Alternatives to DigitalOcean logo

Alternatives to DigitalOcean

Linode, Vultr, Heroku, Microsoft Azure, and Bitnami are the most popular alternatives and competitors to DigitalOcean.
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What is DigitalOcean and what are its top alternatives?

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.
DigitalOcean is a tool in the Cloud Hosting category of a tech stack.

Top Alternatives to DigitalOcean

  • Linode

    Linode

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

  • Vultr

    Vultr

    Strategically located in 16 datacenters around the globe and provides frictionless provisioning of public cloud, storage and single-tenant bare metal. ...

  • Heroku

    Heroku

    Heroku is a cloud application platform – a new way of building and deploying web apps. Heroku lets app developers spend 100% of their time on their application code, not managing servers, deployment, ongoing operations, or scaling. ...

  • 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. ...

  • Bitnami

    Bitnami

    Our library provides trusted virtual machines for every major development stack and open source server application, ready to run in your infrastructure. ...

  • 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. ...

  • 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. ...

  • 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. ...

DigitalOcean alternatives & related posts

Linode logo

Linode

630
543
424
Deploy and Manage Linux Virtual Servers in the Linode Cloud.
630
543
+ 1
424
PROS OF LINODE
  • 102
    Extremely reliable
  • 71
    Good value
  • 59
    Easy to configure
  • 59
    Great customer support
  • 36
    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
    Ssh access
  • 3
    Good price, good cusomter sevice
  • 2
    IP address fail over support
  • 2
    SSH root access
  • 1
    Great performance compared to EC2 or DO
  • 1
    Best customizable VPS
  • 1
    Latest kernels
  • 1
    Cheapest
  • 1
    Ssds
  • 1
    It runs apps with speed
CONS OF LINODE
  • 2
    No "floating IP" support

related Linode posts

Kumar Gaurav
DevOps Engineer at CoRover Private Limited · | 2 upvotes · 9.7K views
Shared insights
on
Microsoft Azure
Linode

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

See more
Vultr logo

Vultr

138
111
7
Deploy Cloud Servers, Bare Metal, and Storage worldwide
138
111
+ 1
7
PROS OF VULTR
  • 3
    <a href="https://hostandprotect.com/">secure</a>
  • 2
    Affordable
  • 2
    Cloud Based
CONS OF VULTR
    Be the first to leave a con

    related Vultr posts

    Paul Whittemore
    Developer and Owner at Appurist Software · | 4 upvotes · 130.3K 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
    Heroku logo

    Heroku

    18.3K
    14K
    3.2K
    Build, deliver, monitor and scale web apps and APIs with a trail blazing developer experience.
    18.3K
    14K
    + 1
    3.2K
    PROS OF HEROKU
    • 702
      Easy deployment
    • 459
      Free for side projects
    • 374
      Huge time-saver
    • 348
      Simple scaling
    • 261
      Low devops skills required
    • 190
      Easy setup
    • 174
      Add-ons for almost everything
    • 154
      Beginner friendly
    • 150
      Better for startups
    • 133
      Low learning curve
    • 48
      Postgres hosting
    • 41
      Easy to add collaborators
    • 30
      Faster development
    • 24
      Awesome documentation
    • 19
      Simple rollback
    • 19
      Focus on product, not deployment
    • 15
      Natural companion for rails development
    • 15
      Easy integration
    • 12
      Great customer support
    • 8
      GitHub integration
    • 6
      Painless & well documented
    • 6
      No-ops
    • 4
      Free
    • 3
      I love that they make it free to launch a side project
    • 3
      Great UI
    • 3
      Just works
    • 2
      PostgreSQL forking and following
    • 2
      MySQL extension
    CONS OF HEROKU
    • 23
      Super expensive
    • 6
      No usable MySQL option
    • 6
      Not a whole lot of flexibility
    • 5
      Storage
    • 4
      Low performance on free tier

    related Heroku posts

    Russel Werner
    Lead Engineer at StackShare · | 29 upvotes · 1.4M views

    StackShare Feed is built entirely with React, Glamorous, and Apollo. One of our objectives with the public launch of the Feed was to enable a Server-side rendered (SSR) experience for our organic search traffic. When you visit the StackShare Feed, and you aren't logged in, you are delivered the Trending feed experience. We use an in-house Node.js rendering microservice to generate this HTML. This microservice needs to run and serve requests independent of our Rails web app. Up until recently, we had a mono-repo with our Rails and React code living happily together and all served from the same web process. In order to deploy our SSR app into a Heroku environment, we needed to split out our front-end application into a separate repo in GitHub. The driving factor in this decision was mostly due to limitations imposed by Heroku specifically with how processes can't communicate with each other. A new SSR app was created in Heroku and linked directly to the frontend repo so it stays in-sync with changes.

    Related to this, we need a way to "deploy" our frontend changes to various server environments without building & releasing the entire Ruby application. We built a hybrid Amazon S3 Amazon CloudFront solution to host our Webpack bundles. A new CircleCI script builds the bundles and uploads them to S3. The final step in our rollout is to update some keys in Redis so our Rails app knows which bundles to serve. The result of these efforts were significant. Our frontend team now moves independently of our backend team, our build & release process takes only a few minutes, we are now using an edge CDN to serve JS assets, and we have pre-rendered React pages!

