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. 

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.

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.