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Resource-Aware Big Data Workflow Orchestration and Optimization Using AWS Serverless Services

Resource-Aware

Resource-Aware Big Data Workflow Orchestration and Optimization Using AWS

  • Use Case: Optimizing complex big data workflows in cloud environments where tasks have varying resource requirements. Use case examples include ETL pipelines, IoT analytics, genomics data processing, and financial data workflows, where efficient scheduling reduces execution time and cost.

Objective

  • Design a resource-aware workflow orchestration system that dynamically optimizes task execution in big data pipelines.

    Reduce execution latency, cost, and resource wastage in serverless/cloud environments.

    Automate dependency management, error handling, and workflow scaling using AWS services.

Project Description

  • This project proposes a serverless workflow optimization framework for big data applications using AWS Step Functions and AWS Lambda.Each workflow consists of multiple tasks (e.g., ETL jobs, ML model training, data transformation) with heterogeneous resource requirements.

    The system monitors resource usage metrics and dynamically allocates compute power using AWS Lambda for lightweight processing and triggers other services for heavy workloads.Step Functions orchestrate the workflow sequence, retries, and parallel execution, while the system scales automatically based on workload.Logs and performance metrics are tracked via CloudWatch, and workflow artifacts are stored in S3 for reproducibility and auditing.

    The approach ensures optimized execution, cost efficiency, and robust error handling for complex big data workflows in the cloud.
    • Key Technologies & AWS Services :
    Category AWS Service / Technology Purpose
    Workflow Orchestration AWS Step Functions Orchestrate, sequence, and manage big data tasks in the workflow.
    Serverless Compute AWS Lambda Execute lightweight or compute-bound tasks in a scalable, on-demand manner.
    Storage Amazon S3 Store intermediate datasets, logs, and workflow artifacts.
    Monitoring Amazon CloudWatch Monitor execution metrics, resource usage, and workflow health.
    Security & Access AWS IAM Manage access control and secure interactions between services.
    Notification Amazon SNS / EventBridge Trigger alerts or downstream processes on workflow events.
    Optimization Custom Resource-Aware Scheduler + Lambda Dynamically optimize task execution based on resource consumption patterns.