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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.https://media.trustradius.com/product-logos/GX/PT/BVRZI5O50A6N.jpegAny language, fast and simpleAWS 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.,8,We see a positive impact on actually developer moral because they are given language freedom. We have also seen a positive impact in reducing the time needed to deploy Rest APIs within a project schedule. Our deployments are quicker and it helps shorten our critical paths. We have seen a small negative impact on monitoring and S3 triggers. They do not always seem to work so you have to pay a little closer attention then we would wish to ensure smooth operation.,9,8,OpenShift, Microsoft Azure and Heroku Platform,AWS IoT, AWS Self-Paced Labs, OpenShiftAWS Lambda for DBA maintenanceAWS 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.,9,AWS Lamdba fulfills our DR requirements and audit requirements. It's cost-saving, and has easy setup and event-triggers.,Jenkins,9,Jenkins, AWS Config, Ubuntu Linux, Datadog, PostgreSQL, Microsoft SQL Server, Amazon Redshift, Snowflake,9AWS Lambda - Cloud functions with infinite scalabilityWe 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.,7,Less infrastructure to manage Easier to scale Easy to use.,10,7,AWS Lambda: Best in Class for ServerlessServerless 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,10,Decreased cost for system maintenance staff Increased performance and scalability of applications Decreased time for interactions/versions and deployments,10,7,The most efficient way to create Serverless Applications.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.,9,It is a tool in constant optimization. Amazon recently added new features to development environments in Linux, so it is very versatile to be multiplatform, so it is always useful, makes the development time faster and more orderly. It allows you to save money, since you only pay for what you use, and the projects scale up correctly without generating unexpected expenses. It helps to modularize projects because it seeks to execute small functions to make a project more orderly, efficient, and maintainable.,,AWS Cloud9, Amazon CloudWatch, Amazon S3 (Simple Storage Service), AWS CodePipeline, Amazon DynamoDB, Amazon Kinesis, Amazon Kinesis Analytics, Amazon API Gateway, AWS WAFExcellent Serverless provided by AWSWe 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.,8,Save cost on both AWS infrastructure and development effort. Improve speed on data processing. Simple to maintain and manage processes.,,Amazon DynamoDB, Amazon Redshift, Amazon S3 (Simple Storage Service), Amazon Elastic Compute Cloud (EC2)AWS Lambda - The Unseen, Low-Cost Workhorse of the CloudWe use AWS Lambda (in conjunction with SAM) to produce a decentralized notification and delivery system for 3rd Party integrations to our SaaS product. This allows us to keep throughput for messages in our app low, and scaling is nearly automatic and instantaneous. We needed a way for our app and data to be presented to a multitude of 3rd party applications and services and didn't want to make all these points of contact happen inside our main app. Therefore we chose a queue-based approach where our main app delivers messages to a queue and the Lambdas pick those messages up and process them until the queue is empty or more Lambdas are needed. Lambdas have proven to be very cost-effective and prevents us from needing to incur uptime for other servers.,Reliability - Lambdas just work. They do their job and quite well. I've never had any hiccups with them as a unit of hardware. Scalability - This automatic scaling and availability are amazing. It's like having a fleet of servers at the ready but only when needed. And at a fraction of the cost. Price - AWS gives you a generous helping of free invocations every month, and even after that, it's still cheap compared to an always-on solution.,The UI and Developer experience is not so great. IF you use an abstraction like Serverless Application Model (SAM), things get pretty easy, but it's still AWS UI/DX you're working with after that (which is to say, not their strength). Documentation is always a mixed bag. Sometimes it's just easier to google your specific problem and see how others have solved it. This can be much faster than trying to find an example that may or may not be there in the documentation (which oftentimes has multiple versions and revisions).,8,The cost savings of Lambda usage (when done right) can't be overstated Decentralizing architecture and logic can come at a higher development cost or learning curve Working with Lambdas is pretty fun when you think about all the things you don't have to deal with server-wise,7,9,Amazon S3 (Simple Storage Service), Amazon Simple Email Service, Amazon Simple Queue Service (SQS) and Amazon API Gateway,Amazon Simple Queue Service (SQS), Amazon API Gateway, JIRA SoftwareAWS Lambda ReviewAWS Lambda is currently being used to respond to events generated within our AWS infrastructure (instances terminated/created) to perform specific actions. Because AWS Lambda is not constantly running, and only in response to events, we're able to save money by only paying for the amount of CPU resources needed when functions are run.,Cost Savings AWS integration Python and Go support,Need to rely on 3rd party tools for complex deployments Precompiled Python dependencies sometimes won't work Inability