How can I get the amount of requests over a given time (dashboard time):
sum by (uri) (increase(http_requests_total[$__range]))
Example Queries
How many nodes are up?
up
Combining values from 2 different vectors (Hostname with a Metric):
up * on(instance) group_left(nodename) (node_uname_info)
Exclude labels:
sum without(job) (up * on(instance) group_left(nodename) (node_uname_info))
Count targets per job:
count by (job) (up)
Amount of Memory Available:
node_memory_MemAvailable_bytes
Amount of Memory Available in MB:
node_memory_MemAvailable_bytes/1024/1024
Amount of Memory Available in MB 10 minutes ago:
node_memory_MemAvailable_bytes/1024/1024 offset 10m
Average Memory Available for Last 5 Minutes:
avg_over_time(node_memory_MemAvailable_bytes[5m])/1024/1024
Memory Usage in Percent:
100 * (1 - ((avg_over_time(node_memory_MemFree_bytes[10m]) + avg_over_time(node_memory_Cached_bytes[10m]) + avg_over_time(node_memory_Buffers_bytes[10m])) / avg_over_time(node_memory_MemTotal_bytes[10m])))
CPU Utilization:
100 - (avg by(instance) (irate(node_cpu_seconds_total{mode="idle", instance="my-instance"}[5m])) * 100 )
CPU Utilization offset with 24hours ago:
100 - (avg by(instance) (irate(node_cpu_seconds_total{mode="idle", instance="my-instance"}[5m] offset 24h)) * 100 )
CPU Utilization per Core:
( (1 - rate(node_cpu_seconds_total{job="node-exporter", mode="idle", instance="$instance"}[$__interval])) / ignoring(cpu) group_left count without (cpu)( node_cpu_seconds_total{job="node-exporter", mode="idle", instance="$instance"}) )
CPU Utilization by Node:
100 - (avg by (instance) (irate(node_cpu_seconds_total{mode="idle"}[10m]) * 100) * on(instance) group_left(nodename) (node_uname_info))
Memory Available by Node:
node_memory_MemAvailable_bytes * on(instance) group_left(nodename) (node_uname_info)
Or if you rely on labels from other metrics:
(node_memory_MemTotal_bytes{job="node-exporter"} - node_memory_MemFree_bytes{job="node-exporter"} - node_memory_Buffers_bytes{job="node-exporter"} - node_memory_Cached_bytes{job="node-exporter"}) * on(instance) group_left(nodename) (node_uname_info{nodename=~"$nodename"})
Load Average in percentage:
avg(node_load1{instance=~"$name", job=~"$job"}) / count(count(node_cpu_seconds_total{instance=~"$name", job=~"$job"}) by (cpu)) * 100
Load Average per Instance:
sum(node_load5{}) by (instance) / count(node_cpu_seconds_total{mode="user"}) by (instance) * 100
Load Average (average per instance_id: lets say the metric has 2 identical label values but are different):
avg by (instance_id, instance) (node_load1{job=~"node-exporter", aws_environment="dev", instance="debug-dev"})
# {instance="debug-dev",instance_id="i-aaaaaaaaaaaaaaaaa"}
# {instance="debug-dev",instance_id="i-bbbbbbbbbbbbbbbbb"}
Disk Available by Node:
node_filesystem_free_bytes{mountpoint="/"} * on(instance) group_left(nodename) (node_uname_info)
Disk IO per Node: Outbound:
sum(rate(node_disk_read_bytes_total[1m])) by (device, instance) * on(instance) group_left(nodename) (node_uname_info)
Disk IO per Node: Inbound:
sum(rate(node_disk_written_bytes_total{job="node"}[1m])) by (device, instance) * on(instance) group_left(nodename) (node_uname_info)
Network IO per Node:
sum(rate(node_network_receive_bytes_total[1m])) by (device, instance) * on(instance) group_left(nodename) (node_uname_info)
sum(rate(node_network_transmit_bytes_total[1m])) by (device, instance) * on(instance) group_left(nodename) (node_uname_info)
Process Restarts:
changes(process_start_time_seconds{job=~".+"}[15m])
Container Cycling:
(time() - container_start_time_seconds{job=~".+"}) < 60
Histogram:
histogram_quantile(1.00, sum(rate(prometheus_http_request_duration_seconds_bucket[5m])) by (handler, le)) * 1e3
Metrics 24 hours ago (nice when you compare today with yesterday):
# query a
total_number_of_errors{instance="my-instance", region="eu-west-1"}
# query b
total_number_of_errors{instance="my-instance", region="eu-west-1"} offset 24h
# related:
# https://about.gitlab.com/blog/2019/07/23/anomaly-detection-using-prometheus/
Number of Nodes (Up):
count(up{job="cadvisor_my-swarm"})
Running Containers per Node:
count(container_last_seen) BY (container_label_com_docker_swarm_node_id)
Running Containers per Node, include corresponding hostnames:
count(container_last_seen) BY (container_label_com_docker_swarm_node_id) * ON (container_label_com_docker_swarm_node_id) GROUP_LEFT(node_name) node_meta
HAProxy Response Codes:
haproxy_server_http_responses_total{backend=~"$backend", server=~"$server", code=~"$code", alias=~"$alias"} > 0
Metrics with the most resources:
topk(10, count by (__name__)({__name__=~".+"}))
the same, but per job:
topk(10, count by (__name__, job)({__name__=~".+"}))
or jobs have the most time series:
topk(10, count by (job)({__name__=~".+"}))
Top 5 per value:
sort_desc(topk(5, aws_service_costs))
Table – Top 5 (enable instant as well):
sort(topk(5, aws_service_costs))
Most metrics per job, sorted:
sort_desc (sum by (job) (count by (__name__, job)({job=~".+"})))
Group per Day (Table) – wip
aws_service_costs{service=~"$service"} + ignoring(year, month, day) group_right
count_values without() ("year", year(timestamp(
count_values without() ("month", month(timestamp(
count_values without() ("day", day_of_month(timestamp(
aws_service_costs{service=~"$service"}
)))
)))
))) * 0
Group Metrics per node hostname:
node_memory_MemAvailable_bytes * on(instance) group_left(nodename) (node_uname_info)
..
