Automating cross-platform data pipelines: a practical walkthrough

说明与用途

Polysync 通过集中身份验证、导入现有作业、设置依赖关系、映射参数、执行限流、调度根任务并提供统一监控视图，自动化跨平台数据管道，消除手动协调。

问题

Teams struggle to coordinate data pipelines across multiple cloud platforms because each platform runs on its own schedule, leading to uncertainty about task completion and failures.

结果

Polysync automates cross-cloud data pipelines by centralizing authentication, importing existing jobs, wiring dependencies, mapping parameters, enforcing governance limits, scheduling roots, and providing a unified monitoring view, eliminating manual coordination and uncertainty.

工作流

• Connect each platform and authenticate via Polysync Service Principal or platform credentials
• Discover existing jobs and import them as Jobs
• Wire dependencies using trigger conditions (On Success, On Failure, On Completion, On Skipped)
• Map outputs of one task to inputs of another across platforms
• Apply concurrency and rate limits via profiles to govern queue execution
• Schedule root tasks with cron expressions
• Monitor the unified pipeline view in Polysync

证据

The pain shows up between them: the pipeline that finishes in the morning, the job that should follow it but instead runs on a fixed schedule and hopes the other one is done

来源

Polysync connects to more than 20 services across Azure, AWS and Google Cloud, including Azure Data Factory, Microsoft Fabric, Synapse Pipelines, Databricks and Power BI, AWS Glue and Step Functions, and Google Cloud Composer, Dataflow and Vertex AI.

来源

Each edge in the graph carries a trigger condition: On Success, On Failure, On Completion, On Skipped.

来源