1.
"Monitoring as Software Validation"
Measure anything,
Measure everything
Serena Lorenzini
serena@biodec.com
Incontro DevOps Italia
Bologna, 21 Feb. 2014

2.
Monitoring:
If it moves... you can track it!
Monitor everything
Network
Machine
Why?
●Learn from your
infrastructure
●Anticipate failure
●Speed up changes
Application

3.
Metrics and Events
Metric: Time + Name + Value
Event: Time + Name
It can be anything

4.
Graphite

5.
Graphite
An all-in-one solution for
storing and visualizing real-time
time-series data
Key features:
Efficient storage and ultra-fast retrieval.
Easy!!
http://graphite.wikidot.com/

6.
Graphite components
Graphite Web
Carbon
Whisper
The front-end of
Graphite. It
provides a
dashboard for
retrieval and
visualization of our
metrics and a
powerful plotting
API.
The core of
Graphite. Carbon
listens for data in a
format, aggregate
it and try to store it
on disk as quickly
as possible using
whisper.
The data storage.
An efficient time
series based
database.

7.
Organization of your data
Everything in Graphite
has a path with
components delimited by
dots.
servers.hostname.metric
applications.appname.metric
Paths reflect the organization
of the data:

8.
Pushing in your data:
Carbon configuration (and limitations)
Carbon listens for data (1) and aggregates them (2).
One can set the two specific behaviors by changing appropriate
variables in the configuration files.
1) How often your data will be collected? It needs to have the
retention time set to a specific value.
For a timespan X I want to store my data at intervals of y
(seconds/hours/days/months).
What happens if I send two metrics at the same time? Carbon
retains only the last one!
2)How do your metrics aggregate? It needs specific keywords to
apply functions to aggregate the data (e.g., “min”, “max”,
“sum”..).

9.
Fast and flexible monitoring: StatsD
StatsD
Front-end application for
Graphite (by Etsy)
Buffers metrics locally
Aggregates the data for
us
Flushes periodically data
to Graphite
Client libraries available
in any language
Send any metric you like
import statsd
HOST = 'hostname.server.com'
PORT = 8181
PREFIX = 'myprefix'
def initialize_client(host, port, prefix):
client = statsd.StatsClient(host, port, prefix)
return client
def send_data(data_name, value, client):
client.gauge(data_name, value)
client = initialize_client(HOST, PORT, PREFIX)
…..CODE.....
send_data('Energy', 1000, client)
https://github.com/etsy/statsd/

10.
Data Types in StatsD
Graphite usually stores the most recent data in 1-minute averaged
timestep, so when you’re looking at a graph, for each stat you
are typically seeing the average value over that minute.
Type
Counters
Timers
Gauges
Definition
Per-second rates
Event duration
Values
Sets
Unique values
passed to a key
Example
Page views
Page latency
How many views
do you have
Number of
registered users
accessing your
website

11.
Fast and flexible monitoring: CollectD
CollectD
A unix daemon that gathers system statistics
Plugin to send metrics to Carbon
Very useful for system metrics
Application-level statistics:
StatsD
System-level statistics:
CollectD
e.g. The number of times
a function is called
e.g. the memory usage
We can combine them in
a dashboard!

12.
Case study:
“Company A”
A project not testing friendly ...
...The Design phase was almost skipped!
We were asked to translate an existing (Matlab!) application
(into Python)
Metrics Driven Development!

13.
Case study:
“Company A”
Task: exploring a
space of
solutions to find
the best one
Method:
Simulated annealing
Probability
Random Number
Metrics Driven Development!
Track the evolution of the process instead of
parsing a (boring) log file to (1) correlate the consequences of
having P(x) > random number and (2) visually inspect the
real-time changing of P(x) values during the simulation

14.
Case study:
“Company B”
A project where multiple applications have to interact
in order to manage the elaboration of a
huge number of pictures every day

15.
Case study:
“Company B”
Monitor to …
1) see the asynchronous
activation of the applications
2) gather a regular pattern
3) CHECK FOR CHANGES IN
THAT PATTERN!
Monitor your system (cpu, ram...) and
applications together to see
if the hardware suits their requirements or not

16.
Case study:
“Company B”
Monitor your system
(cpu,ram...) and
applications together to see
if the hardware suits their
requirements or not.
E.g. picture upload time
Vs packet received/transmitted
Vs memory free/used
and so on...

17.
Case study:
“Company B”
Database queries per second?
Async tasks currently in queue?
How is the application behaving?
Images resized and stored?
Error and warning rates?

18.
Case study:
“Company B”
These applications are running
on several hosts and
their metrics end to the same point.
You can monitor many different servers by
looking at the same dashboard.

19.
Testing and Monitoring
"measure twice,
cut once"-
"Cut it quickly in
several pieces and see
which fits best (now!)”
You can do both!
Testing: just once during the development
Monitoring: it keeps working once the application is
released

20.
Testing and Monitoring
Tests are logical properties of our
application. Metrics are not. But Metrics
offer you the possibility to see what is going
on once the application/system is in
production
inevitable
Failure is not accepted
and detectable!

21.
Monitoring
Provide
informations
✗Frequent
communication
✗Some share
decision making
✗
Dev
Free!
Ops

22.
Wait... I don't like Graphite Web Interface!
No problem!
The world of the interfaces is
In continuous evolution
About 56,100 results

23.
You can't optimize what you can't measure
so monitor and...
Optimize anything,
Optimize everything

24.
Thank you for your attention!
Serena Lorenzini
serena@biodec.com
Incontro DevOps Italia
Bologna, 21 Feb. 2014