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Prometheus for the traditional datacenter
Julien Pivotto (@roidelapluie)
Loadays
April 22nd, 2018
user{name="roidelapluie"} 1
I like Open Source
I like monitoring
I like automation
... and all of that is my job
The DevOps principles: CAMS
(a definition of DevOps)
Culture
Automation
Measurement
Sharing
(Damon Edwards and John Willis, 2010 http://devopsdictionary.com/wiki/CAMS)
Culture
Break down the silo's - make 1 team
Enable direct communication
Work towards a unique goal
Share responsibilities
Automation
Automate everything
Infra as Code
Release and deploy consistontly
More about that later...
Measurement
Measure all the things
(even DEV/ACC/PIL/...)
Business metrics & technical metrics
Take the metrics into consideration to take
decisions
Do alerting right; avoid alert fatigue
Sharing
Share Metrics, lessons learned
Share success, celebrate failure
Share with outside world as well, learn from
the industry
We are in the cloud era.
Here are some buzzwords for you
cloud, API, openstack, devops, docker, bimodal,
stateless, kubernetes, orchestration, automation,
serverless, docker, humanops, ansible, continuous
deployment, cri-o, jenkins, agile, docker, red hat,
containers, virtualization, provisionning,
monitoring, observability...
What is the cloud
Scale
Velocity
Change
On Premise looks like the cloud
Nowadays you have no choice.
Scale
Velocity
Change
What are the needs
Automation
Scalability
TIME TO GO
Bye bye all-in-one tools
Bye bye tools that don't scale
Bye bye tools you can not automate
We need deserve better tools
Our customers ask us to respond fast, in
seconds
We make hundreds of operations per second
What is your frequency... 5 minutes?Â
Time to get better tools /
protocols
Prometheus
https://prometheus.io/
Cloud Native
Easy to configure, deploy, maintain
Designed in multiple services
Container ready
Orchestration ready (dynamic config)
Fuzziness
Data Centric
A Metric in Prometheus has metadata:
myql_global_status_handlers_total{handler="tmp_write"}
1122
And lots of function to filter, change, remove...
those metadata while fetching them.
Open Source
Apache 2.0
Go
Support for multiple OS
Many "exporters":
https://github.com/prometheus/prometheus/wiki/Defa
ult-port-allocations
Performance
Prometheus is designed to fetch data in an
interval measured in SECONDS
You can fine tune its memory usage and when
it flushes to disk
It can also adapt its scraping frequency
dynamically
How does it work?
How does it work?
How does it work?
How does it work?
How does it work?
Exporters
Exporters expose metrics with an HTTP API
Bindings available for many languages
Exporters do not save data ; they are not
"proxies" and don't "cache" anything
Which exporters for your
datacenter?
OS
node_exporter
wmi_exporter
Apache
apache_exporter
grok_exporter
DNS
bind_exporter
blackbox_exporter
Network
snmp_exporter
netscaler_exporter
Databases
sql_exporter
sqlagent+prometheus-sql
Security
Prometheus supports TLS client (also with
authentication)
We use it with traefik (reverse proxy in go with
native metrics)
We manage certs with ansible
Exploring Metrics
Exploring Metrics
Exploring Metrics
Exploring Metrics
PromQL
mysql_global_status_commands_total
PromQL
mysql_global_status_commands_total{command="select"}
PromQL
mysql_global_status_commands_total
{command=~"select|set_options"}
PromQL
mysql_global_status_commands_total{command=~"select|se
t_options"}
PromQL
deriv(mysql_global_status_connections[5m])
PromQL
{__name__=~".+innodb.+cache.*"}
predict_linear(mysql_heartbeat_lag_seconds[5m], 60*2)
sum(rate(mysql_global_status_commands_total{command=~"
(commit|rollback)"}[5m])) without (command)
Storage
Prometheus 2.x uses prometheus/tsdb
2 hours blocks ; later compacted in up to 10
days blocks
Alerting
A word about
Prometheus vs Graphite
Prometheus does not see a metric as an "event".
Metrics are current value until they are replaced.
You can not see when a metric has been included
in Prometheus.
For Events, Prometheus refers to Elasticsearch.
Prometheus for the traditional datacenter
One tool does one job...
Prometheus collects data
Exporters expose data
Grafana graphes data
Alertmanager sends alerts
Alerting and recording rules
(p) yaml files
(p) Queries run at specific intervals
(p) sent to alertmanager
(a) receives
(a) groups
(a) inhibits
(a) dispatch
Grafana
Open Source (Apache 2.0)
Web app
Specialized in visualization
Pluggable
Multiple datasources: prometheus, graphite,
influxdb...
Has an API!
History of Grafana
Grafana is a fork of Kibana 3 ; used to be JS-
Driven.
Now fully featured, requires a database, multi-
projects/users support, etc...
Grafana and Prometheus
Prometheus shipped its own consoles
Now it recommends Grafana and deprecated
its own consoles
Grafana Dashboards
Grafana Dashboards
Time Picker
Configure Prometheus in
Grafana
Configure Prometheus in
Grafana
Prometheus Dashboard
Creating Grafana Dashboards
Takes time
Requires deep knowledge of the tools
Improved over time
Easy to share (json + online library)
Conclusion
Open Source
Flexible and dynamic
Low on resources
Rich ecosystem
For Cloud and On Premise
Julien Pivotto
roidelapluie
roidelapluie@inuits.eu
Inuits
https://inuits.eu
info@inuits.eu
Contact
I will give a
prometheus
workshop
at OSMC.de!

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