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
Oracle Management Cloud
Score 6.1 out of 10
N/A
The Oracle Management Cloud is a PaaS combining a suite of IT infrastructure and application performance monitoring solutions. On the standard edition the Oracle Management Cloud includes Oracle Application Performance Monitoring and Infrastructure Monitoring. On the Enterprise Edition the Management Cloud also includes Oracle IT Analyics and Oracle Orchestration. The Management Cloud is also available in a Log Analytics edition.
N/A
Pricing
AWS Elastic Beanstalk
Oracle Management Cloud
Editions & Modules
No Charge
$0
Users pay for AWS resources (e.g. EC2, S3 buckets, etc.) used to store and run the application.
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.
Ideal for a complex organization with requirements to build very complex reports. Especially useful for organizations that already have numerous Oracle products and need to pull information from them. This tool works best when plugged in with other Oracle tools and databases. If you're a larger company, and/or if you're managing a lot of data, Oracle IT Analytics Cloud Service is the perfect tool to manage your Oracle deployment. It provides a number of different options for intelligent analysis while not being too overwhelming to manage. Companies that want a robust tool to manage all data and present it in a visually appealing way to users will greatly benefit from this tool. The tool is very customizable and can be tailored to meet the needs of different users.
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.
There's a pretty steep learning curve that needs to be overcome in order to properly deploy this tool. So, unless you're a seasoned IT administrator, you may have a fair amount of homework to do. Implementation and maintenance of this takes a bucket of consulting hours from outside consultants to come in and set up the tool and regularly maintain it, in the long run, this could be costly.
The dashboard is not as easy to set up as I would like, however, after setup it will serve your purpose in the best possible way. You may not be able to find out how some data related to another and you can create a report that you think has all the details you need, but it comes up blank because the data really is not connected.
There aren't enough self-learning materials available like tutorials and how-to videos. I would like to have access to more e-tutorials from inside the tool. A steep learning curve for most. It would be nice to have a robust learning portal within the application where users can access self-learning material directly from the application and step to spet guides on how to perform different tasks.
Does not provide the ease of adding additional data sources without lots of complications. Even though it can handle large data sets, rendering of reports can take a fairly long time if the parameter set is large. For some time it seems like processing takes a bit of time when large data sets are being used. This is not the case with other competing tools.
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.
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 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.
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.
Oracle Analytics Cloud is an enterprise solution and can't be compared apple-to-apple with a data visualization tool like Tableau. This is not the same use at all. Before selecting Oracle Analytics Cloud, it is most important to consider the data you are looking to collect and how you plan to visualize it. Other tools like Tableau and microstrategy feel smoother to work with, have better UI's and are quicker when processing data. It is also important to think through how you will use the data across your organizations. Can have a steep learning curve but once you are well trained on this tool, the possibilities are endless. The tool is highly customizable and will generate what you design it to generate. If you are having issues with reports and analytics, it is most likely due to data quality issues. Oracle Analytics Cloud also benefits by adding Essbase in it, to perform multi-dimensional analytics.
