AWS Lambda

AWS Lambda

Customer Verified
AWS Lambda



Power of lambda

Process terabytes of data broken down into small files of 70MB each. Our Lambdas spin an instance for each file and process it within 30 …

AWS Lambda for developers

AWS Lambda serves various purpose accross teams
1. We mainly use AWS Lambda when we have very short time to productionise code and have …
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AWS Lambda rocks

We use Lambda to manage workloads integrated with our API Gateway.
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Popular Features

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Scalability (47)


Services-enabled integration (46)


Platform management overhead (43)


Issue monitoring and notification (43)


Reviewer Pros & Cons

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128 MB


Per 1 ms

1024 MB


Per 1 ms

10240 MB


Per 1 ms

Entry-level set up fee?

  • No setup fee


  • Free Trial
  • Free/Freemium Version
  • Premium Consulting / Integration Services

Features Scorecard



Product Details

What is AWS Lambda?

AWS Lambda is a serverless computing platform that lets developers run code without provisioning or managing servers. With Lambda, users can run code for virtually any type of app or backend service—all with zero administration. It takes care of requirements to run and scale code with high availability. Users pay only for the compute time they consume—there is no charge when their code is not running.

Developers uploading to Lambda don’t have to deal with their code’s environment. It’s a “serverless” service which lets outside code or events invoke functions. Lambda doesn’t store data, but it allows access to other services which do. Users can set up their code to automatically trigger from other AWS services or call it directly from any web or mobile app.

AWS Lambda Technical Details

Deployment TypesSaaS
Operating SystemsUnspecified
Mobile ApplicationNo


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Frequently Asked Questions

What is AWS Lambda?

AWS Lambda is a serverless computing platform that lets users run code without provisioning or managing servers. With Lambda, users can run code for virtually any type of app or backend service—all with zero administration. It takes of requirements to run and scale code with high availability.

What is AWS Lambda's best feature?

Reviewers rate Scalability and Services-enabled integration highest, with a score of 9.4.

Who uses AWS Lambda?

The most common users of AWS Lambda are from Mid-size Companies and the Computer Software industry.

Reviews and Ratings




(1-25 of 305)
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Score 10 out of 10
Vetted Review
Verified User
Review Source
We generally use AWS Lambda to create small functions which will run within 15 minutes these functions generally carry less load and are very economical from the business perspective so for example if we have 60 APIs in a project so we can expose around 40 API is which doesn't do much work in a lambda function and the monthly costing is also quite low the only problem with a Lambda is that it the first request actually start the Lambda engine in the backend of Lambda we have a docker so the first request generally takes some time but after the first request, all the other request generally works quickly.
  • Lambda server and API function.
  • Serverless deployment.
  • Time constraints to extends more than 15 min.
Lambda is best suited for the function which runs for a short period of time and which has a listed dependency so for example if a function has more dependency we can divide it into multiple small functions.
Score 8 out of 10
Vetted Review
Verified User
Review Source
AWS Lambda is widely used in our organization by a number of development teams. It is used in both one-off tasks and coordinated workflows. My team is responsible for infrastructure management, and there are many use cases for which we have opted to use AWS Lambda. AWS Lambda is often a good choice for us when we do not need a standing compute resource.
  • Broad support for different language runtimes: Python, Node.js, C#, Java, Golang, Powershell, Ruby
  • Save money on compute resources by paying by request volume and memory used/time
  • Integrates terrifically with a number of other AWS resources
  • Cold start--you have to account for the runtime environment being spun up every time; for a heavy operation, that can increase runtime duration and, in turn, cost
  • You have to consider networking, which is also true of other compute resources, technically
I would recommend using AWS Lambda when you have one-off tasks that can be accomplished with a single function and do not require a persistent, constantly running compute resource. Some example use cases include file or image processing, data analytics (you might have DynamoDB stream updates to AWS Lambda for processing), in conjunction with API Gateway as a backend.
I would not recommend using AWS Lambda when your Lambda function has potentially long-running, asynchronous calls involved (e.g., calling out to a service hosted in another cloud platform). This can drive up execution time and, in turn, cost. While Lambda layers allow you to share code between Lambda functions, I would not recommend AWS Lambda for cases where there are high degrees of interdependence between the Lambdas. I think that Lambdas work better when considered isolated.
Ojas Elawadhi | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
[AWS Lambda] is being used in specific departments of the company as and when we require it because cost is involved depending upon usage. This can be integrated with multiple AWS tools like redshift, S3 and many other services that helps in easy processing of data. This has positively impacted our maintenance cost.
  • This can be incredibly cheap as you use it whenever you want.
  • This is heavily scalable
  • You can Swiftly deploy and execute the code
  • The documentation is not very clear and could be made more informative
  • Plugins are very limited
  • Logs are very hard to debug
[AWS Lambda] is very well suited for the projects that doesn't have any infra but needs it where short running processes are required. But if your application need to run continuously than this might not be the very apt tool for you.
The customer support is really great and we get a solution for any of our problem in desired amount of time.
June 03, 2021

