What is the difference between AWS Lambda & AWS Elastic Beanstalk - amazon-web-services

I am studying for my AWS Cloud Practitioner Certification and I am confused with the difference between AWS Lambda & AWS Elastic Beanstalk. From my understanding, for both services you upload your code to AWS and AWS essentially manages the underlying infrastructure for you.
I know with Lambda you upload your code to a 'Lambda Function' and set triggers for when the code executes.
With AWS EB you upload your application code and EB automatically handles the deployment, capacity, provisioning, etc...
They both sound very similar as you upload your code to both and both handle underlying instances/environments.
Thanks!

Elastic beanstalk and lambda are very different though some of the features may look similar. At high level, elastic beanstalk deploys a long running application whereas lambda deploys short running code function
Lambda can at maximum run for 15 minutes, whereas EB can run continuously. Generally, we deploy websites/apps on EB whereas lambda are generally used for triggered functionality like processing image when image gets uploaded to S3.
Lambda can only handle one request at a time whereas number of concurrent requests EB can handle depends on your underlying infrastructure. So, if you are having say 100 requests, 100 lambdas will be created whereas these 100 requests can be handled by one underlying EC2 instance in EB
Lambda is serverless (underlying infra is entirely abstracted from developer). Whereas EB is automation over infra provisioning. You can still see your EC2 instances, load balancer, auto scaling group etc. in your AWS console. You can even ssh/rdp to your instance and change running services. AWS EB allows you also to have your custom AMIs.
Lambda is having issue of cold starts as in lambda, infra needs to be provisioned on demand by AWS, whereas in EB, you generally have EC2 instances already provisioned to handle your requests.

All great (and exam-specific) points by SmartCoder. If I may add a general ancillary comment:
Wittgenstein said, "In most cases, the meaning of a word is its use." I think this maxim is remarkably apt for software engineering too. In the context of your question, those two AWS services are used for significantly different purposes.
Lambda - Say you developed a photo uploading application with Node.js that uploads some processed images to an S3 bucket. The core logic for this is probably quite straightforward, and it's got a singular, distinct task. Simply take in an image, do some processing and if not for any exception, store it in a bucket. In this case, it's inefficient to waste time spinning up servers, configuring them with a runtime environment, downloading dependencies, maintenance, etc. A literal copy and paste of your code into the Lambda console while setting up a few configurations should get your job done. Plus, you save a lot of money as infrastructure is "provisioned" only when your Node.js function is invoked. Again, keep in mind the principle of this code performing a singular task.
Elastic Beanstalk - This same photo uploading system mentioned above might now mature into a more complex full-fledged software application that requires user management, authentication, and further processing of the images, which certainly requires more provisioning of resources. This application will probably do a lot of things with multiple code repositories for you to manage and deploy. And yet, you don't want to spend money on a DevOps engineer or learn to use an IaC (Infrastructure as Code) platform like CloudFormation or Terraform. In this case, Elastic Beanstalk is useful for a developer without too much in-depth DevOps knowledge as it's a PaaS (Platform as a Service) tool; it pretty much gives you a clear interface to spin up whole new production-ready systems.
Here are two good whitepapers I read a while back on the above topics.
https://docs.aws.amazon.com/whitepapers/latest/serverless-architectures-lambda/serverless-architectures-lambda.pdf
https://docs.aws.amazon.com/whitepapers/latest/introduction-devops-aws/introduction-devops-aws.pdf

Lambda is run based on specific trigger events.. and it exits as soon as its work is over.

Related

How to deploy Infrastructure as Code on AWS

Had a question regarding infrastructure as code on AWS.
Wondering how to do this (the process of deploying) and also why is this an efficient method for architecture? Also, are there other methods that should be looked at over this?
I am looking to deploy this for a startup I am working for and need assistance in getting this going. Any help is appreciated.
Thank you.
From What is AWS CloudFormation?:
AWS CloudFormation is a service that helps you model and set up your Amazon Web Services resources so that you can spend less time managing those resources and more time focusing on your applications that run in AWS. You create a template that describes all the AWS resources that you want (like Amazon EC2 instances or Amazon RDS DB instances), and AWS CloudFormation takes care of provisioning and configuring those resources for you. You don't need to individually create and configure AWS resources and figure out what's dependent on what; AWS CloudFormation handles all of that.
So, instead of manually creating each bit of architecture (network, instances, queues, storage, etc), you can define them in a template and CloudFormation will deploy them. It is smart enough to mostly know the correct order of creation (eg creating the network before creating an Amazon EC2 instance within the network) and it can also remove resources when the 'stack' is no longer required.
Other benefits:
The template effectively documents the infrastructure
Infrastructure can be checked into a source code repository, and versioned
Infrastructure can be repeatedly and consistently deployed (eg Test environment matches Production environment)
Changes can be made to the template and CloudFormation can update the 'stack' by just deploying the changes
There are tools (eg https://former2.com/) that can generate the template from existing infrastructure, or just create it from code snippets taken from the documentation.
Here's an overview: Simplify Your Infrastructure Management Using AWS CloudFormation - YouTube
There are also tools like Terraform that can deploy across multiple cloud services.

