AWS Elastic Beanstalk vs. Google Compute Engine

AWS Elastic Beanstalk is well suited for [the] rapid development of applications that use standard compute platforms based on popular programming languages. So getting a Go, Python, Ruby, or Node.js app going in AWS Elastic Beanstalk will be easy. For non-standard applications, containers provide another option for using AWS Elastic Beanstalk. In either case, AWS Elastic Beanstalk is well suited for applications that are [self-contained]. AWS Elastic Beanstalk is also good for development or test environments that need a built-in deployment method. AWS Elastic Beanstalk is less appropriate for complex applications that rely on multiple AWS services. While deploying and running the base code might be easy to get going, it may be difficult to apply permissions and integrations with the other services.

Incentivized

It is excellent if you have any workloads that need raw computing or plan to have any state-full services running in your environment like DBs (for which you don't want to use Managed services), cache, etc. It also gives you complete control over which versions of software, OS, etc., you need, and thus, you can build anything and deploy it on GCE.

Incentivized

• Extremely easy to get set up and get apps deployed.
• Integrates really well with existing build processes and is manageable through a suite of CLI tools.
• It is very easy to scale up.
• The documentation is exceptionally detailed and covers a very wide range of deployment scenarios.

Incentivized

• A simple web-based interface that is a breeze to train new engineers to use. Our experienced engineers never have trouble finding or doing anything on GCE.
• Sustained use and Committed use discounts mean we get top-tier VMs for an incredibly competitive price.
• Wonderful identity and access management that gives us peace-of-mind when granting access to machines to contractors and other 3rd parties.
• Fast VMs, lastest in hardware, and enough RAM to power even the hungriest of our services.

Incentivized

• How to more easily integrate with other other AWS services. There are plenty out there, but it's not quite as seamless as I feel like it should be to mix and match products.
• Make backing up easier when scaling the server. It took quite a bit of time to make sure we had everything set up in case something went wrong.
• When you are first starting to use AWS, the dashboard can be very intimidating. There are countless products all with names that aren't very indicative of what they actually do.

Incentivized

• The L7 load balancer can be difficult to get set up. It's limited in its functionality, especially with the container engine.
• It's hard to find certain objects on the web console. Often times the things I need to get to are buried in advanced menus.
• Google's decision to only support MySQL on their relational DB service means that I have to manage Postgres instances in Compute on my own, managing everything from storage to backups.

Incentivized

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.

Incentivized

Its pretty good, easy and good performance. Also, interface is very good for starters compared to competitors. Infra as Code (IaC) using Terraform even added easiness for creation, management and deletion of compute Virtual Machines (VM). Overall, very good and very easy cloud based compute platform which simplified infrastructure, very much recommend.

Incentivized

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

Incentivized

Having interacted with several cloud services, GCE stands out to me as more usable than most. The naming and locating of features is a little more intuitive than most I've interacted with, and hinting is also quite helpful. Getting staff up to speed has proven to be overall less painful than others.

Incentivized

Google Compute Engine works well for cloud project with lesser geographical audience. It sometimes gives error while everything is set up perfectly. We also keep on check any updates available because that's one reason of site getting down. Google Compute Engine is ultimately a top solution to build an app and publish it online within a few minutes

Incentivized

The raw computer power is excellent; our applications feel snappy, pages load almos instantly for our customers and so on. The primary reason it is not a perfect 10 is that the native tools for monitoring individual VM performance can be complex, making it challenging to easily diagnose specific resource bottlenecks without significant configuration

Incentivized

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.

Incentivized

• The documentation needs to be better for intermediate users - There are first steps that one can easily follow, but after that, the documentation is often spotty or not in a form where one can follow the steps and accomplish the task. Also, the documentation and the product often go out of sync, where the commands from the documentation do not work with the current version of the product.
• Google support was great and their presence on site was very helpful in dealing with various issues.

Incentivized

- 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.

Incentivized

There are many services like AWS Elastic beanstalk, but there are none with the maturity in the platform or the cost-effectiveness of AWS Elastic Beanstalk. Also, AWS Elastic Beanstalk is the oldest among them, so there are more people with AWS experience than the other platforms. The only thing is their documentation and UX are a bit old, which doesn't stop it from performing greatly, but yes, if you are looking for better UX, then you can check out other options.

Incentivized

When configuring Amazon ECS, it is a bit confusing as you are not able to find the actual issue. You need to enable Additional AppInsights to get detailed level info, which is not a concern when configuring on the Instance Level. Moreover, Azure VM does not provide an in-browser option; instead, it is Azure Bastion, but for that, you have to enable a dedicated subnet, which is a bit unnecessary.

Incentivized

It works really well with other Google Cloud services, making it easy to build scalable solutions across different teams and locations.

Incentivized

• Elastic Beanstalk removes countless hours from development team responsibility, freeing up those resources to instead focus on building the products that our customers want to use.
• As a business that is already embedded into using EC2 instances, it's essentially free to leverage the work that AWS performs on configuring the Elastic Beanstalk stacks.
• With Elastic Beanstalk, while there is still a responsibility to ensure that applications can work with updated underlying dependencies, it's much easier when AWS handled the heavy lifting of updating the stacks.

Incentivized

• Scalability means flexibility and less upfront costs
• Can become expensive when hard set compute requirements are clear, but things like Spot VMs can help here too, or just having your own infrastructure and scaling up with Google. This is for more advanced cases though
• Ramp up time is long, but after that it is quick to do many things and ROI is awesome

Incentivized