Power of lambda

Akash Singla | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
Process terabytes of data broken down into small files of 70MB each. Our Lambdas spin an instance for each file and process it within 30 seconds. This way the entire batch of 320,000 files is finished in about 2 hours.
  • Execute small tasks quickly.
  • Monitoring can be easy.
  • Integration with s3 and SNS is a boon.
  • Trigger quickly and easily based on events.
  • Deployment via cloud formation.
  • Importing libraries.
  • Execution time could be longer.
Process large datasets where bigger files are broken into smaller ones. Executing step functions. Submitting requests for Sagemaker pipeline. Submitting queries to Redshift data API. Managing dynamodb records (read-write).
The experience we have had with the scalability and efficiency of Lambda is worth noting.
Erlon Sousa Pinheiro | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
We are using AWS Lambda as [much as] we can and when is feasible. When I say feasible, I mean we should observe AWS Lambda limits and costs because even [with] AWS Lambda being an amazing product, you need to be careful with costs since every call to a function will charge you.
  • Triggers from state changes on other AWS technologies.
  • Automate process when someone interacts with AWS S3.
  • Create functions to keep compliance aspects.
  • AWS needs to increase timeout limits for Lambda functions.
  • More templates would be welcome.
  • A better and cheaper charge policy.
I believe the main concern is about costs. If your function calls generates profit, no problem with the amount, as more [is] better. But if this is not the case and your user case trends to grow without associate profit, maybe by provisioning dedicated resources (EC2 instances for example) to run your functions will hurt less in your wallet.
As this is a product where a great part of errors can be at the source code level, AWS support team doesn't dive that further. I mean they don't evaluate problems more complex related to your code, [which] is totally understandable, but this make[s] debug process more tough and painful.
Sai Sreenivas Addepalli | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
We use AWS Lambda to upload data from API to store in AWS. We have also integrated it with AWS DynamoDB, Redshift, S3, Kinesis, MSK, and many other AWS Services for further processing of the stored data. It is being used by a single department. It reduces the maintenance cost and makes development easy. Makes it easy to address any issues in the APIs without any problem to the other Lambda.
  • Serverless Framework. Easy to develop and test in local environment
  • Easy to detect issues. As it does not interlink to any other lambda.
  • There are shared layers in Lambda that can provide common code to be shared between Lambda. Helps in Avoiding the same code to be written multiple times.
  • Difficult to identify all permission issues at once. It would be easier if we can get a list of all permissions which are required to further proceed.
  • Lambda output to trigger more Services. Currently, it supports only 2-3 Services.
  • It would be great if AWS can handle the Lambda cold starts internally.
AWS Lambda is most suited as a Serverless methodology. When you do not want to handle the software and only want to work on logic and code development, AWS Lambda is the best option. You can also trigger AWS Lambda from many AWS services like when a new row is added into DynamoDB or when a new file is uploaded to S3 or also when you want to execute Lambda once a day or at a specific intervals(cron jobs).
Ravi Khunt | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
We have requirements in some projects to run some code backend side without user interaction.
So we developed task schedulers to run cron jobs.
Task schedulers do their jobs, but sometime operating system updates may break those jobs, also it uses our CPU.
Then we are finding new solutions to resolve this issue.
We found great service providing by Amazon which resolves our issues.
Now we are using Lambda to run cron job.
  • Run cron jobs.
  • Remote function call.
  • Run server less node js code.
  • Create lambda complexity for new users.
  • Complex cron job syntax.
  • Errors logs can be improved.
AWS Lambda works very well when you want to execute some code without our server interaction.
It provides sample code also, so you can quick start building our own functions.