to share test events with other users,8,Reduced cost Customized functions in response to events Hooks into other AWS services,8,5,Google App Engine,Google App Engine, IBM Watson Speech to TextAWS Lambda, a best in class serverless workloadWe use AWS Lambda as a microservice platform where we off-load a large number of our common services to the serverless cloud. We have had workloads that have run for years on the platform without issues, and it has allowed us to focus on other areas of developing versus just maintaining code and servers.,Reliable for low workloads. It's an easy entry point for development. Quick speed to market.,It would be good to have more distribution about upgrades or changes to the platform. A little more documentation on the nuances of the offered supported languages. A little more portability of some of the code once you've developed it from other cloud platforms.,8,Due to the nature of fast turn around, our team has to adapt to the new paradigm. AWS Lambda allows us to innovate extremely quickly. Allows new perspective on service development as a platform.,9,9,Microsoft Azure,Azure Bot Service, Microsoft BizTalk Server, Microsoft Azure Service BusMost popular for a reasonMy team uses AWS Lambda as a deployment target for our serverless applications. We develop them using the Serverless framework (using NodeJS) and deploy them to our company's AWS account. As a result, we don't deal with Lambda very much directly, since it's abstracted away through Serverless. But since it's so integrated into the AWS ecosystem our company uses, it is very practical and enables us to run our applications in a stateless was and not need to worry about scaling.,It automatically scales up your functions when demand is high. It allows developers to focus only on business logic, It is very cost-effective, since you're not paying for idle server time.,There is a lot to configure, as is the case with most of AWS's offerings. I wish it were easier to set up API Gateway with Lambda responders. The default logging destination (CloudWatch) leaves much to be desired, and we opted for an external logging tool (Splunk) instead. Cold starts are a persistent problem which can be mitigated with a simple cron job but would ideally be handled by the platform.,9,It has made our services very cheap to run. It has made our services more predictable and easier for our developers to manage. It has empowered our developers to focus on business logic.,8,8,Using AWS Lambda for Data ETLAWS Lambda is mostly being used to run our hourly/daily cron jobs. It is used across the entire organization. It helped us move data between external and internal data sources to the appropriate destinations.,Easy to set up. Support different programming languages. Events-based trigger.,Continuous deployment integration with GitHub. Would like to easily toggle between environments. An interface to map out/organize different functions.,8,AWS Lambda allows us to migrate off our 3rd Party ETL platform, reducing costs by 80% (no longer paying for licensing fee and server cost). It allows us to outsource independent functions to contractors and easily integrate this back into our core process.,Matillion, Amazon Kinesis and Fivetran,Amazon Redshift, Matillion, Tableau Desktop, Tableau ServerServerless data communicationAWS Lambda is being used by my organization to manage machine to machine communication via serverless code. It addresses the problem of sending data between services on Amazon Web Services and it does the job quite well. The lambda handler allows me to set invocations at certain durations and also allows me to pass data back and forth in an automated manner.,Machine to machine communication. Automatic invocation. Error reporting.,Better interface. Deployment methodology.,8,Lower time to deployment. Lower cloud services cost.,Google App Engine,8Most reliable serverless architecture implementationWe are already using other AWS services like EC2, RDS, S3, etc. and they are super reliable and easy to maintain. We use AWS Lambda to host our serverless function which is responsible for authentication. We have also started moving our microservices from EC2 to Lambda.,No need to maintain architecture. Easier operational management with AWS console. Scaling benefits of FaaS beyond costs. You pay only for what you used.,Vendor lock-in, dependency on AWS ecosystem. It's a bit difficult to get started. AWS needs to provide more getting started examples. UI is a bit dull and messy. They should make it cleaner.,9,It is cost-effective, easily scalable, and reliable.,Slack, JIRA Software, IntelliJ IDEAFunctions as a serviceWe use AWS Lambda to efficiently auto scale our NodeJS-based infrastructure without the overhead of needing to manage virtual machines or worry about capacity planning. Additionally, we don’t need to manage security patches for the OS because there is no OS to worry about!,Auto-scaling. Scale to zero. Quick function startup.,Less vendor lock-in. Better integration with community tools like OpenFaaS. Improved cold start times.,9,Reduced costs. Lower security surface area. Quick development feedback loop.,8,10It is amazing. A great alternative to traditional architectures.I used AWS Lambda to interact with the API Gateway and DynamoDB. It was used to retrieve and push data into the database. As a part of the project, it helped us a lot making the task quicker, simpler and more convenient.,Cross Language Support Fast and Scalable Always