Amazon Elastic Container Service (Amazon ECS) vs. AWS Elastic Beanstalk vs. Google App Engine

Amazon ECS is well suited for the scenarios where you want to deploy a microservice to a cloud and instead of manually specifying instance size, number of instances and then specifying the configurations and connecting it with other cloud services like database service, secret manager service etc., you just want to specify these configurations as a file and using that file, the ECS would deploy the service and keep it healthy. It might be less suited for a scenario when you don't want to stick to AWS specific solution for your microservice deployment. The ECS configuration file is specific to AWS ECS and may not be useful for other cloud providers like Azure etc.

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I have been using AWS Elastic Beanstalk for more than 5 years, and it has made our life so easy and hassle-free. Here are some scenarios where it excels -

• I have been using different AWS services like EC2, S3, Cloudfront, Serverless, etc. And Elastic Beanstalk makes our lives easier by tieing each service together and making the deployment a smooth process.
• N number of integrations with different CI/CD pipelines make this most engineer's favourite service.
• Scalability & Security comes with the service, which makes it the absolute perfect product for your business.

Personally, I haven't found any situations where it's not appropriate for the use cases it can be used. The pricing is also very cost-effective.

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App Engine is such a good resource for our team both internally and externally. You have complete control over your app, how it runs, when it runs, and more while Google handles the back-end, scaling, orchestration, and so on. If you are serving a tool, system, or web page, it's perfect. If you are serving something back-end, like an automation or ETL workflow, you should be a little considerate or careful with how you are structuring that job. For instance, the Standard environment in Google App Engine will present you with a resource limit for your server calls. If your operations are known to take longer than, say, 10 minutes or so, you may be better off moving to the Flexible environment (which may be a little more expensive but certainly a little more powerful and a little less limited) or even moving that workflow to something like Google Compute Engine or another managed service.

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• One of the biggest advantages is the flexibility to change underlying EC2 instances. As the traffic or demand increases, we can easily change EC2 instances without any issues.
• Amazon ECS APIs are extremely robust and one can start and stop containers by firing one post request only. So, it is not mandatory to keep the demo solutions up for every time. Just at the time of demo fire the command - make the container up and running - do the demo - down the container with API. A simple portal can control every container which helps non-technical (sales, marketing) to do the demo without keeping the solutions up for the entire time frame.

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• Getting a project set up using the console or CLI is easy compared to other [computing] platforms.
• AWS Elastic Beanstalk supports a variety of programming languages so teams can experiment with different frameworks but still use the same compute platform for rapid prototyping.
• Common application architectures can be referenced as patterns during project [setup].
• Multiple environments can be deployed for an application giving more flexibility for experimentation.

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• Quick to develop, quick to deploy. You can be up and running on Google App Engine in no time.
• Flexible. We use Java for some services and Node.js for others.
• Great security features. We have been consistently impressed with the security and authentication features of Google App Engine.

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• Another AWS Service - While AWS has a service for just about everything, that is also a negative point. There is no service that does 4 out of 4 things you need. This service does 3 out of 4, another service does the fourth thing you need and another two things that the other service does.
• With AWS things in general, it's really hard to remain cloud agnostic. Keep that in mind.

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• Limited to the frameworks and configurations that AWS supports. There is no native way to use Elastic Beanstalk to deploy a Go application behind Nginx, for example.
• It's not always clear what's changed on an underlying system when AWS updates an EB stack; the new version is announced, but AWS does not say what specifically changed in the underlying configuration. This can have unintended consequences and result in additional work in order to figure out what changes were made.

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• There is a slight learning curve to getting used to code on Google App Engine.
• Google Cloud Datastore is Google's NoSQL database in the cloud that your applications can use. NoSQL databases, by design, cannot give handle complex queries on the data. This means that sometimes you need to think carefully about your data structures - so that you can get the results you need in your code.
• Setting up billing is a little annoying. It does not seem to save billing information to your account so you can re-use the same information across different Cloud projects. Each project requires you to re-enter all your billing information (if required)

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As our technology grows, it makes more sense to individually provision each server rather than have it done via beanstalk. There are several reasons to do so, which I cannot explain without further diving into the architecture itself, but I can tell you this. With automation, you also loose the flexibility to morph the system for your specific needs. So if you expect that in future you need more customization to your deployment process, then there is a good chance that you might try to do things individually rather than use an automation like beanstalk.

