AWS Lambda and AWS Fargate compete in the serverless computing and container management categories, respectively. AWS Lambda has a slight advantage due to its ease of use and cost-effective pay-per-use model, which appeals to a wider range of users.
Features: AWS Lambda offers a serverless environment that eliminates infrastructure management, integrates seamlessly with other AWS services, and supports multiple programming languages, providing flexibility and rapid scaling. AWS Fargate simplifies running applications by offering managed containers and integrates seamlessly with AWS ECS, providing control and flexibility over containerized applications, especially benefiting microservice architectures.
Room for Improvement: AWS Lambda faces limitations with execution time and cold start latency for long-running tasks, and could benefit from enhanced integration with external services and more language support. AWS Fargate needs better cost control and monitoring for dynamic scaling, easier configuration, and improved integration with AWS services to enhance accessibility. Both services could improve support documentation and offer simplified setup options.
Ease of Deployment and Customer Service: AWS Lambda is praised for its adaptability in cloud-native deployments, though support delays may occur based on plan levels. Its documentation minimizes frequent technical support needs. AWS Fargate requires understanding container settings for optimal use, and while its enterprise-level support is well-regarded, both services could benefit from improved accessibility and quicker response times, with AWS Lambda also needing enhanced user guidance for beginners.
Pricing and ROI: AWS Lambda's pay-per-use pricing model is economically beneficial for variable workloads and eliminates infrastructure costs, enhancing ROI. Its free-tier provisions provide additional savings. AWS Fargate's pricing depends on compute and storage needs, making it more expensive than Lambda, especially for startups. However, its managed service simplifies deployment complexity and offers value in necessary containerization. Efficient resource management and cost monitoring are crucial for optimizing ROI with both services.
The pay-as-you-go pricing model of AWS Fargate was one of the major drivers for us to move there because we reduced costs while increasing the quality of the processing services by about 30%.
Even though we didn't contract support, every two weeks I had a 30-minute meeting with a cloud architect from AWS to help our team use different products of AWS, especially with SageMaker for a forecasting algorithm we were developing.
I would rate how scalable AWS Lambda is a nine on a scale from 1 to 10, where 1 would be the lowest and 10 would be the highest level of scalability.
For a company that does not require complexity or managing Kubernetes clusters, AWS Fargate is a great way to go.
One of the best features of AWS Fargate is that it was useful for us because we didn't require to run container workloads and we didn't need to deal with the management of a Kubernetes cluster directly, and the ability to run those workloads just in a scheduled manner is also a great feature.
A new compute engine that enables you to use containers as a fundamental compute primitive without having to manage the underlying instances. With Fargate, you don’t need to provision, configure, or scale virtual machines in your clusters to run containers. Fargate can be used with Amazon ECS today, with plans to support Amazon Elastic Container Service for Kubernetes (Amazon EKS) in the future.
Fargate has flexible configuration options so you can closely match your application needs and granular, per-second billing.
AWS Lambda is a compute service that lets you run code without provisioning or managing servers. AWS Lambda executes your code only when needed and scales automatically, from a few requests per day to thousands per second. You pay only for the compute time you consume - there is no charge when your code is not running. With AWS Lambda, you can run code for virtually any type of application or backend service - all with zero administration. AWS Lambda runs your code on a high-availability compute infrastructure and performs all of the administration of the compute resources, including server and operating system maintenance, capacity provisioning and automatic scaling, code monitoring and logging. All you need to do is supply your code in one of the languages that AWS Lambda supports (currently Node.js, Java, C# and Python).
You can use AWS Lambda to run your code in response to events, such as changes to data in an Amazon S3 bucket or an Amazon DynamoDB table; to run your code in response to HTTP requests using Amazon API Gateway; or invoke your code using API calls made using AWS SDKs. With these capabilities, you can use Lambda to easily build data processing triggers for AWS services like Amazon S3 and Amazon DynamoDB process streaming data stored in Amazon Kinesis, or create your own back end that operates at AWS scale, performance, and security.
We monitor all Compute Service reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
