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.
As an expert in cloud computing and infrastructure optimization, I've had extensive experience working with various cloud service providers (CSPs) and helping organizations make informed decisions about their cloud strategy. My background involves hands-on implementation of cloud-native solutions, and I've successfully guided teams through the challenges of selecting the right infrastructure for their applications.
Now, delving into the concepts mentioned in the article about CodeFactor's choice of a cloud hosting provider:
1. CodeFactor as a #SAAS Product: CodeFactor.io is positioned as a Software as a Service (SAAS) product, emphasizing a focus on delivering a code review service for software developers. This implies a need for a robust and scalable cloud infrastructure to support the service's automation, code analysis, and frictionless user experience.
2. Cloud-Native Infrastructure: The article underscores CodeFactor's commitment to a cloud-native infrastructure. This aligns with the contemporary trend of designing and running applications that fully leverage the advantages of cloud environments, emphasizing factors like scalability, resilience, and ease of deployment.
3. Selection Criteria for Cloud Hosting Provider: CodeFactor sought a cloud-hosting provider that met specific criteria, including reliability, cost-effectiveness, and efficiency. The key requirements for their product were agility, instant provisioning, autoscaling, security, availability, and compliance management features.
4. Top Three #IAAS Providers: The article highlights the evaluation of three major Infrastructure as a Service (IAAS) providers: Amazon EC2, Microsoft Azure, and Google Compute Engine (GCP). These platforms are recognized for their dominance in the market and their ability to offer a wide range of services.
5. AWS, Azure, and GCP Comparison:
- AWS (Amazon EC2): Positioned as the oldest and most extensive provider with a massive scale, offering a variety of services and tools.
- Azure (Microsoft Azure): Stands out for integration with Microsoft technologies like .NET and Visual Studio, with a strong emphasis on support for .NET code.
- GCP (Google Compute Engine): Recognized for robust containerization services, particularly its investments in Kubernetes, making it stand out in the containerization space.
6. Containerization Services and Kubernetes: GCP is noted for having the most robust offering in Docker containerization services, primarily due to its investments in Kubernetes. This indicates a preference for containerized deployments and orchestration for CodeFactor's infrastructure.
7. Serverless Computing and Machine Learning Tools: All three providers offer serverless computing (AWS Lambda, Azure Functions, and Google Cloud Functions) and machine learning tools. GCP is highlighted as the most developer-friendly, intuitive, and complete in terms of machine learning and AI capabilities.
8. Pricing Considerations: Pricing played a crucial role in the decision-making process. AWS was identified as the most expensive, GCP as the least expensive, and Azure falling in the middle. Additionally, the article notes differences in billing models, with Azure and GCP offering per-minute billing for autoscaling, contrasting with AWS's per-hour billing.
9. Startup Programs and Financial Incentives: CodeFactor applied for startup programs with all three providers, emphasizing Azure's standout performance in terms of financial incentives. While AWS and GCP could cover about one year of infrastructure costs, Azure's sponsorship could cover approximately two years, showcasing a significant advantage.
10. Platform Agnosticism and Flexibility: The article concludes with the recognition that IAAS offerings with AWS, Azure, and GCP are evolving rapidly. CodeFactor aims to be platform agnostic where practical, retaining the flexibility to select the best products across providers based on evolving requirements.
In summary, CodeFactor's decision-making process involved a thorough analysis of technical capabilities, pricing structures, financial incentives, and the perceived level of partnership and support offered by each cloud provider. The final choice leaned towards GCP, driven by its strengths in containerization, automation toolset, DevOps mindset, and competitive pricing. However, Azure's financial incentives and strong support ultimately influenced the decision, emphasizing the dynamic nature of the cloud computing landscape and the importance of considering various factors in the decision-making process.
