Is there a benefit to Windows Amazon ECS vs EC2 auto-scaling? - amazon-web-services

For multiple high-volume .NET web applications running on Windows and IIS, is there any advantage to changing to CloudFormation and ECS or even EKS instead of just using an AMI of an instance that already has auto-run scripts to update the codebase and configuration on launch, tied into an auto-scaling group behind an ELB?
Our usage is to scale web application servers based on load. Unless I have missed information or grossly misunderstood what has been read, it seems we might not gain anything by moving away from the pure AMI and auto-scaling group.

#sivart Are you using containers? ECS and EKS are container orchestrators. These will benefit you if you package your web applications as docker containers.
CloudFormation helps stand up/down your infrastructure stack using IaC (infrastructure as code) and will help you spin up new infrastructures within minutes without clicking through the AWS console. This will help, for example, when you want to produce production comparable stack for you performance/load/QA before going live. You can create a stack, perform tests and destroy it once happy. You can integrate CloudFormation with your CI/CD pipelines.

Related

Deploying to bare EC2 instances in an ASG?

I have a service that needs to run on our own EC2 instances, since it requires some support from the kernel. My previous experience is all with containers in AWS. The application itself is distributed as a single JAR file and I'm looking for advice for how I should automate deployments. The architecture is:
An ALB in front of the ASG.
EC2 instance running a single Java application.
Any open sockets are open for an hour tops and to not cause any trouble, we have to drain the connections to the EC2 instances before performing an update, so a hard requirement is for the ALB to stop opening new connections for an hour before updating the software. The application is mission critical and ECS has had some issues last year, so I want to minimize the AWS services I depend on. While I could do what I want on my own ECS cluster with custom AMIs, I don't want to do it, since I will run a single instance of the app per host and don't need the extra layer.
My question: What is the simplest method to achieve this using CodePipeline? My understanding is that I need to use a CodeDeploy deployment step to push something to bare EC2 instances. How does draining with an ALB work in this case? We're using CloudFormation for the deployment.
You need to use codedeploy. You can find tutorial on AWS codedeploy documentation.
Codedeploy deployment lifecycle hooks for EC2.
https://docs.aws.amazon.com/codedeploy/latest/userguide/reference-appspec-file-structure-hooks.html#appspec-hooks-server

Jenkins setup on EC2 vs ECS

Currently we have Jenkins that is running on-premise(VMware), planning to move into the cloud(aws). What would be the best approach to install Jenkins whether on ec2 or ECS?
Best way would be running on EC2. Make sure you have granular control over your instance Security Group and Network ACL's. I would recommend using terraform to build your environment as you can write code and also version control it. https://www.terraform.io/downloads.html
Have you previously containerized your Jenkins? On VMWare itself? If not, and if you are not having experience with containers, go for EC2. It will be as easy as running on any other VM. For reproducing the infrastructure, use Terraform or CloudFormartion.
I would recommend dockerize your on-premise Jenkins first. See how much efforts are required in implementation and administrating/scaling it. Then go for ECS.
Else, shift to EC2 and see how much admin overhead + costs you are billed. Then if required, go for ECS.
Another point you have to consider is how your Jenkins is architected. Are you using master-slave? Are you running builds contentiously so that VMs are never idle? Do you want easy scaling such that build environment is created and destroyed per build execution?
If you have no experience with running containers then create it on EC2. Before running on ECS make sure you really understand containers and container orchestration.
Just want to complement the other answers by providing link to official AWS white paper:
Jenkins on AWS
It might be of special interest as it discusses both options in detail: EC2 and ECS:
In this section we discuss two approaches to deploying Jenkinson AWS. First, you could use the traditional deployment on top of Amazon Elastic Compute Cloud (Amazon EC2). Second, you could use the containerized deployment that leverages Amazon EC2 Container Service (Amazon ECS).Both approaches are production-ready for an enterprise environment.
There is also AWS sample solution for Jenkins on AWS for ECS:
https://github.com/aws-samples/jenkins-on-aws:
This project will build and deploy an immutable, fault tolerant, and cost effective Jenkins environment in AWS using ECS. All Jenkins images are managed within the repository (pulled from upstream) and fully configurable as code. Plugin installation is automated, including versioning, as well as configured through the Configuration as Code plugin.

