Site Reliability Engineer 2 at a tech vendor with 1,001-5,000 employees
Real User
Top 5
Feb 19, 2026
Regarding improvements to Insights Hub, I have identified several areas. The first improvement would be smarter AI with clear root cause suggestions. Currently, AI detects anomalies but often only says "unusual increase in failures detected" without clearly stating what changed, which deployment caused it, or what likely component is responsible. Improvements could include automatic correlation with recent deployments, suggested probable root causes such as code changes, infrastructure scale events, or database latency, and a confidence score. This would reduce investigation time even more. The second improvement would be better noise reduction in alerts. Sometimes anomaly detection generates too many notifications and minor fluctuations are treated as incidents. Improvements could include smarter alert grouping, better baseline tuning, and business impact aware alerting, where alerts are not triggered if latency increased but there is no user impact. The third improvement is stronger cross-cloud and hybrid visibility. Many organizations use Azure, AWS, and on-premises infrastructure. Insights Hub could improve multi-cloud correlations and unified dashboards across environments. Currently, cross-platform visibility often requires custom integrations.
Insights Hub is a robust platform for data management and analytics, designed to assist businesses in making informed decisions. It provides comprehensive tools that enable users to leverage data effectively, enhancing their ability to streamline and optimize processes.Insights Hub caters to a variety of industries by offering scalable solutions tailored to specific needs. The platform enables users to integrate and analyze large sets of data seamlessly, providing clarity and actionable...
Insights Hub has a connection with Grafana, but I would like it to be improved.
Regarding improvements to Insights Hub, I have identified several areas. The first improvement would be smarter AI with clear root cause suggestions. Currently, AI detects anomalies but often only says "unusual increase in failures detected" without clearly stating what changed, which deployment caused it, or what likely component is responsible. Improvements could include automatic correlation with recent deployments, suggested probable root causes such as code changes, infrastructure scale events, or database latency, and a confidence score. This would reduce investigation time even more. The second improvement would be better noise reduction in alerts. Sometimes anomaly detection generates too many notifications and minor fluctuations are treated as incidents. Improvements could include smarter alert grouping, better baseline tuning, and business impact aware alerting, where alerts are not triggered if latency increased but there is no user impact. The third improvement is stronger cross-cloud and hybrid visibility. Many organizations use Azure, AWS, and on-premises infrastructure. Insights Hub could improve multi-cloud correlations and unified dashboards across environments. Currently, cross-platform visibility often requires custom integrations.