[Feat/UI]: Build a Low-Overhead SVG Sparkline Chart Element mapping Checkpoint Cache Saturation

Problem

Displaying high-frequency telemetry statistics (such as stateless session checkpoints update velocity parameters) via static numerical variables limits macro infrastructure performance visibility under scaling surges.

Proposed Solution

Build a lightweight, multi-threaded SVG Sparkline Vector Graph inside /dashboard/components/charts/MetricsSparkline.tsx.

• Map incoming streaming telemetry metrics points dynamically onto continuous SVG path vector arrays strings (stroke-dasharray animation tracks).
• Add a subtle flowing glowing tail gradient mask underneath the path layout coordinates to trace data ingestion throughput speeds fluidly.
• Execute metric arrays updates using lock-free polling vectors loops to protect baseline page loading velocity indexes during extreme stress tests blocks execution.

Alternatives

• Importing heavy external canvas tracking packages or charting bundles, which inflates repository footprints and drops contributor onboarding speed scales.

Use Case

Delivers highly attractive, professional terminal-tier data visualizations fields to observe distributed proxy stability metrics without touching backend system tracks.

Additional Notes

Drop a comment below to work on this, and we will assign the tracking node to you within minutes!

Start by reading /dashboard/components/charts/MetricsSparkline.tsx and identify how streaming telemetry points are passed into the component. Define the expected SVG path, animation, and tail-gradient behavior before implementation. Done means the component renders continuously updated checkpoint cache saturation data without adding an external charting package.