Docker for AWS vs pure Docker deployment on EC2

The purpose is production-level deployment of a 8-container application, using swarm.
It seems (ECS aside) we are faced with 2 options:
Use the so called docker-for-aws that does (swarm) provisioning via a cloudformation template.
Set up our VPC as usual, install docker engines, bootstrap the swarm (via init/join etc) and deploy our application in normal EC2 instances.
Is the only difference between these two approaches the swarm bootstrap performed by docker-for-aws?
Any other benefits of docker-for-aws compared to a normal AWS VPC provisioning?
Thx
If you need to provide a portability across different cloud providers - go with AWS CloudFormation template provided by Docker team. If you only need to run on AWS - ECS should be fine. But you will need to spend a bit of time on figuring out how service discovery works there. Benefit of Swarm is that they made it fairly simple, just access your services via their service name like they were DNS names with built-in load-balancing.
It's fairly easy to automate new environment creation with it and if you need to go let's say Azure or Google Cloud later - you simply use template for them to get your docker cluster ready.
Docker team has put quite a few things into that template and you really don't want to re-create them yourself unless you really have to. For instance if you don't use static IPs for your infra (fairly typical scenario) and one of the managers dies - you can't just restart it. You will need to manually re-join it to the cluster. Docker for AWS handles that through IPs sync via DynamoDB and uses other provider specific techniques to make failover / recovery work smoothly. Another example is logging - they push your logs automatically into CloudWatch, which is very handy.
A few tips on automating your environment provisioning if you go with Swarm template:
Use some infra automation tool to create VPC per environment. Use some template provided by that tool so you don't write too much yourself. Using a separate VPC makes all environment very isolated and easier to work with, less chance to screw something up. Also, you're likely to add more elements into those environments later, such as RDS. If you control your VPC creation it's easier to do that and keep all related resources under the same one. Let's say DEV1 environment's DB is in DEV1 VPC
Hook up running AWS Cloud Formation template provided by docker to provision a Swarm cluster within this VPC (they have a separate template for that)
My preference for automation is Terraform. It lets me to describe a desired state of infrastructure rather than on how to achieve it.
I would say no, there are basically no other benefits.
However, if you want to achieve all/several of the things that the docker-for-aws template provides I believe your second bullet point should contain a bit more.
E.g.
Logging to CloudWatch
Setting up EFS for persistence/sharing
Creating subnets and route tables
Creating and configuring elastic load balancers
Basic auto scaling for your nodes
and probably more that I do not recall right now.
The template also ingests a bunch of information about related resources to your EC2 instances to make it readily available for all Docker services.
I have been using the docker-for-aws template at work and have grown to appreciate a lot of what it automates. And what I do not appreciate I change, with the official template as a base.
I would go with ECS over a roll your own solution. Unless your organization has the effort available to re-engineer the services and integrations AWS offers as part of the offerings; you would be artificially painting yourself into a corner for future changes. Do not re-invent the wheel comes to mind here.
Basically what #Jonatan states. Building the solutions to integrate what is already available is...a trial of pain when you could be working on other parts of your business / application.

Choosing the right AWS Services and software tools

I'm developing a prototype IoT application which does the following
Receive/Store data from sensors.
Web application with a web-based IDE for users to deploy simple JavaScript/Python scripts which gets executed in Docker Containers.
Data from the sensors gets streamed to these containers.
User programs can use this data to do analytics, monitoring etc.
The logs of these programs are outputted to the user on the webapp
Current Architecture and Services
Using one AWS EC2 instance. I chose EC2 because I was trying to figure out the architecture.
Stack is Node.js, RabbitMQ, Express, MySQl, MongoDB and Docker
I'm not interested in using AWS IoT services like AWS IoT and Greengrass
I've ruled out Heroku since I'm using other AWS services.
Questions and Concerns
My goal is prototype development for a Beta release to a set of 50 users
(hopefully someone else will help/work on a production release)
As far as possible, I don't want to spend a lot of time migrating between services since developing the product is key. Should I stick with EC2 or move to Beanstalk?
If I stick with EC2, what is the best way to handle small-medium traffic? Use one large EC2 machine or many small micro instances?
What is a good way to manage containers? Is it worth it use swarm and do container management? What if I have to use multiple instances?
I also have small scripts which have status of information of sensors which are needed by web app and other services. If I move to multiple instances, how can I make these scripts available to multiple machines?
The above question also holds good for servers, message buses, databases etc.
My goal is certainly not production release. I want to complete the product, show I have users who are interested and of course, show that the product works!
Any help in this regard will be really appreciated!
If you want to manage docker containers with least hassle in AWS, you can use Amazon ECS service to deploy your containers or else go with Beanstalk. Also you don't need to use Swarm in AWS, ECS will work for you.
Its always better to scale out rather scale up, using small to medium size EC2 instances. However the challenge you will face here is managing and scaling underlying EC2's as well as your docker containers. This leads you to use Large EC2 instances to keep EC2 scaling aside and focus on docker scaling(Which will add additional costs for you)
Another alternative you can use for the Web Application part is to use, AWS Lambda and API Gateway stack with Serverless Framework, which needs least operational overhead and comes with DevOps tools.
You may keep your web app on Heroku and run your IoT server in AWS EC2 or AWS Lambda. Heroku is on AWS itself, so this split setup will not affect performance. You may heal that inconvenience of "sitting on two chairs" by writing a Terraform script which provisions both EC2 instance and Heroku app and ties them together.
Alternatively, you can use Dockhero add-on to run your IoT server in a Docker container alongside your Heroku app.
ps: I'm a Dockhero maintainer

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.