AWS Lambda Reviews

AWS Lambda is primarily used for serverless architecture. I have used it for web applications, particularly during my time at a company where we developed an image processing tool. It helps to trigger events on a runtime basis. AWS Lambda also has various other use cases such as machine learning processes and handling big data tasks.

AWS Lambda's serverless architecture and event-driven programming are highly valuable. You pay only for the events triggered, optimizing costs. It is beneficial for deployment CI/CD tooling and for triggering pipelines for data processing. The cost model is pay-as-you-go, with a tier for free requests and computational time. Scalability and stability are also very efficient.

AWS Lambda could offer support for more programming languages beyond Python and Node.js. The process for creating Lambdas could be simplified for beginners with less expertise in AWS.

I have been working with AWS Lambda for almost eight years.

Deploying AWS Lambda is pretty quick if the process is known. It takes between 30 minutes to one hour to deploy once the code is ready.

AWS Lambda is very stable. Issues are typically related to the user’s code and can be debugged through logs such as CloudWatch.

AWS Lambda's auto-scaling features are crucial for operations and provide great scalability. I rate the scalability of AWS Lambda at eight out of ten.

The documentation for AWS Lambda is comprehensive and thorough, eliminating the need for frequent technical support. A 2000-page guide covers all aspects, from setup to advanced use.

Positive

The initial setup of AWS Lambda can be somewhat challenging for first-time users, primarily due to the learning curve involved. I would rate it a six on the ease scale.

AWS Lambda has a cost model that aligns with usage. There is an initial free tier, after which charges apply based on requests and compute time. Different architectures have distinct pricing models. Despite being a bit expensive initially, the overall cost effectiveness is notable.

AWS Lambda should be used when there is a need for event-driven programming on an as-needed basis. It might become expensive if used for continuous processes. In terms of the overall solution, I rate AWS Lambda at nine out of ten.

Public Cloud

Amazon Web Services (AWS)

We primarily use AWS Lambda for our APIs. Most of our transactions flow through the API, which is managed using API Gateway and AWS Lambda. Our development team works on the API.

We use AWS Lambda because it provides a solution for our needs without requiring us to manage our infrastructure. With the tool, we only pay for the resources we use. Additionally, it is straightforward to implement and integrates with other services like API Gateway.

The tool's serverless nature has had the most significant impact on our workflow. I find it particularly attractive because it eliminates the need for managing servers. In my previous experience, managing upgrades and updates was quite challenging. 

The solution's integration process with other AWS services was relatively easy. We primarily use AWS services such as EventBridge for scheduling processes and log management. 

We need to invest time in learning the tool's language variant. We have encountered instances of downtime as well. 

I have been using the product for a year. 

I rate the tool's stability an eight out of ten. 

The tool is scalable. 

The solution's technical support is good. 

Positive

AWS Lambda's deployment is very easy. 

The solution follows a pay-as-you-go licensing model, which results in cost savings. 

I rate the overall solution a nine out of ten. 

I have used AWS Lambda for deploying our mobile application to integrate it with services like S3 bucket, Bedrock, or SageMaker. It serves to connect our local systems to call servers for mobile application integration.

AWS Lambda operates as a serverless architecture, providing quick responses to events without requiring server management. It supports multiple runtimes like Python, Java, .NET, and Node.js. Additionally, the Lambda timeout service allows processes to run for up to fifteen minutes, enhancing time efficiency. AWS Lambda is useful for integrating with CI/CD pipelines and real-time scenarios.

AWS should provide more trial support for new users and customers. AWS should also provide basic access to perform some actions using different tools on the AWS platform. This would help customers understand the types of integration possible and the various tasks they can perform using AWS services.

I have used AWS Lambda for around one year.

AWS Lambda is very stable, providing good response times compared to other cloud services and requiring a stable network connection.

AWS Lambda is highly scalable. I rate its scalability ten out of ten. It can handle large datasets, and its integration with other AWS services enhances its scalability.

I was previously manually creating models and deploying them to AWS S3 cloud buckets. This process was more time-consuming and took two to four days for large datasets.

The initial setup of AWS Lambda is easy. I would rate the initial setup process ten out of ten. It takes around one to two hours to learn and understand the use cases.

Only one or two people are necessary for the deployment and maintenance of AWS Lambda, as it involves data engineering and deployment only.

AWS Lambda pricing is moderate. You only pay for the services when they are used, unlike EC2 services. Sometimes AWS Lambda seems expensive, rating around five out of ten for pricing.

I have worked with Azure AI Studio and found Azure to have better performance for generative tasks compared to AWS.

AWS Lambda rates ten out of ten. For new users, gaining trial support and understanding the capabilities of AWS's integration are advised. I would give the overall solution a rating of 10 out of 10.

Public Cloud

Amazon Web Services (AWS)

I mostly use the solution for data dips or integrations with third-party applications.

The fact that it is serverless is really important. I can then deploy a microservices architecture. It is quite quick and nimble. The most useful feature for me is the API call, as well as the integration and its flexibility.

The runtime could be improved. There are certain use cases where I need a Lambda function to run longer. I don't know how many minutes it is, however, there's a threshold that I can't exceed. If that time was extendable, it would help in some areas, not all areas, yet some.

I have used the solution since Amazon Connect AWS launched, which I believe was in 2017.

The stability is high. I would rate it eight out of ten in terms of stability since nothing is perfect.

The scalability is ten out of ten. 

I have used their solutions for about ten years. They are pretty good at support.