running,Initial understanding takes time,9,It is better and cheaper than traditional architectures.,,AWS Lambda, Microsoft Visual Studio CodeAWS Lambda can be game changerAWS Lambda is being used by my organization in various projects. In my project, we have more than 10 AWS Lambda services and for each, they are being run on several stages. We are using AWS Lambda for general authentication mechanism integrated with API Gateway. We have an event-driven design and the lambda I have written is consuming and processing events. Those events are also coming from AWS SQS, SNS, and S3. Since AWS Lambda is very easy to configure, it makes you only focus on what you need to do. It is also very easy to integrate it with other AWS services, like consuming AWS SQS or SNS messages, and you can write your own API in minutes while integrating your Lambda with AWS API gateway.,No need to worry about the maintenance of your lambda. It is scalable and you can always change the memory allocation and timeout. Integration with other AWS Services is great! Pricing is reasonable.,I think the cold start of AWS Lambda may be improved. The termination period of a lambda is 15 minutes. If the lambda service being called each time for less than 15 minutes there would be no cold start problem at all. The cold start problem could be solved like triggering a dummy request every 15 minutes, but that would cause some cost for the company.,9,Maintenance costs are low. No need to worry about availability and scalability. It may be pricey if you use it for very high traffic.,Something best for startup projectWe use AWS Lambda and other AWS services for a couple of projects. "Vacation Tracker" project uses the most AWS services. We also use AWS Lambda for Slack Bot, API and notifications. In DynamoDB for DB, we use SNS, SQS, and other AWS services. We saved a lot of time writing the API with AWS Lambda not needing BackEnd programmers. All programmers are Full Stack.It's an easy way to create API for mockup of the product. It's cheap for a startup product. And, with Claudia JS you can create APIs very fast. With the Claudia Bot Builder, you can create a bot for Slack, Facebook, Viber, and more.,No servers to manage. Pay per use. Do not need to be worried about scaling. Faster development cycles.,Logs do not load fast. Max 3GB RAM.,10,Pay per use Faster development cycles Less developer for backend part,Amazon DynamoDB, Amazon Simple Notification Service (SNS), Amazon Simple Queue Service (SQS) and Amazon CloudWatch,Amazon DynamoDB, Amazon Simple Notification Service (SNS), Amazon Simple Queue Service (SQS), Amazon CloudWatchVery developed cost-saving product!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.,8,Positive - Only paying for when code is run, unlike virtual machines where you pay always regardless of processing power usage. Positive - Scalability and accommodating larger amounts of demand is much cheaper. Instead of scaling up virtual machines and increasing the prices you pay for that, you are just increasing the number of times your lambda function is run. Negative - Debugging/troubleshooting, and developing for lambda functions take a bit more time to get used to, and migrating code from virtual machines and normal processes to Lambda functions can take a bit of time.,,Google Hire, Google Kubernetes Engine, Google Mobile-Friendly TestDon't balk at the cost - start with a serverless solution that scalesAWS 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.,8,Positive: Our tech stack is positioned to scale endlessly, which is imperative to what we're trying to accomplish Negative: It's more expensive than building application services from scratch on rented servers,Amazon CloudWatch, Amazon Relational Database Service, Amazon RedshiftBest Cloud PlatformA scalable tool used to configure applications which can be used from outside the organization's environments. The servers are managed on their own by AWS, which is one less task to be taken care of. Can be easily integrated with other back-end APIs like Node.js or Python. Highly scalable, load balancers are configured automatically.,Scalability - No worries for load balancing. Flexibility- Easy to integrate with Python/ Java/ C#/ Node.js, etc API - APIs are easy to integrate. Microservices - Best option is to be able to use microservices with serverless architecture.,UI - The UI part can be groomed for beginners to easily take on the tasks. Debugging - Again it becomes tougher for naive users to onboard and use the tool at its full capacity. Lag- The tool lags on slow networks which can be improved.,9,Debugging - Debugging using the Lambda functions has become easier. Easy to set up and run. Scalability is automatic and does not need too much mind-boggling work.,,Google Cloud AIThe Serverless StandardThe engineering and data science teams at my organization use AWS Lambda to rapidly deliver features that are easy to maintain. We use Lambda with the Serverless framework, API Gateway, and DynamoDB to build managed micro-services that are easy to scale. We use Lambda with AWS Step Functions and S3 to build background jobs.,AWS Lambda is fully-managed. It is easy to build and manage functions and related resources with the Serverless framework. AWS Lambda integrates well with other AWS products. It is easy to use S3, SNS or DynamoDB events to invoke functions. For some use-cases, AWS Lambda is very inexpensive. Sub-second metering is great. Lambda is great for infrequently-used