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
Google Compute Engine
Score 8.6 out of 10
N/A
Google Compute Engine is an infrastructure-as-a-service (IaaS) product from Google Cloud. It provides virtual machines with carbon-neutral infrastructure which run on the same data centers that Google itself uses.
$0
per month GB
Kubernetes
Score 9.0 out of 10
N/A
Kubernetes is an open-source container cluster manager.
N/A
Pricing
Akamai Cloud Computing
Google Compute Engine
Kubernetes
Editions & Modules
No answers on this topic
Preemptible Price - Predefined Memory
0.000892 / GB
Hour
Three-year commitment price - Predefined Memory
$0.001907 / GB
Hour
One-year commitment price - Predefined Memory
$0.002669 / GB
Hour
On-demand price - Predefined Memory
$0.004237 / GB
Hour
Preemptible Price - Predefined vCPUs
0.006655 / vCPU
Hour
Three-year commitment price - Predefined vCPUS
$0.014225 / CPU
Hour
One-year commitment price - Predefined vCPUS
$0.019915 / vCPU
Hour
On-demand price - Predefined vCPUS
$0.031611 / vCPU
Hour
No answers on this topic
Offerings
Pricing Offerings
Akamai Cloud Computing
Google Compute Engine
Kubernetes
Free Trial
Yes
Yes
No
Free/Freemium Version
No
Yes
No
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.
Prices vary according to region (i.e US central, east, & west time zones). Google Compute Engine also offers a discounted rate for a 1 & 3 year commitment.
We have used Kubernetes as a single cluster. It works really well, and it is very good for dev, test, and preproduction environments. With minor DevOps it can be easily prepared for production. In short, it reduced time from development to production.
Information Technology Specialist, Digital Strategist
Chose Akamai Cloud Computing
There are a lot of very good cloud operations. Linode, for us represents a good offering. It offers a simple way to control infrastructure, without being overly simplified. For us, it was a good median giving us the flexibility to explore, experiment and still build for scale. …
The thing that caught my eye was the price to start with. I move to Digital Ocean because they had better options for virtual network isolation, but I came back as soon as Linode fixed the issue. There support is great and things just work.
I am still evaluating DigitalOcean Droplets as their pricepoint has moved more towards Linode, but so far I am leaning back towards Linode. They also don't have the GPU machines. But they do have a wider range of options for CPU. At present if you do lscpu on Linode it lists …
Verified User
Team Lead
Chose Akamai Cloud Computing
Linode often offers the most competitive pricing on regular usage.
Linode provides easier and more understandable pricing and value. I never have to wonder or estimate the month's costs or have any surprises. Linode also is more logically laid out and easy to get things set up and running quickly.
DigitalOcean had very bad communication both internally and externally. Vultr had good features but could not answer questions about Spectre/Meltdown with any specificity. EC2 and GCE's unpredictable costs and higher bandwidth fees make them annoying or expensive for most of my …
Google Computer Engine: it is too expensive. You have to pay for computing resources (CPU, memory), storage, network traffic individually. While the quality of service is good, it's still with the same level of Linode.
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 …
Red Hat OpenShift was the first product I used and it was fantastic--until they changed to a container model and kicked everyone of the previous model. From there I moved to Linode and haven't looked back. You have much more control but it does mean you need to keep on top of a …
Compared to the "big three" cloud providers, Linode does not have the enormous range of service offerings that they do. I would not attempt to build the next Instagram on Linode. But for companies that simply want a straight-forward cloud provider, they're definitely our …
One of our clients was previously hosted on Rackspace, then Google Cloud Services. Their Rackspace services were very expensive and provided little in the way of migration or management. After re-engineering their deployment, we migrated them to Google Cloud Services (GCS) …
The perfect blend of setup flexibility, costing and trust of Google could be my answer to the comparison. This being a server backed service so, ruling out the functions. The Setup flexibility and speed set the GCE apart from Kubernetes. Compliance, regulation and the security …
We have tried using DigitalOcean Droplets for some of our minor and non critical VMs. In our experience, Google Compute Engine fares well in comparison the DigitalOcean Droplets as they provide better availability, better support and in general, a better experience.
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 …
Google Compute Engine provides on-demand computing resources that are easy to scale up or down according to my organization needs. This allows our business to quickly adapt to changes in demand without having to invest in additional hardware. It also offers a very competitive …
Verified User
Engineer
Chose Google Compute Engine
Google was easy to start with in terms of ease of use and support access.
