AWS Lambda Reviews

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.

We primarily use the solution for integration purposes. We use it very closely with Jira, for example. 

The workflow is the best thing about the product. When the integration happened and from where to where is something we can see automatically and navigate the workflow. 

From Jira to AWS Lambda, we're sending data. When we go from Jira to AWS, through webhooks, we are sending data to the Lambda function. From Lambda, they're navigating Jira. Whenever the manual rework is done, they need to perform some job bundles from the AWS to the Jira only. They can operate from Jira to AWS and AWS to Jira, which is great.

The initial setup is pretty easy. 

I don't have much experience after six months. I can't speak to the pros and cons. 

I have seen some drawbacks with certain integrations. 

I started using the solution six months ago. 

I'm not aware of any issues with stability. It's been issue-free so far. 

The solution can scale. We can add more users to it. We have ten to 15 people on the product right now. They are developers. 

I've never needed to reach out to technical support. I haven't had any issues. I can't, therefore, speak to how helpful or responsive they are. 

We found the setup to be straightforward. It's not complicated at all. 

It took me one day to get everything up and running.

I'm not aware of the exact pricing. I don't handle any licensing. 

Our company is looking into ServiceNow to see how it handles integrations. 

We are a customer and end-user. We use the cloud for integration purposes. 

I'm not completely into AWS Lambda just yet. What I can say, integration-wise, Lambda does not require any username or password from the Jira once they start talking to each other. It's integrated very well. 

I'd recommend the solution to others. 

I'd rate the solution seven out of ten. It is a very new tool for me; I need to do some more research on it to really understand it fully.

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.

I have found this solution very useful. By using Lambda, we can use Python code and the Boto3 solution. 

The triggering feature is also valuable. For example, if we are using Kafka, we need to be aware that the language comes in Kafka when we write in Python, and that we are transforming our data into the meaningful server and dumping that into the S3 bucket.

I would like to see a find and replace function as part of Lambda's future releases. Currently, if we want to replace a code, we copy the code into Notepad, then find and replace it, and then copy that to Lambda. This would improve the editing function of the product.

Lambda would benefit from a debugging feature as well. For example, if you want to debug code running in Python and deployed in Lambda, it would be beneficial to have a debugging feature.

I have been working with AWS Lambda for one year.

The solution is stable. There are times when we do need to refresh when we make changes and deploy them. This seldom occurs.

We have five developers using Lambda. 

Technical support can take a long time to respond. I would rate their service a seven out of 10.

Neutral

The initial setup of AWS Lambda is simple.

I would rate this solution a seven out of ten overall. 

AWS Lambda has serverless programming, like Logic Apps from Azure. You just configure the run-time and then they start coding. It is event-driven. It started with my obtaining Salesforce. Salesforce is a low-code and non-code program and totally SAS. Everything starts from the event, from the trigger. You get the trigger and you work at the program. You have some other models, maybe faster or fancier models. But in my opinion, this kind of program is started by locating the system and identifying where the trigger and entry point of the program are. Then you get the full advantage of the program. You don't need to worry about any infrastructure.

I think this is the future. Compared with the EC2, you don't have to pay anything if you don't run it. Otherwise, with EC2 when our client provisions the system and the instances, you always have to pay. There are other tremendous advantages, like flexibility. After you provision EC2 you can write something that does not totally follow the cloud convention. You use it to provision the container. With the program you need to have those 10 principles of cloud computing. Especially recently, within the past four or five years, I have gotten away from DevOps, or the software development life cycle. Even though I researched the product portfolio from DevOps and then the life cycle for DevOps, I try to position myself as an architect with hands-on experience.

In my opinion, Lambda is very similar to Salesforce, which is the original for the SaaS platform and is an extremely low-code environment. With Microsoft and AWS you can say, "Okay. You can choose whatever language you need to make it even more flexible." 

Everything is the cloud. Lambda is a fully managed service. If you want to do it either as a private cloud or on-premise, I'm sure you can do that, too. But I don't know how to manage the pricing structure. But then you've lost the point of Lambda because if you do not use it, you do not pay. Again, I just want to emphasize, I'm not a Lambda expert. But, logically thinking, the big advantage of serverless programming for the customer is that you just use it and pay. Pay and go. You don't need to provision anything.

All my experience with AWS Azure is on the public cloud. We do not get too deep. In IBM we do. When we do sales training we always get the private cloud on-premise. There are many reasons for this. One reason is that IBM lost the battle for the public cloud so we get into it much deeper. We go to the enterprise and we can deploy programs to your data center and offices. But for the tech data for AWS and Azure, we are all using the public cloud as a showcase when we talk to the customer and to the retailer.