or bursty services.,Managing development, staging, and production environments with Lambda is an open question. Some organizations use separate AWS accounts for different environments, but that is not feasible for teams that use ephemeral, per-feature or per-team development environments. AWS Lambda integrates well with other AWS products, and it is natural to build distributed systems from them. It can be difficult to test features that use Lambda functions end-to-end. LocalStack and moto can help. Lambda functions have very limited access to disk space. Container cold-starts can be problematic and difficult to foresee.,10,AWS Lambda has allowed our data science team to rapidly deliver RESTful APIs for machine learning features without engineering support AWS Lambda and API Gateway allow our developers to rapidly develop background jobs and services without configuring and maintaining infrastructure, application servers, reverse proxies, etc. Lambda integrates well with other AWS products; we don't have to implement as much "glue" code.,Amazon Simple Queue Service (SQS), Amazon SageMaker, Amazon Simple Notification Service (SNS)The future of Software is Serverless.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,10,Less focus on servers, more on code Saves money when not in use No more planning reserved instances No more worries about OS upgrades or patchesAWS Lambda a great way to handle quick process inexpensively.I am using AWS Lambda to process data for a U.S. Government client's website. There are a number of short term processing items that are required to be performed every day and the cost of running these processes cannot be too high. AWS Lambda fits this bill perfectly. The website delivers the data to the AWS Lambda functions and the data gets processed and then passed back to tthe website via AWS S3.,AWS Lambda is great for inexpensive, sometimes free, short term processing. AWS Lambda integrates very well with AWS S3 Storage. Since it is possible to store log files on S3, it is possible to easily process AWS website log information.,I think the biggest problem with AWS Lambda are the small number of languages that it currently supports. This number is, however, getting bigger. AWS Lambda would be a bit better if it were possible to have your function run a little longer, however, since it real purpose is to supply fast functions to all who need some short processing, this if too big of a con. It is possible to have the charging kick in on AWS Lambda just because your website or functions get popular or someone is trying to attack you. It would be good if a cap could easily be placed on the chargers so you couldn't go over a set limit.,8,I was able to perform a lot of processing on data delivered from my website and little or no cost. This was a big plus to me. Programming AWS Lambda is quite easy once you understand the time limits to the functions. AWS Lambda has really good integration with the AWS S3 storage system. This a very good method of delivering data to be processed and a good place to pick it up after processing.,Azure API Management,Netwrix Auditor, Microsoft Visual Studio Team System, JenkinsSimple server-less services!We've used AWS Lambda to deploy several "serverless services". The ability to quickly deploy functions, with no architecture, across several languages, with interoperability between other AWS components (such as S3), at an extremely low cost is really cool. We use Lambda to automate simple processes as well as to run code in languages that aren't supported by our main stack.,Very reasonable prices with billing down to the 100ms Super easy to deploy functions and set up triggers from other AWS services Plenty of examples and code snippets (from Amazon and around the web),Vendor lock-in: While a basic function or microservice might be platform independent, when you start to use AWS APIs and interact with other AWS services, your microservice now relies on the AWS ecosystem A bit intimidating at first, however there are a lot of resources. Amazon could offer more templates and examples though,9,Really cost-effective way to automate tasks, run microservices, etc. Saves a lot of time not having to worry about the environment, architecture, etc. Allows us to use other programming languages than those supported by our server architectureAWS Lambda is like no other!We use Lambda functions as a way to implement serverless code without having to manage an underlying infrastructure. Lambdas are a great way to allow devs to very quickly get things out the door when the main task doesn't rely on any specific hardware or software and just needs to do something to a stream of data. Lambdas and kinesis streams go hand in hand and are very powerful tools when implemented correctly.,parsing data log processing and forwarding monitoring the contents of an S3 bucket and performing an action when the contents changes,more languages supported cleaner interface better list of example code,10,Lambda allowed us to write code quickly without having to worry about managing the underlying infrastructure that it runs on Saved us dev time as they're easy to write and iterate on Helps us with a lot of situations where we need to automate our tasks,
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AWS Lambda
201 Ratings
Score 8.7 out of 101
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AWS Lambda
201 Ratings
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Score 8.7 out of 101

