Kubernetes Classroom Series – 03/Sept/2021

PromQL

  • PromQL is the Prometheus Query Language
  • Labels are key part of PromQL and you can use them not only do arbitrary aggregations but also to join different metrics together for arthimetic operations against them.

Aggregation Basics

  • Gauge: These are snapshots of state and usually when you are aggregating them you want to take a sum, average, minimum or maximum.
    • Consider the metric node_filesystem_size_bytes (Node Exporter) which reports the size of each of your mounted filesystems and has device, fstype and mountpoint labels
    • Consider this query
sum without(device, fstype, mountpoint)(node_filesystem_size_bytes)
  • This works as without tells the sum aggregator to sum everything up with the same labels and ignoring these three
  • Consider this query
max without(device, fstype, mountpoint)(node_filesystem_size_bytes)
  • This would return the biggest mounted filesystem on each device.

  • Consider the expression avg without(instance, job)(process_open_fds)

  • Counter: Counter tracks the number or size of events and the value your applications expose on their metrics.

    • When we use counter we would usually want to know how counter is increasing/decreasing over time
    • This can be done by rate function
    rate(node_network_receive_bytes_total[5m])
    
    • The above expression/query calculates amount of network traffic received per second and [5m] provides the rate function with 5 minutes of data
    • The output of rate function is a gauge, so we can use aggregations
    sum without(device)(rate(node_network_receive_bytes_total[5m]))
    
  • Summary: Summary metric usually contains both _sum and _count and sometimes a time series with no suffix with a quantile lablel. _sum and _count are both counters

    • Prometheus exposes http_response_size_bytes summary and http_response_size_bytes_count tracks number of user requests
    • Consider the expression sum without(handler)(rate(http_response_size_bytes_count[5m]))
  • Histogram: Histogram metrics allows you to track the distribution of the size of the events, which allows you to calculate quantiles

    • Prometheus exposes a histogram prometheus_tsdb_compaction_duration_seconds that tracks how many seconds compaction takes for time series database
    • histogram_quantile function takes catre of calculating quantiles
    histogram_quantile(0.9, rate(prometheus_tsdb_compaction_duration_seconds[1d]))
    
    
  • Selectors: working with all the different time series with different label values for a metric can be overwhelming and confusing. Usually you will want to narrow down which time series you are working on

    • process_resident_memory_bytes{job="node"}
    • `job="node" is called a matcher and we have many matcher
    • Matchers: There are four matchers
      • =: this is equality matcher
      • !=: this is negative equality matcher
      • =~: This is regular expression mathcher job=~"n.*"
      • !~: This is negative regular expression matcher instance!~"prod*"
  • Durations:

    • ms: Milliseconds
    • s: seconds
    • m: minutes
    • h: hours
    • d: days
    • w: weeks
    • y: year
    • While using durations write duration as 1 unit
    100m (valid)
    1h40m (invalid)
    
  • Offset: There is a modifier we can use called as offset, which allows you take evaluation time for a query on a per-selector basis

    • process_resident_memory_bytes{job="node"} offset 1h this would get memory usage an hour before the query evaluation time.
    • `rate(process_cpu_seconds_total{job="node"}[5m] offset 1h )
  • by: In addition to without ther s also a by clause. Where without specifies the labels to remove by specifies labesls to keep. you cannot use both by and without in same aggregation

    • sum by(job, instane, device)(node_filesystem_size_bytes)
    • count by(release)(node_uname_info)
  • Operators:

    • sum
    • count
    • avg
    • stddev
    • stdvar
    • min
    • max
    • topk
    • bottomk
    • quantile
    • count_values
  • Arithmetic Operators:

    • /
    • % : modulation
    • ^: exponentiation
  • Comparision Operators

    • == equals
    • != not equals
    • <
    • >
    • >=
    • <=

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