[Feat/Infra]: Build a Lock-Free Ring Buffer Memory Allocator inside internal/storage/ using sync/atomic Flags

Problem

High-frequency logging setups and scraping metrics collectors perform dynamic allocation routines during rapid parallel loops. Locking structural counters during parallel scrape windows triggers tracking jitter and minor data leaks inside telemetry nodes.

Proposed Solution

Refactor the metric pipeline tracking layers in internal/telemetry/collector.go to run on top of an independent Vectorized Lock-Free Metrics Collector Layer.

• Store operational event counters using fixed arrays of primitive 64-bit integer values mapped explicitly to individual telemetry dimensions.
• Update tracking counters exclusively utilizing low-overhead atomic addition routines (atomic.AddInt64).
• Stream compiled tracking data segments down to Prometheus text scrapers utilizing optimized multi-buffer vector writers (unix.Writev) to maximize disk I/O throughput.

Alternatives

• Utilizing standard Prometheus telemetry libraries, which provide convenient abstraction APIs but introduce object allocation loops inside critical hot routing connection pipelines.

Use Case

Maintains flawless system-wide observability statistics visibility under intense stress workloads without introducing a single byte of memory heap allocation overhead.

Additional Notes

Expose these optimized telemetry output channels cleanly alongside standard dashboards definitions mapped within deployments configs.

Start with internal/telemetry/collector.go and trace how metric pipeline tracking currently works, then review the proposed sync/atomic counters and unix.Writev output path. Done means the requested lock-free telemetry layer, optimized Prometheus output channels, and deployment dashboard definitions are implemented without heap allocation in the stated hot paths.