Orchestration, Observability, and Control Over the Hybrid Data Pipeline
Managing hybrid data pipelines is complex, often involving multiple schedulers and real-time data issues. See how an orchestration layer can enhance observability and simplify management.
Today’s data pipelines involve real-time movement, monitoring, and management of data and workloads across hybrid environments, including open-source and proprietary software platforms. It’s challenging to orchestrate hybrid data pipelines; you may be using a variety of schedulers, including those built into the platforms you monitor and control, as well as open-source, cloud, and legacy schedulers. It can be difficult for DataOps professionals to continually gather distributed log data, correlate alerts, and quickly perform root-cause analysis to keep data pipelines healthy.
Join James Kobielus, TDWI senior research director for data management, and Peter Baljet, Stonebranch CTO, as they explore best practices for simplifying orchestration, observability, and control over hybrid enterprise data pipelines. Then see Nils Buer, VP Solution Management, demonstrate Stonebranch’s offering. James, Peter, and Nils will discuss:
- What is a hybrid data pipeline?
- What challenges and pain points do enterprises face when automating orchestration of hybrid data pipelines?
- How are enterprises simplifying orchestration of their hybrid data pipelines and optimizing pipeline performance?
- What types of self-service tools do enterprises require to automate their hybrid data pipelines more effectively?
- What value does centralized observability provide?
- What is the future of enterprise data pipelines?
