AWS Elastic Beanstalk vs. AWS Fargate

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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Fargate is well suited for web APIs, microservices, background jobs, and applications with changing traffic. It is useful when teams want to run containers without managing servers. It is less appropriate for workloads that run constantly at large scale, need special hardware, require deep server control, or depend on very low costs and highly customized networking or storage requirements.

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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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• scalability
• ease of use
• agility to up or downsize

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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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• Offers less control over the underlying server.
• Storage options are more limited than EC2.
• Large numbers of tasks may hit launch-rate limits.

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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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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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It's a very practical service to use. If you need to deploy any application with a Database, disk storage, you're pretty much set.

Everything around that can be taken care of using other AWS services. Like secrets manager, certificate manager, RDS ...

And the CI/CD part is also very easy to setup, you only need on AWS CLI command to trigger a deployment, and done !

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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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AWS provides different support tiers. They are usually very reactive and are able to help solve the issues very quickly.

As for everything, the higher the support tier you get, the better and faster support you get.

If you're also a part of big company, you probably have solution architects at your disposal to help you with any inqueries.

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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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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 found the extra cost saved us frustration and time and ultimately money in the long run

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Pricing and billing of AWS Fargate is loosely tied to your exisiting AWS billing. You're unlikely to only use Fargate in your AWS subscription, so you get billed for everything alltoghter.

Fargate is naturally a bit more expensive that usuel docker services, but with careful planning and architecturing, you can have a very manageable cost.

You can also rely on Saving plans to reduce your bill.

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• 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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• Has made seasonal apps/tools cheap to run/maintain.
• Pay for what you use helps compare many A/B tests.
• No server management means faster deploys.

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