Alternatives to Cloudways  logo

Alternatives to Cloudways

ServerPilot, Runcloud, Kinsta, SiteGround, and Laravel Forge are the most popular alternatives and competitors to Cloudways .
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What is Cloudways and what are its top alternatives?

A platform that facilitates choice, simplicity and performance. All this is backed by caring expert support so that you stay focused on what you do best, win as an individual and succeed as a business.
Cloudways is a tool in the Cloud Hosting category of a tech stack.
Cloudways is an open source tool with GitHub stars and GitHub forks. Here’s a link to Cloudways 's open source repository on GitHub

Top Alternatives to Cloudways

  • ServerPilot

    ServerPilot

    It is a SaaS platform for hosting PHP websites on Ubuntu servers. You can think of it as a modern, centralized hosting control panel. Manage all servers and sites through a single control panel or automate using our API. ...

  • Runcloud

    Runcloud

    SaaS based PHP cloud server control panel. Support Digital Ocean, Linode, AWS, Vultr, Azure and other custom VPS. GIT deployment webhook and easiest control panel to manage Laravel, Cake, Symphony or WordPress. ...

  • Kinsta

    Kinsta

    They provide high performance hosting on Google Apps servers, which means your site runs on the same infrastructure as Google ...

  • SiteGround

    SiteGround

    It is a web hosting company and reports servicing more than 1,800,000 domains worldwide. It provides shared hosting, cloud hosting and dedicated servers as well as email hosting and domain registration ...

  • Laravel Forge

    Laravel Forge

    Provision, host, and deploy PHP applications on AWS, DigitalOcean, and Linode. ...

  • 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. ...

  • 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. ...

Cloudways alternatives & related posts

ServerPilot logo

ServerPilot

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The best way to run WordPress and PHP sites
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+ 1
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PROS OF SERVERPILOT
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    CONS OF SERVERPILOT
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      related ServerPilot posts

      Runcloud logo

      Runcloud

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      PHP web application & server management panel
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      PROS OF RUNCLOUD
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        CONS OF RUNCLOUD
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          Kinsta logo

          Kinsta

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          A WordPress hosting company offering cloud-based hosting
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          PROS OF KINSTA
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            CONS OF KINSTA
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              SiteGround logo

              SiteGround

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              A shared hosting provider that offers its users multiple different hosting options
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              PROS OF SITEGROUND
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                CONS OF SITEGROUND
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                  Laravel Forge logo

                  Laravel Forge

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                  4
                  Painless PHP Servers by Laravel
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                  PROS OF LARAVEL FORGE
                  • 4
                    Simply to use
                  CONS OF LARAVEL FORGE
                  • 2
                    Monthly subscription

                  related Laravel Forge 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!

                  See more
                  Amazon EC2 logo

                  Amazon EC2

                  39.8K
                  28.4K
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                  Scalable, pay-as-you-go compute capacity in the cloud
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                  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 · | 36 upvotes · 920.8K 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 · 3.5M 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.
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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
                  • 112
                    Scales well and quite easy
                  • 94
                    Can use .Net or open source tools
                  • 80
                    Startup friendly
                  • 72
                    Startup plans via BizSpark
                  • 61
                    High performance
                  • 37
                    Wide choice of services
                  • 32
                    Low cost
                  • 31
                    Lots of integrations
                  • 30
                    Reliability
                  • 18
                    Twillio & Github are directly accessible
                  • 12
                    RESTful API
                  • 9
                    Startup support
                  • 9
                    PaaS
                  • 9
                    Enterprise Grade
                  • 7
                    In person support
                  • 7
                    DocumentDB
                  • 6
                    Virtual Machines
                  • 6
                    Free for students
                  • 6
                    Service Bus
                  • 5
                    Redis Cache
                  • 5
                    It rocks
                  • 4
                    Storage, Backup, and Recovery
                  • 4
                    SQL Databases
                  • 4
                    Infrastructure Services
                  • 4
                    CDN
                  • 3
                    Integration
                  • 3
                    Scheduler
                  • 3
                    HDInsight
                  • 3
                    Preview Portal
                  • 3
                    Built on Node.js
                  • 3
                    Big Data
                  • 3
                    BizSpark 60k Azure Benefit
                  • 3
                    IaaS
                  • 2
                    Site Recovery
                  • 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
                    Backup
                  • 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
                    Best cloud platfrom
                  • 1
                    Security
                  • 1
                    Documentation
                  • 1
                    Easy and fast to start with
                  • 1
                    Remote Debugging
                  • 1
                    Open cloud
                  CONS OF MICROSOFT AZURE
                  • 6
                    Confusing UI
                  • 2
                    Expensive plesk on Azure

                  related Microsoft Azure posts

                  Omar Mehilba
                  Co-Founder and COO at Magalix · | 19 upvotes · 262.6K 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!

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                  Kestas Barzdaitis
                  Entrepreneur & Engineer · | 16 upvotes · 464.4K 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.

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                  Google Cloud Platform logo

                  Google Cloud Platform

                  17.5K
                  7K
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                  A suite of cloud computing services
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                  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
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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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                    Sumit Singh Chauhan
                    Data Scientist at Entropik · | 6 upvotes · 9.7K views

                    I have started using AWS Batch for some long ML inference jobs. So far it's working well and giving a decent performance. Since it is fully managed, it saves a lot of extra work as well. But Batch takes a good amount of time to create a new cluster and then load the job based on the priority of the queue. Going forward would love to put effort into something which is fast to start and give more flexibility as well. What other tools you would suggest for long-running backend jobs which can scale well. I am not looking for something fully managed so ignore the options similar to batch in Google Cloud Platform or Microsoft Azure, Looking for open-source alternatives here. Do you think Kubernetes, RabbitMQ/Kafka will be a good fit or just overkill for my problem. Usually w we get 1000s of requests in parallel and each job might take 20-30 mins in a 2 vCPU system.

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