Alternatives to Amazon EC2 logo

Alternatives to Amazon EC2

Amazon LightSail, Amazon S3, Amazon EC2 Container Service, Beanstalk, and Microsoft Azure are the most popular alternatives and competitors to Amazon EC2.
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What is Amazon EC2 and what are its top alternatives?

It is a web service that provides resizable compute capacity in the cloud. It is designed to make web-scale computing easier for developers.
Amazon EC2 is a tool in the Cloud Hosting category of a tech stack.

Top Alternatives to Amazon EC2

  • Amazon LightSail
    Amazon LightSail

    Everything you need to jumpstart your project on AWS—compute, storage, and networking—for a low, predictable price. Launch a virtual private server with just a few clicks. ...

  • Amazon S3
    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

    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
    Beanstalk

    A single process to commit code, review with the team, and deploy the final result to your customers. ...

  • Microsoft Azure
    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. ...

  • Google Cloud Platform
    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. ...

  • DigitalOcean
    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 Compute Engine
    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. ...

Amazon EC2 alternatives & related posts

Amazon LightSail logo

Amazon LightSail

158
360
9
Simple Virtual Private Servers on AWS
158
360
+ 1
9
PROS OF AMAZON LIGHTSAIL
  • 4
    Low cost
  • 4
    Simple Deployment
  • 1
    Simple pricing scheme
CONS OF AMAZON LIGHTSAIL
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    related Amazon LightSail posts

    Paul Whittemore
    Developer and Owner at Appurist Software · | 4 upvotes · 141.5K views

    For those needing hosting on Windows or Windows Server too (and avoiding licensing hurdles), both Vultr and Amazon LightSail offer compelling choices, depending on how much compute power you need. Don't underestimate Amazon LightSail, especially for smaller or starting projects, but Vultr also offers an incremental $16 Windows option on top of their standard compute offerings.

    See more
    Amazon S3 logo

    Amazon S3

    46.4K
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    Store and retrieve any amount of data, at any time, from anywhere on the web
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    PROS OF AMAZON S3
    • 592
      Reliable
    • 492
      Scalable
    • 456
      Cheap
    • 328
      Simple & easy
    • 83
      Many sdks
    • 29
      Logical
    • 12
      Easy Setup
    • 11
      1000+ POPs
    • 10
      REST API
    • 5
      Secure
    • 3
      Easy
    • 2
      Web UI for uploading files
    • 2
      Plug and play
    • 1
      GDPR ready
    • 1
      Flexible
    • 1
      Faster on response
    • 1
      Plug-gable
    • 1
      Easy to use
    • 1
      Easy integration with CloudFront
    CONS OF AMAZON S3
    • 7
      Permissions take some time to get right
    • 6
      Takes time/work to organize buckets & folders properly
    • 5
      Requires a credit card
    • 3
      Complex to set up

    related Amazon S3 posts

    Ashish Singh
    Tech Lead, Big Data Platform at Pinterest · | 37 upvotes · 1.1M views

    To provide employees with the critical need of interactive querying, we’ve worked with Presto, an open-source distributed SQL query engine, over the years. Operating Presto at Pinterest’s scale has involved resolving quite a few challenges like, supporting deeply nested and huge thrift schemas, slow/ bad worker detection and remediation, auto-scaling cluster, graceful cluster shutdown and impersonation support for ldap authenticator.

    Our infrastructure is built on top of Amazon EC2 and we leverage Amazon S3 for storing our data. This separates compute and storage layers, and allows multiple compute clusters to share the S3 data.

    We have hundreds of petabytes of data and tens of thousands of Apache Hive tables. Our Presto clusters are comprised of a fleet of 450 r4.8xl EC2 instances. Presto clusters together have over 100 TBs of memory and 14K vcpu cores. Within Pinterest, we have close to more than 1,000 monthly active users (out of total 1,600+ Pinterest employees) using Presto, who run about 400K queries on these clusters per month.

    Each query submitted to Presto cluster is logged to a Kafka topic via Singer. Singer is a logging agent built at Pinterest and we talked about it in a previous post. Each query is logged when it is submitted and when it finishes. When a Presto cluster crashes, we will have query submitted events without corresponding query finished events. These events enable us to capture the effect of cluster crashes over time.

    Each Presto cluster at Pinterest has workers on a mix of dedicated AWS EC2 instances and Kubernetes pods. Kubernetes platform provides us with the capability to add and remove workers from a Presto cluster very quickly. The best-case latency on bringing up a new worker on Kubernetes is less than a minute. However, when the Kubernetes cluster itself is out of resources and needs to scale up, it can take up to ten minutes. Some other advantages of deploying on Kubernetes platform is that our Presto deployment becomes agnostic of cloud vendor, instance types, OS, etc.