AWS Lambda has very much pre-defined expression structure which can fit almost all our scheduler job requirements.
It also provides test functionality to test function before go to live.
Score 8 out of 10
Vetted Review
Verified User
Review Source
AWS Lambda is mostly in use by our DevOps department with Web portals testing and implementation to support our projects on cloud. We mostly use HTML conversion Lambda functions with our conversion services. It is greatly helpfil to reduce cost of usage and improve integration with Simple Notification Service. Also we work on smart recognition of documents buckets.
  • Serverless compute lets you run code without provisioning and managing
  • It is helpful to reduce costs and administrative loads for web development or mobile apps
  • Easy to manage the compute resources on AWS
  • Better integration with containers
  • API Runtime should be improved with support and integration for other program languages
  • Improves documentation in part of security and network port usage
  • Limits programmers to 1,000 concurrent executions
Working with Web and mobile apps well suited for Lambda. It provides a clear support path and improvement. Also it helps to reduce cost and accelerate speed of reaction on changes.

A sess appropriate scenario would be when CIO push to implement new technology and services without clear understanding of the results and project needs.
AWS always has high level support for their products. Even for new products, they provide fast and consistent answers for customers. Our AWS technician knows the product deeply and can help in most cases with advanced recommendations. Sometimes they point to documentation and demand search and trying simple things first. They provide web links to accelerate the process.
Score 10 out of 10
Vetted Review
Verified User
Review Source
At my current place of work as well as for personal projects AWS Lamba is currently used for many different projects. A few examples are "image resizers", "data processing" and invalidating cache from a 3rd party webhook. It allows for quick, easy, and inexpensive setup and maintenance especially using 3rd party libraries like "Serverless".
  • Easy to use
  • Performant and reliable
  • Can be incredibly cheap
  • A bit of a learning curve when first starting out
  • A refreshed UI to manage AWS Lambda
A great example of using AWS Lambda is when your application needs to be able to render images for the user and have those images be resized and optimized on load. Using AWS Lambda you can create endpoints with a minimal amount of code that allows your applications to request the images and use query parameters to declare the height and width etc.
Score 9 out of 10
Vetted Review
Verified User
Review Source
AWS Lambda serves various purpose accross teams
1. We mainly use AWS Lambda when we have very short time to productionise code and have little time to worry about infrastructure.
2. AWS Lambda takes care of scaling and dynamic increase in inflow of traffic.

  • Scalable
  • Less Infra headaches
  • Just write code and don’t worry about devops
  • Less plugins
  • No integration with springboot
  • Need to provide all library and no management
Well suited:
1. when we need to worry about time to market and we don’t have infra defined.

Not suited:
1. Not suited for Business Client transactions as its server are located out of Switzerland and hence country laws are different
1. The community support is great, At many instance the documents worked for me.
Michael Jenkins | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
My team uses AWS Lambda in two primary ways: as a back end service and as middle-ware for log processing. As a backend, Lambda provides the compute for APIs fronted by AWS API Gateway or one-off tasks that can be handled in the cloud by a small piece of code. As a middle-ware for log processing, Lambda processes logs ingested by AWS Kenesis by feeding them into AWS Cloudwatch and third-party logging services.

