Amazon EC2聽vs聽Google Compute Engine聽vs聽RamNode

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Amazon EC2
Amazon EC2

19.3K
12.7K
+ 1
2.5K
Google Compute Engine
Google Compute Engine

4.2K
3K
+ 1
422
RamNode
RamNode

14
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+ 1
9
- No public GitHub repository available -
- No public GitHub repository available -
- No public GitHub repository available -

What is Amazon EC2?

It is a web service that provides resizable compute capacity in the cloud. It is designed to make web-scale computing easier for developers.

What is Google Compute Engine?

Google Compute Engine is a service that provides virtual machines that run on Google infrastructure. Google Compute Engine offers scale, performance, and value that allows you to easily launch large compute clusters on Google's infrastructure. There are no upfront investments and you can run up to thousands of virtual CPUs on a system that has been designed from the ground up to be fast, and to offer strong consistency of performance.

What is RamNode?

You won't find a better performing VPS anywhere else. Our SSD and SSD-Cached VPSs are the best in the industry. We implement some of the most cutting edge systems and configurations to ensure your VPS meets and exceeds your expectations.
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Why do developers choose Amazon EC2?
Why do developers choose Google Compute Engine?
Why do developers choose RamNode?

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      What companies use Amazon EC2?
      What companies use Google Compute Engine?
      What companies use RamNode?
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        What tools integrate with Amazon EC2?
        What tools integrate with Google Compute Engine?
        What tools integrate with RamNode?
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          What are some alternatives to Amazon EC2, Google Compute Engine, and RamNode?
          Amazon LightSail
          Everything you need to jumpstart your project on AWS鈥攃ompute, storage, and networking鈥攆or a low, predictable price. Launch a virtual private server with just a few clicks.
          Amazon S3
          Amazon Simple Storage Service provides a fully redundant data storage infrastructure for storing and retrieving any amount of data, at any time, from anywhere on the web
          Amazon EC2 Container Service
          Amazon EC2 Container Service lets you launch and stop container-enabled applications with simple API calls, allows you to query the state of your cluster from a centralized service, and gives you access to many familiar Amazon EC2 features like security groups, EBS volumes and IAM roles.
          Beanstalk
          A single process to commit code, review with the team, and deploy the final result to your customers.
          Microsoft Azure
          Azure is an open and flexible cloud platform that enables you to quickly build, deploy and manage applications across a global network of Microsoft-managed datacenters. You can build applications using any language, tool or framework. And you can integrate your public cloud applications with your existing IT environment.
          See all alternatives
          Decisions about Amazon EC2, Google Compute Engine, and RamNode
          Kestas Barzdaitis
          Kestas Barzdaitis
          Entrepreneur & Engineer | 15 upvotes 178.8K views
          atCodeFactorCodeFactor
          Kubernetes
          Kubernetes
          CodeFactor.io
          CodeFactor.io
          Amazon EC2
          Amazon EC2
          Microsoft Azure
          Microsoft Azure
          Google Compute Engine
          Google Compute Engine
          Docker
          Docker
          AWS Lambda
          AWS Lambda
          Azure Functions
          Azure Functions
          Google Cloud Functions
          Google Cloud Functions
          #SAAS
          #IAAS
          #Containerization
          #Autoscale
          #Startup
          #Automation
          #Machinelearning
          #AI
          #Devops

          CodeFactor being a #SAAS product, our goal was to run on a cloud-native infrastructure since day one. We wanted to stay product focused, rather than having to work on the infrastructure that supports the application. We needed a cloud-hosting provider that would be reliable, economical and most efficient for our product.

          CodeFactor.io aims to provide an automated and frictionless code review service for software developers. That requires agility, instant provisioning, autoscaling, security, availability and compliance management features. We looked at the top three #IAAS providers that take up the majority of market share: Amazon's Amazon EC2 , Microsoft's Microsoft Azure, and Google Compute Engine.

          AWS has been available since 2006 and has developed the most extensive services ant tools variety at a massive scale. Azure and GCP are about half the AWS age, but also satisfied our technical requirements.

          It is worth noting that even though all three providers support Docker containerization services, GCP has the most robust offering due to their investments in Kubernetes. Also, if you are a Microsoft shop, and develop in .NET - Visual Studio Azure shines at integration there and all your existing .NET code works seamlessly on Azure. All three providers have serverless computing offerings (AWS Lambda, Azure Functions, and Google Cloud Functions). Additionally, all three providers have machine learning tools, but GCP appears to be the most developer-friendly, intuitive and complete when it comes to #Machinelearning and #AI.

