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
Red Hat OpenShift
Score 8.6 out of 10
N/A
OpenShift is Red Hat's Cloud Computing Platform as a Service (PaaS) offering. OpenShift is an application platform in the cloud where application developers and teams can build, test, deploy, and run their applications.
$0.08
per hour
Pricing
AWS Elastic Beanstalk
Red Hat OpenShift
Editions & Modules
No Charge
$0
Users pay for AWS resources (e.g. EC2, S3 buckets, etc.) used to store and run the application.
The AWS Elastic Beanstalk containerization capability is the best and effective Automatic scalling, high level security management and the platform itself is very easy on initial starting. The Application isolation from workloads and the ability on connecting the AWS Elastic …
The AWS platform provides a great deal of configurability that is abstracted and provided very well through AWS Elastic Beanstalk. This is the main reason for choosing Elastic Beanstalk over competing services. Another reason for selecting AWS Beanstalk was vendor …
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.
Well, in our case, because I have two use cases, one is with the operator, which obviously is super easy with OpenShift because it's just click, click start aside from the issue from the operator. But that's a different interview. And the other point is for the web portal that our portal team uses, it's very easy. Two perform a task needed for them to do their deployment, their pipelines, and their daily Java.
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.
It provides you with a landing pad to modernize what you have in a phased approach so you don't have to do it all at once, right? You can take small pieces of work and implement those on OpenShift over time. It enables us to be able to implement things like GI ops configuration as a service, and infrastructure as a service using the tools that are native to OpenShift, which gives us far greater reliability and consistency as far as monitoring for any kind of drift and configuration or unauthorized changes. So it pretty much gives us a lot of visibility on things that are otherwise relatively difficult to see using the old means of doing what we do. So it provides us with a modern set of tools to accomplish all those objectives.
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.
Network of observability, so having one single screen to see to have some network-related metrics for the pod levels. Also at the cluster itself level and more importantly is ease of use for troubleshooting when there's any timeout. This has been the single kind of issue I've been facing for my three years of experience with OpenShift and it hasn't been an easy task for such troubleshooting.
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.
Leverage OpenShift Online constantly at both the free and paid tiers. While AWS is convenient, it often brings more administration than I want to deal with for a quick application (i.e. Drupal or Wordpress blog). OpenShift also simplifies the DNS registration and ability to share application environments with team members
It is a great tool to manage your applications. You just need to write the codes, and after that with one click, your app will be online and accessible from the internet. That is a huge help for people who do not know about infrastructure or do not want to spend money on maintaining infrastructure.
As I said before, the obserability is one of the weakest point of OpenShift and that has a lot to do with usability. The Kibana console is not fully integrated with OpenShift console and you have to switch from tab to tab to use it. Same with Prometheus, Jaeger and Grafan, it's a "simple" integration but if you want to do complex queries or dashboards you have to go to the specific console
Applications deployed to OpenShift clusters stay responsive when peak load hits or when the traffic dies down - since the platform reacts by scaling out or scaling in the deployed applications elastically - achieved through' policy sense and response automation - leveraging monitoring, measuring (metrics), auto-scaling to meet SLAs, SLOs, and SLIs. This approach works for stateless or stateful business logic hosting applications. The deployed applications perform consistently, stably, and securely across many deployment platforms - public clouds, private data centers, at the edge, or on factory floors - hosted by bare metal or virtual environments.
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.
Their customer support team is good and quick to respond. On a couple of occassions, they have helped us in solving some issues which we were finding a tad difficult to comprehend. On a rare occasion, the response was a bit slow but maybe it was because of the festival season. Overall a good experience on this front.
- 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.
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 had some existing apps and were looking for a platform to modernize our app deployments and scale for future growth. Based on Kubernetes, OpenShift offers more flexibility and customization. We could deploy any type of containerized application, not just Cloud Foundry-specific ones. I particularly liked the built-in security and its focus on rapid and automated deployments. Moreover, our cloud strategy isn't set in stone. OpenShift's flexibility means we could deploy on-prem, in multiple public clouds, or use a hybrid approach - something other products couldn't offer as expected.
It's easy to understand what are being billed and what's included in each type of subscription. Same with the support (Std or Premium) you know exactly what to expect when you need to use it. The "core" unit approach on the subscription made really simple to scale and carry the workloads from one site to another.
I'll say a lot of positive impact because when we started making this product aware to all the application domains in our business, they saw how easy to use. I mean we are giving a lot of control to the development team, how they can scale their application, how can they check the health of the application, and what action they can take if they are in any kind of failure or even meeting the business's SLA. So there are a lot of capabilities and those are really new features they can use. Those I think are a good use of OpenShift.
