps you scale your applications hosted in AWS platform with a seamless experience. - Source: dev.to / about 1 year ago
  • Building a Greener Cloud: The Role of an Architect for Sustainability in AWS
    AWS Auto-Scaling is a service that automatically adjusts the capacity of an application in response to changing demand. It monitors resource utilization and scales resources up or down as necessary. By using AWS Auto Scaling, businesses can ensure that their applications are always running at optimal performance levels, without wasting resources or energy. - Source: dev.to / over 2 years ago
  • AWS vs Digital Ocean cost comparison in 2022
    Auto scaling lets you scale in/out your servers based on various conditions. So, you could choose to have a minimum capacity as default and let AWS scale it up automatically when needed. You could also schedule the scaling events based on time (For ex: scale to 2x servers during peak times and back to normal during normal hours) There are also other benefits that come with AWS like better eco-system of tools and... - Source: dev.to / about 3 years ago
  • Hidden, absolutely broken, mechanics
    Guys, whats this? Sounds kinda OP if you ask me Https://aws.amazon.com/autoscaling/. Source: over 3 years ago
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AWS Lambda mentions (287)

  • Agentic AI Observability with Amazon CloudWatch: Transforming Enterprise AI Monitoring
    CloudWatch Generative AI Observability works with agents across multiple platforms, including https://aws.amazon.com/bedrock/, https://aws.amazon.com/eks/, https://aws.amazon.com/lambda/, on-premises systems, and other cloud providers. - Source: dev.to / 9 days ago
  • Best Way to Run Puppeteer Online: Solutions Compared
    Currently, only a few platforms support running Puppeteer in a serverless manner: Leapcell, AWS Lambda, and Cloudflare Browser Rendering. - Source: dev.to / 21 days ago
  • DuckDB on AWS Lambda: The Easy Way with Layers
    Now combine that with AWS Lambda : instead of Athena queries, RDS instances, or complex ETL pipelines, DuckDB allows you to run analytical workloads on-demand in a Lambda function, paying only for what you actually use. Existing AWS services like Athena or RDS can address similar needs, but they come with different scaling models and pricing strategies. Athena, for example, charges per scanned byte and introduces... - Source: dev.to / 22 days ago
  • Videos REST API with API Gateway, Lambda, Aurora Serverless - FakeTube #5
    So far our high level architecture diagram wasn't very impressive - we only used AWS Amplify service to host our web application. Of course there are many services under the hood like Route 53, CloudFront, Certificate Manager, Lambda and S3, but Amplify provides level of abstraction, so that we don't have to think about it. - Source: dev.to / 3 months ago
  • What is the Most Effective AI Tool for App Development Today?
    Rajesh Pandey outlines key components: "For serverless, AWS Lambda and API Gateway allow you to build low-latency AI APIs without managing servers." Tools like Modal handle GPU deployments. - Source: dev.to / about 2 months ago
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What are some alternatives?

When comparing AWS Auto Scaling and AWS Lambda, you can also consider the following products

Zing - The worry-freeinternational money app

Google App Engine - A powerful platform to build web and mobile apps that scale automatically.

MxToolBox - All of your MX record, DNS, blacklist and SMTP diagnostics in one integrated tool.

Amazon S3 - Amazon S3 is an object storage where users can store data from their business on a safe, cloud-based platform. Amazon S3 operates in 54 availability zones within 18 graphic regions and 1 local region.

IBM Cloud Bare Metal Servers - IBM Cloud Bare Metal Servers is a single-tenant server management service that provides dedicated servers with maximum performance.

Amazon API Gateway - Create, publish, maintain, monitor, and secure APIs at any scale

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