Amazon Fargate vs EC2 container website hosting

I got a project recently in which I have to build a React / NextJS application which will serve occasional high traffic but will mostly sit idle. We are currently looking for the cheapest option in all categories, but also want to build a scalable and manageable app with a quick and easy CI/CD pipeline. For the development server, we chose Heroku's free plan and pipeline, as I think it's perfectly idle for the job. For production, we decided to use Docker as it's the best way to set up a CD pipeline, and with 2000 minutes of free Github Actions per month, the whole Production/Development pipeline will be essentially free of cost for us. We also were thinking to use AWS because of its features and we want to keep a minimum number of bills to manage. For DB we're thinking of using DynamoDB because of free 25GB lifetime storage which will be enough as the only dynamic data in the site will be user data and blogs. And for object storage, the choice is S3.
Here, we're confused between the two offerings by AWS when it comes to Container hosting, ECS EC2, and ECS Fargate. While Fargate definitely feels like a better choice because of the fact that the application will sit idle most of the time, but we're really confused in resource provisioning for containers in Fargate. The app is running on NextJS, so it'll be server-side rendered.
So my question was, will a combo of 0.5 GB RAM x 0.25 vCPU will be enough for a Server Side Rendered NextJS application? Or should I go for a dedicated EC2? Or another cloud provider maybe?
NextJS is a framework that run on top of nodejs, as there is no such specific requirement (nodejs 10 only) mentioned on the documentation but you can treat them as we treat nodejs.
Node.js with V8 suitable for limited memory device?
So my question was, will a combo of 0.5 GB RAM x 0.25 vCPU will be
enough for a Server Side Rendered NextJS application? Or should I go
for a dedicated EC2? Or another cloud provider maybe?
I will not suggest EC2 type ECS service, you can go for fargate with minimal memory and CPU and set auto-scaling of ECS services whenever required.
But I think we have a better option then fargate that is serverless-nextjs
Serverless deployment dramatically improves reliability and scalability by splitting your application into smaller parts (also called [lambdas]3). In the case of Next.js, each page in the pages directory becomes a serverless lambda.
There are a number of benefits to serverless. The referenced link talks about some of them in the context of Express, but the principles apply universally: serverless allows for distributed points of failure, infinite scalability, and is incredibly affordable with a "pay for what you use" model.
Serverless Nextjs