Positive

The initial setup is fairly straightforward. If I am familiar and trained in an AWS environment, then yes. The AWS interface is not great, really. It can be improved, specifically the GUI, however, in general, if I am trained, I need to know how to use these tools. It is fairly straightforward.

I believe its pricing structure is good. On a scale of one to ten, its pricing structure deserves a nine, maybe.

Working with AWS and its solutions is definitely recommended. It is an integral piece of the puzzle, really. I'm basically a research site. I gather reviews of products, from AWS and also from all other vendors, so I can assure you there's no biased opinion here. You can actually find out about all other tools. I am really grateful that you benefited from our website and the IT community with your feedback about AWS Lambda. 

Overall, I would rate the product at nine out of ten.

Public Cloud

Amazon Web Services (AWS)

I use AWS to host our app space within my university, APU. My infrastructure is based on the AWS cloud, and most of my compute workloads are primarily based on Lambda. This setup facilitates all transactions that require engagement from multiple stakeholders, including staff, faculty, students, and administrative staff. I have in-house applications, both mobile and web-based, that engage with Lambda to provide the required scalability, especially during peak hours of university timings. Lambda is a highly utilized service for me.

The most important feature of Lambda for me is that I don't need to manage any resources. I don't have to set up an AWS stack or developer tools, as they are provided by AWS by default. This means that if I need to set up Lambda, it's a matter of minutes to deploy my code, which facilitates my CI/CD pipelines. Time is an important optimization for me, and Lambda is economical. Additionally, it is highly available and sustainable, unlike EC2, which is a single point of failure. Lambda saves me time in configuration and deployment and gives me confidence in its high availability and scalability. I have done my workload migration from an on-premises environment to the cloud, significantly reducing my capital expenditure. The automation improves my planning for product releases and hybrid connectivity. Also, content delivery has improved, and application latency has decreased.

I would say an increase in the current limits would be quite beneficial. Right now, the threshold is fifteen minutes. AWS has increased the limits from three to ten gigabytes, enhancing the productivity of different workloads. If this threshold is extended further, more workloads currently utilizing EC2 could potentially be executed using Lambda.

I have been working with Lambda since 2018.

Speaking of scalability, I would rate this aspect as close to nine out of ten. So far, I haven't had any issues with the usage of Lambda. Since AWS launched its region in Malaysia, the compute is happening right next to my location.

Support is of the highest quality, so I would give it a five out of five.

Positive

Before Lambda, I mainly used my on-premises environment.

The entire Lambda project took less than three months. I'm not the team lead for that setup, so the exact timeline isn't possible for me to provide. Currently, I'm mainly in the training division.

Maintenance of the overall cloud setup involved less than fifty people. They are not only for maintenance, as they are also involved with enhancing other solutions. I would include developers who are creating new products and releasing them. So overall, the staff is around fifty, but specifically for maintenance, there are fewer people.

Azure was one of the options during my evaluation, but I decided to go with AWS.

I would suggest newcomers go through the AWS Well-Architected Framework, especially the serverless application stack offered by AWS, such as Lambda. The cloud adoption framework by AWS is quite in-depth, providing many integration points for reskilling and handling workloads. It’s crucial to explore these frameworks before migrating workloads to the cloud. Additionally, looking into AWS CloudFormation for automating infrastructure provisioning is beneficial. I would rate AWS Lambda as nine out of ten.

Public Cloud

Amazon Web Services (AWS)

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.

Public Cloud

Amazon Web Services (AWS)

We have one or two use cases for real-time file processing. We use the event triggers to detect file arrival.

AWS Lambda is serverless. It is quick to deploy. The event-driven execution model has improved the project efficiency because it is quick and easy to deploy. However, it also introduced a set of new problems. It is the industry traction ever since the network went fully API.

Since the tool is serverless and it is hosted in the cloud, we do not need an initial capital investment on servers. We can pay as we use. We have integrated the product with other AWS services. We use SNS and SQL. There is an offering from AWS for integrated solutions.

We face some problems with the event-driven execution model.

The tool is very stable. There are certain things that we have to do to support it, but once we cross the t's and dot the i’s, it works.

The initial setup seems to be very straightforward.

I will recommend the solution to others for serverless computing needs. It’s a quick delivery. We do not have to set up servers before we start deploying. Overall, I rate the product a nine out of ten.

I use AWS Lambda for serverless computing, and I am charged only for the AWS Lambda instances I use. I value its cost efficiency because it activates instances based on load and tasks initiated.

I appreciate AWS Lambda for its serverless computing, with charges incurred only for the used instances. This serverless architecture enables the activation of instances based on task load, contributing significantly to cost efficiency.

Currently, I don't have any specific suggestions for improvements. However, enhancements could be introduced to better satisfy customer requirements.

I have used AWS Lambda for around two years.

The initial setup of AWS Lambda is quite straightforward and easy.

I rate the stability of AWS Lambda as a ten out of ten, suggesting that it is highly stable.

I rate the scalability of AWS Lambda as eight out of ten. Although it is stable and scalable, the number of instances can be optimized for other workloads when needed.

I rate AWS Lambda's technical support an eight out of ten. The support can be improved by increasing the number of support personnel.

Positive

The initial setup of AWS Lambda is quite easy.

The pricing of AWS Lambda is reasonable. It's beneficial and cost-effective for users regardless of the number of instances used.

I recommend Amazon Web Services Lambda to other users. I rate AWS Lambda as one of the best solutions, giving it a ten out of ten overall.

Public Cloud

Amazon Web Services (AWS)