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Frequently asked questions
Is Sifflet available for VPC deployment on Google Cloud?
Yes it is! You can deploy Sifflet’s observability platform within your own private Google Cloud environment using VPC deployment, giving you full control over data governance and security.
How can I monitor the health of my ETL or ELT pipelines?
Monitoring pipeline health is essential for maintaining data reliability. You can use tools that offer data pipeline monitoring features such as real-time metrics, ingestion latency tracking, and pipeline error alerting. Sifflet’s pipeline health dashboard gives you full visibility into your ETL and ELT processes, helping you catch issues early and keep your data flowing smoothly.
What is the Universal Connector that Sifflet introduced in 2024?
The Universal Connector is one of our most exciting 2024 releases. It enables seamless integration across the entire data lifecycle, helping users achieve complete visibility with end-to-end data observability. This means fewer blind spots and a much more holistic view of your data ecosystem.
Can I see how a business metric is calculated in Sifflet?
Absolutely! With Sifflet’s data lineage tracking, users can view the full column-level lineage from ingestion to consumption. This transparency helps users understand how each metric is computed and how it relates to other data or metrics in the pipeline.
Why is data quality monitoring crucial for AI-readiness, according to Dailymotion’s journey?
Dailymotion emphasized that high-quality, well-documented, and observable data is essential for AI readiness. Data quality monitoring ensures that AI systems are trained on accurate and reliable inputs, which is critical for producing trustworthy outcomes.
How does Sifflet enhance Apache Airflow for data teams?
Sifflet's integration with Apache Airflow brings powerful data observability features directly into your orchestration workflows. It helps data teams monitor DAG run statuses, understand downstream dependencies, and apply data quality monitoring to catch issues early, ensuring data reliability across the stack.
Is Sifflet suitable for large, distributed data environments?
Absolutely! Sifflet was built with scalability in mind. Whether you're working with batch data observability or streaming data monitoring, our platform supports distributed systems observability and is designed to grow with multi-team, multi-region organizations.
Is there a networking opportunity with the Sifflet team at Big Data Paris?
Yes, we’re hosting an exclusive after-party at our booth on October 15! Come join us for great conversations, a champagne toast, and a chance to connect with data leaders who care about data governance, pipeline health, and building resilient systems.













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