Continuous Integration on AWS EMR

We have a long running EMR cluster that has multiple libraries installed on it using bootstrap actions. Some of these libraries are under continuous development and their codebase is on GitHub.
I've been looking to plug Travis CI with AWS EMR in a similar way to Travis and CodeDeploy. The idea is to get the code on GitHub tested and deployed automatically to EMR while using bootstrap actions to install the updated libraries on all EMR's nodes.
A solution I came up with is to use an EC2 instance in the middle, where Travis and CodeDeploy can be first used to deploy the code on the instance. After that a lunch script on the instance is triggered to create a new EMR cluster with the updated libraries.
However, the above solution means we need to create a new EMR cluster every time we deploy a new version of the system
Any other suggestions?
You definitely don't want to maintain an EC2 instance to orchestrate a CI/CD process like that. First of all, it introduces a number of challenges because then you need to deal with an entire server instance, keep it maintained, deal with networking, apply monitoring and alerts to deal with availability issues, and even then, you won't have availability guarantees, which may cause other issues. Most of all, maintaining an EC2 instance for a purpose like that simply is unnecessary.
I recommend that you investigate using Amazon CodePipeline with a Lambda Step Function.
The Step Function can be used to orchestrate the provisioning of your EMR cluster in a fully serverless environment. With CodePipeline, you can setup a web hook into your Github repo to pull your code and spin up a new deployment automatically whenever changes are committed to your master Github branch (or whatever branch you specify). You can use EMRFS to sync an S3 bucket or folder to your EMR file system for your cluster and then obtain the security benefits of IAM, as well as additional consistency guarantees that come with EMRFS. With Lambda, you also get seamless integration into other services, such as Kinesis, DynamoDB, and CloudWatch, among many others, that will simplify many administrative and development tasks, as well as enable you to have more sophisticated automation with minimal effort.
There are some great resources and tutorials for using CodePipeline with EMR, as well as in general. Here are some examples:
https://aws.amazon.com/blogs/big-data/implement-continuous-integration-and-delivery-of-apache-spark-applications-using-aws/
https://docs.aws.amazon.com/codepipeline/latest/userguide/tutorials-ecs-ecr-codedeploy.html
https://chalice-workshop.readthedocs.io/en/latest/index.html
There are also great tutorials for orchestrating applications with Lambda Step Functions, including the use of EMR. Here are some examples:
https://aws.amazon.com/blogs/big-data/orchestrate-apache-spark-applications-using-aws-step-functions-and-apache-livy/
https://aws.amazon.com/blogs/big-data/orchestrate-multiple-etl-jobs-using-aws-step-functions-and-aws-lambda/
https://github.com/DavidWells/serverless-workshop/tree/master/lessons-code-complete/events/step-functions
https://github.com/aws-samples/lambda-refarch-imagerecognition
https://github.com/aws-samples/aws-serverless-workshops
In the very worst case, if all of those options fail, such as if you need very strict control over the startup process on the EMR cluster after the EMR cluster completes its bootstrapping, you can always create a Java JAR that is loaded as a final step and then use that to either execute a shell script or use the various Amazon Java libraries to run your provisioning commands. In even this case, you still have no need to maintain your own EC2 instance for orchestration purposes (which, in my opinion, still would be hard to justify even if it was running in a Docker container in Kubernetes) because you can easily maintain that deployment process as well with a fully serverless approach.
There are many great videos from the Amazon re:Invent conferences that you may want to watch to get a jump start before you dive into the workshops. For example:
https://www.youtube.com/watch?v=dCDZ7HR7dms
https://www.youtube.com/watch?v=Xi_WrinvTnM&t=1470s
Many more such videos are available on YouTube.
Travis CI also supports Lambda deployment, as mentioned here: https://docs.travis-ci.com/user/deployment/lambda/

Exploring tools to trigger build script to rollout specific git branch to a subset of the amazon ec2 instances

We have multiple amazon ec2 instances behind a load balancer. Our build script is written in phing and is integrated with git.
We are looking for a tool (like Jenkins or Amazon code deploy) which could display all the active instances currently behind load balancer and then allow us to select some of them (or select a group defined previously) and then trigger either of the following (whichever is better) -
a build script hosted on the same dedicated server where the tool is hosted.
or the respective build scripts hosted on the selected ec2 instances.
We should be able to do the following -
specify a git branch name, optionally, when we trigger the build script for any group of instances.
be able to roll out in batches of boxes, so as to get some time to monitor load, and then move to next batch if all is good. Best way, I guess, would be to specify a size of the batch (e.g. 10), so that the process waits for a user prompt after rollout on every batch completes.
So, if we have to rollout two different git branches to two groups of instances, we should be able to run them in two steps (if we do not specify batch size).
Would like to know about experiences of people who dealt with something similar.
For CodeDeploy, it supports Git (more precisely, GitHub). It also allows you to deploy only to tagged EC2 instances. If combined with custom DeploymentConfig (http://docs.aws.amazon.com/codedeploy/latest/userguide/how-to-create-deployment-configuration.html), you can also control how fast (the size of the batch) to deploy.
I would re-structure the question:
The choices you have for application deployment
and whether the tool has option to perform rolling deployments.
Jenkins is software for CI/CD, which will have to use plugins,custom scripting or leverage an existing orchestration software setup for doing the deployments.
For software orchestration, you have many choices, some of the more famous tools are Chef, puppet, ansible etc.. All of these would need you to manage some kind of centralized setup. All such software support application deployment.
You need to make a decision on whether you would want to invest in maintaining such a setup.
If you decide against such a setup, you have the option of using managed services such as AWS OpsWorks, AWS CodeDeploy, hosted chef etc.
In choosing any of these services, you delegate the management of orchestration software to a vendor, which will ensure the service is up all the time.
AWS code deploy and AWS OpsWorks are managed services on aws and work pretty well on AWS setups.
AWS OpsWorks uses chef under the hood.
AWS CodeDeploy only provides a subset of what OpsWorks provides and is responsible only for deployments. With AWS code deploy you get convenient visualization of your software deployments through AWS console.
With AWS code deploy, you can achieve the goal of partial roll out to ec2 instances.
You can do the same with other tools as well but CodeDeploy on AWS environment will take least amount of work.
CodeDeploy also allows you to deploy from GIT. Please refer to the following aws documentation
http://docs.aws.amazon.com/codedeploy/latest/userguide/github-integ-tutorial.html
The pitfall with code deploy is the fact that the agent that will run on instances has been tested for and is supported for only a limited number of OS combinations.(http://docs.aws.amazon.com/codedeploy/latest/userguide/how-to-run-agent.html#how-to-run-agent-supported-oses)
Also in future if you decide to move away from AWS, you will have to redo the deployment related work.
CodeDeploy service only charges you for the underneath AWS resources.
Please find the link to pricing documentation below:
https://aws.amazon.com/codedeploy/pricing/

