Alternatives to HP Cloud Compute logo

Alternatives to HP Cloud Compute

Amazon EC2, Amazon Web Services (AWS), Google Cloud Platform, Microsoft Azure, and DigitalOcean are the most popular alternatives and competitors to HP Cloud Compute.
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What is HP Cloud Compute and what are its top alternatives?

Now backed by an industry-leading Service Level Agreement, HP Cloud Compute delivers reliable computing resources to handle your production workloads. Configure and scale your capacity in an open cloud environment. With HP Cloud Compute, you gain control over your workloads while only paying for the resources you actually use.
HP Cloud Compute is a tool in the Cloud Hosting category of a tech stack.

Top Alternatives to HP Cloud Compute

  • Amazon EC2
    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. ...

  • Amazon Web Services (AWS)
    Amazon Web Services (AWS)

    It is a comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. ...

  • 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. ...

  • 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. ...

  • 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. ...

  • Linode
    Linode

    Get a server running in minutes with your choice of Linux distro, resources, and node location. ...

  • Rackspace Cloud Servers
    Rackspace Cloud Servers

    Cloud Servers is based on OpenStack, the open and scalable operating system for building public and private clouds. With the open cloud, you get reliable cloud hosting, without locking your data into one proprietary platform. ...

HP Cloud Compute alternatives & related posts

Amazon EC2 logo

Amazon EC2

47.4K
35K
2.5K
Scalable, pay-as-you-go compute capacity in the cloud
47.4K
35K
+ 1
2.5K
PROS OF AMAZON EC2
  • 647
    Quick and reliable cloud servers
  • 515
    Scalability
  • 393
    Easy management
  • 277
    Low cost
  • 271
    Auto-scaling
  • 89
    Market leader
  • 80
    Backed by amazon
  • 79
    Reliable
  • 67
    Free tier
  • 58
    Easy management, scalability
  • 13
    Flexible
  • 10
    Easy to Start
  • 9
    Elastic
  • 9
    Web-scale
  • 9
    Widely used
  • 7
    Node.js API
  • 5
    Industry Standard
  • 4
    Lots of configuration options
  • 2
    GPU instances
  • 1
    Simpler to understand and learn
  • 1
    Extremely simple to use
  • 1
    Amazing for individuals
  • 1
    All the Open Source CLI tools you could want.
CONS OF AMAZON EC2
  • 13
    Ui could use a lot of work
  • 6
    High learning curve when compared to PaaS
  • 3
    Extremely poor CPU performance

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Ashish Singh
Tech Lead, Big Data Platform at Pinterest · | 38 upvotes · 2.8M 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 · | 30 upvotes · 8.8M 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 Web Services (AWS) logo

Amazon Web Services (AWS)

28.5K
2.6K
0
A comprehensive and broadly adopted cloud platform
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2.6K
+ 1
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PROS OF AMAZON WEB SERVICES (AWS)
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    CONS OF AMAZON WEB SERVICES (AWS)
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      Santiago Velasco
      Java Software Developer at ViewNext · | 8 upvotes · 10.6K views

      Hello everyone, I would like to start using a cloud service to host my projects, which are web applications. If anyone has enough experience with Microsoft Azure, Amazon Web Services (AWS) or Google Cloud Platform, I would like to know which of these is most recommended to use, depending on the features they have or how used they are. Thank you so much.

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      waheed khan
      Associate Java Developer at txtsol · | 8 upvotes · 4K views

      I want to make application like Zomato, #Foodpanda.

      Which stack is best for this? As I have expertise in Java and Angular. What is the best stack you will recommend?

      Web Micro-service / Mono? Angular / React? Amazon Web Services (AWS) / Google Cloud Platform? DB : SQL or No SQL

      Mob Cross-platform: React Native / Flutter

      Note: We are a team of 5. what languages do you recommend if I go with microservices?

      Thanks

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      Google Cloud Platform logo

      Google Cloud Platform

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      A suite of cloud computing services
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      PROS OF GOOGLE CLOUD PLATFORM
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        Good app Marketplace for Beginner and Advanced User
      • 4
        1 year free trial credit USD300
      • 3
        Premium tier IP address
      • 3
        Live chat support
      • 3
        Cheap
      CONS OF GOOGLE CLOUD PLATFORM
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        My days of using Firebase are over! I want to move to something scalable and possibly less cheap. In the past seven days I have done my research on what type of DB best fits my needs, and have chosen to go with the nonrelational DB; MongoDB. Although I understand it, I need help understanding how to set up the architecture. I have the client app (Flutter/ Dart) that would make HTTP requests to the web server (node/express), and from there the webserver would query data from MongoDB.

        How should I go about hosting the web server and MongoDb; do they have to be hosted together (this is where a lot of my confusion is)? Based on the research I've done, it seems like the standard practice would be to host on a VM provided by services such as Amazon Web Services, Google Cloud Platform, Microsoft Azure, etc. If there are better ways, such as possibly self-hosting (more responsibility), should I? Anyways, I just want to confirm with a community (you guys) to make sure I do this right, all input is highly appreciated.

