AWS Lambda Reviews

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. 

My primary use cases for AWS Lambda is collecting data from other systems through API, pre-calculations, and ETL.

The feature I found most valuable about Lambda is the fact that it's serverless.

I would like the layers to have a bigger volume. I would like to be able to add more. I don't want to be limited by the layer. 

In addition, writing temporary data to Lambda is not straightforward. Sometimes I use the S3 for that. I found it a little bit challenging. 

I have been using AWS Lambda for a couple of years.

My impression is that it is a stable solution.

I would rate the scalability of this solution a 10, on a scale of one to 10, with one being not scalable and 10 being very scalable.

I have never used Amazon's tech support.

I would say the initial setup was straightforward.

We required two technical staff to do the deployment and maintenance.

We have about 15 to 20 users of Lambda in our company and plan to expand.

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.

AWS Lambda is mainly used for automation. To simplify, in AWS Lambda, I define a function, and I can invoke that function or feature whenever I want and on schedule.

For example, if I have data to collect daily from different services, I schedule the AWS Lambda function to do that, and it does the job. That's one of the use cases of the tool.

Another use case for AWS Lambda is when you have multiple servers running and need to shut down the servers at night. You can configure an AWS Lambda function that would shut down the servers every night on schedule. You can also use it as a backend and invoke it through API, so you deploy your backend from an AWS Lambda function, then link it with the API gateway, then you can invoke your function through the API.

What I like best about AWS Lambda is that it's feature-rich, and I appreciate that. I also like that it's stable and supports many languages.

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.

I've been using AWS Lambda for one year and a half.

AWS Lambda is a stable product.

I have yet to contact the AWS Lambda technical support team because I haven't experienced any difficulty with the tool.

One of the reasons my company went with AWS Lambda is that it's serverless, so you don't need to manage any server because AWS will handle it. This means that a lot of responsibilities will be taken care of by AWS, which helps you avoid many problems.

Another reason for choosing AWS Lambda is its stability. Latency is also not a problem on AWS Lambda, allowing you to use different services in your AWS account securely. For example, when you want to reach the AWS billing service, you can do it within the environment of your AWS account without an external tool, which makes it very secure. AWS Lambda also helps you reach other AWS accounts securely because it depends on roles rather than search keys or passwords.

The initial setup for AWS Lambda is straightforward. It's effortless to start using AWS Lambda.

Price-wise, AWS Lambda is very cheap. It's not free, but it's not that expensive.

I'm using the latest version of AWS Lambda because when a framework or tool is deployed on a public cloud, it's always the newest version, and you don't get to choose the version.

I'd tell first-time users of AWS Lambda, or anyone looking into using the tool, that you can deploy every application within AWS Lambda, and it's very easy to set up and deploy. You can also use it with any application regardless of language because AWS Lambda supports many languages such as Go, Bison, Node, GS, and .NET. The tool is very code-agnostic, and not coded with programming languages, so you can still use Docker images to start your AWS Lambda function, for example.

My rating for AWS Lambda is nine out of ten because of how hard AWS worked on having good latency, security, and an intuitive start. The tool supports different languages and is stable, so I gave it a high rating.

I'm a customer of AWS Lambda.

We have some services deployed that we need to consume in Lambda because it's a faster and better implementation. We have a model that microservice in the product, which we implement in AWS. For that reason, we use Lambda.

The solution has improved our organization by providing us with better communication with the different services, dependencies, and implementations our clients require. The solution is faster and the consumption is really good.

There are some restrictions. For example, we have some services that if you have more than 60 seconds in consumption of this service, we don't use it, because they have that restriction with the gateway. Those services we implement with Fargate and with Docker.

The most valuable feature is that there is no need to implement it in a server because it is a service.

The 60 seconds limitation with the consumption of the service is really restrictive for a service and the solution can be improved by eliminating that.

I have been using the solution for one year.

The solution is stable.

The solution is scalable.

The initial setup is easy but you do need some experience.

The implementation was completed in-house.

The return on investment is good because it is a Cloud-based solution that doesn't require maintenance or a server on-premises saving you money.

I give the solution a seven out of ten.

One person with AWS knowledge is sufficient for deploying and maintaining the solution.

We currently have around 160 people using the solution.

All of the products we implement are in AWS so we do have plans to increase the usage of Lambda, Fargate, and all of the services in AWS to help speed up the implementations.

For anyone thinking about using the solution, you must make sure you have some experience in AWS or another cloud, maybe Azure, and have some experience with software development. If you don't have software development skills, maybe you have experience in deploying services on IIS or something like that.

I am using AWS Lambda for building web and mobile applications.

AWS Lambda has helped my organization by making it easier to code and it is less costly.

The valuable feature of AWS Lambda is the ease of coding. It is easier to code using the solution.

AWS Lambda can improve its file system-based sharing capabilities and restrictions.

I have been using AWS Lambda for approximately six years.

AWS Lambda is stable.

The scalability of AWS Lambda is good.

We have approximately 1.3 million users using the application that uses the solution. We have 10,000 to 20,000 new users added every month.

The support from AWS Lambda is good.

I rate the support from AWS Lambda a four out of five.

The initial setup of AWS Lambda is easy. The full implementation took us there to four months.

I rate the setup of AWS Lambda a four out of five.

We did the implementation of AWS Lambda in-house.

We migrated from an on-premise server to the cloud with the Lamda solution and we found it less than one-10th of the cost of what it used to be. We have 90 percent savings.

I rate the ROI of AWS Lambda a four out of five.

AWS Lambda license is paid on a monthly basis.

I rate the price of AWS Lambda a four out of five.

My advice to new users is I would recommend strongly going with AWS Lambda for all API-based solutions.

I rate AWS Lambda an eight out of ten.

Essentially, I use AWS Lambda to run Python code. Usually, I set up triggers for other parts of AWS. It's really basic programming tasks.

AWS Lambda is more integrable than other code software, which is a significant advantage. Given my software development experience, I find its integration with the cloud easier than with other platforms. There haven't been any problems while using it during my three-month internship.

A very minor improvement would be to simplify the instructions on setting a trigger, as I had to read through them multiple times at the start.

I have used AWS Lambda for three months.

AWS Lambda is entirely stable. I never encountered any issues while using it.

I haven't used it extensively, however, it seems scalable. During my internship, scalability hasn't been critical to what I've used it for.

I have never needed to communicate with technical support for AWS Lambda.

Positive

The initial setup was extremely easy. AWS Lambda is significantly easier compared to other IDEs or Visual Studio Code.

There is no specific advice I can provide at the moment because I've only done a short internship. Overall, I would rate AWS Lambda a ten out of ten.

We are building a Twitter-like application in the boot camp. I have used Lamda for the integration of the post-confirmation page in the application. This will help you get your one-time password via mail. You can log in with the help of a post-confirmation page. We didn’t want to set up an instance specifically for confirmation. We used the Lambda function so that it goes back to sleep after pushing up.

The tool changes its UI every month which is very frustrating for me. I don’t know why AWS keeps changing the UI. They can’t stick to a specific one.

I have not faced any stability issues with the tool.

I know that AWS has flexible support but if I encounter any problem, then I just Google it. I get a lot of support from Google, YouTube videos, and Discord channels.

The solution’s initial setup was neither easy nor complex. I started learning about cloud services about six to seven months ago and already had a background in it. However, the implementation was not easy since a lot of errors just popped up. I had to check the CloudWatch logs and look into the bugs in the code. It wasn’t interesting. The deployment took around two hours to complete.

I would rate the solution a ten out of ten. The solution works fine for us and we didn’t require the need to maintain it. I didn’t face any problems working with the product.