AWS Lambda Reviews

AWS Lambda is a serverless architecture. So, you can use three languages like Java, Python, and Node. You can write your code in any language. The main use is if you have a team and your team has one Java developer, one Python developer, or one JavaScript developer. You all want to work together and in a single project, you can use multiple languages, by any of the users.

All of the features are very good and useful.

The most valuable feature for example Java needs a server, so you need to host your application somewhere. AWS Lambda is itself serverless, and it is connected to the API gateway, and you can directly call the API through the API gateway and connect through AWS Lambda.

I would like to see the five zero four AWS Lambda invocation fixed. This is basically a time-out error. Having consistency in this aspect will enhance how robust the solution is for us.

I have been working with AWS Lambda for the past two years.

The stability overall is good. As I mentioned before sometimes you get a couple of time-out errors that need to be fixed.

It is highly scalable. You can use any of the features I mentioned, and you can write a number of functions in one project. We already use around twenty-five functions in one project.

The initial setup is difficult. You need a lot of the code background. You should be at least five to ten years as an experienced developer.

If it is a single deployment it will not take very much time. However, it does take more time as you increase code and volume.

The clients have seen a return on investment.

The price is expensive and is based on usage. The more users you have the higher the cost.

I would rate AWS Lambda an eight out of ten.

I use AWS Lambda for event-driven computing and various other projects that benefit from its serverless architecture.

AWS Lambda supports event-driven computing, which is incredibly beneficial for our projects. Its scalability allows us to handle varying amounts of load efficiently, and it integrates smoothly with other AWS services to enhance our application workflows. 

Additionally, AWS Lambda is cost-effective, providing noticeable cost savings.

I would like to see improvements in AWS Lambda's stability and setup processes, as there were some complexities encountered initially.

I have been working with AWS Lambda for a substantial amount of time.

We have faced some stability issues with AWS Lambda, although it generally performs well.

AWS Lambda is scalable, and we have found its scalability beneficial for our projects.

I have not escalated any significant issues to customer support regarding AWS Lambda, but generally, AWS support is helpful.

Positive

I have experience with other compute services from different vendors, such as Azure.

The initial setup of AWS Lambda was somewhat complex and not entirely straightforward.

AWS Lambda has contributed to cost savings and performance improvements in our organization.

The pricing of AWS Lambda is reasonable, though there is always room for more flexibility.

I have evaluated solutions from other vendors, including Google and Microsoft Azure.

Overall, I would recommend AWS Lambda to others due to its capabilities. On a scale of one to ten, I would rate it quite high - and eight.

AWS Lambda is used only by the DevOps team. I can use the solution to configure and set up all the requirements for testing the application and test code.

AWS Lambda should improve its compatibility with the language used to write the code. I would like to be able to choose a different language to code in AWS Lambda.

I have been using AWS Lambda for six months.

Around 15 to 20 users work with AWS Lambda in our organization. The solution is used by different teams, including the DevOps, testing, and development teams.

I faced some challenges when we worked on the migration. I raised tickets to the support team, and they helped me.

The solution's initial setup can be done with the help of documents.

AWS Lambda is not expensive for micro testing but is expensive if used for long deployment or long services.

It is not difficult for a beginner to learn to use AWS Lambda for the first time because it has good documentation.

Overall, I rate the solution a five out of ten.

As a platform team, we had to enable a light-weight ingestion platform ensuring the aspects of governance were baked into the platform and the business teams could accelerate their cloud adoption and only develop the business logic.

AWS Lambda improved our productivity and also enabled the business teams to build their ingestion systems at ease.

AWS Lambda's best feature is the lightweight framework that allowed us to bring down a lot of boilerplate code as part of platform capabilities and give the developers an opportunity to only write business-specific logic.

There were some timeout issues with AWS Lambda as the options provided didn't suit our business cases. In the next release, AWS Lambda should include integration with an IoT.

I've been using AWS Lambda for about a year.

AWS Lambda scales really well.

AWS Lambda is cost-effective, with a minimal maintenance cost.

I would rate AWS Lambda eight 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. 

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.