    #BigData #AWS #DataScience #DataEngineering

    See more
    Simon Reymann
    Senior Fullstack Developer at QUANTUSflow Software GmbH · | 29 upvotes · 4.6M views

    Our whole DevOps stack consists of the following tools:

    • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
    • Respectively Git as revision control system
    • SourceTree as Git GUI
    • Visual Studio Code as IDE
    • CircleCI for continuous integration (automatize development process)
    • Prettier / TSLint / ESLint as code linter
    • SonarQube as quality gate
    • Docker as container management (incl. Docker Compose for multi-container application management)
    • VirtualBox for operating system simulation tests
    • Kubernetes as cluster management for docker containers
    • Heroku for deploying in test environments
    • nginx as web server (preferably used as facade server in production environment)
    • SSLMate (using OpenSSL) for certificate management
    • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
    • PostgreSQL as preferred database system
    • Redis as preferred in-memory database/store (great for caching)

    The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

    • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
    • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
    • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
    • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
    • Scalability: All-in-one framework for distributed systems.
    • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
    See more
    Amazon EC2 Container Service logo

    Amazon EC2 Container Service

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    Container management service that supports Docker containers
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    PROS OF AMAZON EC2 CONTAINER SERVICE
    • 100
      Backed by amazon
    • 72
      Familiar to ec2
    • 53
      Cluster based
    • 42
      Simple API
    • 26
      Iam roles
    • 7
      Scheduler
    • 7
      Cluster management
    • 7
      Programmatic Control
    • 4
      Socker support
    • 4
      Container-enabled applications
    • 2
      No additional cost
    • 1
      Easy to use and cheap
    CONS OF AMAZON EC2 CONTAINER SERVICE
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      related Amazon EC2 Container Service posts

      Cyril Duchon-Doris

      We build a Slack app using the Bolt framework from slack https://api.slack.com/tools/bolt, a Node.js express app. It allows us to easily implement some administration features so we can easily communicate with our backend services, and we don't have to develop any frontend app since Slack block kit will do this for us. It can act as a Chatbot or handle message actions and custom slack flows for our employees.

      This app is deployed as a microservice on Amazon EC2 Container Service with AWS Fargate. It uses very little memory (and money) and can communicate easily with our backend services. Slack is connected to this app through a ALB ( AWS Elastic Load Balancing (ELB) )

      See more
      Russel Werner
      Lead Engineer at StackShare · | 7 upvotes · 210.7K views

      We began our hosting journey, as many do, on Heroku because they make it easy to deploy your application and automate some of the routine tasks associated with deployments, etc. However, as our team grew and our product matured, our needs have outgrown Heroku. I will dive into the history and reasons for this in a future blog post.

      We decided to migrate our infrastructure to Kubernetes running on Amazon EKS. Although Google Kubernetes Engine has a slightly more mature Kubernetes offering and is more user-friendly; we decided to go with EKS because we already using other AWS services (including a previous migration from Heroku Postgres to AWS RDS). We are still in the process of moving our main website workloads to EKS, however we have successfully migrate all our staging and testing PR apps to run in a staging cluster. We developed a Slack chatops application (also running in the cluster) which automates all the common tasks of spinning up and managing a production-like cluster for a pull request. This allows our engineering team to iterate quickly and safely test code in a full production environment. Helm plays a central role when deploying our staging apps into the cluster. We use CircleCI to build docker containers for each PR push, which are then published to Amazon EC2 Container Service (ECR). An upgrade-operator process watches the ECR repository for new containers and then uses Helm to rollout updates to the staging environments. All this happens automatically and makes it really easy for developers to get code onto servers quickly. The immutable and isolated nature of our staging environments means that we can do anything we want in that environment and quickly re-create or restore the environment to start over.

      The next step in our journey is to migrate our production workloads to an EKS cluster and build out the CD workflows to get our containers promoted to that cluster after our QA testing is complete in our staging environments.

