Overview of Apinizer Gateway Metrics

Apinizer Gateway collects various metrics about API traffic, external connections, cache operations, and JVM status. These metrics are provided in Prometheus format and are divided into six categories: API traffic metrics, external connection metrics, cache metrics, JVM metrics, system metrics, and process metrics. Each metric is collected in two formats: general and tagged, and uses Prometheus’s Counter, Gauge, Timer, and DistributionSummary metric types.

ApinizerMetricsService collects various metrics about API traffic, external connections, cache operations, and JVM status. These metrics are provided in Prometheus format and can be integrated with monitoring systems.

API Traffic Metrics

API requests, success/error rates, response times, and sizes

External Connection Metrics

Requests made to external services, success/error rates, response times

Cache Metrics

Cache operations, success/error rates, response times

JVM Metrics

Memory usage, GC, thread status, processor usage

Each metric is collected in two formats:

• General Metric: Total values without labels (e.g., total count of all API requests)

• Tagged Metric: Metrics enriched with labels for detailed analysis (e.g., requests by API ID)

• API Traffic Metrics: API requests, success/error rates, response times, and sizes

• External Connection Metrics: Requests made to external services, success/error rates, response times

• Cache Metrics: Cache operations, success/error rates, response times

• JVM Metrics: Memory usage, GC, thread status, processor usage

Each metric is collected in two formats:

• General Metric: Total values without labels (e.g., total count of all API requests)
• Tagged Metric: Metrics enriched with labels for detailed analysis (e.g., requests by API ID)

Prometheus Metric Types

Gateway metrics are collected using Prometheus’s four basic metric types. 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)

Counter is a value that only increases. It starts from zero when the application runs and only resets when the application is restarted. Counter type metrics are ideal for tracking continuously increasing values such as total request count, error count, or completed operation count.

Available Operations:

• sum: The total value itself
• rate: Calculates the rate of increase over time (such as how much it increases per second)
• increase: Calculates the total increase over a specific time range

Gauge (Indicator)

Gauge represents an instantaneous value. This value can increase, decrease, or remain constant. Gauge type metrics are used to monitor an instantaneous state or level such as current memory usage, instantaneous CPU usage, or number of active threads.

Available Operations:

• sum: Sum of Gauge values grouped by labels
• mean: Average of Gauge values grouped by labels
• min/max: Minimum or maximum of values grouped by labels

Timer (Timer)

Timer measures how long an operation takes (usually in milliseconds or seconds). Although not technically a special type in Prometheus, it is a metric created by libraries like Micrometer through a combination of DistributionSummary and Counter. These metrics provide information such as average duration, maximum duration, and percentiles.

Available Operations:

• sum: Gives the total duration
• count: Gives how many times the operation was performed in total
• mean: Calculates the average duration of the operation
• max: Gives the longest observed duration
• histogram_quantile: Calculates percentiles

DistributionSummary (Distribution Summary)

DistributionSummary is used to track the distribution of a value. It works similarly to Timer, but instead of measuring time, it measures arbitrary numerical values such as request size, file size. This metric also provides statistical information such as average, maximum, and percentiles.

Available Operations:

• sum: Gives the total value
• count: Gives the number of observed values
• mean: Calculates the average of values
• max: Gives the largest observed value
• histogram_quantile: Calculates percentiles

API Traffic Metrics

These metrics are used to monitor and measure the performance of API requests passing through Apinizer. While total request, success, error, and cache hit rates are tracked numerically, request processing duration and data sizes are measured for performance analysis. Some metrics are provided with api_id and api_name tags for detailed API-based examination.

Metric Name	Description	Type	Labels
apinizer_api_traffic_total_count	Total API traffic requests	Counter	-
apinizer_api_traffic_success_count	Successful API requests	Counter	-
apinizer_api_traffic_error_count	Failed API requests	Counter	-
apinizer_api_traffic_blocked_count	Blocked API requests	Counter	-
apinizer_api_traffic_request_pipeline_time	API request pipeline duration (ms)	Timer	-
apinizer_api_traffic_routing_time	API routing duration (ms)	Timer	-
apinizer_api_traffic_response_pipeline_time	API response pipeline duration (ms)	Timer	-
apinizer_api_traffic_total_time	API total duration (ms)	Timer	-
apinizer_api_traffic_request_size	API request size (byte)	DistributionSummary	-
apinizer_api_traffic_response_size	API response size (byte)	DistributionSummary	-
apinizer_api_traffic_cache_hits_count	API cache hit count	Counter	-
apinizer_api_traffic_total_count_tagged	Total API traffic requests	Counter	api_id, api_name
apinizer_api_traffic_success_count_tagged	Successful API requests	Counter	api_id, api_name
apinizer_api_traffic_error_count_tagged	Failed API requests	Counter	api_id, api_name
apinizer_api_traffic_blocked_count_tagged	Blocked API requests	Counter	api_id, api_name
apinizer_api_traffic_request_pipeline_time_tagged	API request pipeline duration (ms)	Timer	api_id, api_name
apinizer_api_traffic_routing_time_tagged	API routing duration (ms)	Timer	api_id, api_name
apinizer_api_traffic_response_pipeline_time_tagged	API response pipeline duration (ms)	Timer	api_id, api_name
apinizer_api_traffic_total_time_tagged	API total duration (ms)	Timer	api_id, api_name
apinizer_api_traffic_request_size_tagged	API request size (byte)	DistributionSummary	api_id, api_name
apinizer_api_traffic_response_size_tagged	API response size (byte)	DistributionSummary	api_id, api_name
apinizer_api_traffic_cache_hits_count_tagged	API cache hit count	Counter	api_id, api_name

