AWS EC2 Instance info for my use case.

Based on your use case involving Kafka and Spark pipelines for stream and batch processing along with Lambda and DynamoDB, you'll need to consider an EC2 instance that can handle compute and memory requirements effectively.

Since you're currently on the free tier, you should be aware of what's available to you without incurring charges. If your AWS account is less than 12 months old and was created before July 15, 2025, you can use a t2.micro instance for free (or t3.micro in regions where t2.micro isn't available). If your account was created on or after July 15, 2025, you have access to t3.micro, t3.small, t4g.micro, t4g.small, c7i-flex.large, and m7i-flex.large instance types for 6 months or until your credits are used up.

However, for a Kafka and Spark workload, these free tier instances may be underpowered, especially for production use. Once you move beyond the free tier, consider:

1. For compute-intensive workloads like Spark processing: Compute-optimized instances would be appropriate.

2. For memory-intensive operations: Memory-optimized instances would be better suited.

3. For cost efficiency: AWS Graviton-based instances deliver up to 40% better price performance than comparable non-Graviton instances.

4. For flexibility: EC2 Flex instances are good for applications that don't fully utilize all compute resources and can provide up to 19% better price performance.

To find the optimal instance type for your specific workload, you can use tools like Amazon Q EC2 instance type selector, Instance Type Explorer, or EC2 Instance Discovery.

As your workload grows, consider implementing Amazon EC2 Auto Scaling to automatically adjust capacity based on demand, which will help optimize costs while maintaining performance.
Sources
features
Launch an Amazon EC2 instance - Amazon Elastic Compute Cloud
Amazon EC2 Cost and Capacity Optimization | Amazon Web Services