DB Cache Hit Rate Chart
DB cache hit rate is the measurement of Database Server accesses that result in cache hits, measured as a percentage of hits versus total attempts. A high cache hit rate indicates efficiency.
Turbonomic collects cache hit rate data from Database Servers discovered by Databases, APM, and Cloud targets. When you set the scope to one or several Database Servers, the data that Turbonomic collected displays in the DB Cache Hit Rate chart.
The chart shows average and peak/low values over time. Use the selector at the bottom left section of the chart to change the time frame.
An empty chart could be the result of delayed discovery, target validation failure, unavailable data for the given time frame, or an unsupported Database Server (see the next section for a list of supported Database Servers).
Supported Database Servers
Data is available in the DB Cache Hit Rate chart for Database Servers discovered via the following targets:
|
Target |
Supported Database Servers |
|---|---|
|
AWS |
RDS |
|
Azure |
SQL |
|
AppDynamics |
SQL, Oracle |
|
Dynatrace |
SQL |
|
Instana |
MySQL, SQL, Oracle |
|
MySQL |
MySQL |
|
New Relic |
SQL, MySQL |
|
Oracle |
Oracle |
|
SQL |
SQL |
Effect on Memory Resize Actions
Actions to resize database memory are driven by data on the Database Server, which is more accurate than data on the hosting VM. Turbonomic uses database memory and cache hit rate data to decide whether resize actions are necessary.
A high cache hit rate value indicates efficiency. The optimal value is 100% for on-prem (self-hosted) Database Servers, and 90% for cloud Database Servers. When the cache hit rate reaches the optimal value, no action generates even if database memory utilization is high. If utilization is low, a resize down action generates.
When the cache hit rate is below the optimal value but database memory utilization remains low, no action generates. If utilization is high, a resize up action generates.