Lambda provides an interface to managed compute resources without the overhead of the team having to mange servers or other resources.
  • Lambda provides multiple methods for triggering functions, this includes AWS resources and services and external triggers like APIs and CLI calls.
  • The compute provided my Lambda is largely hands off for operations teams. Once the function is deployed, the management overhead is minimal since there are no servers to maintain.
  • Lambda's pricing can be very cost effective given that users are only charged for the time the function runs and associated costs like network or storage if those are used. A function that executes quickly and is not called often can cost next to nothing.
  • Developing test cases for Lambda functions can be difficult. For functions that require some sort of input it can be tough to develop the proper payload and event for a test.
  • For the uninitiated, deploying functions with Infrastructure as Code tools can be a challenging undertaking.
  • Logging the output of a function feels disjointed from running the function in the console. A tighter integration with operational logging would be appreciated, perhaps being able to view function logs from the Lambda console instead of having to navigate over to CloudWatch.
  • Sometimes its difficult to determine the correct permissions needed for Lambda execution from other AWS services.
I would definitely recommend using Lambda for short-running, event-triggered processes that are dedicated to a single function. This could be for one-off processing or intermediate tasks between other resources like objects stored in buckets and queues for processing those objects. Also, since Lambda executions can be scheduled, processes that need to happen on regular intervals can be implemented with Lambda as well.
I would not recommend using Lambda for anything that needs to run longer than a few seconds. Long running processes like ETL jobs or intensive computations may be better suited for step functions, batch jobs, or even a server based approach.
AWS provides decent documentation and plenty of resources for getting started with Lambda. Our support engineers are readily available to answer questions and if there are ongoing issues, the support process is pretty good. I haven't had any problems with tickets falling through the cracks or issues not being followed up. My team also has a good relationship with our account managers if there is ever a need for escalation but really that's never been the case.
Score 9 out of 10
Vetted Review
Verified User
Review Source
We use AWS Lambda to help us automate the process of start/stop EC2 instances in AWS. We use it in infrasctructure but it affects the whole organization and most of our internal servers and customer servers are in AWS. With this automation, we cut our cost by 35% which is a very significant amount for a small company.
  • Flexible. You can use it with many programming languages.
  • Easy. It's all configurable and as soon as you understand how it works it becomes very easy to maintain.
  • The integration with other AWS tools helps a lot the automation of tasks.
  • In the beginning, I think the documentation is not very informative so you have to look at user examples online.
The main area in my point of view is the automation reduction of costs. You can program and use Lambda to execute several tasks based in several types of events like logs, schedules, and output from other AWS tools. With the AWS API, you can do almost anything you want and your function will use only the needed resource (memory, cpu) so it is optimized.
The support in terms of AWS documentation is vast but its difficult to understand in a first glimpse. I needed examples so I have to look outside AWS like youtube and internet articles.
February 07, 2020

AWS Lambda rocks

Score 7 out of 10
Vetted Review
Verified User
Review Source
We use Lambda to manage workloads integrated with our API Gateway.
  • Simplicity
  • Security
  • Scalability
  • API calls
I think it works really well for managing workloads without the need to manage the underneath infrastructure.
AWS support is good.
Score 8 out of 10
Vetted Review
Verified User
Review Source
Our university department is responsible for several web applications on campus that support student success, including providing online services for students directly, as well as supporting workflows and activities of other departments and divisions. As we move more and more of our applications into the AWS cloud, we have found Lambda to be a great way to simplify some of our web services and "housekeeping" processes; the fact that we're only charged for Lambda function calls, and not for the infrastructure which supports Lambda, helps us save on hosting costs, as well!
  • AWS Lambda is a welcoming platform, supporting several languages, including Java, Go, PowerShell, Node.js, C#, Python, and Ruby. And if you need to deploy a Lambda function in another language, AWS offers a Runtime API for integration.
  • We really appreciate how AWS Lambda is always-on for our functions, with only a brief "cold-start" waiting period the first time a function is called after being dormant.
  • In addition to only generating costs when it's actually being used, AWS Lambda really puts the "serverless" in serverless architecture, offering turnkey scaleability and high availability for our code with zero effort on our part.
  • Putting a significant portion of your codebase into AWS Lambda and taking advantage of the high level of integration with other AWS services comes with the risk of vendor lock-in.
  • While the AWS Lambda environment is "not your problem," it's also not at your disposal to extend or modify, nor does it preserve state between function executions.
  • AWS Lambda functions are subject to strict time limitations, and will be aborted if they exceed five minutes of execution time. This can be a problem for some longer-running tasks that are otherwise well-suited to serverless delivery.
AWS Lambda is a great way to deploy smaller-scale data synchronization jobs and other "housekeeping" routines that don't require preservation of state. We use it to build API gateway tools used by our larger applications (many of which are hosted on AWS EC2 instances) and it's a perfect fit.

