We performed a comparison between Amazon EC2 Auto Scaling and AWS Lambda based on our users’ reviews in four categories. After reading all of the collected data, you can find our conclusion below.
Comparison Results: Both products are very effective in providing compute service (IaaS) solutions. AWS Lambda slightly nudges ahead of Amazon EC2 Auto Scaling as many users feel it is easier to code using the solution. AWS Lambda is serverless, server configuration is not required, and can easily run it directly anywhere.
"The solution is scalable."
"The tool helps me to process large data sets while scaling up."
"Can handle traffic spikes so the system doesn't overload."
"The feature I found most valuable was the vertical and horizontal scaling."
"The product is flexible."
"Having a load balancer in between is very helpful when you have huge traffic."
"We appreciate that this solution allows us to run all of our severs through it, meaning that our workloads are mainly on the EC2 instance only."
"I like the fact that you don't need to pay for it when you aren't using it, especially in a disaster recovery scenario. The pricing is transparent, so you know what you're going to pay for it."
"The main features of this solution are the ability to integrate multiple AWS applications or external applications very quickly and organize all of them. Additionally, it is easy to use and you can run various programming languages, such as Python, Go, and Java."
"The utilization of containers is particularly beneficial in overcoming the size limitations imposed on Lambda functions which not only allows us to work around these constraints but also contributes to the improvement and maintenance of our code."
"We have no issues with the technical support."
"Lambda makes the administration of all our services related to Amazon really easy."
"I have found all of the features valuable. It's an easy and cheap solution."
"Lambda has improved our organization by making it possible to transform data."
"Because AWS Lambda is serverless, server configuration is not required, and we can run it directly anywhere."
"The initial setup is pretty easy."
"The primary area for improvement is the pricing model."
"The product does not explain why a particular instance is terminated."
"As we are transitioning to managing containerized applications, the solution could improve by adding more managed container services as a feature in the solution."
"I would like to see the security portal improved in the future."
"It's an expensive solution."
"There is room for improvement in the scalability."
"The solution's configuration process could be better."
"There should be an AWS instance in South Africa, where the latency would be even lower. It might happen soon since AWS has recently opened more data centres in Nigeria. AWS may extend its reach to South Africa, and offer hosted CLI servers there. Most of the problems with AWS are not to do with the solution itself but with configuration. It is something on design, more or less."
"It can be a bit difficult to switch between accounts when creating services for customers."
"There is room for improvement in user-friendliness. When comparing this solution to others it is not as user-friendly."
"What could be improved in AWS Lambda is a tricky question because I base the area for improvement on a specific matrix, for example, latency, so I'm still determining if I can be the judge on that. However, room for improvement could be when you're using AWS Lambda as a backend, it can be challenging to use it for monitoring. Monitoring is critical in development, and I don't have much expertise in the area, but you can use other services such as Xray. I found that monitoring on AWS Lambda is a challenge. The tool needs better monitoring. Another area for improvement in AWS Lambda is the cold start, where it takes some time to invoke a function the first time, but after that, invoking it becomes swift. Still, there's room for improvement in that AWS Lambda process. In the next release of AWS Lambda, I'd like AWS to improve monitoring so that I can monitor codes better."
"The price in general could always be better."
"I would like to see more integration with other platforms."
"AWS Lambda can improve its file system-based sharing capabilities and restrictions."
"AWS Lambda could be improved by increasing the size of the payload. Also, sometimes Lambda doesn't implement well for bigger solutions."
"Security needs to be improved."
Amazon EC2 Auto Scaling is ranked 2nd in Compute Service with 39 reviews while AWS Lambda is ranked 1st in Compute Service with 70 reviews. Amazon EC2 Auto Scaling is rated 8.8, while AWS Lambda is rated 8.6. The top reviewer of Amazon EC2 Auto Scaling writes "Well-documented setup process and highly stable solution". On the other hand, the top reviewer of AWS Lambda writes "An easily scalable solution with a variety of use cases and valuable event-based triggers". Amazon EC2 Auto Scaling is most compared with AWS Fargate, AWS Batch, Oracle Compute Cloud Service and Amazon Elastic Inference, whereas AWS Lambda is most compared with AWS Batch, Apache NiFi, Apache Spark, AWS Fargate and Google Cloud Dataflow. See our AWS Lambda vs. Amazon EC2 Auto Scaling report.
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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.
