Ddosify is a comprehensive performance testing platform, designed specifically to evaluate backend load and latency. It offers three distinct deployment options to cater to various needs: Ddosify Engine, Ddosify Self-Hosted, and Ddosify Cloud.

Ddosify is a magic wand that instantly spots glitches and guarantees the smooth performance of your infrastructure and application while saving you time and money. Ddosify Platform includes Performance Testing and Kubernetes Observability capabilities.

Hello Everyone ✋ I'm excited to introduce a new open-source observability platform and would love to hear your feedback. Ddosify is a magic wand that instantly spots glitches and guarantees the smooth performance of your infrastructure and application while saving you time and money. Ddosify Platform includes Performance Testing and Kubernetes Observability capabilities. It uniquely integrates these two parts and effortlessly spots the performance issues. We are aware that there are lots of open-source/commercial tools out there. However, we believe that monitoring the clusters and extracting actionable insights requires deep know-how about the tools/domain. We mainly focused on this problem. 🐝 Our eBPF agent is installed on your K8S cluster as DaemonSet. Thanks to eBPF - our agent collects traces directly from Linux kernels. This means there's no need for sidecars, instrumentations, or service restarts. 🎯 The UI not only visualizes data but also provides actionable insights. Using the Service Map, you can: - View latencies and RPS between services. - Detect zombie services and underperforming SQL queries. - Monitor golden signals, such as 5xx status codes. In addition, Alaz(our eBPF agent) can capture system resources like CPU, Memory, Disk, and Network through the Prometheus Node Exporter, which is embedded in the agent. 🚀 Setting up is straightforward: just install Alaz as a DaemonSet, and the platform will handle the rest. Finally, the combination of Alaz and Ddosify Performance Testing makes it possible to do load testing and simultaneously monitor the system to find bottlenecks instantly. Your feedback would be greatly appreciated! 🙏