AWS Lambda Reviews

Our primary use case for the solution is automation. There was a scenario where we tried to reduce cost in our environment using Instance Scheduler, where the AWS Lambda function was also used during that process. So we use it for automation and tagging.

The solution has helped our organization with cost optimization. So we have used AWS Lambda for consolidated billing.

The automation feature is valuable.

The runtime for the solution can be improved.

We have been using the solution for approximately two years.

The solution is stable. I rate it a nine out of ten.

The solution is scalable, and I rate it a ten out of ten.

The initial setup was straightforward.

The solution is very expensive.

I rate the solution a nine out of ten.

Lambda is basically a serverless computation service. We are partners with AWS and I'm a consultant. 

Because Lambda is serverless, it has optimized our resources. There's no need to worry about capacity. 

Lambda is very handy because it gives us the parallelism of computation. If you want to launch thousands of instances simultaneously, it can be done on one site. The solution has a 15-minute computation limit but you can create a chain with the same code so that the output automatically switches to another functionality after 15 minutes. 

The only issue is that if you have Lambda in one AWS account and want to utilize it in another account, it can't be done. It's a limitation of the solution. S3 bucket provides that option with its resource access management. If you have a Python library and want to package it, you have to create the package of those libraries. It requires changing the conflict file and the patent library to create the package because the configuration is a little difficult for beginners. They should simplify package creation and configuration. Writing test cases is a little difficult because of the memory and short duration. Your computation has to be finished within that time limit. 

I've been using this solution for five years. 

We haven't had any performance issues because Lambda automatically gauges the kind of computation required.

The scalability is excellent and there is no capacity limit. 

Provided the person deploying the solution knows the format of the input, the setup is relatively simple for experienced users. Deployment doesn't take long because of the integrated machine services. Our implementation was carried out in-house. It doesn't require any maintenance once it has run for a month.

Licensing costs are reasonable even though you have to pay for the computation and for the volume of data. Once the work is done, the storage is freed up so you only get charged for the instance. 

If an organization wants to go serverless, Lambda offers a truly serverless service. Even though there are some areas that could be improved, I rate this solution 10 out of 10. 

There a variety of use cases for this solution but it is mostly used for data processing type transformations from one source to a target. In instances when Lambda works well, we are planning to increase usage. 

Deployment and maintenance of Lambda requires two people but this may increase depending on the size of the deployment.

Lambda has improved our organization by making it possible to transform data.

Lambda has limitations on the amount of memory you can use and is not a good solution for long running processes. If the amount of data is reasonably small, it will run and transform successfully. If you have tons of data coming in, it stops working and you have to restart it.

The orchestration and coordination between different Lambdas could also be improved.

I have used this solution or a couple of years.

This is a fairly stable solution. 

This solution has some limitations on scalability due to the problem with coordination between the different Lambdas. Is it not very straightforward and you have to do a lot of testing.

The initial setup was fairly straightforward.

I would advise others to use it in those circumstances where it works well and to be aware of the problems with coordination and orchestration. Make sure that it doesn't have to process tons of data.

I would rate this solution a seven out of ten.

Our company uses the solution as a function engine to deploy triggered events for customers. We have a team of twelve developers and our deployments have 1,000 to 2,000 customers during peak times. 

The solution runs on the latest cloud technology so it is easy to deploy cloud-native projects. 

The solution is very useful for managing triggered events. 

It can be a bit difficult to switch between accounts when creating services for customers. 

I have been using the solution for one year. 

The solution is cloud-based so of course it is stable as long as the cloud is available. 

The solution is scalable. 

We have not needed technical support. We utilize available documents that contain content for solving any issues. 

The solution is serverless computing so there is no setup. You just launch the service, write your code, and run it. 

The solution is part of the AWS subscription model that is paid annually. There is no charge for monthly usage. 

There are many calculation criteria for AWS services or licenses. It is difficult to say whether the solution reasonably priced or expensive. Each company weighs price against the benefits and efficiencies provided by the solution. 

AWS is the pioneer of cloud computing and they lead the industry in innovations. Other providers follow in AWS' footsteps to implement similar features and service levels. 

AWS has differentiated the use cases for serverless computing. Lambda is used for basic capabilities like triggered events and Fargate is used for extended capabilities. 

I started using Lambda for a specific use case and I continue to use Lambda and Fargate for use cases as recommended by AWS. 

I definitely recommend the solution and rate it a ten out of ten. 

AWS Lambda's most valuable feature is serverless architecture.

There are sometimes issues following an update.

I've been using AWS Lambda for about five years. 

AWS Lambda is stable.

AWS Lambda is scalable.

The initial setup was straightforward and took only a few minutes.

AWS Lambda's cloud version isn't expensive, and I'd rate its pricing as five out of five.

I would rate AWS Lambda ten out of ten.

Lambda makes the administration of all our services related to Amazon really easy. 

The metrics and reporting for this solution could be improved. 

I have been using this solution since 2017. 

From a stability perspective, I would rate it a seven out of ten. There is some room for improvement when it comes to stability of the features. 

This is a scalable solution. I would rate it a nine out of ten in this regard. 

The initial setup is complex. 

I would recommend this solution to others. Overall, the solution has improved since we started using it in 2017. 

I would rate this solution a nine out of ten.

We use AWS Lambda for jobs that we just want to offload to a cloud function. We are an educational institution, and if I want to upload an exam I generated for all my students, then I just write the script on AWS Lambda. That is, we use it for independent jobs that we can offload on their own.

I like the pay-for-what-you-use feature. This is the main reason why we use AWS Lambda. I don't have to manage servers; I just have to configure Lambda and expose it to an API gateway.

AWS Lambda's cold start needs to be improved. It has to warm up first, and so, the response time is slower.

Another challenge I've noticed is that there is a limit to the environment variables such as the 4 KB limit. Although, the advice is to use parameters or other things to store the details when the limit has exceeded the data, this adds additional intensity to the application. If the size limits for environment variables can be revealed, it would be helpful. Even if we have to pay for it, at least we would know that we are not dealing with latency. So, I would like to see the size of the environment variables increased.

I've been using AWS Lambda for one year.

It's very stable.

AWS Lambda is scalable; I don't need to worry about it. At present, we have less than 10 people using this solution.

The initial setup is straightforward. It can be done on the console, and you can use the infrastructure as the code.

The deployment time can vary from 10 minutes to an hour depending on your needs and how comfortable you are with AWS Lambda.

AWS Lambda now supports multiple languages, but find out if the language you want to use to write your jobs is supported by it. If it is supported, then you are good to go.

Because AWS Lambda is scalable and does what it's meant to do, I would rate it at nine on a scale from one to ten.

AWS Lambda is used for the whole surface, it does the backups, and schedules, and learns some of the core functionalities but it can depend on the topic or application. The solution is used to build APIs and many other functions 

AWS Lambda has some size limitations in the code line, you can't do a couple of functions to do the job.

I have been using AWS Lambda for approximately six years.

AWS Lambda is stable.

AWS Lambda is in the cloud which makes it scalable.

I have worked in many companies that have used this solution and some of them had a lot of users.

The support from AWS Lambda is very good, they are responsive.

I rate AWS Lambda a nine out of ten.