Amazon EC2 Auto Scaling helps users maintain application availability and allows users to automatically add or remove EC2 instances according to definable conditions.
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AWS Elastic Beanstalk
Score 8.1 out of 10
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AWS Elastic Beanstalk is the platform-as-a-service offering provided by Amazon and designed to leverage AWS services such as Amazon Elastic Cloud Compute (Amazon EC2), Amazon Simple Storage Service (Amazon S3).
$35
per month
Pricing
Amazon EC2 Auto Scaling
AWS Elastic Beanstalk
Editions & Modules
No answers on this topic
No Charge
$0
Users pay for AWS resources (e.g. EC2, S3 buckets, etc.) used to store and run the application.
The main reason is our total infra is created on AWS and we tend to use the natural service by AWS rather than third party tools, which has more advantages when the auto scaling interacts with other AWS services and its way easy to configure when we compare it with counter …
If you need to establish a system right away, in the past it took weeks or months to request a quote from the vendor and receive the equipment. Now, with Amazon EC2 in less than tens of minutes or hours, you can create a test environment and test it without any inconvenience.
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.
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.
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.
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.
Usability is good since we already know how AWS works. For those that are new it might be a little bit confusing at the beginning but they are improving it at a fast pace. Even though AWS keeps changing the user interface constantly, it is still powerful, understandable and easy to use. For technical people, they still offer the CLI.
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
The platform works as is. The help and tutorials on the help page can help you to setup the entire platform without problems, and also provides help on a huge variety of problems. Amazon also provides support plans. We have the basic support plan, but Amazon offers three support tiers, and we know that it works perfect.
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.
- 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.
The main reason is our total infra is created on AWS and we tend to use the natural service by AWS rather than third party tools, which has more advantages when the auto scaling interacts with other AWS services and its way easy to configure when we compare it with counter parts like Autoscale from Microsoft Azure.
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.
We will devote more time to development than server administration, but we will require additional time if you migrate from another ecosystem.
Fault detection and reporting are automated in the old server, and bandwidth is fixed per month, but everything is manageable automatically. We only pay for the resources we use.
After some months, we met our return on investment (ROI).