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Jesse Bickel, MS - PMP profile photo
Score 8 out of 10
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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.
Read Jesse Bickel, MS - PMP's full review
Jacob Biguvu profile photo
Score 9 out of 10
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Verified User
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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.
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Richard Rout profile photo
Score 7 out of 10
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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.
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Stephen Groat profile photo
Score 10 out of 10
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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 serverless.io, 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.
Read Stephen Groat's full review
Winston Mendes profile photo
Score 9 out of 10
Vetted Review
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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.
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Score 8 out of 10
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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.
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Score 8 out of 10
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We use AWS Lambda (in conjunction with SAM) to produce a decentralized notification and delivery system for 3rd Party integrations to our SaaS product.

This allows us to keep throughput for messages in our app low, and scaling is nearly automatic and instantaneous. We needed a way for our app and data to be presented to a multitude of 3rd party applications and services and didn't want to make all these points of contact happen inside our main app. Therefore we chose a queue-based approach where our main app delivers messages to a queue and the Lambdas pick those messages up and process them until the queue is empty or more Lambdas are needed.

Lambdas have proven to be very cost-effective and prevents us from needing to incur uptime for other servers.
  • Reliability - Lambdas just work. They do their job and quite well. I've never had any hiccups with them as a unit of hardware.
  • Scalability - This automatic scaling and availability are amazing. It's like having a fleet of servers at the ready but only when needed. And at a fraction of the cost.
  • Price - AWS gives you a generous helping of free invocations every month, and even after that, it's still cheap compared to an always-on solution.
  • The UI and Developer experience is not so great. IF you use an abstraction like Serverless Application Model (SAM), things get pretty easy, but it's still AWS UI/DX you're working with after that (which is to say, not their strength).
  • Documentation is always a mixed bag. Sometimes it's just easier to google your specific problem and see how others have solved it. This can be much faster than trying to find an example that may or may not be there in the documentation (which oftentimes has multiple versions and revisions).
If you're not afraid to get your hands dirty in wiring things up yourselves or you can use AWS' own abstractions like Amplify or SAM, then Lambdas and their surrounding platform pairings (Like SQS, API gateway) are great tools that can help you create a backend or infrastructure for a relatively low cost. If you don't find yourself in that camp, but you know your way around full-stack JavaScript frameworks and tooling, you may be better served with a higher level abstraction like what Zeit Now or Netlify offers.
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August 13, 2019