What is the difference between Elastic Beanstalk and CloudFormation for a .NET project? [closed]

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I have developed a .NET MVC application and have started playing around with AWS and deploying it via the Visual Studio Toolkit. I have successfully deployed the application using the Elastic Beanstalk option in the toolkit.
As I was going over the tutorials for deploying .NET apps to AWS with the toolkit, I noticed there are tutorials for deploying with both Elastic Beanstalk and CloudFormation. What is the difference between these two?
From what I can tell, it seems like they both essentially are doing the same thing - making it easier to deploy your application to the AWS cloud (setting up EC2 instances, load balancer, auto-scaling, etc). I have tried reading up on them both, but I can't seem to get anything other than a bunch of buzz-words that sound like the same thing to me. I even found an FAQ on the AWS website that is supposed to answer this exact question, yet I don't really understand.
Should I be using one or the other? Both?
They're actually pretty different. Elastic Beanstalk is intended to make developers' lives easier. CloudFormation is intended to make systems engineers' lives easier.
Elastic Beanstalk is a PaaS-like layer on top of AWS's IaaS services which abstracts away the underlying EC2 instances, Elastic Load Balancers, auto-scaling groups, etc. This makes it a lot easier for developers, who don't want to be dealing with all the systems stuff, to get their application quickly deployed on AWS. It's very similar to other PaaS products such as Heroku, EngineYard, Google App Engine, etc. With Elastic Beanstalk, you don't need to understand how any of the underlying magic works.
CloudFormation, on the other hand, doesn't automatically do anything. It's simply a way to define all the resources needed for deployment in a huge JSON/YAML file. So a CloudFormation template might actually create two Elastic Beanstalk environments (production and staging), a couple of ElasticCache clusters, a DynamoDB table, and then the proper DNS in Route53. I then upload this template to AWS, walk away, and 45 minutes later everything is ready and waiting. Since it's just a plain-text JSON/YAML file, I can stick it in my source control which provides a great way to version my application deployments. It also ensures that I have a repeatable, "known good" configuration that I can quickly deploy in a different region.
For getting started quickly deploying a standard .NET web-application, Elastic Beanstalk is the right service for you.
AWS CloudFormation: "Template-Driven Provisioning"
AWS CloudFormation gives developers and systems administrators an easy way to create and manage a collection of related AWS resources, provisioning and updating them in an orderly and predictable fashion.
CloudFormation (CFn) is a lightweight, low-level abstraction over existing AWS APIs. Using a static JSON/YAML template document, you declare a set of Resources (such as an EC2 instance or an S3 bucket) that correspond to CRUD operations on the AWS APIs.
When you create a CloudFormation stack, CloudFormation calls the corresponding APIs to create the associated Resources, and when you delete a stack, CloudFormation calls the corresponding APIs to delete them. Most (but not all) AWS APIs are supported.
AWS Elastic Beanstalk: "Web Apps Made Easy"
AWS Elastic Beanstalk is an easy-to-use service for deploying and scaling web applications and services developed with Java, .NET, PHP, Node.js, Python, Ruby, Go, and Docker on familiar servers such as Apache, Nginx, Passenger, and IIS.
You can simply upload your code and Elastic Beanstalk automatically handles the deployment, from capacity provisioning, load balancing, auto-scaling to application health monitoring.
Elastic Beanstalk (EB) is a higher-level, managed 'platform as a service' (PaaS) for hosting web applications, similar in scope to Heroku. Rather than deal with low-level AWS resources directly, EB provides a fully-managed platform where you create an application environment using a web interface, select which platform your application uses, create and upload a source bundle, and EB handles the rest.
Using EB, you get all sorts of built-in features for monitoring your application environment and deploying new versions of your application.
Under the hood, EB uses CloudFormation to create and manage the application's various AWS resources. You can customize and extend the default EB environment by adding CloudFormation Resources to an EB configuration file deployed with your application.
Conclusion
If your application is a standard web-tier application using one of Elastic Beanstalk's supported platforms, and you want easy-to-manage, highly-scalable hosting for your application, use Elastic Beanstalk.
If you:
Want to manage all of your application's AWS resources directly;
