When deploying a data stack, selecting the right instance size is a critical step to ensure your tools run efficiently while optimizing costs. At Visionarist, we’ve simplified the process by offering machine sizes that can scale based on your workload. In this guide, we'll walk you through how to choose the best instance size for your needs and provide practical advice for scaling as your business grows.

Understanding instance sizes

We designed our instance sizes to simplify the process of selecting the right machine, offering a range from XS to XL. These sizes are based on the maximum number of nodes you can run for each size, making it easy to scale as needed.

• XS: Ideal for small projects or testing environments. Suitable for teams with lightweight data pipelines.
  • Min nodes: 1
  • Max nodes: 2

Minimal usage:

• S: Great for mid-size projects with moderate data processing needs.
  • Min nodes: 1
  • Max nodes: 5
• M: Perfect for teams running more complex workflows, including larger pipelines and more data transformation.
  • Min nodes: 2
  • Max nodes: 6
• L: Suited for large-scale operations or companies with intensive data workloads.
  • Min nodes: 3
  • Max nodes: 10
• XL: For enterprise-grade applications or teams handling massive amounts of data.
  • Min nodes: 6
  • Max nodes: 20

Each size allows for a minimum of nodes and scales up depending on your specific needs.

Step-by-step guide to choosing your instance size

Choosing the right instance size depends on three main factors: workload complexity, scalability, and cost. Here’s how to decide which size is best for your project:

1. Assess your workload

Start by evaluating the complexity of your data stack:

• How much data will you be processing daily?
• Are your pipelines simple (e.g., data ingestion and storage) or complex (e.g., real-time data transformation, AI workloads)?