- Hazelcast cache statistics
- API performance metrics
- JVM
- System Metrics
Prometheus Metric Types
Cache metrics are collected using four metric types of Prometheus. These types are designed to best represent different data types and behaviors. Each metric type serves different purposes depending on how you collect and analyze the data.Counter
Counter is a value that only increases. It starts from zero when the application runs and increases, and is reset only when the application is restarted. Counter type metrics are ideal for tracking continuously increasing values such as total request count, error count, or number of completed operations.Available Operations:
sum: The total value itselfrate: Calculates the rate of increase over time (such as how much it increases per second)increase: Calculates the total increase in a specific time range
Gauge
Gauge represents an instant value. This value can increase, decrease, or remain constant. Gauge type metrics are used to monitor an instant state or level such as current memory usage, instant CPU usage, or number of active threads.Available Operations:
sum: Sum of Gauge values grouped by labelsmean: Average of Gauge values grouped by labelsmin/max: Minimum or maximum of values grouped by labels
Timer
Timer measures how long an operation takes (usually in milliseconds or seconds). Although technically not a special type in Prometheus, it is a metric created by libraries such as Micrometer with a combination of DistributionSummary and Counter. These metrics provide information such as average duration, maximum duration, and percentile slices.Available Operations:
sum: Gives the total durationcount: Gives how many times the operation was performed in totalmean: Calculates the average duration of the operationmax: Gives the longest duration observedhistogram_quantile: Calculates percentile slices
Summary
Summary is a metric that calculates both the total of observed values and predetermined percentile slices (quantiles). Its difference from Timer and DistributionSummary is that it collects percentile slices directly; since these are calculated when the metric is collected, not at query time, percentile slices are more accurate.Available Operations:
sum: Total of observed valuescount: Number of observed values- Predetermined percentile slices (
<metric_name>{quantile="0.99"})
Cache Metrics
These metrics monitor Cache’s cache performance. Cache searches, additions, and latencies are tracked to analyze efficiency. In addition, memory cost and distribution by partitions are measured.| Metric | Description | Type |
|---|---|---|
| cache_gets_total | Total cache searches (hits and misses) | Counter |
| cache_puts_total | Total cache additions | Counter |
| cache_size | Current number of entries in cache | Gauge |
| cache_entries | Number of entries per cache partition | Gauge |
| cache_entry_memory_bytes | Memory cost of cache entries | Gauge |
| cache_gets_latency_seconds | Cache access latency | Summary |
| cache_puts_latency_seconds | Cache addition latency | Summary |
| cache_removals_latency_seconds | Cache removal latency | Summary |
API Metrics
These metrics monitor the performance of Cache’s APIs. API performance is evaluated with data such as request count, response time, and error rates.| Metric | Description | Type |
|---|---|---|
| apinizer_cache_api_requests_total | Total API request count | Counter |
| apinizer_cache_api_response_time | API response time (seconds) | Timer |
| apinizer_cache_api_errors_total | Total API error count | Counter |
JVM Metrics
These metrics monitor Cache’s memory and thread usage. JVM performance is analyzed with data such as memory usage, GC (Garbage Collection) pause durations, and active threads.| Metric | Description | Type |
|---|---|---|
| jvm_memory_used_bytes | Memory usage by area (heap/non-heap) | Gauge |
| jvm_memory_committed_bytes | Committed memory by area | Gauge |
| jvm_memory_max_bytes | Maximum memory by area | Gauge |
| jvm_gc_pause_seconds | GC pause duration | Summary |
| jvm_threads_live_threads | Current number of live threads | Gauge |
| jvm_threads_daemon_threads | Current number of daemon threads | Gauge |
System Metrics
These metrics monitor Cache’s general performance with data such as CPU usage, processor count, and load average. In addition, resource usage is evaluated with data such as process duration and number of open files.| Metric | Description | Type |
|---|---|---|
| system_cpu_usage | CPU usage of main system | Gauge |
| system_cpu_count | Number of available processors | Gauge |
| system_load_average_1m | System load average (1 minute) | Gauge |
| process_cpu_usage | CPU usage of JVM process | Gauge |
| process_uptime_seconds | Runtime of JVM process | Gauge |
| process_files_open_files | Number of open file descriptors | Gauge |