AWS Lambda Review

Score 8 out of 10
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AWS Lambda is currently being used to respond to events generated within our AWS infrastructure (instances terminated/created) to perform specific actions. Because AWS Lambda is not constantly running, and only in response to events, we're able to save money by only paying for the amount of CPU resources needed when functions are run.
  • Cost Savings
  • AWS integration
  • Python and Go support
  • Need to rely on 3rd party tools for complex deployments
  • Precompiled Python dependencies sometimes won't work
  • Inability to share test events with other users
AWS Lambda is best used in environments where you need to perform specific actions in response to an event happening. This reduces cost and will only be billed for the CPU time it takes to run the function. For long-running tasks, AWS Lambda is not good because of the timeouts set by the function.
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Score 8 out of 10
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We use AWS Lambda as a microservice platform where we off-load a large number of our common services to the serverless cloud. We have had workloads that have run for years on the platform without issues, and it has allowed us to focus on other areas of developing versus just maintaining code and servers.
  • Reliable for low workloads.
  • It's an easy entry point for development.
  • Quick speed to market.
  • It would be good to have more distribution about upgrades or changes to the platform.
  • A little more documentation on the nuances of the offered supported languages.
  • A little more portability of some of the code once you've developed it from other cloud platforms.
AWS Lambda is great for atomic micro services and being leveraged as a conduit for other Amazon services. It's great for a quick way to innovate other resources that you already have on the platform. It marries well with the ecosystem and allows for easy deployments and updates to the program based on the tools.
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Score 9 out of 10
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My team uses AWS Lambda as a deployment target for our serverless applications. We develop them using the Serverless framework (using NodeJS) and deploy them to our company's AWS account. As a result, we don't deal with Lambda very much directly, since it's abstracted away through Serverless. But since it's so integrated into the AWS ecosystem our company uses, it is very practical and enables us to run our applications in a stateless was and not need to worry about scaling.
  • It automatically scales up your functions when demand is high.
  • It allows developers to focus only on business logic,
  • It is very cost-effective, since you're not paying for idle server time.
  • There is a lot to configure, as is the case with most of AWS's offerings. I wish it were easier to set up API Gateway with Lambda responders.
  • The default logging destination (CloudWatch) leaves much to be desired, and we opted for an external logging tool (Splunk) instead.
  • Cold starts are a persistent problem which can be mitigated with a simple cron job but would ideally be handled by the platform.
For its price, flexibility, and integration with other tools, AWS Lambda is the most popular serverless functions platform for a reason. In my opinion, it's best used as the backing behind some higher abstraction like Serverless or even Netlify Functions, but from what I've seen, it would be a great option even if used directly. In generall, serverless architecture works well for stateless applications, API aggregation, event-driven processes, and where the scale/demand is unpredictable.
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Score 8 out of 10
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AWS Lambda is mostly being used to run our hourly/daily cron jobs. It is used across the entire organization. It helped us move data between external and internal data sources to the appropriate destinations.
  • Easy to set up.
  • Support different programming languages.
  • Events-based trigger.
  • Continuous deployment integration with GitHub.
  • Would like to easily toggle between environments.
  • An interface to map out/organize different functions.
AWS Lambda allows us to develop certain process without setting up a server. I would recommend AWS Lambda for a process that doesn't need to be real-time or needs to be always on.
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Score 8 out of 10
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AWS Lambda is being used by my organization to manage machine to machine communication via serverless code. It addresses the problem of sending data between services on Amazon Web Services and it does the job quite well. The lambda handler allows me to set invocations at certain durations and also allows me to pass data back and forth in an automated manner.
  • Machine to machine communication.
  • Automatic invocation.
  • Error reporting.
  • Better interface.
  • Deployment methodology.
AWS Lambda is well suited in cases where the entire stack is on AWS. It doesn't make sense to use lambda when you have services with other cloud providers.
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Score 9 out of 10
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We are already using other AWS services like EC2, RDS, S3, etc. and they are super reliable and easy to maintain. We use AWS Lambda to host our serverless function which is responsible for authentication. We have also started moving our microservices from EC2 to Lambda.
  • No need to maintain architecture.
  • Easier operational management with AWS console.
  • Scaling benefits of FaaS beyond costs. You pay only for what you used.
  • Vendor lock-in, dependency on AWS ecosystem.
  • It's a bit difficult to get started. AWS needs to provide more getting started examples.
  • UI is a bit dull and messy. They should make it cleaner.
Product engineers can innovate rapidly as serverless architecture has alleviated the problems of system engineering. Thus, you spend less time on operational issues and it makes devops life easier.
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August 14, 2019

Functions as a service

Score 9 out of 10
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We use AWS Lambda to efficiently auto scale our NodeJS-based infrastructure without the overhead of needing to manage virtual machines or worry about capacity planning. Additionally, we don’t need to manage security patches for the OS because there is no OS to worry about!
  • Auto-scaling.
  • Scale to zero.
  • Quick function startup.
  • Less vendor lock-in.
  • Better integration with community tools like OpenFaaS.
  • Improved cold start times.
AWS Lambda is great for distributed systems in which scaling of independent components is critical and you don’t want to manage the overhead of needing to maintain a fleet of virtual machines.
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Score 9 out of 10
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I used AWS Lambda to interact with the API Gateway and DynamoDB. It was used to retrieve and push data into the database. As a part of the project, it helped us a lot making the task quicker, simpler and more convenient.
  • Cross Language Support
  • Fast and Scalable
  • Always running
  • Initial understanding takes time
Anywhere where you just pay for what you use. AWS Lambda is the best in those areas. As it is fast and scalable it can provide an excellent alternative for server backend making the whole application serverless. You just don't need the server running every time. Just run it when you need it.
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Score 9 out of 10
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AWS Lambda is being used by my organization in various projects. In my project, we have more than 10 AWS Lambda services and for each, they are being run on several stages. We are using AWS Lambda for general authentication mechanism integrated with API Gateway. We have an event-driven design and the lambda I have written is consuming and processing events. Those events are also coming from AWS SQS, SNS, and S3. Since AWS Lambda is very easy to configure, it makes you only focus on what you need to do.

