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Monitoring large scale Docker
production environments
Alois Reitbauer, Dynatrace
@aloisreitbauer
Docker Adoption comes in two flavors
Why do we talk about monitoring?
46 % of all respondants see
monitoring as criticial for
Docker in production
Get the full report
https://www.ruxit.com/docker
Why is monitoring so hard/different?
We are at the verge of a paradigm shift
90 % of 2013 best practices are about to
become anti-patterns
Develop
Big monolithic application. Small interconnected purpose-built services.
Two Pizza Box Teams
3 – 6 people teams can deliver features into production
New Rules in the Game
You build it, you run it.
Werner Vogels, CTO Amazon
Polyglot Development requires Polyglot
Monitoring
Wide and deep
Built-in expert knowledge
Monitoring is a platform feature
https://vimeo.com/131385890 - James Turnmbull Monitoring as a s Service Monitorama 2015
Ship
Deploy
Big Bang Releases of single special built applications. Small continuous service delivery of standardized delivery blocks.
Microservice drive web-scale monitoring
Environments are usually 20 times larger
Network Monitoring on the rise
Machine-Assisted Problem resolution
From Infrastructure to Application
https://www.youtube.com/watch?v=smEuX-Hq6RI -
Monitoring Micro Services, Adrian Cockcroft Keynote O’Reilly Software Architecture Conference
Problems tend to become complex
820 Billion dependencies
Network Problem
Mushroom cloud
effect
The mastery – Liquid Environments
Deployments are no longer static
7:00 a.m.
Low Load and Service running
on minimum redudancy
12:00 p.m.
Scaled up service during peak load
with failover of problematic node
7:00 p.m.
Scaled down again to lower load
and move to different geo location
Monitor your Orchestration Layer
Monitoring Container Dynamics
Monitoring Netflix OSS Components
Network Monitoring is key
Monitoring as a Platform Feature
Auto-Injection
Self-configuration
Monitoring Requirements for Docker
Visualize automation impact
Automated problem analysis
Monitor orchestration platforms
Network monitoring core capability
Massive scalability
http://bit.ly/2016-hours-of-monitoring
Thank you!
Alois Reitbauer, Dynatrace Ruxit
@aloisreitbauer

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Monitoring large scale Docker production environments

Notas do Editor

  1. 20x larger: Axel springer moved to docker  about 20x more instances  no changes otherwise network monitoring: networking issues just happen in such dynamic and complex cloud environments and are challenging to find  needs new approaches machine-assisted: humans cannot deal with this complexity, its just too much – just like we use a navigation system to find quickly the shortest/fastest path to somewhere / use google to get results ranked by many factors to provide high likelyhood of usefulness. server monitoring is dead: it is about the entire application stack including infrastructure that serves end-users=business; and that needs monitoring