Incident Response Optimization
A Seriously Smart Upgrade.
Prevent, detect and resolve incidents faster than ever before. No matter what your data stack throws at you, your data quality will reach new levels of performance.

No More Over Reacting
Sifflet takes you from reactive to proactive, with real-time detection and alerts that help you to catch data disruptions, before they happen. Watch your mean time to detection fall rapidly. On even the most complex data stacks.
- Advanced capabilities such as multidimensional monitoring help you seize complex data quality issues, even before breaks
- ML-based monitors shield your most business-critical data, so essential KPIs are protected and you get notified before there is business impact
- OOTB and customizable monitors give you comprehensive, end-to-end coverage and AI helps them get smarter as they go, reducing your reactivity even more.

Resolutions in Record Time
Get to the root cause of incidents and resolve them in record time.
- Quickly understand the scope and impact of an incident thanks to detailed system visibility
- Trace data flow through your system, identify the start point of issues, and pinpoint downstream dependencies to enable a seamless experience for business users, all thanks to data lineage
- Halt the propagation of data quality anomalies with Sifflet’s Flow Stopper


Frequently asked questions
Can I customize how alerts are routed to ServiceNow from Sifflet?
Absolutely! You can customize routing based on alert metadata like domain, severity, or affected system. This ensures the right team gets notified without any manual triage, making your data pipeline monitoring more actionable and reliable.
How does Sifflet enhance data lineage tracking for dbt projects?
Sifflet enriches your data lineage tracking by visually mapping out your dbt models and how they connect across different projects. This is especially useful for teams managing multiple dbt repositories, as Sifflet brings everything together into a clear, centralized lineage view that supports root cause analysis and proactive monitoring.
What exactly is the modern data stack, and why is it so popular now?
The modern data stack is a collection of cloud-native tools that help organizations transform raw data into actionable insights. It's popular because it simplifies data infrastructure, supports scalability, and enables faster, more accessible analytics across teams. With tools like Snowflake, dbt, and Airflow, teams can build robust pipelines while maintaining visibility through data observability platforms like Sifflet.
What challenges did Hypebeast face when transitioning to full-scale data observability?
One major challenge was shifting the company culture from being data-aware to truly data-driven. Technically, integrating new observability tools into existing infrastructures and managing the initial investment in time and resources also posed hurdles.
Why is using WHERE instead of HAVING so important for performance?
Using WHERE instead of HAVING when not working with GROUP BY clauses is crucial because WHERE filters data earlier in the query execution. This reduces the amount of data processed, which improves query speed and supports better metrics collection in your observability platform.
Can Sifflet integrate with our existing data tools and platforms?
Absolutely! Sifflet is designed to integrate seamlessly with your current stack. We support a wide range of tools including Airflow, Snowflake, AWS Glue, and more. Our goal is to provide complete pipeline orchestration visibility and data freshness checks, all from one intuitive interface.
How can I ensure SLA compliance during data integration?
To meet SLA compliance, it's crucial to monitor ingestion latency, data freshness checks, and throughput metrics. Implementing data observability dashboards can help you track these in real time and act quickly when something goes off track. Sifflet’s observability platform helps teams stay ahead of issues and meet their data SLAs confidently.
Why is collaboration important in building a successful observability platform?
Collaboration is key to building a robust observability platform. At Sifflet, our teams work cross-functionally to ensure every part of the platform, from data lineage tracking to real-time metrics collection, aligns with business goals. This teamwork helps us deliver a more comprehensive and user-friendly solution.