If you have complicated workflows that run a long time, or require state to be saved between function calls, AWS Lambda is probably not the right choice for a serverless solution.
Amazon consistently provides comprehensive and easy-to-parse documentation of all AWS features and services. Most development team members find what they need with a quick internet search of the AWS documentation available online. If you need advanced support, though, you might need to engage an AWS engineer, and that could be an unexpected (or unwelcome) expense.
November 16, 2019

AWS Lambda for Education

Score 9 out of 10
Vetted Review
Verified User
Review Source
I've used AWS Lambda to create Alexa skills. I write articles about these skills and teach university students to create skills.
  • Rapid deployment of code.
  • Rapid execution of code.
  • Cost-effective use of the cloud.
  • The setup pages for AWS Lambda could be more intuitive.
  • AWS Lambda could have better Java integration.
AWS Lambda is very well suited to the scenario in which I use it; namely, Alexa skills. To respond to an Alexa skill request, it would be inefficient to spin up a server. For applications that run continuously and are not event-driven, AWS Lambda is not well-suited.
My only support experience is reading the documentation, which I find useful in most cases.
Jesse Bickel, MS - PMP | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
AWS Lambda is used primarily by about 20% of our staff and only in our development department. We use AWS Lambda for developing and managing our application over the cloud platform. We internally provide cloud-related solutions to our dev groups and develop web apps and services on cloud for them. So whenever we have to provide any computation related work for that particular app than I use AWS Lambda because it is easy to use and scalable and also costs less than any previous solution we have reviewed.
  • AWS Lambda is a great compute engine that allows you to run and execute your computation code without the need of maintaining servers and the overhead that comes with that.
  • We all can use our favorite programming language to develop the functions.
  • AWS Lambda is the fastest server setup on the market.
  • The relationship with S3 Triggers leaves a lot of room for improvement.
  • The solution community forums leave a lot to be desired.
  • The AWS Lambda UI experience could aid an overhaul. It's not unusable but not a great reflection of how great the service product is.
I know a lot of our developers use this personally to develop Alexa skills. The best use case for us is building simple rest API's with minimal effort and overhead. It is easy to use and scalable. You can also through a lot of load against it very quickly with little to no performance issues that I have seen. Also, it is very well suited in environments where developers have language freedoms.
AWS support is great for this product but the community forums and online admins could use a lot of work. We have a premium support agreement with a TAM which really helps.
Jacob Biguvu | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
AWS Lambda is an event-driven, serverless computing platform and a compute service that runs code in response to events and automatically manages the computing resources required by the code. AWS Lambda is being used by our team and across the whole organization. It's being used as part of our DR solution to run the code at scheduled times.
  • I have used the AWS Lambda for moving the RDS snapshots from cross-region like East to West and West to East. We used it as part of our DR solution. AWS Lambda is the service provided by AWS, and it makes it easy to manage the AWS resources.
  • I have used AWS Lambda for running a cleanup code against the database at scheduled times. I use Python as the coding language. AWS Lambda is the service provided by AWS, which makes easy to manage the AWS resources.
  • We can use AWS lambda function for serverless architecture.
  • We can use AWS Lambda for managing Micro-service architecture.
  • AWS Lambda has not worked in an efficient way for running long-lived applications, especially on serverless architecture.
  • AWS Lambda provides a zip deployment method, but there is a limit on size, like 500MB.
  • AWS Lambda has a significant issue with "Cold Start." It takes some time for it to handle the first request -- there, we see a real problem.
AWS Lambda is best for short-lived applications/codes. Configure AWS Lambda to act based on the events that are produced on certain services. It works. We used it to move the RDS snapshot from WEST to EAST and EAST to WEST whenever the RDS automatic backups are done. It helps in other scenarios, like when application teams don't have a server or don't have a place to run a job on a regular basis. Then we can leverage this AWS Lambda to run the code against the database. As I mentioned, this is not suited for long-lived applications.
No need to manage server/architecture and easy to setup and run the code. It is function as a service. it support different languages such as python, java, Node.js and Go.
Richard Rout | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User
Review Source
We use AWS Lambda to host our micro-services that don't need to worry about too much infrastructure. Lambdas are great at running pieces of code that don't necessarily have to belong in the main infrastructure. We have a few different lambdas that each have single responsibilities, such as creating and uploading files to S3, and running complex calculations.
  • Runs "functions" in the cloud. Pretty simple really
  • Always having the latest version available
  • Not having to worry about infrastructure
  • Anything too complex is not a great solution
  • Can take a little while to spin up if inactive for a while
  • Can be easy to misuse or abuse.
Anywhere you have an isolated responsibility of your code, AWS Lambdas are well suited for. If you have something that has to perform an intensive calculation - it makes sense to offload that to something like an AWS Lambda. Or something that needs to send data and integrate with another service, it can be a good place for that interface/job to live.

