Great question! With our new ServiceNow integration, Sifflet can automatically create incidents from any data alert, helping your team respond faster and stay on top of critical issues. It's a big win for incident response automation and keeps your data observability workflows smooth and efficient.

Traditional monitoring often relies on batch processing, leading to delays in inventory updates. It also struggles with data silos, lacks robust data quality monitoring, and is mostly reactive. In contrast, modern observability tools provide real-time insights, dynamic thresholding, and predictive analytics monitoring to keep up with fast-paced retail environments.

Great question! At Sifflet, we believe data observability is about operationalizing trust, not just catching issues. It’s the foundation for reliable data pipelines, helping teams ensure data quality, track lineage, and resolve incidents quickly so business decisions are always based on trustworthy data.

The 'right to be forgotten' introduces several technical hurdles. For example, deleting user data across multiple systems, backups, and caches can be tricky. That's where data lineage tracking and pipeline orchestration visibility come in handy. They help you understand dependencies and ensure deletions are complete and safe without breaking downstream processes.

Absolutely! With Sifflet's observability platform, you can view the health status of your Firebolt tables in real time. This allows for proactive data pipeline monitoring and helps ensure SLA compliance across your analytics workflows.

If your team already uses ServiceNow for incident management, having your data alerts show up there means fewer missed issues and faster resolution times. It brings transparency to your data pipelines and supports better data governance and trust.

Data observability is crucial no matter which integration method you use. With ETL or ELT, you're moving and transforming data across multiple systems, which can introduce errors or delays. An observability platform like Sifflet helps you track data freshness, detect anomalies, and ensure SLA compliance across your pipelines. This means fewer surprises, faster root cause analysis, and more reliable data for your business teams.

Yes! Sifflet now offers an officially-supported Terraform provider that allows you to manage your observability setup as code. This includes configuring monitors and other Sifflet objects, which helps enforce data contracts, improve reproducibility, and strengthen data governance.