What is Ploi and what are its top alternatives?
Ploi is a powerful server management tool designed to simplify the deployment and management of PHP applications. Key features of Ploi include easy server provisioning, automatic SSL certificate generation, webhook integrations, server security optimizations, and server monitoring. However, some limitations of Ploi include a limited selection of server providers, pricing based on the number of servers, and potential scalability issues for larger projects.
- ServerPilot: ServerPilot is a cloud-based server management platform that automates PHP applications deployment and management. Key features include easy server setup, server monitoring, SSL certificate management, and team collaboration tools. Pros: user-friendly interface, robust security measures. Cons: limited server providers supported.
- RunCloud: RunCloud is a server management tool that offers features like easy PHP application deployment, server monitoring, SSL certificate management, and team collaboration tools. Pros: support for multiple server providers, affordable pricing plans. Cons: limited integrations with third-party services.
- Forge: Forge is a server management tool specifically designed for Laravel projects, offering features like easy server provisioning, server monitoring, automated deployments, and SSL certificate management. Pros: optimized for Laravel projects, seamless deployment process. Cons: limited support for non-Laravel applications.
- SpinupWP: SpinupWP is a WordPress-specific server management tool that simplifies the deployment and management of WordPress sites. Key features include server setup automation, server monitoring, SSL certificate management, and automatic backups. Pros: optimized for WordPress sites, user-friendly interface. Cons: limited support for non-WordPress applications.
- Cloudways: Cloudways is a cloud-based server management platform that allows users to deploy and manage applications on various cloud hosting providers. Key features include server setup automation, server monitoring, auto-scaling, and team collaboration tools. Pros: support for multiple cloud providers, flexible pricing plans. Cons: potential learning curve for beginners.
- EasyEngine: EasyEngine is a command-line tool that simplifies the deployment and management of WordPress sites on servers. Key features include one-click WordPress installations, server optimization tools, and SSL certificate management. Pros: fast deployment process, optimization for WordPress sites. Cons: limited graphical interface, steep learning curve for command-line usage.
- CyberPanel: CyberPanel is a web hosting control panel that offers features like automated WordPress installations, server monitoring, SSL certificate management, and website staging. Pros: lightweight and fast performance, free version available. Cons: limited third-party integrations, less user-friendly for beginners.
- Vultr: Vultr is a cloud hosting provider that offers easy server deployment, scaling, and monitoring tools. Key features include SSD storage, global data centers, and flexible pricing plans. Pros: variety of server locations, competitive pricing. Cons: fewer management features compared to dedicated server management tools.
- GridPane: GridPane is a server management tool designed for hosting WordPress websites on virtual private servers. Key features include server setup automation, server monitoring, automatic updates, and security optimizations. Pros: optimized for WordPress hosting, robust security measures. Cons: limited support for non-WordPress applications.
- VestaCP: VestaCP is an open-source web hosting control panel that offers features like domain management, email hosting, database management, and server monitoring. Pros: free and open-source, lightweight control panel. Cons: limited advanced features compared to commercial server management tools.
Top Alternatives to Ploi
- 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
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. ...
- Forge
Fastest possible way to host lighting-fast static websites for small businesses, web startups, and app developers. ...
- Ansible
Ansible is an IT automation tool. It can configure systems, deploy software, and orchestrate more advanced IT tasks such as continuous deployments or zero downtime rolling updates. Ansible’s goals are foremost those of simplicity and maximum ease of use. ...
- Terraform
With Terraform, you describe your complete infrastructure as code, even as it spans multiple service providers. Your servers may come from AWS, your DNS may come from CloudFlare, and your database may come from Heroku. Terraform will build all these resources across all these providers in parallel. ...
- Dotenv
It is a zero-dependency module that loads environment variables from a .env file into process.env. Storing configuration in the environment separate from code is based on The Twelve-Factor App methodology. ...
- Chef
Chef enables you to manage and scale cloud infrastructure with no downtime or interruptions. Freely move applications and configurations from one cloud to another. Chef is integrated with all major cloud providers including Amazon EC2, VMWare, IBM Smartcloud, Rackspace, OpenStack, Windows Azure, HP Cloud, Google Compute Engine, Joyent Cloud and others. ...
- Puppet Labs
Puppet is an automated administrative engine for your Linux, Unix, and Windows systems and performs administrative tasks (such as adding users, installing packages, and updating server configurations) based on a centralized specification. ...
Ploi alternatives & related posts
related ServerPilot posts
related Runcloud posts
related Forge posts
Ansible
- Agentless284
- Great configuration210
- Simple199
- Powerful176
- Easy to learn155
- Flexible69
- Doesn't get in the way of getting s--- done55
- Makes sense35
- Super efficient and flexible30
- Powerful27
- Dynamic Inventory11
- Backed by Red Hat9
- Works with AWS7
- Cloud Oriented6
- Easy to maintain6
- Vagrant provisioner4
- Simple and powerful4
- Multi language4
- Simple4
- Because SSH4
- Procedural or declarative, or both4
- Easy4
- Consistency3
- Well-documented2
- Masterless2
- Debugging is simple2
- Merge hash to get final configuration similar to hiera2
- Fast as hell2
- Manage any OS1
- Work on windows, but difficult to manage1
- Certified Content1
- Dangerous8
- Hard to install5
- Doesn't Run on Windows3
- Bloated3
- Backward compatibility3
- No immutable infrastructure2
related Ansible posts
Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).