{cloud_provider="amazon",instance="x.x.x.x:9100",job="node_n1",my_hostname="n1.x.x",nodename="n1.x.x"}
Subtract two gauge metrics (exclude the label that dont match):
polkadot_block_height{instance="polkadot", chain=~"$chain", status="sync_target"} - ignoring(status) polkadot_block_height{instance="polkadot", chain=~"$chain", status="finalized"}
Container CPU Average for 5m:
(sum by(instance, container_label_com_amazonaws_ecs_container_name, container_label_com_amazonaws_ecs_cluster) (rate(container_cpu_usage_seconds_total[5m])) * 100)
Container Memory Usage: Total:
sum(container_memory_rss{container_label_com_docker_swarm_task_name=~".+"})
Container Memory, per Task, Node:
sum(container_memory_rss{container_label_com_docker_swarm_task_name=~".+"}) BY (container_label_com_docker_swarm_task_name, container_label_com_docker_swarm_node_id)
Container Memory per Node:
sum(container_memory_rss{container_label_com_docker_swarm_task_name=~".+"}) BY (container_label_com_docker_swarm_node_id)
Memory Usage per Stack:
sum(container_memory_rss{container_label_com_docker_swarm_task_name=~".+"}) BY (container_label_com_docker_stack_namespace)
Remove metrics from results that does not contain a specific label:
container_cpu_usage_seconds_total{container_label_com_amazonaws_ecs_cluster!=""}
Remove labels from a metric:
sum without (age, country) (people_metrics)
View top 10 biggest metrics by name:
topk(10, count by (__name__)({__name__=~".+"}))
View top 10 biggest metrics by name, job:
topk(10, count by (__name__, job)({__name__=~".+"}))
View all metrics for a specific job:
{__name__=~".+", job="node-exporter"}
View all metrics for more than one job using vector selectors
{__name__=~".+", job=~"traefik|cadvisor|prometheus"}
Website uptime with blackbox-exporter:
# https://www.robustperception.io/what-percentage-of-time-is-my-service-down-for
avg_over_time(probe_success{job="node"}[15m]) * 100
Remove / Replace:
- https://medium.com/@texasdave2/replace-and-remove-a-label-in-a-prometheus-query-9500faa302f0
Client Request Counts:
irate(http_client_requests_seconds_count{job="web-metrics", environment="dev", uri!~".*actuator.*"}[5m])
Client Response Time:
irate(http_client_requests_seconds_sum{job="web-metrics", environment="dev", uri!~".*actuator.*"}[5m]) /
irate(http_client_requests_seconds_count{job="web-metrics", environment="dev", uri!~".*actuator.*"}[5m])
Requests per Second:
sum(increase(http_server_requests_seconds_count{service="my-service", env="dev"}[1m])) by (uri)
is the same as:
sum(rate(http_server_requests_seconds_count{service="my-service", env="dev"}[1m]) * 60 ) by (uri)
See this SO thread for more details
Scrape Config
relabel configs:
# full example: https://gist.github.com/ruanbekker/72216bea59fc56af189f5a7b2e3a8002
scrape_configs:
- job_name: 'multipass-nodes'
static_configs:
- targets: ['ip-192-168-64-29.multipass:9100']
labels:
env: test
- targets: ['ip-192-168-64-30.multipass:9100']
labels:
env: test
# https://grafana.com/blog/2022/03/21/how-relabeling-in-prometheus-works/#internal-labels
relabel_configs:
- source_labels: [__address__]
separator: ':'
regex: '(.*):(.*)'
replacement: '${1}'
target_label: instance
static_configs:
scrape_configs:
- job_name: 'prometheus'
scrape_interval: 5s
static_configs:
- targets: ['localhost:9090']
labels:
region: 'eu-west-1'
dns_sd_configs:
scrape_configs:
- job_name: 'mysql-exporter'
scrape_interval: 5s
dns_sd_configs:
- names:
- 'tasks.mysql-exporter'
type: 'A'
port: 9104
relabel_configs:
- source_labels: [__address__]
regex: '.*'
target_label: instance
replacement: 'mysqld-exporter'
Reference – ruanbekker , Official Documents.