          The prices between providers are competitive across the board. For our requirements, AWS would have been the most expensive, GCP the least expensive and Azure was in the middle. Plus, if you #Autoscale frequently with large deltas, note that Azure and GCP have per minute billing, where AWS bills you per hour. We also applied for the #Startup programs with all three providers, and this is where Azure shined. While AWS and GCP for startups would have covered us for about one year of infrastructure costs, Azure Sponsorship would cover about two years of CodeFactor's hosting costs. Moreover, Azure Team was terrific - I felt that they wanted to work with us where for AWS and GCP we were just another startup.

          In summary, we were leaning towards GCP. GCP's advantages in containerization, automation toolset, #Devops mindset, and pricing were the driving factors there. Nevertheless, we could not say no to Azure's financial incentives and a strong sense of partnership and support throughout the process.

          Bottom line is, IAAS offerings with AWS, Azure, and GCP are evolving fast. At CodeFactor, we aim to be platform agnostic where it is practical and retain the flexibility to cherry-pick the best products across providers.

          See more
          Omar Mehilba
          Omar Mehilba
          Co-Founder and COO at Magalix | 18 upvotes 111.3K views
          atMagalixMagalix
          Kubernetes
          Kubernetes
          Microsoft Azure
          Microsoft Azure
          Google Kubernetes Engine
          Google Kubernetes Engine
          Amazon EC2
          Amazon EC2
          Go
          Go
          Python
          Python
          #Autopilot

          We are hardcore Kubernetes users and contributors. We loved the automation it provides. However, as our team grew and added more clusters and microservices, capacity and resources management becomes a massive pain to us. We started suffering from a lot of outages and unexpected behavior as we promote our code from dev to production environments. Luckily we were working on our AI-powered tools to understand different dependencies, predict usage, and calculate the right resources and configurations that should be applied to our infrastructure and microservices. We dogfooded our agent (http://github.com/magalixcorp/magalix-agent) and were able to stabilize as the #autopilot continuously recovered any miscalculations we made or because of unexpected changes in workloads. We are open sourcing our agent in a few days. Check it out and let us know what you think! We run workloads on Microsoft Azure Google Kubernetes Engine and Amazon EC2 and we're all about Go and Python!

          See more
          Mohamed Labouardy
          Mohamed Labouardy
          Founder at Komiser | 5 upvotes 31.8K views
          atKomiserKomiser
          Google Compute Engine
          Google Compute Engine
          Amazon Web Services
          Amazon Web Services
          OVH
          OVH
          Microsoft Azure
          Microsoft Azure
          Go
          Go
          GitHub
          GitHub

          Google Compute Engine Amazon Web Services OVH Microsoft Azure Go GitHub

          Last week, we released a fresh new release of Komiser with support of multiple AWS accounts. Komiser support multiple AWS accounts through named profiles that are stored in the credentials files.

          You can now analyze and identify potential cost savings on unlimited AWS environments (Production, Staging, Sandbox, etc) on one single dashboard.

          Read the full story in the blog post.

          See more
          Mohamed Labouardy
          Mohamed Labouardy
          Founder at Komiser | 5 upvotes 39.1K views
          atKomiserKomiser
          Google Compute Engine
          Google Compute Engine
          Amazon Web Services
          Amazon Web Services
          Go
          Go
          Docker
          Docker
          Material Design for Angular
          Material Design for Angular
          Microsoft Azure
          Microsoft Azure
          GitHub
          GitHub

          Google Compute Engine Amazon Web Services Go Docker Material Design for Angular Microsoft Azure GitHub I鈥檓 super excited to annonce the release of Komiser:2.1.0 with beta support of Google Cloud Platform. You can now use one single open source tool to detect both AWS and GCP overspending.

          Komiser allows you to analyze and manage #cloud cost, usage, #security, and governance in one place. Hence, detecting potential vulnerabilities that could put your cloud environment at risk.

          It allows you also to control your usage and create visibility across all used services to achieve maximum cost-effectiveness and get a deep understanding of how you spend on the #AWS, #GCP and #Azure.

          See more
          Interest over time
          Reviews of Amazon EC2, Google Compute Engine, and RamNode
          Review ofAmazon EC2Amazon EC2

          A VPS gives the full access that I need, because most of what I do has complex integrations and there is plenty of legacy - very stable, highly tuned code developed over two decades - that I carry with me. My use is also limited to during development, so there is no point going for a full server.

          Amazon EC2 is a VPS, except it is cheaper.

          Additionally, I used to previously take the code developed on my VPS and deploy it to whatever server the client brought.

