Akamai Cloud Computing (formerly Linode) include scalable and accessible Linux cloud solutions and services. These products and services support developers and enterprises as they build, deploy, secure, and scale applications.
$5
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
Google App Engine
Score 8.2 out of 10
N/A
Google App Engine is Google Cloud's platform-as-a-service offering. It features pay-per-use pricing and support for a broad array of programming languages.
$0.05
Per Hour Per Instance
Pricing
Akamai Cloud Computing
AWS Lambda
Google App Engine
Editions & Modules
No answers on this topic
128 MB
$0.0000000021
Per 1 ms
1024 MB
$0.0000000167
Per 1 ms
10240 MB
$0.0000001667
Per 1 ms
Starting Price
$0.05
Per Hour Per Instance
Max Price
$0.30
Per Hour Per Instance
Offerings
Pricing Offerings
Akamai Cloud Computing
AWS Lambda
Google App Engine
Free Trial
Yes
No
No
Free/Freemium Version
No
No
Yes
Premium Consulting/Integration Services
Yes
No
No
Entry-level Setup Fee
Optional
No setup fee
No setup fee
Additional Details
CPU, transfer, storage, and RAM are bundled into one price. Storage capacity can be increased with additional Block Storage or S3-compatible Object Storage. Instant Backups can be added with complete independence to the stack. Linode NodeBalancers ensure applications are available.
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More Pricing Information
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Akamai Cloud Computing
AWS Lambda
Google App Engine
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I've tried all of Digital Ocean, AWS EC2 and AWS Lightsail - I found Linode to give the best price/performance for a VPS. However, compared to serverless functions like AWS Lambda, there's a lot of maintenance work if you want to keep your VPS up-to-date. If you're looking for …
We built some applications on Google App Engine, and in comparison to Linode, you are more locked in and there is a steeper learning curve, as you have to adapt to Google's tools. In Linode, you can use whatever you are used to. With AWS, you are able to make whatever setup you …
Linode has been intutive to use. It is easier to find things. Billing is easier to keep track off and it is cheaper then others. Linode VM's are faster then the others.
Linode ticks almost all the checkboxes you need to host modern applications and systems. Price, scalability and customer service is the main reason for me to use Linode. We use Google Cloud and Azure for certain things, but when it comes to VPS Linode is way better. We have …
I used a lot of different services, a lot of services inside Amazon AWS and Digital ocean, but I found at Linode a different way to do all what I need, without having to be worried about weird costs calculations and other things like that.
Though I have used DigitalOcean and also had a generally positive experience using them, I disliked that the IPv4 addresses given to me when using D.O. almost always failed MX blacklist checks and required me to intervene on my own to get them delisted. Because I have not …
For simple VMs or Kubernetes, Linode is cheaper and it also has consistently good performance. As long as this is what you need, you get all you'd want. AWS and GCP shine when you need their other services. Oracle Cloud was bare bone and expensive. Droplets are easy to start …
Linode is competitively priced, but more importantly its management interface is fantastic. Over the past seven years, I have seen firsthand the deep expertise behind the decisions they make in both their physical layers (data centers) and software stacks.
We have considered both AWS and Google Cloud. We are sticking with Linode because we're comfortable administering our systems and don't need the global scale (and corresponding cost) of the bigger cloud platforms. As noted previously, Linode is a great solution for …
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 …
For our organization, we selected Google App Engine which provides a reliable and efficient way to create and deploy apps moreover it supports a lot of languages and provides automatic debugging of code which enables us to deploy code to production as soon as development is …
If you have a small team which is also responsible for development of the product then surely go for it. And if you have a larger team with dedicated person to take care of deployments. Go for cheaper options such as compute engine or AWS (be sure to do your research on pricing …
You can create and scale Kubernetes clusters quickly, but you have to keep an eye on that cluster. In-App Engine, you don't have to worry about infrastructure, but in some scenarios, Kubernetes fits better.
Azure App Service is in par with Google App Engine although you may want to use Azure App Service if you are integrating with other Microsoft IT components, for example SQL Server. Google App Engine is great when in long run, you will be using Google cloud components, for …
The two giants are Google and Amazon. Both are very similar however Google App Engine allows you to deploy your web applications through platforms like Python where as if you're using AWS, you have full control on the operating system services. Google is good because you pay as …
I think that Microsoft and Amazon are simply investing more in their offerings, and there are a bunch of cool PaaS solutions out there as well. Google App Engine is solid, and is probably the right choice for some projects. But ultimately one should evaluate each platform …
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
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.
App Engine is such a good resource for our team both internally and externally. You have complete control over your app, how it runs, when it runs, and more while Google handles the back-end, scaling, orchestration, and so on. If you are serving a tool, system, or web page, it's perfect. If you are serving something back-end, like an automation or ETL workflow, you should be a little considerate or careful with how you are structuring that job. For instance, the Standard environment in Google App Engine will present you with a resource limit for your server calls. If your operations are known to take longer than, say, 10 minutes or so, you may be better off moving to the Flexible environment (which may be a little more expensive but certainly a little more powerful and a little less limited) or even moving that workflow to something like Google Compute Engine or another managed service.
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.
There is a slight learning curve to getting used to code on Google App Engine.
Google Cloud Datastore is Google's NoSQL database in the cloud that your applications can use. NoSQL databases, by design, cannot give handle complex queries on the data. This means that sometimes you need to think carefully about your data structures - so that you can get the results you need in your code.
Setting up billing is a little annoying. It does not seem to save billing information to your account so you can re-use the same information across different Cloud projects. Each project requires you to re-enter all your billing information (if required)
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.
App Engine is a solid choice for deployments to Google Cloud Platform that do not want to move entirely to a Kubernetes-based container architecture using a different Google product. For rapid prototyping of new applications and fairly straightforward web application deployments, we'll continue to leverage the capabilities that App Engine affords us.
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.
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.
I had to revisit the UI after a year of just setting up and forgetting. The UI got some improvements but the amount of navigation we have to go through to setup a new app has increased but also got easier to setup. Gemini now is integrated and make getting answers faster
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.
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.
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.
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.
Good amount of documentation available for Google App Engine and in general there is large developer community around Google App Engine and other products it interacts with. Lastly, Google support is great in general. No issues so far with them.
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
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.
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.
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
We were on another much smaller cloud provider and decided to make the switch for several reasons - stability, breadth of services, and security. In reviewing options, GCP provided the best mixtures of meeting our needs while also balancing the overall cost of the service as compared to the other major players in Azure and AWS.
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.
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.
Effective integration to other java based frameworks.
Time to market is very quick. Build, test, deploy and use.
The GAE Whitelist for java is an important resource to know what works and what does not. So use it. It would also be nice for Google to expand on items that are allowed on GAE platform.