    #StackDecisionsLaunch #SSR #Microservices #FrontEndRepoSplit

    See more
    Simon Reymann
    Senior Fullstack Developer at QUANTUSflow Software GmbH · | 28 upvotes · 2.6M 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
    Microsoft Azure logo

    Microsoft Azure

    15.9K
    9.7K
    746
    Integrated cloud services and infrastructure to support computing, database, analytics, mobile, and web scenarios.
    15.9K
    9.7K
    + 1
    746
    PROS OF MICROSOFT AZURE
    • 112
      Scales well and quite easy
    • 93
      Can use .Net or open source tools
    • 80
      Startup friendly
    • 72
      Startup plans via BizSpark
    • 61
      High performance
    • 36
      Wide choice of services
    • 32
      Low cost
    • 31
      Lots of integrations
    • 29
      Reliability
    • 18
      Twillio & Github are directly accessible
    • 11
      RESTful API
    • 9
      Enterprise Grade
    • 9
      Startup support
    • 9
      PaaS
    • 7
      Free for students
    • 7
      DocumentDB
    • 7
      In person support
    • 6
      Virtual Machines
    • 5
      Service Bus
    • 5
      It rocks
    • 4
      Storage, Backup, and Recovery
    • 4
      Infrastructure Services
    • 4
      SQL Databases
    • 4
      Redis Cache
    • 4
      CDN
    • 3
      Scheduler
    • 3
      BizSpark 60k Azure Benefit
    • 3
      HDInsight
    • 3
      Big Data
    • 3
      Integration
    • 3
      IaaS
    • 3
      Built on Node.js
    • 3
      Preview Portal
    • 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
      Backup
    • 2
      Site Recovery
    • 2
      Active Directory
    • 2
      Multi-Factor Authentication
    • 2
      Visual Studio Online
    • 2
      Application Insights
    • 2
      Automation
    • 2
      Big Compute
    • 2
      Mobile
    • 2
      Media
    • 2
      Dev-Test
    • 2
      Web
    • 2
      Storage
    • 2
      StorSimple
    • 2
      Operational Insights
    • 2
      Key Vault
    • 2
      Infrastructure near your customers
    • 2
      Easy Deployment
    • 2
      SaaS
    • 1
      Best cloud platfrom
    • 1
      Easy and fast to start with
    • 1
      Documentation
    • 1
      Open cloud
    • 1
      Remote Debugging
    • 1
      Enterprise customer preferences
    • 1
      Security
    CONS OF MICROSOFT AZURE
    • 6
      Confusing UI
    • 2
      Expensive plesk on Azure

    related Microsoft Azure posts

    Omar Mehilba
    Co-Founder and COO at Magalix · | 18 upvotes · 251.3K 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 · 415.9K 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
    Bitnami logo

    Bitnami

    114
    149
    6
    The App Store for Server Software
    114
    149
    + 1
    6
    PROS OF BITNAMI
    • 6
      Cloud Management
    CONS OF BITNAMI
      Be the first to leave a con

      related Bitnami posts

      Amazon EC2 logo

      Amazon EC2

      36.1K
      25.1K
      2.5K
      Scalable, pay-as-you-go compute capacity in the cloud
      36.1K
      25.1K
      + 1
      2.5K
      PROS OF AMAZON EC2
      • 644
        Quick and reliable cloud servers
      • 515
        Scalability
      • 391
        Easy management
      • 276
        Low cost
      • 269
        Auto-scaling
      • 88
        Market leader
      • 80
        Backed by amazon
      • 78
        Reliable
      • 66
        Free tier
      • 57
        Easy management, scalability
      • 12
        Flexible
      • 10
        Easy to Start
      • 9
        Web-scale
      • 8
        Widely used
      • 8
        Elastic
      • 7
        Node.js API
      • 4
        Industry Standard
      • 3
        Lots of configuration options
      • 2
        GPU instances
      • 1
        Amazing for individuals
      • 1
        Extremely simple to use
      • 1
        All the Open Source CLI tools you could want.
      • 1
        Simpler to understand and learn
      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

      related Amazon EC2 posts

      Ashish Singh
      Tech Lead, Big Data Platform at Pinterest · | 35 upvotes · 753.3K 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 · | 28 upvotes · 2.6M 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
      Google Cloud Platform logo

      Google Cloud Platform

      15.5K
      5.3K
      10
      A suite of cloud computing services
      15.5K
      5.3K
      + 1
      10
      PROS OF GOOGLE CLOUD PLATFORM
      • 3
        1 year free trial credit USD300
      • 2
        Cheap
      • 2
        Good app Marketplace for Beginner and Advanced User
      • 2
        Premium tier IP address
      • 1
        Live chat support
      CONS OF GOOGLE CLOUD PLATFORM
        Be the first to leave a con

        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.

        See more
        Jorge Cortell
        Founder & CEO at Kanteron Systems · | 1 upvote · 54.5K views

        We use Google Cloud Platform, Microsoft Azure and Amazon S3 (amongst others) because our platform needs to be cloud-independent to give customers the freedom they need and deserve. But being in the healthcare enterprise space, we believe Azure is the top choice... today (it tends to change often).

        See more
        Google Compute Engine logo

        Google Compute Engine

        8.5K
        6.1K
        424
        Run large-scale workloads on virtual machines hosted on Google's infrastructure.
        8.5K
        6.1K
        + 1
        424
        PROS OF GOOGLE COMPUTE ENGINE
        • 88
          Backed by google
        • 80
          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
          One Click Setup Options
        • 3
          Good documentation
        • 3
          Free $300 credit (12 months)
        • 2
          Great integration and product support
        • 2
          Ease of Use and GitHub support
        • 1
          Integration with mobile notification services
        • 1
          Nice UI
        • 1
          Escort
        • 1
          Low cost
        • 1
          Support many OS
        • 1
          Very Reliable
        • 1
          Easy Snapshot and Backup feature
        CONS OF GOOGLE COMPUTE ENGINE
          Be the first to leave a con

          related Google Compute Engine posts

          Kestas Barzdaitis
          Entrepreneur & Engineer · | 16 upvotes · 415.9K 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