Google Compute Engine is better than other in terms of the pricing and the performance. But when it comes to ease of use i would prefer Azure Virtual Machines. Other than this I find GCE very competitive with these other solutions
Similar in capabilities, slightly slicker APIs and CLIs. More observability in the default UI and the CLIs. Easier to setup, the google console is slick. Azure has a good user interface as well with lots of documentation to help. CLI is slightly less intuitive, but decent. AWS …
The best GCP products - GKE for containerization workload fit to the VM machines specified for different application type (monolithic). These services can be easily integrated with each other with additional benefits.
AWS's UI could use a lot of work, and their API documentation was much worse compared to Google's, which was already tough to read and figure out. Google's free trial of their services through a platform credit (which AWS doesn't offer), also helped us test their compute …
GCE was an easy choice for us after evaluating our options. We needed something that was dynamic enough to handle our specialized stack, but easy enough that our engineers weren't spending too much time configuring and launching. We found AWS's offering to be similar but …
AWS has a ton of options in terms of tools that you can use. It's pricing model is hit or miss (some offerings are simply unaffordable). Some of the API design is questionable at best and frustrating at worst. Microsoft Azure is a newcomer in the market with focus on enterprise …
We ultimately chose Google Compute for the price difference as compared to other providers. Google's pricing for Windows servers is even lower than Microsoft's own cloud service, Azure. The terminology used across Google Compute is much easier to understand than the …
When planning our latest product we tried out many hosted container service and a few local tools. These included services run by Google, Microsoft, and Amazon and tools from companies like Docker and Apache. We ended up selecting Kubernetes because it was compatible with all …
With AWS ECS, you have to provision the virtual hardware, then use that hardware as a pool for your container service. Each service has to be built out and scaled independently. Kubernetes allows us to use a cluster of machines like a big pool of resources, scaling and shipping …
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
You can use Google Cloud Compute Engine as an option to configure your Gitlab, GitHub, and Azure DevOps self-hosted runners. This allows full control and management of your runners rather than using the default runners, which you cannot manage. Additionally, they can be used as a workspace, which you can provide to the employees, where they can test their workloads or use them as a local host and then deploy to the actual production-grade instance.
K8s should be avoided - If your application works well without being converted into microservices-based architecture & fits correctly in a VM, needs less scaling, have a fixed traffic pattern then it is better to keep away from Kubernetes. Otherwise, the operational challenges & technical expertise will add a lot to the OPEX. Also, if you're the one who thinks that containers consume fewer resources as compared to VMs then this is not true. As soon as you convert your application to a microservice-based architecture, a lot of components will add up, shooting your resource consumption even higher than VMs so, please beware. Kubernetes is a good choice - When the application needs quick scaling, is already in microservice-based architecture, has no fixed traffic pattern, most of the employees already have desired skills.
Scaling - whether it's traffic spikes or just steady growth, Google Compute Engine's auto-scaling makes sure we've got the compute power we need without any manual juggling acts
Load balancing - Keeping things smooth with that load balancing across multiple VMs, so our users don't have to deal with slow load times or downtime even when things get crazy busy
Customizability - Mix and match configs for CPU, RAM, storage and whatnot to suit our specific app needs
Local development, Kubernetes does tend to be a bit complicated and unnecessary in environments where all development is done locally.
The need for add-ons, Helm is almost required when running Kubernetes. This brings a whole new tool to manage and learn before a developer can really start to use Kubernetes effectively.
Finicy configmap schemes. Kubernetes configmaps often have environment breaking hangups. The fail safes surrounding configmaps are sadly lacking.
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.
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.
The Kubernetes is going to be highly likely renewed as the technologies that will be placed on top of it are long term as of planning. There shouldn't be any last minute changes in the adoption and I do not anticipate sudden change of the core underlying technology. It is just that the slow process of technology adoption that makes it hard to switch to something else.
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.
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.
It is an eminently usable platform. However, its popularity is overshadowed by its complexity. To properly leverage the capabilities and possibilities of Kubernetes as a platform, you need to have excellent understanding of your use case, even better understanding of whether you even need Kubernetes, and if yes - be ready to invest in good engineering support for the platform itself
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.
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
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.
It works great all the time except for occasional issues, but overall, I am very happy with the performance. It delivers on the promise it makes and as per the SLAs provided. Networking is great with a premium network, and AZs are also widespread across geographies. Overall, it is a great infra item to have, which you can scale as you want.
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.
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.
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.
Google Compute Engine provides a one stop solution for all the complex features and the UI is better than Amazon's EC2 and Azure Machine Learning for ease of usability. It's always good to have an eco-system of products from Google as it's one of the most used search engine and IoT services provider, which helps with ease of integration and updates in the future.
Most of the required features for any orchestration tool or framework, which is provided by Kubernetes. After understanding all modules and features of the K8S, it is the best fit for us as compared with others out there.
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.