AWS Lambda Reviews

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.

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.

We have used Lambda for

batch processing for specific schedules.

different bot functions that run regularly,

Application business logic

Easy to impliment without any environment provisioning

 The initial setup is straightforward. 

The stability is good.

It has good monitoring. the visibility is great.

From a very high-level perspective, it is a good solution, however, there are certain limitations. This becomes challenging for us. Specifically, a limitation is Lambda cannot continuously execute for more than 15 minutes. That could be one limitation. On an implementation level, there are certain limitations that I know about yet would not be the best person to explain as I am not technical.

The execution timeout can be increased so that if we have a lengthy process, it will not fail before their timeouts. We've had to revamp the way that it works due to that 15-minute timeout limitation.

We've been using over 2 years

It's very stable, and it's easy to monitor. They have all the required logs and dashboards available on AWS to see the progress. The visibility of it also is good when a Lambda runs and completes.

I would not say it's scalable in terms of usage. As the demands increase it is scalable. But if the lambda need more time to process it's not scalable beyond 15 mts.

I've never dealt with technical support. I can't comment on their services. 

Positive

It seems to be a straightforward process. However, I'm not directly totally involved with the Lambda implementation.

We are implementors and can set up the solution for clients. 

The ROI is very good. It's a positive thing as there's no investment at all. It's purely on usage you have to pay. There's no upfront investment required, and it's only on the requirement that you have to choose Lambda. With the cost not being very big, the ROI is very good.

The cost is based on the number of Lambdas used if I'm not mistaken. It's only a usage charge, not a license charge.

We are an extensively using

I'd recommend the solution to other users and organizations. 

With time-out limitation, it's not a perfect fit for the batch process which takes more than 10 min.

Our primary use case for AWS Lambda is a backend service module. Thanks to this solution, we do not need to worry about hardware or resource utilization. It saves us time. 

It saves us a lot of setup time. And, because it's our code, we will use Lambda. Lambda is the best AWS product we can use for running our code and it is very quick for the developers. All they have to do is commit their codes and, once we set up our code pipeline once after committing the code and building and deploying to our Lambda, the project will be up and running in the market. This setup is better than managing on EC2. We don't need to use EC2 in this case. 

My opinion is that the integration could be improved in this solution. We have had some difficulties integrating the EC2 module, but we found a solution for that by ourselves. I would say the integration needs to be improved.

I have been using AWS Lambda for about three years.

This solution is very stable.

My impression is that this solution is 100% scalable. The Lambda function is the most powerful product that the developer needs. 

We have one Lambda used by 50 to 100 people, and then we have another Lambda method that could be used by thousands.

My impression is that the setup was quite straightforward.

Overall, I would rate this solution a 10, on a scale from one to 10, with one being the worst and 10 being the best. I would definitely recommend this solution to other people.

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.

AWS Lambda is good because if you chop up your application into small pieces and that is something that can be accomplished as a Lambda-based solution on the cloud, you will save on the cost of your applications.

The reason Amazon AWS has provided AWS Lambda is to allow people to write small pieces of application tasks that will run on Amazon's own internal servers.

The most valuable feature of AWS Lambda, from a conceptual point, is its functions. For example, it's mathematical templates into which you can write, and create your solution. You write small pieces of a solution under given parameters.

I have been using AWS Lambda for approximately two and a half years.

Scalability is an in-house feature of AWS Lambda, it can scale well.

My team in the company is using this solution. I do not know how many other teams in the company might be using it.

We plan to use the solution in the future because there is always a use case for it.

I rate the scalability of AWS Lambda a ten out of ten.

I rate the support from AWS Lambda a ten out of ten.

Positive

We did not use another solution prior to AWS Lambda.

The initial setup of AWS Lambda is easy, it can be done with a couple of clicks.

We use Amazon's CodeBuild, which does the deployment for us, and we use CodeDeploy to write our software application, which submits the code into our Git DevOps operation. From there it gets built and deployed automatically. It's similar to a CICD operation.

We have seen a return on investment using AWS Lambda. We don't have to pay for the solution, such as whatever logic that is implemented. If we had to build it ourselves as a microservice, we would be paying for the infrastructure.

There are other similar solutions, such as Google Cloud Platform or Microsoft Azure. They might be better for small tasks. Everyone can use the cloud providers' solution rather than building their own infrastructure. Any cloud provider has benefits.

I would advise others to try the solution.

I rate AWS Lambda a nine out of ten.

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.

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.

My prior company used the solution to perform event-based actions and notifications, process data in an S3 bucket, and send messages in the SQS queue. 

Our development team worked with 300 users across different departments to integrate the solution. 

The serverless format is a benefit because on-demand computing can be performed without having to run machines.

The solution integrates well with API gateways and S3 events via its AWS ecosystem. 

The solution works with various programming languages including .NET and Java. 

The solution should continue to streamline integrations with AWS services. 

At one point, there was an issue receiving support for a new version. Support was behind by two versions and this presented challenges, but they caught up over time. 

I have been using the solution for three years. 

The solution is very stable. 

The solution is scalable for users because it is serverless. You can provision IAM users and easily give them access.

We scaled a core from one million to ten millions runs with no issues.  

I never needed to contact support. 

The setup is very easy and onboarding happens quickly. 

We implemented the solution in-house.

Implementation includes determining which APS you need, writing code, and packaging it all for upload. There is no real deployment other than adding the package to your CI/CD pipeline and pushing it. We do not consider this work to be substantial. 

The operational push takes a matter of minutes. 

The ROI is definitely worthwhile because pricing is based on use. 

The pricing is on-demand and based on runs or times that are billed out monthly. 

For example, one million requests might cost 20 cents. 

Our company wanted to compute in an ad-hoc manner. The solution allowed us to schedule cron jobs which made things easier. 

The solution also integrates well with the AWS suite of products so can be used with an API gateway and S3 functions. 

The solution can be used for many scenarios encountered by IT developers. There is a general push to create serverless systems that have on-demand use and price models. For most use cases, there is a 50% chance the solution will be a good fit.  

I rate the solution a nine out of ten. 

We use AWS Lambda extensively for our maintenance work, for our products, and in our daily actions. We try to move some data based on alerts in certain situations and events. For example, if we are using queues based on the queue methods, we prefer to trigger different Lambdas for different functions (to enable some functionality across products). There are also a few Lambdas for audits. There are a few Lambdas for backups and many other use cases. 

I like that it's easy to use and maintain. Lambda is good and supports different platforms, so you don't need to worry about language or maintenance.

The execution time could be better. One of the major limitations is the time period because it doesn't give you more than seven minutes. So, before thinking about Lambda, you should think through your use case and ensure it's a good fit. Otherwise, you can use batch, step functions, or other methods. 

Reports and the monitoring board could also be improved in terms of alerts. The threshold alerts are there but can be improved. It takes some time to get used to these methods and get the hang of them. 

I have been using AWS Lambda for about five years.

AWS Lambda is pretty stable.

AWS Lambda is scalable. There are some concurrency issues where threshold values play a role. We might end up making a request to increase those threshold values or the limit quota, but otherwise, it's pretty decent.

AWS Lambda tech support is pretty decent. 

On a scale from one to five, I would give AWS Lambda tech support a four.

Positive

The initial setup is more about usage. Implementing this solution takes about 15 minutes, but the code and debugging will take some time. Two or three people can manage and maintain this solution.

On a scale from one to five, I would give the initial setup a five.

AWS Lambda cost is pretty decent. 

I recommend this solution to new users as this tool simplifies mundane tasks and achieves a few things between the two systems.

On a scale from one to ten, I would give AWS Lambda an eight.