Alternatives to Microsoft Azure logo

Alternatives to Microsoft Azure

Amazon Web Services, Google Cloud Platform, DigitalOcean, OneDrive, and Hadoop are the most popular alternatives and competitors to Microsoft Azure.
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What is Microsoft Azure and what are its top alternatives?

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

Microsoft Azure alternatives & related posts

Amazon Web Services logo

Amazon Web Services

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The world’s most comprehensive and broadly adopted cloud platform, offering over 165 fully featured services
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Amazon Web Services
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Microsoft Azure

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Mohamed Labouardy
Mohamed Labouardy
Founder at Komiser · | 5 upvotes · 31.4K views
atKomiserKomiser
Google Compute Engine
Google Compute Engine
Amazon Web Services
Amazon Web Services
Go
Go
Docker
Docker
Material Design for Angular
Material Design for Angular
Microsoft Azure
Microsoft Azure
GitHub
GitHub

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

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

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

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Mohamed Labouardy
Mohamed Labouardy
Founder at Komiser · | 5 upvotes · 24.6K views
atKomiserKomiser
Google Compute Engine
Google Compute Engine
Amazon Web Services
Amazon Web Services
OVH
OVH
Microsoft Azure
Microsoft Azure
Go
Go
GitHub
GitHub

Google Compute Engine Amazon Web Services OVH Microsoft Azure Go GitHub

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

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

Read the full story in the blog post.

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Google Cloud Platform logo

Google Cloud Platform

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A suite of cloud computing services
    Be the first to leave a pro
    Google Cloud Platform logo
    Google Cloud Platform
    VS
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    Microsoft Azure

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    Jorge Cortell
    Jorge Cortell
    Founder & CEO at Kanteron Systems · | 1 upvotes · 11.5K views
    atKanteron SystemsKanteron Systems
    Google Cloud Platform
    Google Cloud Platform
    Microsoft Azure
    Microsoft Azure
    Amazon S3
    Amazon S3

    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).

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    DigitalOcean logo

    DigitalOcean

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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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    DigitalOcean
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    Microsoft Azure

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    Rajat Jain
    Rajat Jain
    Devops Engineer at Aurochssoftware · | 1 upvotes · 16.8K views
    Amazon EC2
    Amazon EC2
    Amazon S3
    Amazon S3
    Bitbucket
    Bitbucket
    GitLab
    GitLab
    PyCharm
    PyCharm
    Ubuntu
    Ubuntu
    DigitalOcean
    DigitalOcean
    Docker
    Docker
    Git
    Git

    Building my skill set to become Devops Engineer-Tool chain: Amazon EC2, Amazon S3, Bitbucket, GitLab, PyCharm, Ubuntu, DigitalOcean, Docker, Git

    IT engineer with more than 6 months of experience in startups with focus on DevOps, Cloud infrastructure & Testing (QA). I had set up CI process, monitoring and infrastructure on dev/test (lower) environments

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    OneDrive logo

    OneDrive

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    Save your files and photos to OneDrive and get them from any device, anywhere
      Be the first to leave a pro
      OneDrive logo
      OneDrive
      VS
      Microsoft Azure logo
      Microsoft Azure
      Hadoop logo

      Hadoop

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      Open-source software for reliable, scalable, distributed computing
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      Microsoft Azure

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      StackShare Editors
      StackShare Editors
      | 4 upvotes · 171.3K views
      atUber TechnologiesUber Technologies
      Kafka
      Kafka
      Kibana
      Kibana
      Elasticsearch
      Elasticsearch
      Logstash
      Logstash
      Hadoop
      Hadoop

      With interactions across each other and mobile devices, logging is important as it is information for internal cases like debugging and business cases like dynamic pricing.

      With multiple Kafka clusters, data is archived into Hadoop before expiration. Data is ingested in realtime and indexed into an ELK stack. The ELK stack comprises of Elasticsearch, Logstash, and Kibana for searching and visualization.

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      StackShare Editors
      StackShare Editors
      Prometheus
      Prometheus
      Chef
      Chef
      Consul
      Consul
      Memcached
      Memcached
      Hack
      Hack
      Swift
      Swift
      Hadoop
      Hadoop
      Terraform
      Terraform
      Airflow
      Airflow
      Apache Spark
      Apache Spark
      Kubernetes
      Kubernetes
      gRPC
      gRPC
      HHVM (HipHop Virtual Machine)
      HHVM (HipHop Virtual Machine)
      Presto
      Presto
      Kotlin
      Kotlin
      Apache Thrift
      Apache Thrift

      Since the beginning, Cal Henderson has been the CTO of Slack. Earlier this year, he commented on a Quora question summarizing their current stack.

