Numerous open-source projects develop software-defined data planes targeting network use cases such as Discrete Appliances, Cloud Infrastructure, Virtual Network Functions and now also Cloud-Native deployments. These may be based on foundation toolkits such DPDK, eBPF/XDP, Snabb and so on, and may implement a diverse range of network functions, applied in many combinations and on different compute platforms and devices. The need for a consistent and repeatable, use-case driven performance validation and benchmarking approach has never been greater. Enabling both the development community and the end-user to understand, measure and verify expected performance. Achieving great performance with Network Software, should not be accidental, it should be data-driven! This talk explains how the FD.io CSIT project aims to meet this need by developing and providing Continuous Performance Lab platform for benchmarking, validation, performance trending and regression detection. Founded on multi-vendor collaboration, CSIT leverages deep multi-platform understanding and telemetry tools to analyze and correlate benchmarking results leading to consistent, repeatable and reliable performance validation the FD.io user base can rely on. This talk will cover A brief overview of FD.io CSIT Recent FD.io VPP release performance data is presented and discussed in this context. Recent CSIT Community Innovations Performance Trending graphs, MLRSearch and PMU Tooling are presented. Debugging a real system setup issue with FD.io CSIT is also covered