This talk is a quick intro to Prometheus with an overview on all its components. The presentation points to a generally available demo so that you can see all its components in action.

1. Cloud-Native Monitoring
With Prometheus
Jacopo Nardiello
Founder & DevOps Engineer
@jnardiello

2. Thanks to our sponsors

3. KubePrimer Workshop
14/07, Milano
http://kubeprimer.sighup.io

4. What is Prometheus?
Community Driven Open-source Monitoring and
Alerting toolkit, ships a time series database, an
alerting entity and a number of integration tools to
expose metrics.

5. A bit of context around Prometheus
Started in 2012 as a SoundCloud
internal project
Second project to join CNCF after
Kubernetes

6. Focus
Operational systems monitoring
Dynamic cloud environments

7. Natively integrates with existing
providers/tools and extract
scrape targets

9. Core features
● A powerful query language - PromQL
● Dimensional Data model
● Optimized to be efficient
● Operational & Architectural simplicity

10. Pull
/metrics endpoints
Model & typical monitoring scenario

11. The Architecture behind Prometheus

12. Let’s go a bit hands-on

13. Time Series Database
&
Web UI
http://demo.robustperception.io:9090/graph

14. Alert-Manager
http://demo.robustperception.io:9090/graph

15. Graphs & Dashboards
http://demo.robustperception.io:3000/dashboard/db/host-stats

16. PromQL & Label based queries
http_requests_total all time series related to the metric http_requests_total
http_requests_total{code="200",method="get"} time series related to successful request with
method get for the metric http_requests_total
http_requests_total{code="200",method="get"}[5m] returns a range vector
http_requests_total{status!~"^4..$"}
Selecting all errors-related time series using
regexes
sum(rate(http_requests_total[5m])) by (job) Applying functions, in this case we sum over a
range vector and aggregating by job

17. ACHTUNG!
Labels are transparent to Prometheus
whatever you define when exposing a metric, will be
available to query in the db.

18. Pulling metrics
● How do you expose those metrics?
● Exporters
● Language specific SDKs

19. /metrics
# HELP hash_seconds Time taken to create hashes
# TYPE hash_seconds histogram
hash_seconds_bucket{code="200",le="1"} 2
hash_seconds_bucket{code="200",le="2.5"} 2
hash_seconds_bucket{code="200",le="5"} 2
hash_seconds_bucket{code="200",le="10"} 2
hash_seconds_bucket{code="200",le="+Inf"} 2
hash_seconds_sum{code="200"} 9.370800000000002e-05
hash_seconds_count{code="200"} 2

20. Exporters
The community has contributed
writing exporters for pretty much
everything
https://prometheus.io/docs/instrumenting/exporters/

21. Alerting, Writing alerts: a simple example
ALERT <alert_name>
IF <condition>
FOR 5m
LABELS { severity="error" }
ANNOTATIONS {
summary = <summary>,
description = <description>,
}

22. Alert-Manager, Writing alerts: a real-world example
ALERT NODE_DISK_FREE_SPACE_ROOT_PARTITION_80
IF ((node_filesystem_size{fstype="rootfs"}-node_filesystem_avail{fstype="rootfs"})/node_filesystem_size{fstype="rootfs"})*100 > 80
FOR 5m
LABELS { severity="error" }
ANNOTATIONS {
summary = "Current disk usage on root partition is {{ $value }}% on node {{ $labels.instance }}",
description = "Current disk usage on root partition is {{ $value }}% on node {{ $labels.instance }}",
fixes = "Current disk usage on root partition is {{ $value }}% on node {{ $labels.instance }}",
}

23. Alert Dispatching
Job of the alert-manager is to dispatch
alerts to the right channel according to
their severity

24. Wrapping up

25. Thanks, questions?