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App Engine is a solid choice for deployments to Google Cloud Platform that do not want to move entirely to a Kubernetes-based container architecture using a different Google product. For rapid prototyping of new applications and fairly straightforward web application deployments, we'll continue to leverage the capabilities that App Engine affords us.

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Aside from some ECS-specific terms to learn at first, learning & starting to use ECS is relatively straightforward. AWS docs on the topic are also of high quality, with sound & relevant examples to follow. Troubleshooting container issues is also a breeze thanks to CloudWatch integration & helpful error messages on the AWS console.

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The overall usability is good enough, as far as the scaling, interactive UI and logging system is concerned, could do a lot better when it comes to the efficiency, in case of complicated node logics and complicated node architectures. It can have better software compatibility and can try to support collaboration with more softwares

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I had to revisit the UI after a year of just setting up and forgetting. The UI got some improvements but the amount of navigation we have to go through to setup a new app has increased but also got easier to setup. Gemini now is integrated and make getting answers faster

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Support is relatively good, although the documentation sometimes is lacking, as well as outdated in our experience, especially when we initiated the process of using this service. But once we found how to assemble things, we haven't really required support from anyone at AWS, the service works without problems so we haven't had the need to contact support, which speaks well of how ECS is built.

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As I described earlier it has been really cost effective and really easy for fellow developers who don't want to waste weeks and weeks into learning and manually deploying stuff which basically takes month to create and go live with the Minimal viable product (MVP). With AWS Beanstalk within a week a developer can go live with the Minimal viable product easily.

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Good amount of documentation available for Google App Engine and in general there is large developer community around Google App Engine and other products it interacts with. Lastly, Google support is great in general. No issues so far with them.

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- Do as many experiments as you can before you commit on using beanstalk or other AWS features. - Keep future state in mind. Think through what comes next, and if that is technically possible to do so. - Always factor in cost in terms of scaling. - We learned a valuable lesson when we wanted to go multi-region, because then we realized many things needs to change in code. So if you plan on using this a lot, factor multiple regions.

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I chose Amazon ECS over Amazon EKS and other products because the whole infrastructure was decided to be designed on AWS cloud and Amazon ECS made it easier to make the clusters live in just a few minutes. Amazon ECS has better integration with other AWS services and we don't have to look for plugins to do the things, everything is available and can be configured from the AWS console.

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We also use Heroku and it is a great platform for smaller projects and light Node.js services, but we have found that in terms of cost, the Elastic Beanstalk option is more affordable for the projects that we undertake. The fact that it sits inside of the greater AWS Cloud offering also compels us to use it, since integration is simpler. We have also evaluated Microsoft Azure and gave up trying to get an extremely basic implementation up and running after a few days of struggling with its mediocre user interface and constant issues with documentation being outdated. The authentication model is also badly broken and trying to manage resources is a pain. One cannot compare Azure with anything that Amazon has created in the cloud space since Azure really isn't a mature platform and we are always left wanting when we have to interface with it.

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We were on another much smaller cloud provider and decided to make the switch for several reasons - stability, breadth of services, and security. In reviewing options, GCP provided the best mixtures of meeting our needs while also balancing the overall cost of the service as compared to the other major players in Azure and AWS.

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• Easy to manage as it has an orchestrator to manage the containers.
• Less costs and more flexibility with Fargate.
• Negative (tied to AWS, so could not easily integrate other tools like running a Redis cluster. Still, it works but not easily like Kubernetes.

• till now we had not Calculated ROI as the project is still evolving and we had to keep on changing the environment implementation
• it meets our purpose of quick deployment as compared to on-premises deployment
• till now we look good as we also controlled our expenses which increased suddenly in the middle of deployment activity

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• Effective employee adoption through ease of use.
• Effective integration to other java based frameworks.
• Time to market is very quick. Build, test, deploy and use.
• The GAE Whitelist for java is an important resource to know what works and what does not. So use it. It would also be nice for Google to expand on items that are allowed on GAE platform.

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