It is also very easy to integrate it with other AWS services, like consuming AWS SQS or SNS messages, and you can write your own API in minutes while integrating your Lambda with AWS API gateway.
  • No need to worry about the maintenance of your lambda.
  • It is scalable and you can always change the memory allocation and timeout.
  • Integration with other AWS Services is great!
  • Pricing is reasonable.
  • I think the cold start of AWS Lambda may be improved. The termination period of a lambda is 15 minutes. If the lambda service being called each time for less than 15 minutes there would be no cold start problem at all. The cold start problem could be solved like triggering a dummy request every 15 minutes, but that would cause some cost for the company.
AWS Lambda is great if you have a software design considering microservices with it. You can write an API with AWS Lambda and integrate it with API Gateway or you can integrate AWS Lambda consuming SQS or SNS events. You can even write an authorization lambda in front of your product.
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Score 10 out of 10
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We use AWS Lambda and other AWS services for a couple of projects. "Vacation Tracker" project uses the most AWS services. We also use AWS Lambda for Slack Bot, API and notifications. In DynamoDB for DB, we use SNS, SQS, and other AWS services. We saved a lot of time writing the API with AWS Lambda not needing BackEnd programmers. All programmers are Full Stack.
It's an easy way to create API for mockup of the product. It's cheap for a startup product. And, with Claudia JS you can create APIs very fast. With the Claudia Bot Builder, you can create a bot for Slack, Facebook, Viber, and more.
  • No servers to manage.
  • Pay per use.
  • Do not need to be worried about scaling.
  • Faster development cycles.
  • Logs do not load fast.
  • Max 3GB RAM.
It's good for a startup project because you do not need to spend too much money for the server and DevOps teams. With AWS Lambda, you do not need to worry about server managing, scaling, or managed infrastructure. It's free for 1 million requests per month, fewer developers are needed for the backend part, and it has fast deployment.
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Score 8 out of 10
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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".
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Score 8 out of 10
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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)
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April 12, 2019

Best Cloud Platform

Score 9 out of 10
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A scalable tool used to configure applications which can be used from outside the organization's environments. The servers are managed on their own by AWS, which is one less task to be taken care of. Can be easily integrated with other back-end APIs like Node.js or Python. Highly scalable, load balancers are configured automatically.
  • Scalability - No worries for load balancing.
  • Flexibility- Easy to integrate with Python/ Java/ C#/ Node.js, etc
  • API - APIs are easy to integrate.
  • Microservices - Best option is to be able to use microservices with serverless architecture.
  • UI - The UI part can be groomed for beginners to easily take on the tasks.
  • Debugging - Again it becomes tougher for naive users to onboard and use the tool at its full capacity.
  • Lag- The tool lags on slow networks which can be improved.
Can be used for creating:
  • Alexa skills.
  • Serverless architectures.
  • Ability to create RESTful APIs.
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February 09, 2019

