AWS Lambda Reviews

I have to send daily reports. We have many child accounts in AWS Organizations. We need reports on the cost of the accounts. I use AWS Lambda because we have to run the code without provisioning the servers. AWS Lambda is a serverless computing service.

The tool scales automatically based on the number of incoming requests. It supports multiple languages. We can use Python, Java, and Ruby. We can use the solution to stop and start the instances.

We must at least know the basics of languages like Python or Java to implement automatic processes and daily schedules. We must learn the Lambda function and the languages to use the tool.

I have been using the solution for three months.

I rate the tool’s stability a nine out of ten.

I rate the scalability an eight out of ten. We have more than 100 users.

The support team does not know how to implement and build the solution.

Neutral

We must know Python or Java to implement the product. It is not easy, but it is not difficult. We need some experience.

We only need to pay for the compute time our code consumes. The solution does not cost much.

I will recommend the product to others. We can automate the processes and integrate the solution with other services. The product provides elasticity and automatic scaling features. Overall, I rate the product 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. 

I primarily use AWS Lambda for building serverless applications. I integrate it with services such as S3 and DynamoDB.

The capability of AWS Lambda to automatically scale thousands of requests simultaneously without requiring manual intervention is invaluable. 

Additionally, its integration with other AWS services such as Amazon S3 and DynamoDB has been very beneficial. The pay-as-you-go pricing model ensures that I only pay for the resources used, providing cost-effectiveness. 

The serverless computing feature eliminates the need to manage servers, provision, or scale.

AWS Lambda has a limitation where the execution time is capped at 15 minutes per task. Increasing this time would allow for handling heavier tasks more efficiently. 

While the documentation is satisfactory, beginners might encounter some challenges, so any improvements could be helpful.

I have been working with AWS Lambda for about six months.

AWS Lambda is quite stable, with a high level of availability and the ability to distribute functions across multiple availability zones. I'd rate it at nine out of ten in terms of stability.

AWS Lambda can automatically scale to handle increasing requests. For example, I used it in a personal project to integrate with a Simple Notification Service, which ensured I received real-time notifications during peak times without manual scaling.

I did not use a different solution before AWS Lambda.

The initial setup was moderately challenging, especially for beginners. Although the documentation is adequate, new users might find it not entirely straightforward and may face some challenges. It took me around five to ten minutes to deploy Lambda for the first time.

I deployed AWS Lambda by myself while learning about it and sought help from friends when necessary.

Lambda provides a cost-saving advantage because of its serverless design and automatic scaling without manual infrastructure needs. Its pay-as-you-go model means I only pay for what I use, which is financially beneficial for handling applications with fluctuating traffic levels.

AWS Lambda is cost-effective and flexible, particularly suitable for small applications. I am using the service within a free tier account, which influences the pricing experience.

I rate AWS Lambda overall at ten out of ten. New users should thoroughly read the documentation and start with small projects to understand the platform. It's important to be aware of AWS Lambda's limitations, take advantage of monitoring and debugging tools, and stay updated with new releases. Joining a community for learning and sharing is also recommended.

I have used AWS Lambda for simple messaging for SQS, creating a cron job, and delay messaging. Creating a cron job ensures emails are automatically sent to users at a specific time we set. For example, a mail would be sent automatically instead of manually to a user whose subscription is about to expire.

AWS Lambda functions have many versions. Sometimes, it takes a little time to load and run the commands in AWS Lambda. We can write anything as code, but the solution will not give proper error information. It is a little time-consuming to understand where the error came from.

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

The solution's initial setup is easy. You can easily code in AWS Lambda if you have good coding experience in any coding language.

The solution is free of cost for the first year, and after that, it becomes expensive.

If you are using AWS Lambda for the first time, you need to know about AWS. You need good coding knowledge to work with AWS Lambda. If you want to code a node, you must know about node and node syntax. If we are using AWS Lambda with Python, you have to know about Python. It is easy to learn AWS Lambda if you have good coding knowledge.

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

Lambda is essentially a serverless computing service offered by AWS. It allows you to run your code or applications without needing to manage servers. You can deploy your IT code or applications, and it seamlessly integrates with other AWS services, like S3 for data storage. You don't need to purchase or manage any servers. So, Lambda offers a way to run applications without the complexity of infrastructure.

The best feature of AWS Lambda is its scalability and security. It's a highly scalable service, making it suitable for a range of applications.  

AWS Lambda, like other services offered by AWS, SAP, or Azure, is already quite advanced. However, when considering improvements, it's more about how you write and optimize your applications.

