removes memory overhead metrics

Signed-off-by: Roshan Khatri <rvkhatri@amazon.com>

Author: roshkhatri

_data/perf.toml

@@ -9,7 +9,7 @@
 
 [[dashboards]]
 title = "Valkey Performance Dashboards"
-description = "Valkey Performance Dashboards provide a consolidated view of throughput and memory efficiency trends across versions, helping teams validate improvements and identify regressions."
+description = "Valkey Performance Dashboards provide a consolidated view of throughput trends across versions, helping teams validate improvements and identify regressions."
 link = "/performance/"
 
 # Performance dashboard sections for /performance page
@@ -20,9 +20,3 @@ title = "Throughput Across Versions"
 iframe_url = "https://perf-dashboard.valkey.io/public-dashboards/38ad683dbd06456c829b547d97e2b7da"
 description = "This dashboard visualizes throughput trends across Valkey versions. It helps compare key releases side by side, highlight performance gains from new features. Read more about [Unlocking 1 Million RPS in Valkey](/blog/unlock-one-million-rps/)."
 methodology = "These metrics are generated using the [valkey-perf-benchmark](https://github.com/valkey-io/valkey-perf-benchmark) tool an AWS `c8g.metal.24xl` instance, running a matrix of configurations that vary pipelining (1, 10), I/O threading (1, 9), and with a data size of 512 bytes. To further stabilize results, we apply IRQ tuning by pinning network interrupts away from CPUs dedicated to the server process, and we isolate the server and benchmark client on separate NUMA nodes to remove L3 cache contention."
-
-[[sections]]
-title = "Memory Overhead Across Versions"
-iframe_url = "https://perf-dashboard.valkey.io/public-dashboards/0501007755004ae098dcc27d06bcda6a"
-description = "This dashboard visualizes Memory Efficiency trends across Valkey versions. It helps compare releases side by side, highlight Memory Efficiency gains from new features. Discover how [our new hash table design](/blog/new-hash-table/) reduces memory overhead."
-methodology = "These benchmarks are generated by starting an empty instance of Valkey for each test, measuring memory usage, then adding 3 million string items of a certain data size, then measuring Valkey memory usage again. We take the increase in memory use, divide by the number of items, and subtract the size of the user data (key and value) to get the extra overhead bytes Valkey uses to track and organize the data. For this graph, we tested every value size from 8B to 128B inclusive, then averaged the numbers for each range in this chart."