Want to manage or heavily customize your instance-provisioning or deployment process;
Need to use an application platform not supported by Elastic Beanstalk; or
Just don't want/need any of the higher-level Elastic Beanstalk features
then use CloudFormation directly and avoid the added configuration layer of Elastic Beanstalk.
Cloud Formation is a service that lets you deploy AWS services. You create a template file that describes which services you want. When you deploy that template, Cloud Formation creates the resources for you as a "package". All the resources you defined in your template are started and terminated together. Examples of types of resources that can be created with Cloud Formation are: S3, EC2 instances, AutoScaling, DynamoDb, etc. For EC2, Cloud Formation also gives you the ability to make use of "cfn-init" scripts; which can be used in conjunction with the template to boot strap your instances.
Elastic Beanstalk uses Cloud Formation templates and scipts to: 1. Create a Load Balancer and Auto Scaling Group, 2. Copy your code to S3, 3. Bootstrap an Ec2 instance to Download the code from S3 and deploy it.
Cloud Formation is not as easy to use as EB, but it is much more powerful, because you can create resources other than EC2 instances, control how the cfn-init script, and etc.
There are other differences worth noting. Elastic beanstalk is designed as a container for a single app. I've a set of several websites and services but found it very difficult to deploy multiple websites with beanstalk and was advised, after several attempts, by AWS help to use cloud formation in this situation as it has the extra flexibility.
Theres a really helpful article on bootstrapping AWS cloud formation and updating a running site here thats much clearer than the AWS pages. Still trying to work out if we can deploy from VS straight to the cloud formation template stored on S3 and get it to auto update like beanstalk...
These services are designed to complement each other. AWS Elastic Beanstalk provides an environment to easily deploy and run applications in the cloud. It is integrated with developer tools and provides a one-stop experience for you to manage the lifecycle of your applications. AWS CloudFormation is a convenient provisioning mechanism for a broad range of AWS and third party resources. It supports the infrastructure needs of many different types of applications such as existing enterprise applications, legacy applications, applications built using a variety of AWS resources and container-based solutions (including those built using AWS Elastic Beanstalk).
AWS CloudFormation supports Elastic Beanstalk application environments as one of the AWS resource types. This allows you, for example, to create and manage an AWS Elastic Beanstalk–hosted application along with an RDS database to store the application data. In addition to RDS instances, any other supported AWS resource can be added to the group as well.
Both are for provisioning infrastructure; but they differ in their approach.
Beanstalk: The starting point is the code. I have a NodeJs code I want to upload & run it; please provision the infrastructure for me. (PaaS) Platform as a Service
CloudFormation: The starting point is the infrastructure. Please create an EC2 instance, with one LoadBalancer, Security Group etc so that I can uploaded my NodeJs code to it. Infrastructure as Code (IaC).
Elastic Beanstalk automatically handles the deployment, from capacity provisioning, load balancing, auto-scaling to application health monitoring based on the code you upload to it, where as CloudFormation is an automated provisioning engine designed to deploy entire cloud environments via a JSON script.
Beanstalk: Gives the developer the ability to manage only code and not systems
Cloud Formation: Simplifies and makes everything easier for a Systems Engineer
If a developer or the dev team is looking for a quick MVP testing, the best option is to quickly get deployed with Beanstalk and check.
When a AWS migration happens, systems engineer will get involved in provisioning and Cloud Formation will help a lot and give much more granular control.
Beanstack internally uses cloudformation.
Beanstalk - Basically helpful for software developers.
Example : You want to start the PC quickly and run an application. You don't buy the PC items (harddisk, ram, Processor) separately. You buy a whole CPU or a laptop of a required config. You dont care how its running inside as you want your application to run for you. Beanstalk gives you this feature of everything ready made with no worries.
Cloudformation - Basically helpful for system engineer/ Hardware.
Example : You want to assemble 100's of PC's and give it to the developers then instead of assembling so many PC's you can just give a list of items and the PC is assembled for you by the retailer.
Similarly create a template and send it to cloudformation it will finish your work with no effort.