scaling and monitoring docker environments
TRANSCRIPT
Scaling and Monitoring Docker environments
Alois Mayr @mayralois [email protected]
Docker Meetup Amsterdam, Sep 17th 2015
whoami
• Alois Mayr • Full stack developer for 10+ years • 5+ years researcher for so@ware quality and code analysis • Developer Advocate, Evangelist at Ruxit • Austrian
The pitch...
A full-‐stack applicaIon monitoring soluIon designed for highly dynamic cloud environments
Easy installaIon Auto discovery Scales to large environments
Who are you folks?
Docker’s Mission
docker build docker commit docker push
docker -‐H docker pull
docker run docker kill/stop
Any App, Anywhere
Ship and run – Orchestra3on and scaling
• How are containers related and need to be co-‐located? • Where do containers run? • What are the resource limits for containers? • Are there noisy neighbors on a machine? • How many containers of a certain image are required to run simultaneously? • How to check if a container is sIll in service? • How to manage failovers and load balancing? • How to manage container updates?
A DevOps’ job doesn’t stop with docker run commands
• How well are my deployments working? • Is my applicaIon healthy? • Is my applicaIon fast? • How healthy is my environment? • What are the criIcal components in terms of scalability? • Is my architecture scale well?
DevOps need applica3on monitoring!
Build, Ship, Run... Any App, Anywhere Who monitors? Any App, Anywhere
MONITORS
Top 5 challenges of monitoring Docker environments
#1 – Infrastructure and container dynamics
• Infrastructures are dynamic and fragile • Cloud instances come and go • Containers are started and killed frequently on purpose (by user acIon) • OrchestraIon tools and plaTorms kill and redeploy containers once they’re unhealthy
• Containers are ephemeral – they are caVle or even chicken
#2 – Container deployment tracking
• Deployment architecture validaIon • Co-‐located containers • Checking impact of noisy neighbors • Resource allocaIon and uIlizaIon • Capacity planning
#3 – Analysis of containerized services
• It’s what’s running inside that counts • Availability and performance of services maVer • App-‐centric and runIme specific metrics
• Response Ime • Failure rate • Throughput • GC suspension Ime
• Error analysis through applicaIon deep dive
#4 – Applica3on service dependency recogni3on
• Architecture validaIon • Service communicaIon for applicaIon health • Inbound service calls • Outbound service calls • Breakdown of response Imes
#5 – Don’t let your monitoring tool be a challenge
• ConfiguraIon hassle for each and every container
• AdapIng CI/CD environment to get monitoring running
• AdapIng applicaIon deployment bundles / images
Live demo...
Free trial -‐ hVps://ruxit.com/docker-‐monitoring/ Blog -‐ hVps://blog.ruxit.com/
@ruxit
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