I am exploring options to quickly deploy and start a project on AWS stack. And I came across above two services, "LightSail" and "CodeStar".
I could not find any comparison of these two services from internet. Hence would like to know more about these two services compared to each other ?
Amazon LightSail is a Virtual Private Server (VPS) that can be launched with a number of pre-built images such as WordPress. Think of it as a simpler version of EC2 with flat-rate pricing.
AWS CodeStar is a central hub for managing various interconnected services relating to software development, from writing code to deploying code.
The reason you couldn't find a comparison is that they are rather different services.
Basically, if you already have your code and just want to run it somewhere, then use EC2 or LightSail.
If you want to develop code using lots of AWS tools, use CodeStar.
Related
Firstly, I apologize for the rather basic question. I am just beginning to learn about Microservices Architecture and would like to get my basics right.
I was wondering if topics such as AWS cloud services/web services imply the Microservices architecture. For instance, if someone is working on an AWS project does that mean that he is using a microservice architecture? I do understand AWS, Docker etc is more of a platform. Are they exclusively for Microservices?
I would really appreciate a short clarification
Microservices, cloud infrastructure like Amazon Web Services, and container infrastructure like Docker are three separate things; you can use any of these independently of the others.
"Microservices" refers to a style of building a large application out of independently-deployable parts that communicate over the network. A well-designed microservice architecture shouldn't depend on sharing files between components, and could reasonably run distributed across several systems. Individual services could run on bare-metal hosts and outside containers. This is often in contrast to a "monolithic" application, a single large deployable where all parts have to be deployed together, but where components can communicate with ordinary function calls.
Docker provides a way of packaging and running applications that are isolated from their host system. If you have an application that depends on a specific version of Python with specific C library dependencies, those can be bundled into a Docker image, and you can just run it without needing to separately install them on the host.
Public-cloud services like AWS fundamentally let you rent someone else's computer by the hour. An AWS Elastic Compute Cloud (EC2) instance literally is just a computer that you can ssh into and run things. AWS, like most other public-cloud providers offers a couple of tiers of services on top of this; a cloud-specific networking and security layer, various pre-packaged open-source tools as services (you can rent a MySQL or PostgreSQL database by the hour using AWS RDS, for example), and then various proprietary cloud-specific offerings (Amazon's DynamoDB database, analytics and machine-learning services). This usually gives you "somewhere to run it" more than any particular design features, unless you're opting to use a cloud's proprietary offerings.
Now, these things can go together neatly:
You design your application to run as microservices; you build and unit-test them locally, without any cloud or container infrastructure.
You package each microservice to run in a Docker container, and do local integration testing using Docker Compose, without any cloud infrastructure.
You further set up your combined application to deploy in Kubernetes, using Docker Desktop or Minikube to test it locally, again without any cloud infrastructure.
You get a public-cloud Kubernetes cluster (AWS EKS, Google GKE, Azure AKS, ...) and deploy the same application there, using the cloud's DNS and load balancing capabilities.
Again, all of these steps are basically independent of each other. You could deploy a monolithic application in containers; you could deploy microservices directly on cloud compute instances; you could run containers in an on-premises environment or directly on cloud instances, instead of using a container orchestrator.
No, using a cloud provider does not imply using a microservice architecture.
AWS can be (and is often) used to spin up a monolithic service, e.g. just a single EC2 server which uses a single RDS database.
Utilizing Docker and a container orchestrator like ECS or EKS, also does not mean on its own that one has a microservice architecture. If you split your backend and frontend into two Docker containers that get run on ECS, that's really not a microservice architecture. Even if you'd horizontally scale them, so you'd have multiple identical containers running for both the backend and frontend service, they still wouldn't be thought of as microservices.
I have created a Spring cloud microservices based application with netflix APIs (Eureka, config, zuul etc). can some one explain me how to deploy that on AWS? I am very new to AWS. I have to deploy development instance of my application.
Do I need to integrate docker before that or I can go ahead without docker as well.
As long as your application is self-contained and you have externalised your configurations, you should not have any issue.
Go through this link which discusses what it takes to deploy an App to Cloud Beyond 15 factor
Use AWS BeanStalk to deploy and Manage your application. Dockerizing your app is not a predicament inorder to deploy your app to AWS.
If you use an EC2 instance then it's configuration is no different to what you do on your local machine/server. It's just a virtual machine. No need to dockerize or anything like that. And if you're new to AWS, I'd rather suggest to to just that. Once you get your head around, you can explore other options.
For example, AWS Beanstalk seems like a popular option. It provides a very secure and reliable configuration out of the box with no effort on your part. And yes, it does use docker under the hood, but you won't need to deal with it directly unless you choose to. Well, at least in most common cases. It supports few different ways of deployment which amazon calls "Application Environments". See here for details. Just choose the one you like and follow instructions. I'd like to warn you though that whilst Beanstalk is usually easier then EC2 to setup and use when dealing with a typical web application, your mileage might vary depending on your application's actual needs.
Amazon Elastic container Service / Elastic Kubernetes Service is also a good option to look into.
These services depend on the Docker Images of your application. Auto Scaling, Availability cross region replication will be taken care by the Cloud provider.
Hope this helps.
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
Can IBM Integration Bus((and /or Websphere message Broker) be implemeted on AWS ? Can my on-premise ESB be migrated to AWS Cloud ?
Thanks in Advance
AWS EC2 allows importing VMs into an AMI then you can start an EC2 instance using that image. If you are new to AWS you can check the link below
https://aws.amazon.com/ec2/vm-import/
However, you should be careful about IIB license and how many machines you can install it on before regesting the AMI in a launch configuration and create an autoscaling group and set a scaling policy that can start instances more that what you purchased.
That's very much possible. There are several possible approaches.
1. IIB on EC2
Installing and configuring IIB on an EC2 instance is very much similar to doing the same in on-premise servers. Only difference is that the physical server is in AWS Cloud. While this approach gives you maximum flexibility to design your architecture any way, it does not take advantage of the basic features of the cloud.
2. Quick Start
IIB is available for deployment under AWS Quick Start. You can read more about this here. This helps you get started quickly by setting up the entire environment in a few clicks. But, if you're planning to migrate your existing architecture to AWS, this may not suit you as the architecture is pre-defined with limited options for customization.
3. IIB on Containers
ACE 11 provides better support for containerization. You can read more about running IIB 10 on containers here and ACE 11 on containers here. After this, the containers can be deployed into fully managed containers such as AWS Elastic Container Service or your own container configuration such as Docker on EC2.
Yes of course, AWS provides the IAAS and you just install whatever you want inside. Make sure you open ports, use specific credentials for the instalation (dont use admin) and everything should work.
IBM also provides docker images of integration bus v10 and APP Connect Enterprise v11. This is true for all their integration tools, MQ, API Management and more.
Not restricted to AWS.
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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.