Akamai Technologies, headquartered in Boston, offers Akamai Connected Cloud, a content delivery network (CDN) with a variety of services used to guarantee application, API, and media delivery.
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AWS Elastic Beanstalk
Score 8.0 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
AWS Lambda
Score 8.3 out of 10
N/A
AWS Lambda is a serverless computing platform that lets users run code without provisioning or managing servers. With Lambda, users can run code for virtually any type of app or backend service—all with zero administration. It takes of requirements to run and scale code with high availability.
$NaN
Per 1 ms
Pricing
Akamai CDN
AWS Elastic Beanstalk
AWS Lambda
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.
I am just getting into AWS at work and it will be difficult to supplant the incumbent Akamai solution as there is simply nothing wrong with it - from my point of view. I suspect we will be looking at integrating Akamai/AWS solutions in the future as the effort and or business …
We've used -- and considered -- a whole number of CDN offerings. The good news is that almost all of the CDN products on the market are terrific, and will pay for themselves via increased customer satisfaction and lower monthly hosting bills. For some cases, we're still more …
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 …
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 …
Honestly, I haven't tried any other alternative products. As already mentioned, I am already heavily invested in AWS, so EBS was a natural choice for me. In other reviews, I have found, AWS is better than its competitors. There are more flavors, and options in AWS, better …
AWS Lambda is much easier to use than the near alternatives. It is so straightforward and lightweight it is my primary service for handling small transactions or triggers. The other services require more setup time and are more complex to use. AWS Lambda takes your code snippet …
AWS is great product and a close match our expectations. It is close to Azure in function but more feature rich with API and support documents. From my experience, it is cheaper compared with our competitors and provides better interface. Overall our dev engineers prefer AWS …
Akamai is a well-established brand name with a great product. It meets and many time exceeds the needs for global content delivery and security management layer at the edge. Fine grain security tuning seems cumbersome as the definition of the app keeps changing. It also requires an investment of time for the setup which doesn't necessarily make sense for smaller scale scenarios. Some products offered by AWS, Azure or the Google Cloud can be more tightly integrated with cloud provider offerings thus easier to configure.
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.
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.
Content offloading - once rules are set up within Akamai you don't need to even think about how many images or large JavaScript or CSS files (for example) are being served from your own estate, Akamai takes care of it all via rules that are quick, easy and flexible.
Page caching - for pages that don't change very often Akamai allows you to set up rules, quickly and easily, to serve up your page content for you, which takes even more load away from your origin servers.
Quick rollback - the Akamai system allows easy testing of rules and changes via a staging system, and also offers a quick rollback option, which is perfect for the rare occasions when something has been set up incorrectly.
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.
The interface in their control centre could be a bit more user-friendly with some of the settings in places that you wouldn't expect them to be. The search offsets this problem to an extent but it's still sometimes slower than you'd like to find what you are looking for.
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.
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.
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.
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
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.
Their support documents are excellent and provide a lot of useful information for all their services. The only reason I didn't give them a 10 is that the time it takes for them to respond to an issue could be slightly faster.
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.
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.
- 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've used -- and considered -- a whole number of CDN offerings. The good news is that almost all of the CDN products on the market are terrific, and will pay for themselves via increased customer satisfaction and lower monthly hosting bills. For some cases, we're still more likely to suggest CloudFlare (which has a free tier) or an integrated offering from a cloud provider, like Cloudfront.
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.
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
Akamai RoI improved over a period of times since it comes with heavy costs, however global deliveries in over 100 counties and global web platforms usage helps improve RoI
With the complex UI challenges, ROI could be impacted negatively when you have to invest in operations and time.
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.
