AWS Lambda Reviews

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.

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.

In our organization, we have a huge number of users using Lambda, approximately around 100. We are using Lambda based on several considerations like costs, and scalability and it provides us with high availability and scalability in our processes.

Lambda being serverless is a great feature that is appropriate for our use cases.

Memory limitation is one of the weaknesses of AWS Lambda and as a result, we have to use several Lambda, instead of just one.

Recently, I met with an Amazon employee, who is responsible for Lambda as a product. It appears Amazon has some plans with Lambda, so I don’t have to add something to the additional features.

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

I would rate the stability eight out of ten because of certain bugs in the solution.

 I would rate the scalability eight out of ten because we have certain limitations in terms of memory and size. I see it as a gradual shift of mindset rather than limitation, where AWS Lambda is trying to incorporate everything according to the industry standards, which is everything is domain-driven design and suppression of microservices. Some people even have issues with the User Interface (UI).

We have a special collaboration with AWS, so we have regular meetings with AWS and Amazon, to report issues and they further report it to the concerned team. We have meetings, face-to-face and evaluation meetings with them and their solution engineers.

Positive

We previously used Azure and Volvo

The initial setup is straightforward. 

I implemented the solution  by myself because I was once a tech lead. 

I think the price is okay. However, if they add more functionality, they can have better prices. In fact, they should have better and more flexible packages for clients who have greater consumption of Lambda.    

I would rate six out of ten overall for AWS Lambda and all the Lambda solutions,. Because we don’t have the solution for each of our use cases. It is not available in various aspects and sometimes, it is not suitable.

AWS Lambda needs to improve its stability. 

I have been using the solution for a couple of months. 

I would rate AWS Lambda an eight out of ten. 

The solution is scalable. I would rate it around eight out of ten. 

AWS Lambda is cheap. 

I would rate the tool an eight out of ten. 

We are using the solution for creating the functionality. We store files over S3 and trigger that functionality to deploy our application. We use the solution for serverless activity. Once we store the files inside our S3 bucket, we write specific scripts in Lambda for auto-configuration. Afterward, whenever we send any data inside the S3, it gets automatically picked and deployed in the particular server.

The solution's most valuable feature is its ability to work as a serverless application.

They should work on the solution's stability and pricing.

We have been using the solution for a year.

It is averagely stable.

It is a scalable solution. I rate its scalability as a five.

The initial setup took work. I have worked on the development activity of the solution. The cloud architect of the solution needs to learn Python programming, like coding activities, to update new scripts inside Lambda. It requires a team for the process. I came across some issues during the deployment process and was able to fix them within an hour. So, fixing the problems after raising a ticket while deploying the solution takes time. I rate the setup process as two or three for a medium-level expert. Further, I rate the process as a nine for an executive with knowledge of Python programming. If everything works well, it takes 45 minutes to deploy the solution.

We took help from an Integrator to implement the solution. We were a team of a business analyst, DevOps engineers, and one developer working on the setup. We looped in another person in case we faced any issues.

The solution's price is average, and I rate it as a five for pricing.

The solution doesn't require any maintenance if you are creating an instance on your own. In case of any issues with Lambda services, you can check with their AWS support team. Also, they have provided a support portal inside the dashboard. You can ask for their help. 

AWS Lambda is a good solution. If you are well versed with Linux, AWS will be more accessible. I rate the solution as an eight 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.

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.

We're using AWS Lambda to trigger jobs and receive SQS messages. We're also using the tool as a single unit where you have computing, storage, and network.

AWS Lambda has improved my company through its usage in a distributed system, particularly event-driven architecture. When an event is passed to AWS Lambda from Amazon SQS asynchronously, the tool can call an ETL job, and it can trigger that job, and that job can trigger an AWS Lambda function, which can then send a message to the queue to complete the entire use case.

The most valuable feature of AWS Lambda is that you can trigger and run jobs instantly, and after you complete the job, that function is either destroyed or stopped.

The feature to attach external storage, such as an S3 or elastic storage, must be added to AWS Lambda. This is its area for improvement.

I've been using AWS Lambda for two years.

Stability-wise, AWS Lambda is an eight out of ten.

Scalability-wise, AWS Lambda is an eight out of ten.

I have not encountered any problems with AWS Lambda, so I didn't need to contact its technical support team.

We didn't use a different solution apart from AWS Lambda.

The initial setup for AWS Lambda was straightforward.

I saw ROI from AWS Lambda.

Price-wise, AWS Lambda is a five out of ten.

One person is enough for maintenance for a cloud-based tool, such as AWS Lambda.

I cannot share the number of AWS Lambda direct users in my company, as that figure is confidential.

My advice to others looking into implementing the tool is that it's easy to use as long as you know the basics.

AWS Lambda has good features, so I'm giving it an eight out of ten.