It can be possible to build a larger architecture using a series of AWS Lambdas, but it could become hard to maintain and be hard to understand very quickly.
Like all things AWS. There is a bit of a learning curve, and support can be a bit complicated. The docs are aimed at AWS aficionados, the make sense eventually but may require a few reads. Also I'm not sure what other level of support AWS gives if you pay for it, but it's the standard for all AWS products.
Stephen Groat | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
Serverless platforms are the future, and AWS is leading the way with AWS Lambda. Lambda completely integrates into the AWS ecosystem, with IAM, the AWS SDK, and all other features, allowing for infinitely scalable applications to be rapidly developed that require little to no maintenance. Limiting maintenance through the use of serverless application allows organizations to grow more effectively.
  • Easy to configure and maintain
  • Infrastructure as Code (IaC) configuration options
  • AWS integrations
  • Can be more expensive once scale gets higher
  • LImited language support
  • Can be more difficult to debug
AWS Lambda is best for new, small applications. With frameworks like, the deployment issue is completely negated. Managing large serverless applications becomes easy. With the technology, a significant amount of the scaling and other performance related issues are handled. Programmers are left to deal with RAM and processor issues on a per execution basis.
AWS support, including around Lambda, seems to be hit and miss. The first level tech support usually cannot handle complicated technical questions. Without a support contract, there little hope of getting a question answered. With a contract, the answers can come days late, significantly after they are useful or even needed.
Winston Mendes | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
AWS Lambda is used by the programming department and allows to coordinate applications, without a server, in a very fast, simple, and economic way. It is perfect for scalable projects, where small functions are executed and it is not necessary to have a complete layer behind the application or the website. It also helps with continuous integration, since you can add functions independently and it is easy to automate functions. AWS Lambda integrates very well with Cloudwatch, which allows us to monitor at all times the records that return functions.
  • It is an excellent tool for continuous integration.
  • It allows for executing code triggered by other services of AWS.
  • Ideal for serverless applications.
  • Cross-platform support.
  • A great tool for scalable projects, which allows us to configure the resources and time necessary to execute a function.
  • It constantly changes from one instance to another, so there is no control over the execution environment.
  • It is not ideal to run functions that take a long time to run. For example, the upload of heavy files, videos, etc.
  • The learning curve is steep. It requires a lot of knowledge to be able to take advantage of it, since you have to know the average time of execution of a function to be able to configure it correctly, besides having the most optimized code possible.
Lambda is ideal for the development of apps and serverless webapps, which are fragmented into small functions independently. It is also very useful for companies that look for an economic solution for their developments, and do not have an estimated number of users. This tool should not be used for very extensive functions, when it is better to divide the code. It's also not ideal for file processing or content loading, only less heavy photos that won't pause the execution of a function while waiting for the file to load.
Fedor Paretsky | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
We use AWS Lambda to host our serverless lambda functions. It allows us to execute segments of our computational code that don't require actual virtual machines hosted on compute engines. This allows us to achieve very low costs for simple pieces of code that can be run quickly a large number of times.
  • Short computational code - For those that need scalability without maintaining servers, AWS lambda basically achieves all of this as one service.
  • Scalability - For most lambda services, you are charged by run amount, as long as run-time remains low.
  • Non-hosted websites/serverless code - Services like Netlify implement similar lambda functionality that is completely free. There may be services hosted on Amazon that achieve the same.
  • UI could use some improvement - Like the rest of the Amazon Web Services UI, much of the interface is complex and hard to understand at the beginning.
  • Hard to troubleshoot/debug - Lambda, in itself, is set up in an environment that makes it difficult to troubleshoot in the product. The use of staging production code is absolutely necessary.
  • The pricing is a bit more expensive when compared to other services that provide lambda function execution services.
AWS Lambda and Lambda functions, in general, are an amazing tool to run segments of code that don't need to be run actively. This allows us to save lots of money running code and only paying for it when it is actually run. Every company undoubtedly has code that can be run in this way for cost-saving. For companies that focus on computation, optimization, and other services, Lambda may not be the best, since it is unlikely that this code is executed quickly in "bursts".
