Akamai Cloud Computing vs. AWS Elastic Beanstalk vs. AWS Lambda

Akamai Connected Cloud Linode would be a good service to host a content delivery network (CDN) because of its edge network but I'd prefer not to use Akamai Connected Cloud Linode for tasks that need GPU power such as Machine Learning or Artificial Intelligence (AI) because Akamai Connected Cloud Linode lacks deep GPU compute compared to AWS or Google Cloud or Microsoft Azure

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.

Incentivized

Lambda excels at event-driven, short-lived tasks, such as processing files or building simple APIs. However, it's less ideal for long-running, computationally intensive, or applications that rely on carrying the state between jobs. Cold starts and constant load can easily balloon the costs.

Incentivized

• It's super easy-to-use - set up a complete virtual environment in a few minutes.
• Linode is the ONLY service I know that will let you DOWNSIZE a VM - super useful.
• The price is right - spin up any size server and add additional block storage if needed.
• Object memory is cheap and integrates very well with S3 CLIs and applications.
• I've been very happy with the knowledgeable and friendly customer service.
• The more recent additions of a firewall and Kubernetes is a welcome plus.
• The load balancer ("Load Balancer") service is easy to spin up and configure.

Incentivized

• 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.

Incentivized

• No provisioning required - we don't have to pay anything upfront
• Serverless deployment - it gets executed only when request comes and we pay only for the time the request is getting executed
• Integrates well with AWS CloudWatch triggers so it is easy to setup scheduled tasks like cron jobs

Incentivized

• Some of the documentation requires some hand-holding to get started. It does explain how to do things, but sometimes finding the answer takes work.
• Some of the settings are not obvious, or in locations that are not completely clear without experience.

Incentivized

• 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.

Incentivized

• Developing test cases for Lambda functions can be difficult. For functions that require some sort of input it can be tough to develop the proper payload and event for a test.
• For the uninitiated, deploying functions with Infrastructure as Code tools can be a challenging undertaking.
• Logging the output of a function feels disjointed from running the function in the console. A tighter integration with operational logging would be appreciated, perhaps being able to view function logs from the Lambda console instead of having to navigate over to CloudWatch.
• Sometimes its difficult to determine the correct permissions needed for Lambda execution from other AWS services.

Incentivized

I've been with them a long time. They provide me with the capabilities I need coupled with knowledgeable support that's not pay-for-extra. However, if I move to a non-Linux OS, the level of support by necessity will drop off. I can still ask questions about the infrastructure but I my ability to ask about OS features will decrease.

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

Simple and clear, no BS interface. From a design perspective it's no Apple or Stripe, but it does what it needs without making me want to stick a fork in my eyes, like when being forced to use Azure, AWS or GCP.

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

I give it a seven is usability because it's AWS. Their UI's are always clunkier than the competition and their documentation is rather cumbersome. There's SO MUCH to dig through and it's a gamble if you actually end up finding the corresponding info if it will actually help. Like I said before, going to google with a specific problem is likely a better route because AWS is quite ubiquitous and chances are you're not the first to encounter the problem. That being said, using SAM (Serverless application model) and it's SAM Local environment makes running local instances of your Lambdas in dev environments painless and quite fun. Using Nodejs + Lambda + SAM Local + VS Code debugger = AWESOME.

Incentivized

There is very little planned downtime. Whenever planned downtime is necessary I'm always given lots of advanced notice and an explanation that I can pass along to my users that they'll understand. I really appreciate that Linode appreciates my commitment to reliable service to my users. It shows that they believe they've been successful when I'm successful.

Incentivized

Servers are well dimensioned and price performant. Of course one always wants more, so if they were to upgrade their hardware for the same price I'd consider moving more workloads. Networking - never had an issue. Hardware speeds - disks are fast and can grow to great size.

Incentivized

Support was excellent and fast. The documentation is extensive and helpful. I learned many things from their online documentation. I did not contact them by phone, but email took a day or less. Complex problems would probably need a service contract. I liked the friendly and polite tone of the support.

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

Amazon consistently provides comprehensive and easy-to-parse documentation of all AWS features and services. Most development team members find what they need with a quick internet search of the AWS documentation available online. If you need advanced support, though, you might need to engage an AWS engineer, and that could be an unexpected (or unwelcome) expense.

Incentivized

We got kick started with an initial walkthrough along with some free credits. The initial walkthrough helped us to understand Linode's ecosystem and start our hands on with Linode. We tried out some apps from Marketplace initially with the free credits, which not only helped us understand Linode better, but also those apps. We had implemented many such apps to our customers with Linode

Incentivized

We're a small organization. The implementation of our Linode solution was trivial. Once I justified a cloud server to my bosses over a co-location -- the co-lo wasn't as fast as our linode server in load tests -- it was a matter of moving one Linux implementation to another. Trivial.

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

We switched to Linode from Namecheap due to poor uptime, and never had any issues with stability ever again after switching. We also cut our costs in half by switching. We compared Linode to DigitalOcean and Vultr, with the primary factor that caused us to go with Linode initially being their documentation. After using Linode for 3 years, their amazing support is another reason why we wouldn't consider anyone else at this point.

Incentivized

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.

Incentivized

AWS Lambda is good for short running functions, and ideally in response to events within AWS. Google App Engine is a more robust environment which can have complex code running for long periods of time, and across more than one instance of hardware. Google App Engine allows for both front-end and back-end infrastructure, while AWS Lambda is only for small back-end functions

Incentivized

Although I use only a fraction of their product offerings, the total set makes scalability an easy goal to shoot for. As I said, I have a few customers that use the services my Linode provides...and I like it that way. However, should I need to scale up, I can...without incurring any more cost than I need to.

Incentivized

• With the partnership of Linode, Configr is today the best performance hosting solution in Brazil.
• With Linode, Configr can provide a PaaS solution without the cost of taking care of all the infrastructure issues such as IaaS.
• Linode allowed Configr to be one of the biggest hosting companies in Brazil.

Incentivized

• 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

Incentivized

• Positive - Only paying for when code is run, unlike virtual machines where you pay always regardless of processing power usage.
• Positive - Scalability and accommodating larger amounts of demand is much cheaper. Instead of scaling up virtual machines and increasing the prices you pay for that, you are just increasing the number of times your lambda function is run.
• Negative - Debugging/troubleshooting, and developing for lambda functions take a bit more time to get used to, and migrating code from virtual machines and normal processes to Lambda functions can take a bit of time.

Incentivized