APITable AWS Kubernetes Deployment Infrastructure Requirements
In this documentation, we will discuss the infrastructure requirements for deploying Kubernetes APITable on AWS using EKS.
You may need to provision the following AWS resources initially to deploy your APITable Enterprise edition for Kubernetes:
For Scalable Production
AWS Resource | Configuration | Quantity |
|---|---|---|
Amazon EKS | Fully managed Kubernetes service for deploying, managing, and scaling containerized applications using Kubernetes. | 1 |
Amazon EC2 | r5.2xlarge instance type with 8 vCPUs, 64 GiB RAM, 200G Storage, and EBS-optimized instances for creating EC2 instances that run your Kubernetes nodes. | 2 up |
Amazon RDS for MySQL | r5.2xlarge instance type with 8 vCPUs, 64 GiB RAM, and 100 GB of storage for storing data with enterprise features such as encryption, backup and restore, and high availability. | 1 |
Amazon ElastiCache for Redis | cache.t4g.medium node type with 2 vCPUs, 3.09 GiB RAM, for storing and managing Redis cache. | 1 |
Amazon Elastic Load Balancer (ELB) | Classic Load Balancer for automatically distributing incoming application traffic across multiple targets, such as EC2 instances, for load balancing traffic. | 1 |
Amazon CloudWatch | Monitoring and observability service for providing metrics, logs, and traces for your AWS resources and applications. | 1 |
For Development Environment
Amazon EC2 | t3.2xlarge instance type with 8 vCPUs, 32 GiB RAM, 200G Storage, and EBS-optimized instances for creating EC2 instances that run your Kubernetes nodes. | 1 |
Amazon RDS for MySQL | t3.2xlarge instance type with 8 vCPUs, 32 GiB RAM, and 100 GB of storage for storing data with enterprise features such as encryption, backup and restore, and high availability. | 1 |
Yes, it's important to note that the resources listed above are estimates and may not be suitable for all use cases.
The exact resources needed for your APITable Enterprise edition will depend on factors such as the size and complexity of your application, the amount of traffic it receives, and the level of redundancy and fault tolerance required.
You may need to adjust the quantity or type of resources based on your specific requirements.
For example, you may need more EC2 instances to handle a higher volume of traffic, or you may need to use larger instance types for improved performance.
It's recommended to start with the estimated resources listed above and monitor the performance and utilization of your resources over time.
You can use AWS CloudWatch to monitor your resources and identify any bottlenecks or areas for optimization.
We can also use AWS Auto Scaling to automatically adjust the number of resources based on demand. This can help ensure that your APITable solution is always available and can handle fluctuating traffic.
Overall, it's important to carefully plan and monitor your resources to ensure that your APITable Enterprise edition is scalable, reliable, and cost-effective.