External Connection Metrics

These metrics are used to monitor external requests made through Apinizer. External service performance is analyzed by measuring total request, error count, and response time. Some metrics are provided with the url tag for detailed URL-based examination.

Metric Name	Description	Type	Labels
apinizer_external_requests_total_count	Total external request count	Counter	-
apinizer_external_errors_total_count	Total external error count	Counter	-
apinizer_external_response_time	External response time (ms)	Timer	-
apinizer_external_requests_total_count_tagged	Total external request count	Counter	url
apinizer_external_errors_total_count_tagged	Total external error count	Counter	url
apinizer_external_response_time_tagged	External response time (ms)	Timer	url

Cache Metrics

These metrics are used to monitor the worker (gateway) pod’s interaction with cache. The worker pod’s cache operations and performance are analyzed by measuring total request, error count, and response time.

Metric Name	Description	Type	Labels
apinizer_cache_requests_total_count	Total cache request count	Counter	-
apinizer_cache_errors_total_count	Total cache error count	Counter	-
apinizer_cache_response_time	Cache operation response time (ms)	Timer	-

JVM Metrics

These metrics are used to monitor JVM performance and resource usage in the worker (gateway) pod. They help analyze system efficiency by providing detailed information about memory, GC (Garbage Collection) activity, and thread status.

Metric Name	Description	Type	Labels
jvm_buffer_count_buffers	Number of buffers used by JVM	Gauge	-
jvm_buffer_memory_used_bytes	Total buffer memory used (byte)	Gauge	-
jvm_buffer_total_capacity_bytes	Buffer total capacity (byte)	Gauge	-
jvm_gc_live_data_size_bytes	Data size surviving after GC (byte)	Gauge	-
jvm_gc_max_data_size_bytes	Maximum data size for GC (byte)	Gauge	-
jvm_gc_memory_allocated_bytes_total	Memory allocated by GC (byte)	Counter	-
jvm_gc_memory_promoted_bytes_total	Memory promoted by GC (byte)	Counter	-
jvm_gc_pause_seconds_count	Total number of GC pauses	Counter	-
jvm_gc_pause_seconds_max	Longest GC pause (seconds)	Gauge	-
jvm_gc_pause_seconds_sum	Total GC pause duration (seconds)	Gauge	-
jvm_memory_committed_bytes	Memory allocated by JVM (byte)	Gauge	-
jvm_memory_max_bytes	Maximum memory available to JVM (byte)	Gauge	-
jvm_memory_used_bytes	Memory used by JVM (byte)	Gauge	-
jvm_threads_daemon_threads	Number of running daemon threads	Gauge	-
jvm_threads_live_threads	Number of actively running threads	Gauge	-
jvm_threads_peak_threads	Highest thread count reached	Gauge	-
jvm_threads_started_threads_total	Total number of threads started	Counter	-
jvm_threads_states_threads	Number of different thread states	Gauge	state

System Metrics

These metrics are used to monitor the worker (gateway) pod’s CPU and system load. Provides information about CPU core count, usage rate, and load average.

Metric Name	Description	Type	Labels
system_cpu_count	Total CPU core count	Gauge	-
system_cpu_usage	System-wide CPU usage rate	Gauge	-
system_load_average_1m	System load average for the last 1 minute	Gauge	-

Process Metrics

These metrics monitor the resource usage of the JVM process running in the worker (gateway) pod. Provides information about CPU usage, open file count, and maximum file limit.

Metric Name	Description	Type	Labels
process_cpu_usage	JVM’s CPU usage rate	Gauge	-
process_files_max_files	Maximum number of files that can be opened	Gauge	-
process_files_open_files	Number of open files	Gauge	-