Instance Types

Python tasks in Datablast can be configured with different instance types to match your workload requirements.

Available Instance Types

Instance Type	CPU Limit	Memory Limit	CPU Request	Memory Request	Use Case
`d1.nano`	250m	512Mi	250m	256Mi	Lightweight tasks, testing (Default)
`d1.small`	500m	1200Mi	500m	1Gi	Small data processing
`d1.medium`	750m	2400Mi	750m	2Gi	Medium workloads
`d1.large`	1	4400Mi	1	4Gi	Large data processing
`d1.xlarge`	2	6600Mi	2	6Gi	Heavy workloads, ML training

Default Instance: d1.nano - No need to specify unless you need more resources.

⚠️ Important: Using instance types other than d1.nano may incur additional charges. Please consult with your Datablast representative for pricing details before upgrading instance types.

Configuration Examples

YAML Configuration

name: "ml_models.churn_prediction"
type: "python"
description: "Generate churn predictions using trained model"
run: "churn_prediction.py"
instance: "d1.large"  # Specify instance type

Annotation-based Configuration

# @blast.type: python
# @blast.description: Generate churn predictions using trained model
# @blast.instance: d1.large

import os
import pandas as pd
import numpy as np

# Your Python logic here
execution_date = os.getenv('BLAST_START_DATE')
result = process_data(execution_date)
print(f"Successfully processed data for {execution_date}")

Instance Type Selection

Lightweight Tasks (`d1.nano`)

name: "data.validation"
type: "python"
instance: "d1.nano"  # Default, can be omitted
run: "validate_data.py"

Small Data Processing (`d1.small`)

name: "data.aggregation"
type: "python"
instance: "d1.small"
run: "aggregate_data.py"

Medium Workloads (`d1.medium`)

name: "data.transformation"
type: "python"
instance: "d1.medium"
run: "transform_data.py"

Large Data Processing (`d1.large`)

name: "ml.model_training"
type: "python"
instance: "d1.large"
run: "train_model.py"

Heavy Workloads (`d1.xlarge`)

name: "ml.deep_learning"
type: "python"
instance: "d1.xlarge"
run: "train_deep_model.py"

Configuration Parameters

Required Fields

name: Unique task identifier
type: Must be python
run: Python file to execute

Optional Fields

description: Human-readable description
instance: Instance type (defaults to d1.nano)
depends: Task dependencies
secrets: Secret management
connections: Database connections

Python Development Guide - Best practices and advanced features
Python Task Overview
Environment Variables
Dependencies