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        Santiago Velasco
        Java Software Developer at ViewNext · | 8 upvotes · 10.6K views

        Hello everyone, I would like to start using a cloud service to host my projects, which are web applications. If anyone has enough experience with Microsoft Azure, Amazon Web Services (AWS) or Google Cloud Platform, I would like to know which of these is most recommended to use, depending on the features they have or how used they are. Thank you so much.

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        Microsoft Azure logo

        Microsoft Azure

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        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
        • 96
          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
          PaaS
        • 10
          Enterprise Grade
        • 10
          Startup support
        • 8
          DocumentDB
        • 7
          In person support
        • 6
          Free for students
        • 6
          Service Bus
        • 6
          Virtual Machines
        • 5
          Redis Cache
        • 5
          It rocks
        • 4
          Storage, Backup, and Recovery
        • 4
          Infrastructure Services
        • 4
          SQL Databases
        • 4
          CDN
        • 3
          Integration
        • 3
          Scheduler
        • 3
          Preview Portal
        • 3
          HDInsight
        • 3
          Built on Node.js
        • 3
          Big Data
        • 3
          BizSpark 60k Azure Benefit
        • 3
          IaaS
        • 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
          Documentation
        • 1
          Security
        • 1
          Best cloud platfrom
        • 1
          Easy and fast to start with
        • 1
          Remote Debugging
        CONS OF MICROSOFT AZURE
        • 7
          Confusing UI
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          Expensive plesk on Azure

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        Omar Mehilba
        Co-Founder and COO at Magalix · | 19 upvotes · 423.6K 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 · 757.1K 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
        DigitalOcean logo

        DigitalOcean

        17.6K
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        Deploy an SSD cloud server in less than 55 seconds with a dedicated IP and root access.
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        PROS OF DIGITALOCEAN
        • 560
          Great value for money
        • 364
          Simple dashboard
        • 362
          Good pricing
        • 300
          Ssds
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          Nice ui
        • 191
          Easy configuration
        • 156
          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
          LAMP
        • 4
          Debian
        • 4
          CoreOS
        • 3
          1Gb/sec Servers
        • 3
          Word Press
        • 3
          LEMP
        • 3
          Simple Control Panel
        • 3
          Mean
        • 3
          Ghost
        • 2
          Runs CoreOS
        • 2
          Quick and no nonsense service
        • 2
          Django
        • 2
          Good Tutorials
        • 2
          Speed
        • 2
          Ruby on Rails
        • 2
          GitLab
        • 2
          Hex Core machines with dedicated ECC Ram and RAID SSD s
        • 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
          No live support chat
        • 3
          Pricing

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        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

        12K
        8.9K
        423
        Run large-scale workloads on virtual machines hosted on Google's infrastructure.
        12K
        8.9K
        + 1
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        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 · 757.1K 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
          Linode logo

          Linode

          730
          618
          422
          Deploy and Manage Linux Virtual Servers in the Linode Cloud.
          730
          618
          + 1
          422
          PROS OF LINODE
          • 100
            Extremely reliable
          • 70
            Good value
          • 60
            Great customer support
          • 58
            Easy to configure
          • 37
            Great documentation
          • 24
            Servers across the world
          • 18
            Managed/hosted DNS service
          • 15
            Simple ui
          • 11
            Network and CPU usage graphs
          • 7
            IPv6 support
          • 6
            Multiple IP address support
          • 3
            Good price, good cusomter sevice
          • 3
            Ssh access
          • 2
            IP address fail over support
          • 2
            SSH root access
          • 1
            Great performance compared to EC2 or DO
          • 1
            It runs apps with speed
          • 1
            Best customizable VPS
          • 1
            Latest kernels
          • 1
            Cheapest
          • 1
            Ssds
          CONS OF LINODE
          • 2
            No "floating IP" support

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          Kumar Gaurav
          DevOps Engineer at CoRover Private Limited · | 2 upvotes · 181.6K views
          Shared insights
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          Microsoft AzureMicrosoft AzureLinodeLinode

          What is the data transfer out cost (Bandwidth cost) on Linode compared to Microsoft Azure?

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          Rackspace Cloud Servers logo

          Rackspace Cloud Servers

          291
          210
          107
          Powerful Linux and Windows servers in minutes
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          + 1
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          PROS OF RACKSPACE CLOUD SERVERS
          • 42
            Quick and reliable cloud servers
          • 29
            Great customer support
          • 20
            SSDs
          • 10
            Uses OpenStack
          • 2
            Windows server 2012 possible
          • 2
            Easy integration with Github
          • 1
            Ubuntu
          • 1
            Ssh access
          CONS OF RACKSPACE CLOUD SERVERS
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