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Struggling with a Prometheus percentile query on jvm stats
Prometheus - Docker/JVM MonitoringPrometheus Startup queryPrometheus nested alert query in prometheusQuery span duration in PrometheusPrometheus query returns invalid valueHow to measure HTTP Latency with Percentile in PrometheusAverage Memory Usage Query - PrometheusPrometheus - debugging slow queryHow to monitor pool stats in Atomikos with prometheusPrometheus/Grafana plot wait time percentiles for jobs
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I'm writing a query to get the 95th percentile on the rate of change in the jvm_gc_collection_seconds_count
. I want to trigger an alert when there is an unexpected spike. The purpose is to send me an alert when the JVM is working harder than usual.
I am using jvm_memory_bytes_used
for testing as the rate of the GC does not show any anomalies right now. Below is an example of the data I get back from the jvm_memory_bytes_used
. Should the first top two blue spikes not be returned as data points? The bottom red line should surely be picked up as an anomaly.
I have calculated the sum of the rate over 30 minutes grouped by instance. With that I try to get the 95th percentile.
histogram_quantile(0.95, sum(rate(jvm_memory_bytes_used[30m])) by (instance, le))
I've tried lowering the percentile which has no effect.
- Am I using the correct variable to calculate the GC stats?
- How can I get the
histogram_quantile
to produce results? - Am I taking the right approach using a percentile to achieve my goal?
prometheus
add a comment |
I'm writing a query to get the 95th percentile on the rate of change in the jvm_gc_collection_seconds_count
. I want to trigger an alert when there is an unexpected spike. The purpose is to send me an alert when the JVM is working harder than usual.
I am using jvm_memory_bytes_used
for testing as the rate of the GC does not show any anomalies right now. Below is an example of the data I get back from the jvm_memory_bytes_used
. Should the first top two blue spikes not be returned as data points? The bottom red line should surely be picked up as an anomaly.
I have calculated the sum of the rate over 30 minutes grouped by instance. With that I try to get the 95th percentile.
histogram_quantile(0.95, sum(rate(jvm_memory_bytes_used[30m])) by (instance, le))
I've tried lowering the percentile which has no effect.
- Am I using the correct variable to calculate the GC stats?
- How can I get the
histogram_quantile
to produce results? - Am I taking the right approach using a percentile to achieve my goal?
prometheus
add a comment |
I'm writing a query to get the 95th percentile on the rate of change in the jvm_gc_collection_seconds_count
. I want to trigger an alert when there is an unexpected spike. The purpose is to send me an alert when the JVM is working harder than usual.
I am using jvm_memory_bytes_used
for testing as the rate of the GC does not show any anomalies right now. Below is an example of the data I get back from the jvm_memory_bytes_used
. Should the first top two blue spikes not be returned as data points? The bottom red line should surely be picked up as an anomaly.
I have calculated the sum of the rate over 30 minutes grouped by instance. With that I try to get the 95th percentile.
histogram_quantile(0.95, sum(rate(jvm_memory_bytes_used[30m])) by (instance, le))
I've tried lowering the percentile which has no effect.
- Am I using the correct variable to calculate the GC stats?
- How can I get the
histogram_quantile
to produce results? - Am I taking the right approach using a percentile to achieve my goal?
prometheus
I'm writing a query to get the 95th percentile on the rate of change in the jvm_gc_collection_seconds_count
. I want to trigger an alert when there is an unexpected spike. The purpose is to send me an alert when the JVM is working harder than usual.
I am using jvm_memory_bytes_used
for testing as the rate of the GC does not show any anomalies right now. Below is an example of the data I get back from the jvm_memory_bytes_used
. Should the first top two blue spikes not be returned as data points? The bottom red line should surely be picked up as an anomaly.
I have calculated the sum of the rate over 30 minutes grouped by instance. With that I try to get the 95th percentile.
histogram_quantile(0.95, sum(rate(jvm_memory_bytes_used[30m])) by (instance, le))
I've tried lowering the percentile which has no effect.
- Am I using the correct variable to calculate the GC stats?
- How can I get the
histogram_quantile
to produce results? - Am I taking the right approach using a percentile to achieve my goal?
prometheus
prometheus
asked Mar 26 at 4:26
cbillowescbillowes
2,0182 gold badges21 silver badges39 bronze badges
2,0182 gold badges21 silver badges39 bronze badges
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add a comment |
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