      Apps
      • Web: a mix of JavaScript/ES6 and React.
      • Desktop: And Electron to ship it as a desktop application.
      • Android: a mix of Java and Kotlin.
      • iOS: written in a mix of Objective C and Swift.
      Backend
      • The core application and the API written in PHP/Hack that runs on HHVM.
      • The data is stored in MySQL using Vitess.
      • Caching is done using Memcached and MCRouter.
      • The search service takes help from SolrCloud, with various Java services.
      • The messaging system uses WebSockets with many services in Java and Go.
      • Load balancing is done using HAproxy with Consul for configuration.
      • Most services talk to each other over gRPC,
      • Some Thrift and JSON-over-HTTP
      • Voice and video calling service was built in Elixir.
      Data warehouse
      • Built using open source tools including Presto, Spark, Airflow, Hadoop and Kafka.
      Etc
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      Amazon EC2 logo

      Amazon EC2

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      Scalable, pay-as-you-go compute capacity in the cloud
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      Amazon EC2
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      Microsoft Azure

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      Ashish Singh
      Ashish Singh
      Tech Lead, Big Data Platform at Pinterest · | 26 upvotes · 97.2K views
      Apache Hive
      Apache Hive
      Kubernetes
      Kubernetes
      Kafka
      Kafka
      Amazon S3
      Amazon S3
      Amazon EC2
      Amazon EC2
      Presto
      Presto
      #DataScience
      #DataEngineering
      #AWS
      #BigData

      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

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      John-Daniel Trask
      John-Daniel Trask
      Co-founder & CEO at Raygun · | 19 upvotes · 110K views
      atRaygunRaygun
      Amazon S3
      Amazon S3
      Amazon RDS
      Amazon RDS
      nginx
      nginx
      Amazon EC2
      Amazon EC2
      AWS Elastic Load Balancing (ELB)
      AWS Elastic Load Balancing (ELB)
      #CloudHosting
      #WebServers
      #CloudStorage
      #LoadBalancerReverseProxy

      We chose AWS because, at the time, it was really the only cloud provider to choose from.

      We tend to use their basic building blocks (EC2, ELB, Amazon S3, Amazon RDS) rather than vendor specific components like databases and queuing. We deliberately decided to do this to ensure we could provide multi-cloud support or potentially move to another cloud provider if the offering was better for our customers.

      We’ve utilized c3.large nodes for both the Node.js deployment and then for the .NET Core deployment. Both sit as backends behind an nginx instance and are managed using scaling groups in Amazon EC2 sitting behind a standard AWS Elastic Load Balancing (ELB).

      While we’re satisfied with AWS, we do review our decision each year and have looked at Azure and Google Cloud offerings.

      #CloudHosting #WebServers #CloudStorage #LoadBalancerReverseProxy

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      Kestas Barzdaitis
      Kestas Barzdaitis
      Entrepreneur & Engineer · | 14 upvotes · 131.2K views
      atCodeFactorCodeFactor
      Kubernetes
      Kubernetes
      CodeFactor.io
      CodeFactor.io
      Amazon EC2
      Amazon EC2
      Microsoft Azure
      Microsoft Azure
      Google Compute Engine
      Google Compute Engine
      Docker
      Docker
      AWS Lambda
      AWS Lambda
      Azure Functions
      Azure Functions
      Google Cloud Functions
      Google Cloud Functions
      #SAAS
      #IAAS
      #Containerization
      #Autoscale
      #Startup
      #Automation
      #Machinelearning
      #AI
      #Devops

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

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

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

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

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

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

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

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      Marcel Kornegoor
      Marcel Kornegoor
      CTO at AT Computing · | 5 upvotes · 209K views
      atAT ComputingAT Computing
      Linux
      Linux
      Ubuntu
      Ubuntu
      CentOS
      CentOS
      Debian
      Debian
      Red Hat Enterprise Linux
      Red Hat Enterprise Linux
      Fedora
      Fedora
      Visual Studio Code
      Visual Studio Code
      Jenkins
      Jenkins
      VirtualBox
      VirtualBox
      GitHub
      GitHub
      Docker
      Docker
      Kubernetes
      Kubernetes
      Google Compute Engine
      Google Compute Engine
      Ansible
      Ansible
      Puppet Labs
      Puppet Labs
      Chef
      Chef
      Python
      Python
      #ATComputing

      Since #ATComputing is a vendor independent Linux and open source specialist, we do not have a favorite Linux distribution. We mainly use Ubuntu , Centos Debian , Red Hat Enterprise Linux and Fedora during our daily work. These are also the distributions we see most often used in our customers environments.

      For our #ci/cd training, we use an open source pipeline that is build around Visual Studio Code , Jenkins , VirtualBox , GitHub , Docker Kubernetes and Google Compute Engine.

      For #ServerConfigurationAndAutomation, we have embraced and contributed to Ansible mainly because it is not only flexible and powerful, but also straightforward and easier to learn than some other (open source) solutions. On the other hand: we are not affraid of Puppet Labs and Chef either.

      Currently, our most popular #programming #Language course is Python . The reason Python is so popular has to do with it's versatility, but also with its low complexity. This helps sysadmins to write scripts or simple programs to make their job less repetitive and automating things more fun. Python is also widely used to communicate with (REST) API's and for data analysis.

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      Vultr logo

      Vultr

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      Deploy Cloud Servers, Bare Metal, and Storage worldwide
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      Microsoft Azure

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      Paul Whittemore
      Paul Whittemore
      Developer and Owner at Appurist Software · | 4 upvotes · 47.4K views
      Vultr
      Vultr
      Amazon LightSail
      Amazon LightSail
      Windows
      Windows
      Windows Server
      Windows Server

      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.

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      Amazon LightSail logo

      Amazon LightSail

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      Simple Virtual Private Servers on AWS