AWS Lambda Reviews

I use AWS Lambda for serverless services to avoid running applications on an instance. I use it for my personal website. When people want to view my website, the service is trigger-based, so it only operates when accessed, allowing for cost efficiency.

I like AWS Lambda as it is cheaper compared to other AWS services that require applications to be running continuously. Lambda is trigger-based, which means it only activates when accessed, ensuring cost savings. 

It's also serverless and makes processes easier despite the initial difficulty in setting it up. Being able to configure Lambda to work in a trigger-based manner is highly beneficial for my needs.

AWS Lambda is a bit difficult to set up if someone doesn't know how to code. It would be helpful to have a chatbot or resource that can guide users through the process, especially for those not proficient in coding. Setting up workflows that connect multiple AWS services can be challenging without guided support.

I've been using AWS Lambda for some months now.

There are no stability issues. AWS Lambda is very fast and secure, and I've not encountered any problems with it.

AWS Lambda's scalability depends on the number of users. It might not handle a high volume of requests efficiently, so it's better suited for small-scale operations where the number of users is limited.

The initial setup of AWS Lambda can be difficult, especially for those who do not know how to code. It took me about a week to set it up properly.

I am the only person maintaining the AWS Lambda setup.

I can't provide specific cost savings numbers, yet, due to the fact that AWS Lambda is trigger-based, it offers cost savings compared to instances that are always running.

AWS Lambda is cheaper compared to running an instance continuously. You only pay for what you use, making it cost-effective.

I would recommend AWS Lambda based on the use case. It's suitable for small applications where user access is limited. However, it's not ideal for large-scale platforms due to limitations in managing high traffic. 

I rate AWS Lambda a seven out of ten.

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 it for event-based retrieval. This is just to process for trigger purposes.

It has access to various other AWS resources like S3. You can use it to configure event-based triggers or conditions. You don't need to configure the servers; it will automatically execute the job and go idle. In that regard, Lambda is good and serves the purpose.

Integration capabilities:

They have the built-in IDE, so everything happens without integration issues. 

AI-features:

Just the Amazon Q [Amazon Simple Queue Service (SQS)] will also be there, like a pop-up in the AWS console. We can use that for Lambda as well, but no other integration. I wish there were AI integration for the code, like CodeWhisperer. That would be a good add-on.

They could add Copilot or their own suggestion tool, like CodeWhisperer, to the AWS IDE. The current IDE seems outdated and could be improved. 

Also, Lambda is restricted in terms of Internet access. 

You can't get public connectivity directly. You need to download packages manually elsewhere, zip the files, and add the layer manually. You can't install packages directly from the Internet, like PIP install Pandas.

I have been using it for two to three months. 

It is a stable product. 

On a scale of zero to ten, maybe seven out of ten, with ten being best.

I have faced a few challenges while implementing Lambda. There are possible limitations, like the timeout error. Initially, you'll have that timeout issue. Based on the scenario and load, you need to adjust the timeout manually. Otherwise, the job will fail, timeout, and go idle again. 

You need to manually verify the process, check the logs, and adjust the required time. 

Tip: Regarding layers, you need to manually zip and install them. This step needs practice, and you might need to do it several times. Be aware of that.

Deployment time:

For deployment, simple use cases need some apps to deploy. For new issues without proper documentation, you may need two or three days.

Maintenance and Costs

No maintenance is needed if it is deployed correctly. If it passes your tests, the function will work properly in the background. It's not expensive. It costs maybe less than ten dollars per month in my use case. If deployed on a manual server, you need to run it for the whole month. Lambda does the job and goes idle, providing good value for money.

It's not expensive, it is okay when it comes to licensing. It costs maybe less than $10 per month in my use case.

Overall, I would rate it a seven out of ten. 

My recommendation:

Regarding layers, you need to manually zip and install them. This step needs practice, and you might need to do it three to four times to get a hang of it. Be aware of that.

My primary use case for AWS Lambda involves completing tasks assigned by my teacher, developing projects with event-driven architecture, server management, auto-scaling, supporting multiple languages, and integrating with AWS services. I also use it for building APIs, file processing, data transformation, IoT applications, and scheduling tasks.

