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Google Compute Engine
Google Compute Engine

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Google Compute Engine vs Packet: What are the differences?

What is Google Compute Engine? Run large-scale workloads on virtual machines hosted on Google's infrastructure. 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 Packet? The Leading Bare Metal Cloud for Developers. Deploy screaming fast dedicated servers in under 10 minutes via portal, API, or common cloud orchestration tools. No hypervisor, modern IPv6 network, and hourly pricing.

Google Compute Engine and Packet belong to "Cloud Hosting" category of the tech stack.

Some of the features offered by Google Compute Engine are:

  • High-performance virtual machines- Compute Engine鈥檚 Linux VMs are consistently performant, scalable, highly secure and reliable. Supported distros include Debian and CentOS. You can choose from micro-VMs to large instances.
  • Powered by Google鈥檚 global network- Create large compute clusters that benefit from strong and consistent cross-machine bandwidth. Connect to machines in other data centers and to other Google services using Google鈥檚 private global fiber network.
  • (Really) Pay for what you use- Google bills in minute-level increments (with a 10-minute minimum charge), so you don鈥檛 pay for unused computing time.

On the other hand, Packet provides the following key features:

  • Premium configs, always available
  • Fully dedicated, no hypervisors
  • Deploy in less than 10 minutes

"Backed by google" is the primary reason why developers consider Google Compute Engine over the competitors, whereas "Great performance" was stated as the key factor in picking Packet.

- No public GitHub repository available -
- No public GitHub repository available -

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 Packet?

Deploy screaming fast dedicated servers in under 10 minutes via portal, API, or common cloud orchestration tools. No hypervisor, modern IPv6 network, and hourly pricing.
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Why do developers choose Google Compute Engine?
Why do developers choose Packet?

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      What are some alternatives to Google Compute Engine and Packet?
      Google App Engine
      Google has a reputation for highly reliable, high performance infrastructure. With App Engine you can take advantage of the 10 years of knowledge Google has in running massively scalable, performance driven systems. App Engine applications are easy to build, easy to maintain, and easy to scale as your traffic and data storage needs grow.
      DigitalOcean
      We take the complexities out of cloud hosting by offering blazing fast, on-demand SSD cloud servers, straightforward pricing, a simple API, and an easy-to-use control panel.
      Google Cloud Platform
      It helps you build what's next with secure infrastructure, developer tools, APIs, data analytics and machine learning. It is a suite of cloud computing services that runs on the same infrastructure that Google uses internally for its end-user products, such as Google Search and YouTube.
      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.
      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 Google Compute Engine and Packet
      Kestas Barzdaitis
      Kestas Barzdaitis
      Entrepreneur & Engineer | 14 upvotes 176.6K 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
      Mohamed Labouardy
      Mohamed Labouardy
      Founder at Komiser | 5 upvotes 31.5K 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 38.8K 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 Google Compute Engine and Packet
      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

      How developers use Google Compute Engine and Packet
      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 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 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 Google Compute Engine cost?
      How much does Packet cost?
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