The Serverless Standard

Score 10 out of 10
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The engineering and data science teams at my organization use AWS Lambda to rapidly deliver features that are easy to maintain. We use Lambda with the Serverless framework, API Gateway, and DynamoDB to build managed micro-services that are easy to scale. We use Lambda with AWS Step Functions and S3 to build background jobs.
  • AWS Lambda is fully-managed. It is easy to build and manage functions and related resources with the Serverless framework.
  • AWS Lambda integrates well with other AWS products. It is easy to use S3, SNS or DynamoDB events to invoke functions.
  • For some use-cases, AWS Lambda is very inexpensive. Sub-second metering is great. Lambda is great for infrequently-used or bursty services.
  • Managing development, staging, and production environments with Lambda is an open question. Some organizations use separate AWS accounts for different environments, but that is not feasible for teams that use ephemeral, per-feature or per-team development environments.
  • AWS Lambda integrates well with other AWS products, and it is natural to build distributed systems from them. It can be difficult to test features that use Lambda functions end-to-end. LocalStack and moto can help.
  • Lambda functions have very limited access to disk space.
  • Container cold-starts can be problematic and difficult to foresee.
AWS Lambda is excellent for small organizations that want to focus on shipping features rather than maintaining infrastructure. Developers can iterate very rapidly using AWS Lambda, API Gateway, and the Serverless framework. AWS Lambda is not appropriate for some load patterns; services with uniformly high loads will be expensive to run on Lambda.
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Score 10 out of 10
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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.
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Score 8 out of 10
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I am using AWS Lambda to process data for a U.S. Government client's website. There are a number of short term processing items that are required to be performed every day and the cost of running these processes cannot be too high. AWS Lambda fits this bill perfectly. The website delivers the data to the AWS Lambda functions and the data gets processed and then passed back to tthe website via AWS S3.
  • AWS Lambda is great for inexpensive, sometimes free, short term processing.
  • AWS Lambda integrates very well with AWS S3 Storage.
  • Since it is possible to store log files on S3, it is possible to easily process AWS website log information.
  • I think the biggest problem with AWS Lambda are the small number of languages that it currently supports. This number is, however, getting bigger.
  • AWS Lambda would be a bit better if it were possible to have your function run a little longer, however, since it real purpose is to supply fast functions to all who need some short processing, this if too big of a con.
  • It is possible to have the charging kick in on AWS Lambda just because your website or functions get popular or someone is trying to attack you. It would be good if a cap could easily be placed on the chargers so you couldn't go over a set limit.
AWS Lambda is great for fast processing of data that can be placed on Amazon S3 storage. As long as the processing of the function is not longer than what AWS says a Lambda should run for and you do not do much processing, it is great. The cost can also be very good as long as you keep the price in the free area.
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Score 9 out of 10
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We've used AWS Lambda to deploy several "serverless services". The ability to quickly deploy functions, with no architecture, across several languages, with interoperability between other AWS components (such as S3), at an extremely low cost is really cool. We use Lambda to automate simple processes as well as to run code in languages that aren't supported by our main stack.
  • Very reasonable prices with billing down to the 100ms
  • Super easy to deploy functions and set up triggers from other AWS services
  • Plenty of examples and code snippets (from Amazon and around the web)
  • Vendor lock-in: While a basic function or microservice might be platform independent, when you start to use AWS APIs and interact with other AWS services, your microservice now relies on the AWS ecosystem
  • A bit intimidating at first, however there are a lot of resources. Amazon could offer more templates and examples though
When to use:
Easily deploys functions/microservices without a server. Deploy code in several different languages (For instance: Your main app is Node.js but you want to launch a Python microservice? Simple!). Automate small tasks between different AWS services.

When not to use:

When you don't really have a microservice and you actually need a server! Or when you're not going to rely on other AWS services to make up for the lack of a server.
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Score 10 out of 10
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We use Lambda functions as a way to implement serverless code without having to manage an underlying infrastructure. Lambdas are a great way to allow devs to very quickly get things out the door when the main task doesn't rely on any specific hardware or software and just needs to do something to a stream of data. Lambdas and kinesis streams go hand in hand and are very powerful tools when implemented correctly.
  • parsing data
  • log processing and forwarding
  • monitoring the contents of an S3 bucket and performing an action when the contents changes
  • more languages supported
  • cleaner interface
  • better list of example code
Eeveryone should be using Lambda functions for situations where code needs to be executed in response to something happening. Lambdas can be used in situations where you have lots of persistent data but in my opinion, they work better in ephemeral environments. Counting things with Lambdas is hard too, so you should probably avoid that.
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Feature Scorecard Summary

Ease of building user interfaces (15)
8.1
Scalability (31)
9.3
Platform management overhead (29)
8.2
Workflow engine capability (25)
8.4
Platform access control (28)
8.5
Services-enabled integration (30)
8.8
Development environment creation (26)
7.7
Development environment replication (25)
7.4
Issue monitoring and notification (27)
7.9
Issue recovery (24)
8.0
Upgrades and platform fixes (24)
8.5

About 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

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Mobile Application:No