Score 8 out of 10
Vetted Review
Verified User
Review Source
We are building a system for log and data processing in AWS Lambda, S3, DynamoDB and Redshift. Data is collected and uploaded to S3 and a Lambda will be invoked to do the main processing function. It extracts and analyzes data, then puts metadata into DynamoDB and main data into Redshift. With Lambda, we are able to spin up thousands of the instances to process input S3 objects in a very short time and then remove them when finished, all with the same pattern and high performance. It saves on our development cost as implementing and deploying AWS Lambda is quite simple compared with EC2 or other services.
  • Simple implementation and deployment.
  • Quickly scale up and down on demand.
  • High performance and high availability.
  • Well integrated with other AWS services like S3, SQS, IAM, and SNS.
  • Save costs as we only pay for our Lambda function when it is triggered.
  • Have a limit on accessing underline VM.
  • Lack of name and documentation for Lambda function.
  • Not well integrated with VPC, which will face an issue when Lambda function needs to access the resource both inside and outside VPC.
AWS Lambda is suitable when we need to process data on demand and require a large number of instances. AWS Lambda is not too complex, and it will fit well in case we need an authentication function to verify user login information, process input data in S3, retrieve and execute message SQS or triggered on demand by the user. AWS Lambda would not fit if we needed to constantly receive user requests, run background processes or needed to access VM underline.
Kyle Reichelt | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
AWS Lambdas are the true workhorses powering our ETL (Extract, Transform, and Load), Data Warehouse, and Business Intelligence solution. We integrate with dozens of registration platforms and third-party services, loading fully normalized customer data into RDS and Redshift, enabling machine learning, forecasting, CRM, marketing automation, business intelligence, and performance monitoring.
  • It scales endlessly. We chose AWS's serverless architecture specifically for its ability to start small and scale as needed.
  • Its always available. AWS's geographic redundancy and serverless architecture mean there's no server downtime. Ever.
  • From a PM's perspective, there's a learning curve. We've had to either hire out experience engineers, or absorb the not-insignificant orientation of not-yet-initiated engineers. But I suppose the same is true of anything.
Well suited if:
  • Your organization is fairly well established (see: runway)
  • You're married to AWS Infrastructure
  • You hate servers
Not well suited if:
  • You aren't utilizing AWS's manages services
  • Your organization is still in the boot-strapped stage (trying to run as lean as possible)
Chris Moyer | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
At Newstex, we use AWS Lambda for a large portion of our AWS workload. We are slowly transitioning all of our services over to Lambda from our previous EC2 servers. Currently we use Lambda to run feed processing, categorization, and normalization of blog posts. We are also using it to monitor our CloudWatch Logs for anomalies and alert our on-call staff to potential issues. We trigger Lambda from CloudWatch events (scheduled) as well as DynamoDB streams and SQS Queues.
  • Easy to deploy
  • Easy to integrate with DynamoDB
  • SQS Support makes it easier to monitor and integrate
  • Easy to scale
  • Pay for what you use, not idle time
  • Focus on your business logic
  • Some errors are hard to track
  • Hard to plan for costs
  • Maximum of 5 minutes of execution time per invoke
Web requests are perfectly suited for Lambda, as are any events that can happen quickly. As Lambda supports more languages, such as Go and Node.JS, it becomes easy to ignore things like frameworks and just focus on a single function. Keep in mind that Lambda functions do not run constantly in the background, and only run when requested, so they are ideal for spikey workloads on-demand.
Kevin Van Heusen | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
AWS Lambda is a great way to perform operations in the cloud without requiring a server. We have used Lambda in our engineering team to help automate AWS related tasks and do so in a way that does not require running an AWS instance. This helped us because sometimes Lambda is one of the most efficient ways to solve a problem that involves the AWS infrastructure.
  • One of the best serverless cloud based functions out there
  • Deep integration with Amazon Web Services
  • Support for a variety of programming languages
  • Deployment of Lambda functions could be a bit more intuitive
  • Amazon could provide more examples of Lambda functions to help get started
  • A Lambda based workflow can be more complex to debug because of all the different functions that may be called as a result of your workflow
Lambda is great when you have specific bite-sized functionality that you can split into multiple discrete functions. It is not well suited for large functions that do quite a bit. Sometimes you are able to split those tasks down into separate Lambda functions that effectively get chained together. For the cases where you can't, it's better to go with a standard backend.