It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up
or vagrant reload
we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.
I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up
, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.
We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.
If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.
The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).
Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.
Heroku was a decent choice to start a business, but at some point our platform was too big, too complex & too heterogenic, so Heroku started to be a constraint, not a benefit. First, we've started containerizing our apps with Docker to eliminate "works in my machine" syndrome & uniformize the environment setup. The first orchestration was composed with Docker Compose , but at some point it made sense to move it to Kubernetes. Fortunately, we've made a very good technical decision when starting our work with containers - all the container configuration & provisions HAD (since the beginning) to be done in code (Infrastructure as Code) - we've used Terraform & Ansible for that (correspondingly). This general trend of containerisation was accompanied by another, parallel & equally big project: migrating environments from Heroku to AWS: using Amazon EC2 , Amazon EKS, Amazon S3 & Amazon RDS.
Terraform
- Infrastructure as code122
- Declarative syntax73
- Planning45
- Simple28
- Parallelism24
- Well-documented8
- Cloud agnostic8
- It's like coding your infrastructure in simple English6
- Immutable infrastructure6
- Platform agnostic5
- Extendable4
- Automation4
- Automates infrastructure deployments4
- Portability4
- Lightweight2
- Scales to hundreds of hosts2
- Doesn't have full support to GKE1
related Terraform posts
We recently moved our main applications from Heroku to Kubernetes . The 3 main driving factors behind the switch were scalability (database size limits), security (the inability to set up PostgreSQL instances in private networks), and costs (GCP is cheaper for raw computing resources).
We prefer using managed services, so we are using Google Kubernetes Engine with Google Cloud SQL for PostgreSQL for our PostgreSQL databases and Google Cloud Memorystore for Redis . For our CI/CD pipeline, we are using CircleCI and Google Cloud Build to deploy applications managed with Helm . The new infrastructure is managed with Terraform .
Read the blog post to go more in depth.
We are in the process of building a modern content platform to deliver our content through various channels. We decided to go with Microservices architecture as we wanted scale. Microservice architecture style is an approach to developing an application as a suite of small independently deployable services built around specific business capabilities. You can gain modularity, extensive parallelism and cost-effective scaling by deploying services across many distributed servers. Microservices modularity facilitates independent updates/deployments, and helps to avoid single point of failure, which can help prevent large-scale outages. We also decided to use Event Driven Architecture pattern which is a popular distributed asynchronous architecture pattern used to produce highly scalable applications. The event-driven architecture is made up of highly decoupled, single-purpose event processing components that asynchronously receive and process events.
To build our #Backend capabilities we decided to use the following: 1. #Microservices - Java with Spring Boot , Node.js with ExpressJS and Python with Flask 2. #Eventsourcingframework - Amazon Kinesis , Amazon Kinesis Firehose , Amazon SNS , Amazon SQS, AWS Lambda 3. #Data - Amazon RDS , Amazon DynamoDB , Amazon S3 , MongoDB Atlas
To build #Webapps we decided to use Angular 2 with RxJS
#Devops - GitHub , Travis CI , Terraform , Docker , Serverless
related Dotenv posts
- Dynamic and idempotent server configuration110
- Reusable components76
- Integration testing with Vagrant47
- Repeatable43
- Mock testing with Chefspec30
- Ruby14
- Can package cookbooks to guarantee repeatability8
- Works with AWS7
- Has marketplace where you get readymade cookbooks3
- Matured product with good community support3
- Less declarative more procedural2
- Open source configuration mgmt made easy(ish)2
related Chef posts
In late 2013, the Operations Engineering team at PagerDuty was made up of 4 engineers, and was comprised of generalists, each of whom had one or two areas of depth. Although the Operations Team ran its own on-call, each engineering team at PagerDuty also participated on the pager.
The Operations Engineering Team owned 150+ servers spanning multiple cloud providers, and used Chef to automate their infrastructure across the various cloud providers with a mix of completely custom cookbooks and customized community cookbooks.
Custom cookbooks were managed by Berkshelf, andach custom cookbook contained its own tests based on ChefSpec 3, coupled with Rspec.
Jenkins was used to GitHub for new changes and to handle unit testing of those features.
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.
- Devops52
- Automate it44
- Reusable components26
- Dynamic and idempotent server configuration21
- Great community18
- Very scalable12
- Cloud management12
- Easy to maintain10
- Free tier9
- Works with Amazon EC26
- Declarative4
- Ruby4
- Works with Azure3
- Works with OpenStack3
- Nginx2
- Ease of use1
- Steep learning curve3
- Customs types idempotence1
related Puppet Labs posts
By 2014, the DevOps team at Lyft decided to port their infrastructure code from Puppet to Salt. At that point, the Puppet code based included around "10,000 lines of spaghetti-code,” which was unfamiliar and challenging to the relatively new members of the DevOps team.
“The DevOps team felt that the Puppet infrastructure was too difficult to pick up quickly and would be impossible to introduce to [their] developers as the tool they’d use to manage their own services.”
To determine a path forward, the team assessed both Ansible and Salt, exploring four key areas: simplicity/ease of use, maturity, performance, and community.
They found that “Salt’s execution and state module support is more mature than Ansible’s, overall,” and that “Salt was faster than Ansible for state/playbook runs.” And while both have high levels of community support, Salt exceeded expectations in terms of friendless and responsiveness to opened issues.
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.