Cloud, DevOps, Engineering, and Site Reliability leaders at companies relying on Splunk, Datadog, or New Relic continuously encounter cost dilemmas, resorting to log filtration and shorter retention periods. Similarly, organizations utilizing CloudWatch, ELK for logs, and Prometheus for metrics face limitations managing an open-source stack, hindering agile product development and innovation. The incessant changes in microservices, constantly integrating new code into production, escalate challenges and complexities, overwhelming traditional tools with vast telemetry data from modern distributed applications. This slows down incident response times, leading to prolonged Mean Time to Resolution (MTTR) durations.

Efficient observability unlocks a treasure trove of advantages for your business. Rapid incident resolution empowers engineers to focus on enhancing customer experiences through innovative features. Moreover, it shields your engineering teams from late-night disruptions, fostering greater job satisfaction and curbing attrition rates. This streamlined system not only reduces conflicts during incident escalations but also trims down time and financial investments, fostering a more contented work environment.

Our approach revolutionizes data management by eradicating log, metric, and trace silos, consolidating all data within a unified Data Lake. Leveraging cost-efficient cloud storage, it slashes expenses by tenfold while ensuring human-readable and easily navigable data through a comprehensive Data Graph. This contextualization accelerates investigations by tripling the speed of accessing pertinent information. Our strategy empowers users, ensuring productivity within their initial five minutes through intuitive Data Apps. Moreover, it offers pre-configured observability tailored for prevalent environments like K8s or AWS and integrates GPT across every phase, delivering AI-backed assistance at every turn.