My main use case for Apache SkyWalking is a project that started in 2023 for a retail client facing serious performance issues on their new distributed architecture on AWS. The technical criticality is clear. We have an observability black hole on a high-traffic payment flow where we cannot distinguish if latencies are caused by microservices on Amazon EKS or by calls to legacy on-premises databases. We chose Apache SkyWalking through the AWS Marketplace to integrate it immediately into the existing infrastructure with the goal of monitoring a massive environment consisting of over 80 microservices and about 600 active pods. This solution allows us to manage and analyze volumes in the order of 50 million traces per day, correlating every single end-to-end transaction in real time from front end to database and pinpointing bottlenecks that are invisible with traditional logging systems.
Find out what your peers are saying about Apache, SigNoz, Elastic and others in Application Performance Monitoring (APM) and Observability. Updated: January 2026.
Application Performance Monitoring (APM) and Observability help improve the efficiency of applications by providing visibility and insights into system performance.
Application Performance Monitoring and Observability involve tracking and analyzing the performance of applications and infrastructure. APM focuses on detecting and diagnosing performance issues, while Observability emphasizes gaining insight into the internal state of systems. By combining these approaches, IT teams can ensure...
My main use case for Apache SkyWalking is a project that started in 2023 for a retail client facing serious performance issues on their new distributed architecture on AWS. The technical criticality is clear. We have an observability black hole on a high-traffic payment flow where we cannot distinguish if latencies are caused by microservices on Amazon EKS or by calls to legacy on-premises databases. We chose Apache SkyWalking through the AWS Marketplace to integrate it immediately into the existing infrastructure with the goal of monitoring a massive environment consisting of over 80 microservices and about 600 active pods. This solution allows us to manage and analyze volumes in the order of 50 million traces per day, correlating every single end-to-end transaction in real time from front end to database and pinpointing bottlenecks that are invisible with traditional logging systems.