      See more
      Beanstalk logo

      Beanstalk

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      251
      51
      Private code hosting for teams.
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      251
      + 1
      51
      PROS OF BEANSTALK
      • 14
        Ftp deploy
      • 9
        Deployment
      • 8
        Easy to navigate
      • 4
        Code Editing
      • 4
        HipChat Integration
      • 4
        Integrations
      • 3
        Code review
      • 2
        HTML Preview
      • 1
        Security
      • 1
        Blame Tool
      • 1
        Cohesion
      CONS OF BEANSTALK
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        related Beanstalk posts

        Microsoft Azure logo

        Microsoft Azure

        20.6K
        13.6K
        767
        Integrated cloud services and infrastructure to support computing, database, analytics, mobile, and web scenarios.
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        PROS OF MICROSOFT AZURE
        • 114
          Scales well and quite easy
        • 95
          Can use .Net or open source tools
        • 81
          Startup friendly
        • 73
          Startup plans via BizSpark
        • 62
          High performance
        • 38
          Wide choice of services
        • 32
          Low cost
        • 32
          Lots of integrations
        • 31
          Reliability
        • 19
          Twillio & Github are directly accessible
        • 13
          RESTful API
        • 10
          Startup support
        • 10
          Enterprise Grade
        • 10
          PaaS
        • 8
          DocumentDB
        • 7
          In person support
        • 6
          Service Bus
        • 6
          Free for students
        • 6
          Virtual Machines
        • 5
          It rocks
        • 5
          Redis Cache
        • 4
          SQL Databases
        • 4
          CDN
        • 4
          Infrastructure Services
        • 4
          Storage, Backup, and Recovery
        • 3
          IaaS
        • 3
          HDInsight
        • 3
          Integration
        • 3
          Preview Portal
        • 3
          Built on Node.js
        • 3
          Big Data
        • 3
          BizSpark 60k Azure Benefit
        • 3
          Scheduler
        • 2
          Backup
        • 2
          Open cloud
        • 2
          Web
        • 2
          SaaS
        • 2
          Big Compute
        • 2
          Mobile
        • 2
          Media
        • 2
          Dev-Test
        • 2
          Storage
        • 2
          StorSimple
        • 2
          Machine Learning
        • 2
          Stream Analytics
        • 2
          Data Factory
        • 2
          Event Hubs
        • 2
          Virtual Network
        • 2
          ExpressRoute
        • 2
          Traffic Manager
        • 2
          Media Services
        • 2
          BizTalk Services
        • 2
          Site Recovery
        • 2
          Active Directory
        • 2
          Multi-Factor Authentication
        • 2
          Visual Studio Online
        • 2
          Application Insights
        • 2
          Automation
        • 2
          Operational Insights
        • 2
          Key Vault
        • 2
          Infrastructure near your customers
        • 2
          Easy Deployment
        • 1
          Enterprise customer preferences
        • 1
          Security
        • 1
          Documentation
        • 1
          Best cloud platfrom
        • 1
          Easy and fast to start with
        • 1
          Remote Debugging
        CONS OF MICROSOFT AZURE
        • 6
          Confusing UI
        • 2
          Expensive plesk on Azure

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        Omar Mehilba
        Co-Founder and COO at Magalix · | 19 upvotes · 274.7K views

        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
        Kestas Barzdaitis
        Entrepreneur & Engineer · | 16 upvotes · 519.8K views

        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
        Google Cloud Platform logo

        Google Cloud Platform

        20.4K
        9.4K
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        A suite of cloud computing services
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        PROS OF GOOGLE CLOUD PLATFORM
        • 3
          Good app Marketplace for Beginner and Advanced User
        • 3
          1 year free trial credit USD300
        • 2
          Cheap
        • 2
          Premium tier IP address
        • 1
          Live chat support
        CONS OF GOOGLE CLOUD PLATFORM
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          related Google Cloud Platform posts

          I am currently working on a long term mobile app project. Current stack: Frontend: Dart/Flutter Backend: Go, AWS Resources (AWS Lambda, Amazon DynamoDB, etc.) Since there are only two developers and we have limited time and resources, we are looking for a BAAS like Firebase or AWS Amplify to handle auth and push notifications for now. We are prioritizing developing speed so we can iterate quickly. The only problem is that AWS amplify support for flutter is in developer preview and has limited capabilities (We have tested it out in our app). Firebase is the more mature option. It has great support for flutter and has more than we need for auth, notifications, etc. My question is that, if we choose firebase, we would be stuck with using two different cloud providers. Is this bad, or is this even a problem? I am willing to change anything on the backend architecture wise, so any suggestions would be greatly appreciated as I am somewhat unfamiliar with Google Cloud Platform. Thank you.

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          Hello Everyone, My motive is to build an MLOps pipeline that is 100% independent from Cloud services like AWS, Google Cloud Platform, and Microsoft Azure. I have a project for a client in a production factory and would like to build a Camera based Object Tracking ML service for them. I want to build this pipeline in my own server or (on-premise computer). I am really confused about what stacks I should use. I keep ending up with a Cloud component based solution. It would be great to get some advice on what are the components that I can use and preferably open source.