There's always room for enhancement in terms of resource allocation and management for high-demand applications.

Performance issues can arise depending on how you allocate resources within Lambda. For example, if you're running a new application with a significant load, you need to be prepared for potential bottlenecks. 

It's essential to control network interactions and optimize for the type of application you're running. Lambda is excellent for small and lightweight applications, but for more resource-intensive tasks, you might need to look at other AWS services or a more distributed storage environment.

AWS Lambda could greatly benefit from enhancements in handling large-scale applications to support heavy workloads. This is actually feasible, but there is a need for further development in this area. 

Additionally, improvements in resource control optimization are crucial. For instance, enabling users to run data-intensive applications using a limited number of resources without compromising performance would be a valuable addition.

I have used it for three years.

I have interacted with the AWS support team. They have a large customer base, which sometimes leads to delays, but overall, their support is excellent.

They categorize issues effectively and provide prompt support for critical issues. Even for less critical issues from the customer's perspective, their response is adequate. They are usually quick to respond, especially when the issue is critical, and they provide effective support.

Positive

The initial setup of AWS Lambda is very straightforward and quick.

If you have a data application with a huge number of users that requires frequent user interaction, AWS Lambda may not be the best fit. However, it's suitable for applications with less frequent user interaction, like those accessed periodically, maybe every few minutes or hours.

For lightweight applications, AWS Lambda is a ten out of ten.

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.

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.

Usually, it is for small transactions. They're very atomic transactions. For example, we built a solution for an ad platform where an electronic ad runs for about 15 seconds a piece. Every time one of the ads runs, we have to record where did it run, how long did it run for, who was in the room, and how many people. There is a bunch of data around that. We typically send that transaction through an Amazon Kinesis pipe into a Lambda function, and then Lambda will take it and store it in S3 or target it to Redshift or put it in some kind of data store. That's one example of what we would use it for. That's a typical model for Lambda. 

It is serverless and scalable. It can scale infinitely. You don't have to worry about the size of the servers that you're pre-allocating. You don't have to build server scale-out models. Auto scale and other similar features are just inherent in Lambda. So, for atomic and fairly non-persistent transactional units of work, Lambda works very well.

My engineers work with it on a daily basis. I just don't have enough depth of knowledge about what kinds of edge cases they may have tried and found lacking. There may be some issues with some language support at one point or another because we couldn't get the underlying libraries in there. A lot of what we do is either in JavaScript, Python, or some of the non-compiled languages. I'm not sure if we've ever tried building a C# solution, for instance, in Lambda or a Java solution in Lambda. It doesn't mean those aren't its capabilities. I would rather refer to my engineers for where the boundaries are.

It has probably been five or six years since we've been migrating functionality from EC2 instances to Lambda.

Its stability is really good, and it is also highly available. The stability is inherent, but it also naturally gives you a high availability model because you don't have to have multiple EC2 instances running in, for instance, different regions. It is baked into the model. So, you can allow for inter-region Lambda functionality. It all becomes very highly available across Amazon's footprint.

It is endlessly scalable. In terms of its users, Lambda is typically baked into the middle of an application somewhere. Our ad platform solution is a fully-automated IoT solution. So, there are no people involved. The whole thing is automated from end to end. So, sometimes people don't even come into the equation.

We probably do or have dealt with their support, but that would be at the end engineer level. It is not something to which I would have much visibility. 

It is straightforward in my understanding. From the engineering perspective, I haven't gotten feedback that it is at all burdensome.

You're not paying for a server if you're not using it, which is another reason I like it. So, you're not paying if you're not using it. It scales, and you're charged based on usage. It all depends on the use case. Some can be extremely inexpensive if you have very low volume transaction rates. That way, you don't have to fire up and absorb the cost of the servers just sitting there waiting for a transaction to come through. You're only paying when you use it. So, depending upon the use model, Lambda could be highly efficient relative to an EC2 solution. You don't have to have things reallocated.

Understanding what your use model looks like is the key. All these cloud providers have so many different ways of implementing a solution that you really have to understand the near-term and long-term picture for that solution. What does it look like? When you're first building it, there might be a more expedited way to get it off the ground, but that may not scale properly, or your cost can get out of control. So, it is very important to align the right set of features within an AWS or Azure environment for not just getting the initial MVP built but also making sure that you're building it in a way that allows scaling and optimization of the cost model over time as the application scales. There's no one answer. The way you build the solution in the cloud is very dependent upon what the use case is.

From my perspective, not being at the engineering level, I would give it a nine out of ten. There is always room for improvement, but it has been a terrific advance over what was previously available just having to build everything in EC2.