The most valuable features are its serverless nature, which allows deployment without worrying about infrastructure scaling or maintenance. The automatic scaling and pay-as-you-go pricing are also beneficial. AWS Lambda supports multiple programming languages, is highly available and fault-tolerant, and is easy to deploy with CI/CD. Event-driven integration capabilities are important too.

AWS Lambda's limited execution uptime of fifteen minutes and cold start latency for some use cases are areas that could be improved, especially for event-driven applications, backend services for mobile and web applications, and real-time data processing.

I have been using AWS Lambda for six to eight months.

The initial deployment of AWS Lambda took approximately ten to fifteen minutes. The deployment process involved planning Lambda functions, choosing a runtime like Python, Node.js, or Java, preparing dependencies, developing the function, packaging the code, deploying using the AWS management console, AWS CLI, or Terraform, configuring tests, and monitoring with CloudWatch.

I rate AWS Lambda's stability as nine out of ten because this level of stability is important as it provides confidence in handling unpredictable workloads, supports microservices, and ensures reliable performance for event-driven architectures.

I rate AWS Lambda's scalability as eight out of ten. It is important for handling traffic spikes, supporting global scalability, managing concurrent requests, and preventing bottlenecks in complex workflows.

Customer support is responsive, providing fast replies to emails and tickets, which is helpful for resolving issues quickly.

Positive

I have only two years of experience and have worked with AWS Lambda from the beginning. I have not used any other services.

The initial setup of AWS Lambda was easy, with a rating of nine out of ten. I faced no problems during the initial setup.

The deployment required two to four people, while maintenance requires a team of five to seven people.

AWS Lambda is not costly, and I rate the pricing as eight out of ten. Although it is expensive, it provides value for money. I do not directly pay for AWS Lambda as I am a student and use it within the context of a company.

Overall, I rate AWS Lambda nine out of ten. Scalability and stability are crucial for handling automatic scaling, supporting event-driven architectures, and flexible integration with AWS services. The technical support is efficient, and the integration capabilities are very beneficial for various workflows and projects.

Public Cloud

Amazon Web Services (AWS)

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)

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.

Public Cloud

We use AWS Lambda for various tasks, such as triggering reports, queueing calls for displays on our dashboard, and integrating with environmental variables for different outputs.

AWS Lambda saves a lot of time in our project deployments by allowing us to create users, establish user policies, handle voice mail set-ups, and develop dashboards with live views of agent status and queue additions, thus enhancing overall efficiency and cost-effectiveness.

One of the really handy features is keeping the environment variables in the Lambda for our outputs. It makes configurations more convenient as changes can be made through the environmental variables without altering the main code.

One area of improvement is Lambda's runtime version management. It currently requires manual user maintenance to upgrade and evaluate, and an automated provision for this would be beneficial.

We have been using AWS Lambda for more than two years, starting from the deployment of Amazon Connect.

AWS Lambda is quite stable. However, any changes in versions may require small code adjustments, which we must manage.

AWS Lambda offers a high level of scalability. It can handle multiple calls automatically when busy and reduce to one when free. I rate it a nine for scalability.

AWS offers excellent technical support. They have been very helpful, especially when one of our Lambdas was not functioning due to a minor code discrepancy that required a simple fix.

Positive

The setup for AWS Lambda is quite easy. The challenge lies mostly in ensuring our code is error-free for successful execution.

AWS Lambda is very cost-effective. It allows for one hundred thousand requests for free per month, and subsequent requests incur a very low cost per trigger.

Ensure that you have foundational knowledge of cloud formations or other AWS services for an optimal experience with AWS Lambda.

I'll rate the solution ten out of ten.

Hybrid 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)

AWS Lambda is used only by the DevOps team. I can use the solution to configure and set up all the requirements for testing the application and test code.

AWS Lambda should improve its compatibility with the language used to write the code. I would like to be able to choose a different language to code in AWS Lambda.

I have been using AWS Lambda for six months.

Around 15 to 20 users work with AWS Lambda in our organization. The solution is used by different teams, including the DevOps, testing, and development teams.

I faced some challenges when we worked on the migration. I raised tickets to the support team, and they helped me.

The solution's initial setup can be done with the help of documents.

AWS Lambda is not expensive for micro testing but is expensive if used for long deployment or long services.

It is not difficult for a beginner to learn to use AWS Lambda for the first time because it has good documentation.

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