In this post, we will discuss how to deploy a Spring Boot application on three popular cloud platforms – AWS, GCP, and Azure. We will also compare and contrast their containerization services.
Sure, here is a comparison table for the containerization services provided by AWS, GCP, and Azure:
| Criteria | AWS | GCP | Azure |
|---|---|---|---|
| Service Name | Amazon Elastic Container Service (ECS), Amazon Elastic Kubernetes Service (EKS) | Google Kubernetes Engine (GKE) | Azure Kubernetes Service (AKS) |
| Kubernetes Support | EKS | GKE | AKS |
| Docker Support | Yes | Yes | Yes |
| Scaling | Auto Scaling groups, Fargate | Kubernetes-native autoscaling | Kubernetes-native autoscaling, Azure Container Instances |
| Networking | VPC, Route 53, API Gateway | VPC, Cloud DNS, Cloud Load Balancing | VNet, Azure DNS, Application Gateway |
| Load Balancing | Application Load Balancer, Network Load Balancer | Inbuilt load balancing | Azure Load Balancer, Azure Traffic Manager |
| Integrated developer tools | AWS CodeBuild, AWS CodeDeploy, AWS CodePipeline | Cloud Source Repositories, Cloud Build | Azure DevOps |
| Storage services | EBS, EFS, S3 | Persistent Disk, Cloud Storage | Azure Disk, Azure File, Azure Blob Storage |
| Security and Access Control | IAM, Security Groups, VPC | IAM, Network Policies, VPC | Azure AD, Azure RBAC, Network Policies |
| Compliance Certifications | Extensive list including HIPAA, GDPR, SOC | Extensive list including HIPAA, GDPR, SOC | Extensive list including HIPAA, GDPR, SOC |
| Pricing | Pay as you go, Savings Plans, Spot instances | Pay as you go, committed use contracts | Pay as you go, Azure Cost Management |
| Integrated CI/CD support | AWS CodePipeline | Google Cloud Build | Azure Pipelines |
| Service mesh integration | AWS App Mesh | Istio, Anthos Service Mesh | Azure Service Fabric, Azure Logic Apps |
Table of Contents
Prerequisites
- A Spring Boot application ready for deployment.
- AWS, GCP, and Azure accounts.
- Basic knowledge of cloud deployment.
Deploying on AWS using Elastic Beanstalk
AWS Elastic Beanstalk supports the deployment of applications as containerized applications, using Docker, or directly in a Java runtime environment.
- Go to the AWS Elastic Beanstalk console and create a new application.
- Choose ‘Web server environment’.
- For ‘Platform’, choose ‘Java’ and upload your Spring Boot JAR file.
- Choose ‘Create environment’. AWS Elastic Beanstalk will take care of the rest, from setting up an EC2 instance to starting your application.
Deploying on GCP using App Engine
Google Cloud’s App Engine is a fully managed, serverless platform for developing and hosting web applications at scale.
- In the Google Cloud Console, go to the ‘App Engine’ section and create a new application.
- Choose a region for your application and then select ‘Java’ as the runtime.
- Upload your Spring Boot JAR file and choose ‘Deploy’. GCP will handle the rest, from creating a new instance to launching your application.
Deploying on Azure using App Service
Azure App Service is a fully managed platform for building, deploying, and scaling your web apps.
- Go to the Azure portal and create a new ‘App Service’.
- In the ‘Runtime stack’ dropdown, select ‘Java 8’ or ‘Java 11’.
- Upload your Spring Boot JAR file and choose ‘Review + create’.
- After review, click ‘Create’. Azure will handle the rest, from provisioning a server to starting your application.
Comparing AWS, GCP, and Azure Containerization Services
When it comes to containerization services, each of the three major cloud platforms offers robust and feature-rich solutions. However, there are some notable differences among AWS’s ECS & EKS, GCP’s GKE, and Azure’s AKS.
AWS provides two containerization services: Elastic Container Service (ECS) and Elastic Kubernetes Service (EKS). ECS is a highly scalable, fast container management service that makes it easy to run, stop, and manage Docker containers on a cluster. On the other hand, EKS is a managed service that makes it easy for you to run Kubernetes on AWS without needing to install and operate your own Kubernetes control plane or worker nodes.
Google Cloud Platform (GCP) offers Google Kubernetes Engine (GKE), a managed environment for deploying, managing, and scaling your containerized applications using Google infrastructure. GKE’s selling point is its deep integration with Google’s infrastructure, tooling, and ecosystem. If your application already relies heavily on Google’s other cloud services, GKE might be a natural fit.
Azure Kubernetes Service (AKS) is Azure’s dedicated Kubernetes service. Like EKS and GKE, AKS is a fully managed service, providing automated Kubernetes version upgrades and patching. It also integrates well with the Azure DevOps ecosystem, making it a great choice for teams already working with Microsoft’s suite of development tools.
In terms of performance, all three platforms offer similar capabilities, including auto-scaling, load balancing, and rolling updates. However, differences start to appear when you look at their respective ecosystems and integration points. GKE has an edge with its superior integration with Google’s other cloud services. AKS integrates seamlessly with Azure DevOps, and AWS’s ECS and EKS shine when it comes to integration with other AWS services like IAM for security, CloudWatch for logging, and Elastic Load Balancer for traffic distribution.
Pricing models vary among the three platforms. AWS charges for the EC2 instances and other services you use alongside ECS and EKS, but there’s no additional charge for ECS itself. EKS, however, comes with a flat fee per cluster per hour. GCP charges for GKE based on the compute engine resources used, including a per-cluster management fee. Azure’s AKS does not charge for the Kubernetes management infrastructure, but you pay for the virtual machines, storage, and networking resources consumed.
Security is a top priority across all platforms. AWS’s IAM offers finely grained access control, while GCP and Azure leverage their respective Cloud IAM and Azure Active Directory services. All three providers offer compliance certifications and support for private networking and storage encryption.
In terms of usability, AWS can be complex due to its wide range of options and features. GCP offers a more streamlined experience, particularly for those already familiar with Google’s cloud services. Azure is praised for its user-friendly interface, which is particularly appealing to teams already familiar with Microsoft’s ecosystem.
In conclusion, your choice between AWS, GCP, and Azure for containerization services will depend on various factors, including your specific use case, the cloud ecosystem you’re most invested in, pricing, and personal preference. All three providers offer robust, secure, and scalable solutions for running containerized applications.