[Feat/UI]: Implement Real-Time Kernel Event and Hardware Register Mapping inside the Operations Dashboard Engine

Problem

Standard infrastructure performance observability dashboards and logging aggregation platforms (such as generic Grafana charts or standard DataDog agent monitoring metrics setups) are engineered around user-space data collection routines. They poll application endpoints at discrete intervals to display macro system traits but fail to deliver absolute visibility into low-level infrastructure properties inside the hot routing loop.

When optimizing sub-2ms failure masking, systems operators cannot trace transient kernel-level events—such as eBPF map memory pollution statistics, AVX-512 execution instruction registers saturation levels, or hardware-level PCIe bus cache-line false sharing locks—introducing blindspots that mask real infrastructure degradation markers.

Proposed Solution

Develop an advanced, low-overhead hardware-layer visual metrics telemetry pipeline within a dedicated console directory internal/telemetry/ui/.

• Build native background collection hooks that read diagnostics data points directly from compiled kernel space eBPF ring buffers (BPF_MAP_TYPE_RINGBUF) and hardware performance tracking counters.
• Expose specialized dashboard analytics components engineered to visualize: PCIe DMA direct memory channel transfer bandwidth velocities, AVX-512 parallel instruction vector execution efficiencies, and eBPF sockmap connection redirection latency down to precise nanosecond metrics fields.
• Execute the metrics aggregation thread loops asynchronously using low-overhead lock-free sync/atomic counters to prevent the data scraping operations from introducing a single byte of memory heap allocation inside the gateway routing plane.

Alternatives

• Deploying a standard third-party software exporter package inside critical paths, which injects noticeable allocation overhead loops and introduces garbage collection spikes that corrupt real benchmark values.

Use Case

Delivers complete system observability diagnostics transparency to enterprise cluster administrators, providing verifiable visual proof of kernel-level runtime optimizations and establishing absolute operational authority over traditional passive log tools.

Additional Notes

Ensure all telemetry dashboard asset configurations map natively within local Docker Compose installation manifests to preserve easy open-source contributor onboarding.

Begin by inspecting the dedicated console directory internal/telemetry/ui/ and the local Docker Compose installation manifests, which are the only project locations named. Establish the required kernel, hardware-counter, dashboard, and allocation constraints before attempting implementation; done means the proposed telemetry values are collected and visualized without disrupting the routing plane.