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          DigitalOcean logo

          DigitalOcean

          15.7K
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          Deploy an SSD cloud server in less than 55 seconds with a dedicated IP and root access.
          15.7K
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          PROS OF DIGITALOCEAN
          • 559
            Great value for money
          • 364
            Simple dashboard
          • 362
            Good pricing
          • 300
            Ssds
          • 250
            Nice ui
          • 192
            Easy configuration
          • 155
            Great documentation
          • 138
            Ssh access
          • 135
            Great community
          • 24
            Ubuntu
          • 13
            Docker
          • 12
            IPv6 support
          • 10
            Private networking
          • 8
            99.99% uptime SLA
          • 7
            Simple API
          • 7
            Great tutorials
          • 6
            55 Second Provisioning
          • 5
            One Click Applications
          • 4
            Dokku
          • 4
            Node.js
          • 4
            Debian
          • 4
            CoreOS
          • 4
            LAMP
          • 3
            LEMP
          • 3
            Ghost
          • 3
            Simple Control Panel
          • 3
            Word Press
          • 3
            1Gb/sec Servers
          • 2
            Quick and no nonsense service
          • 2
            Speed
          • 2
            Mean
          • 2
            Hex Core machines with dedicated ECC Ram and RAID SSD s
          • 2
            Django
          • 2
            Runs CoreOS
          • 2
            Good Tutorials
          • 2
            GitLab
          • 2
            Ruby on Rails
          • 1
            CentOS
          • 1
            Spaces
          • 1
            KVM Virtualization
          • 1
            Amazing Hardware
          • 1
            Transfer Globally
          • 1
            Fedora
          • 1
            FreeBSD
          • 1
            Drupal
          • 1
            FreeBSD Amp
          • 1
            Magento
          • 1
            ownCloud
          • 1
            RedMine
          • 1
            My go to server provider
          • 1
            Ease and simplicity
          • 1
            Nice
          • 1
            Find it superfitting with my requirements (SSD, ssh.
          • 1
            Easy Setup
          • 1
            Cheap
          • 1
            Static IP
          • 1
            It's the easiest to get started for small projects
          • 1
            Automatic Backup
          • 1
            Great support
          • 1
            Quick and easy to set up
          • 1
            Servers on demand - literally
          • 1
            Reliability
          • 0
            Variety of services
          • 0
            Managed Kubernetes
          CONS OF DIGITALOCEAN
          • 3
            Pricing
          • 3
            No live support chat

          related DigitalOcean posts

          Hello, I'm currently writing an e-commerce website with Laravel and Laravel Nova (as an admin panel). I want to start deploying the app and created a DigitalOcean account. After some searches about the deployment process, I saw that the setup via DigitalOcean (using Droplets) isn't very easy for beginners. Now I'm not sure how to deploy my app. I am in between Laravel Forge and DigitalOcean (?Apps Platform or Droplets?). I've read that Heroku and Laravel Vapor are a bit expensive. That's why I didn't consider them yet. I'd be happy to read your opinions on that topic!

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          Hi, I'm a beginner at using MySQL, I currently deployed my crud app on Heroku using the ClearDB add-on. I didn't see that coming, but the increased value of the primary key instead of being 1 is set to 10, and I cannot find a way to change it. Now I`m considering switching and deploying the full app and MySql to DigitalOcean any advice on that? Will I get the same issue? Thanks in advance!

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          Google Compute Engine logo

          Google Compute Engine

          10.4K
          7.7K
          423
          Run large-scale workloads on virtual machines hosted on Google's infrastructure.
          10.4K
          7.7K
          + 1
          423
          PROS OF GOOGLE COMPUTE ENGINE
          • 87
            Backed by google
          • 79
            Easy to scale
          • 75
            High-performance virtual machines
          • 58
            Performance
          • 52
            Fast and easy provisioning
          • 15
            Load balancing
          • 12
            Compliance and security
          • 9
            Kubernetes
          • 8
            GitHub Integration
          • 7
            Consistency
          • 3
            Good documentation
          • 3
            One Click Setup Options
          • 3
            Free $300 credit (12 months)
          • 2
            Ease of Use and GitHub support
          • 2
            Great integration and product support
          • 2
            Escort
          • 1
            Integration with mobile notification services
          • 1
            Easy Snapshot and Backup feature
          • 1
            Low cost
          • 1
            Support many OS
          • 1
            Very Reliable
          • 1
            Nice UI
          CONS OF GOOGLE COMPUTE ENGINE
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            related Google Compute Engine posts

            Kestas Barzdaitis
            Entrepreneur & Engineer · | 16 upvotes · 519.8K views

            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

            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