You can use example PromQL queries to analyze Apinizer Cache metrics. You can use ready queries for cache analyses, Cache API analyses, JVM analyses and system analyses in Prometheus and Grafana.
sum(increase(cache_gets_total[1h]))
sum(increase(cache_puts_total[10m]))
(sum(increase(cache_gets_total[5m])) - sum(increase(apinizer_cache_api_errors_total[5m]))) / sum(increase(cache_gets_total[5m])) * 100
sum(cache_size)
topk(5, sum by (cache) (cache_entry_memory_bytes))
sum(increase(apinizer_cache_api_requests_total[1h]))
(sum(increase(apinizer_cache_api_requests_total[10m])) - sum(increase(apinizer_cache_api_errors_total[10m]))) / sum(increase(apinizer_cache_api_requests_total[10m])) * 100
(sum(jvm_memory_used_bytes{application="apinizer-cache"}) * 100) / sum(jvm_memory_max_bytes{application="apinizer-cache"})
sum(rate(jvm_gc_pause_seconds_sum{application="apinizer-cache"}[5m]))
sum(jvm_threads_live_threads{application="apinizer-cache"})
sum(rate(container_cpu_usage_seconds_total{namespace="apinizer"}[5m])) by (pod) * 100
sum(process_uptime_seconds)
sum(process_files_open_files{application="apinizer-cache"})