The number one feature with AWS Lambda is that it is fully managed. From the developer's perspective, you get the coding much more easily. Now many situations are not using code. You plug in, assemble it, and configure it. Lambda makes it low-code. I come from being a Java certified developer for 15 years. You configure the environment for deployment just like in DevOps. That was always the most challenging part as a developer. You identified when to trigger it. If the program can't facilitate it, then 80% is gone. With 20% you just Lose Syntax. You can use Lose Syntax with any programming language as a reference finding out the variables, the statements, the loop, and what other kinds of things you can do. Just follow that to where you can plot it into your business system. 

They might think to have the business benefits say, "Hey, if you don't like it, no need to pay." So, potentially, you can save. If the future is going to be serverless, that's what I think the future of something like Salesforce will be. Programming is getting much easier and does not need a lot of configuration because step-by-step abstraction starts from the infrastructure service. You can replace your hardware, but you still need to do a lot of things in the abstract. The environment now is totally fully managed. I'm not sure if we're totally aligned there. I always talk against those aspects in the Salesforce situation. But I believe Lambda is a comparable peer, apples to apples.

I can only speak from the user experience. Salesforce integrates SharesPost efficiently. How? They say, "Okay, I invented another language called Apex. Forget about anything else. This is my language." The benefit of this language is that everything is simplified. Your system is super easy to maintain. But AWS then assures you that they are flexible, that they have a collection of 10 or 20 languages, and you just choose your environment and range. That's the reason I appreciate Salesforce. They always make things easier. They have their loop reasoning because they are a different kind of company. Microsoft and AWS really get the full spec. They want to own the business. But Salesforce data wants the simplest way.

So, this is my understanding and unique experience.

I think that perhaps Lambda could explore its functionality more.

I have been using AWS Lambda for a few months.

I didn't explore enough information to evaluate that.

I didn't experience the scalability personally, only from my reading. Amazon takes care of the scalability. That's the right way. It's automatic and it's fully managed. That's one benefit of Lambda.

We have all kinds and sizes of resellers. There are large enterprises and small businesses. It's different. And some of them are product based, they are creating their own products. Some of them are consultant based. It's really different. Tech data is different vs. a business model.

I contacted support many times. My experience was very little and I just saw how Lambda was working, to try to understand if it is okay.

I don't actually use AWS Lambda. I'm a distributor. I try to explain solutions to the vendor. I previously used Salesforce Apex. I use the Azure Logic App service.

Salesforce does not have so many options to choose from, such as Java or C++. Salesforce said, lets invent a language. They call it "invent" but actually they just made a simplified edition of Java and eliminated a lot of complex features. Now all the syntax is the same. Salesforce is a business company. They focus on business solutions development and they make the customer's lifecycle development simple. AWS really does not stick to any business because they are a technology company.

Let me explain the similar things that Lambda has to Salesforce. When you get the event you have to see our form. With the sales approval process, if you have the 50% to get to the half million and above, you need the vice president to get the approval. You can use this trigger based serverless program. All you want to do is to write down the logic and then put it under the trigger of whenever a certain number changes in the half billion, and then you need to do the multiple steps.

This kind of programming is easily defined in the business. All you need to do is get the logic done, get it tested, see the steps you are doing, and then fix up the errors. As for Lambda, as I said, I've just experienced two very simple examples in the AWS, but they were the same thing.

Logic App and Lambda should be doing the same thing - fully managed coding. You focus on the logic triggered by the certain events. And there are other additions within the Lambda family. It can be scheduled as a batch job. I don't think it's originally lack of motivation from the serverless. The serverless is from the trigger.

The initial setup is straightforward. If you follow a 30 or 45 minute lab, it seems pretty clear.

Everybody should check out AWS Lambda. That's why I didn't explore much and it was at the top of my list. This is a fully managed model. The number one. This is for the future. In the future, many of the EC2 applications may be replaced by Lambda. If I started something from scratch, I would try to use Lambda. It's much simpler. It can simplify a lot. If you add the scalability into the picture, it could have 80% or 90% of the complexity. They are very important. All the servlets are very important from a cloud computing perspective.

On a scale of one to ten, I would rate AWS Lambda an eight.

I am a fan of the no-code, low-code if you consistently improve to make it even simpler. Maybe they could do something to simplify the language. I'm not sure if Lambda has the code for the Microsoft Logic App, which means they can eliminate most of the code and everything becomes drag and a drop. Because they eliminated those "if errors." They have those kinds of functions. I think mostly because I have not explored the whole portfolio of AWS. I believe there is a full suite of them.

I believe their full suite of the service is complemented with Lambda. But I do believe the competition is going to make it simple with low-code, no-code. There is no-code, low-code and also no infrastructure. That is going to be the key. Also, maybe you can have the Lambda ecosystem and have some component of the module built above the Lambda so that people can make graphing and plotting even easier. This is not just any software, you get the module there which is much better. But AWS is big enough to neutralize the ecosystem. I believe it will come but the people don't have the patience to start from scratch these days.

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.

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.