          With Amazon EC2 the deployment is already done. All that remains it to scale up, add other products like dns, mail, storage and so on, and change the billing so that the client gets invoiced. That makes the process that much more predictable and seamless, and the end result much more stable.

          Review ofGoogle Compute EngineGoogle Compute Engine
          • I use Google Compute Engine instances as flexible, reproducible infrastructure that scale with my data science tasks.

          • Between Google Cloud and Amazon Web Services, I chose Google Cloud for its intuitive UI. SSH within the browser is very convenient.

          • Related blog post with example usage: Running an IPython Notebook on Google Compute Engine from Chrome

          Review ofAmazon EC2Amazon EC2

          Just started using EC2 myself, but it was the platform used by my previous employer, as well. They are getting easier to use, dashboard improvements over time were well done. Responded fast to outages. They offer a limited free tier which is perfect for my current project, allowing me time to build it to the point where I will need a paid solution. Overall, I'm liking it so far.

          How developers use Amazon EC2, Google Compute Engine, and RamNode
          Avatar of imgur
          imgur uses Amazon EC2Amazon EC2

          About a year and a half ago (written June 2013) we moved from dedicated servers over to AWS. Thanks to AWS, we no longer have to think on a server level. Instead, we think of everything as a cluster of instances, and an instance is essentially a virtual server where we don鈥檛 have to worry about the hardware. It鈥檚 a relief to not have to worry about the hardware behind the instances.

          The clusters we have are: WWW, API, Upload, HAProxy, HBase, MySQL, Memcached, Redis, and ElasticSearch, for an average total of 80 instances. Each cluster handles the job that its name describes, all working together for the common goal of giving you your daily (hourly?) dose of image entertainment.

          Below is a diagram of how they all work together:

          http://i.imgur.com/GiBQsmf.png

          Avatar of Samuel Harrold
          Samuel Harrold uses Google Compute EngineGoogle Compute Engine
          • I use Google Compute Engine instances as flexible, reproducible infrastructure that scales with my data science tasks.
          • Between Google Cloud and Amazon Web Services, I chose Google Cloud for its intuitive UI. SSH within the browser is very convenient.
          • Related blog post with example usage: Running an IPython Notebook on Google Compute Engine from Chrome
          Avatar of Instacart
          Instacart uses Amazon EC2Amazon EC2

          We liked a lot of things about Heroku. We loved the build packs, and we still in fact use Heroku build packs, but we were frustrated by lack of control about a lot of things. It鈥檚 nice to own the complete stack, or rather as far down as AWS goes. It gave us a lot of flexibility and functionality that we didn鈥檛 have before. We use a lot of Amazon technology.

          Avatar of Volkan 脰z莽elik
          Volkan 脰z莽elik uses Amazon EC2Amazon EC2

          I like containers and all, but for zerotoherojs.com I am a one-man band, who also works full time. I don鈥檛 have any (dev)ops budget, and therefore I need the reliability and uptime of an actual virtual machine.

          That鈥檚 where AWS EC2 comes in handy.

          Avatar of jasonmjohnson
          jasonmjohnson uses Amazon EC2Amazon EC2

          Docker containers will be hosted and run on a single Amazon EC2 instance. This will likely be the t2.small or t2.medium instance type as listed here: https://aws.amazon.com/ec2/instance-types/

          Avatar of Jeff Flynn
          Jeff Flynn uses Amazon EC2Amazon EC2

          Because servers. Lots of them. Lots of configurations. Great for mission-specific functions. Video encoding, data aggregation, dedicated processing, mission-critical data stores. Anything you can't hang off your Heroku environment.

          Avatar of Casey Smith
          Casey Smith uses Google Compute EngineGoogle Compute Engine

          Infrastructure for Google App Engine, Google Cloud Endpoints, Memcached, and Google Cloud SQL components, as well as Git repository and Jenkins CI server.

          Avatar of Cyril Nettey
          Cyril Nettey uses RamNodeRamNode

          RamNode provides the hosting platform for my personal and production projects.

          Avatar of BitBank
          BitBank uses Google Compute EngineGoogle Compute Engine

          Compute engine is used to run our live forecaster and cron jobs

          Avatar of Jonathan Fries
          Jonathan Fries uses Google Compute EngineGoogle Compute Engine

          Ghost runs on a VM from Google Compute Engine.

          Avatar of Partners in School Innovation
          Partners in School Innovation uses Google Compute EngineGoogle Compute Engine

          Hosting our Bitnami PSQL instance

          How much does Amazon EC2 cost?
          How much does Google Compute Engine cost?
          How much does RamNode cost?
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