What is Gandi and what are its top alternatives?
Top Alternatives to Gandi
We provide a set of DNS servers spread across the US and Europe to deliver highly reliable DNS services to everyone. By choosing Namecheap.com as your domain registrar, you are choosing a highly reputable and reliable partner. Namecheap.com is rated 4.6 out of 5 - Based on 1,395 reviews via Google Checkout ...
Go Daddy makes registering Domain Names fast, simple, and affordable. It is a trusted domain registrar that empowers people with creative ideas to succeed online. ...
It is a domain registration service which includes top website builders. The privacy is included at no additional cost. It also includes simple domain management tools. ...
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. ...
HostGator is a Houston-based provider of shared, reseller, virtual private server, and dedicated web hosting with an additional presence ...
It is a web service that provides resizable compute capacity in the cloud. It is designed to make web-scale computing easier for developers. ...
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
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. ...
Gandi alternatives & related posts
- Free privacy protection9
- Awesome customer support6
- Free email forwarding5
- Free custom DNS3
- Premium DNS1
- 24/7 Customer Support1
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- Flexible payment methods for domains7
- .io support3
- Constantly trying to upsell you2
- Not a great UI1
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- Minimalist Design2
- Great support1
- Easy website builder integration1
- It takes long time for DNS propagation1
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- Great value for money559
- Simple dashboard363
- Good pricing360
- Nice ui248
- Easy configuration192
- Great documentation155
- Ssh access137
- Great community134
- IPv6 support12
- Private networking10
- 99.99% uptime SLA7
- Great tutorials7
- Simple API7
- 55 Second Provisioning6
- One Click Applications5
- 1Gb/sec Servers3
- Simple Control Panel3
- Word Press3
- Runs CoreOS2
- Quick and no nonsense service2
- Good Tutorials2
- Ruby on Rails2
- Hex Core machines with dedicated ECC Ram and RAID SSD s2
- My go to server provider1
- Ease and simplicity1
- Find it superfitting with my requirements (SSD, ssh.1
- Easy Setup1
- Transfer Globally1
- FreeBSD Amp1
- Amazing Hardware1
- KVM Virtualization1
- Static IP1
- It's the easiest to get started for small projects1
- Automatic Backup1
- Great support1
- Quick and easy to set up1
- Servers on demand - literally1
- Variety of services0
- Managed Kubernetes0
- No live support chat3
related DigitalOcean 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!
Hi, I'm a beginner at using MySQL, I currently deployed my crud app on Heroku using the ClearDB add-on. I didn't see that coming, but the increased value of the primary key instead of being 1 is set to 10, and I cannot find a way to change it. Now I`m considering switching and deploying the full app and MySql to DigitalOcean any advice on that? Will I get the same issue? Thanks in advance!
related HostGator posts
- Quick and reliable cloud servers644
- Easy management391
- Low cost276
- Market leader88
- Backed by amazon80
- Free tier66
- Easy management, scalability57
- Easy to Start10
- Widely used8
- Node.js API7
- Industry Standard4
- Lots of configuration options3
- GPU instances2
- Amazing for individuals1
- Extremely simple to use1
- All the Open Source CLI tools you could want.1
- Simpler to understand and learn1
- Ui could use a lot of work13
- High learning curve when compared to PaaS6
- Extremely poor CPU performance3
related Amazon EC2 posts
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
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.
- Scales well and quite easy112
- Can use .Net or open source tools94
- Startup friendly80
- Startup plans via BizSpark72
- High performance61
- Wide choice of services37
- Low cost32
- Lots of integrations31
- Twillio & Github are directly accessible18
- RESTful API12
- Startup support9
- Enterprise Grade9
- In person support7
- Service Bus6
- Free for students6
- Virtual Machines6
- It rocks5
- Redis Cache5
- Storage, Backup, and Recovery4
- SQL Databases4
- Infrastructure Services4
- BizSpark 60k Azure Benefit3
- Built on Node.js3
- Preview Portal3
- Big Data3
- Active Directory2
- Big Compute2
- Machine Learning2
- Stream Analytics2
- Data Factory2
- Event Hubs2
- Virtual Network2
- Traffic Manager2
- Media Services2
- BizTalk Services2
- Site Recovery2
- Multi-Factor Authentication2
- Visual Studio Online2
- Application Insights2
- Operational Insights2
- Key Vault2
- Infrastructure near your customers2
- Easy Deployment2
- Best cloud platfrom1
- Easy and fast to start with1
- Remote Debugging1
- Open cloud1
- Enterprise customer preferences1
- Confusing UI6
- Expensive plesk on Azure2
related Microsoft Azure posts
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!
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.
- 1 year free trial credit USD3003
- Good app Marketplace for Beginner and Advanced User2
- Premium tier IP address2
- Live chat support1
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.
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.