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Docker Usage Patterns - Docker Meetup Palo Alto...

Docker Usage Patterns - Docker Meetup Palo Alto - Nov 2015

Ilan Rabinovitch

November 03, 2015
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  1. Docker Usage Patterns No Hype, Just Data Docker Meetup Palo

    Alto
 Nov 3, 2015 Ilan Rabinovitch Director, Community
 Datadog
  2. About Me • Long time Datadog user. • Prior to

    Datadog built automation and monitoring tooling at Ooyala and Edmunds.com
 • Love Community Events
 SCALE and Texas Linux Fest DevOpsDay LA DevOpsDay Silicon Valley Ilan Rabinovitch
 Datadog
  3. DevOpsDays Silicon Valley • Nov 6-7, 2015 • Computer History

    Museum • Presentations, Open Spaces • Promo Code DOCKR for 20% off! • More info on devopsdays.org
  4. Quick Overview of Datadog Datadog gathers performance data from all

    your application and infrastructure components. • Monitoring for modern applications 1. Dynamic Infrastructure 2. Containers (Docker, ECS, Mesos, k8s, and more…) 3. Microservices • Time series storage of metrics and events • Trending, alerting and anomaly detection. • We’re hiring! (Remote, NY, Boston, Paris)
  5. Adopter: the average number of containers running during the month

    was at least 50% the number of distinct hosts run, or there were at least as many distinct containers as distinct hosts run during the month. Dabbler: used Docker during the month, but did not reach the “adopter” threshold. Abandoner: a currently active company that used Docker in the past, but hasn't used it at all in the last month. Docker Adoption
  6. Operational Complexity • Average containers per host: N (N=4, 10/2015)

    • Instances live about 4x the length of their containers • N-times as many “hosts” to manage • Affects • provisioning: prep’ing & building containers • configuration: passing config to containers • orchestration: deciding where/when containers run • monitoring: making sure containers run properly
  7. Monitoring Needs and Pains: Static vs Dynamic • Avoid Static

    config files tracking dynamic infrastructure. 
 Configuration management is awesome, but….
  8. Monitoring Needs and Pains • Avoid Static config files tracking

    dynamic infrastructure. • Avoid a host centric view. Focus on service level.
  9. Monitoring Needs and Pains • Avoid Static config files tracking

    dynamic infrastructure. • Avoid a host centric view. Focus on service level. • Use tags, labels, etc on your hosts and metrics to form queries.
  10. Monitoring Needs and Pains: Query Based Monitoring “Show me rate

    of HTTP 500 responses from nginx” “… in region us-east-1 across all availability zones” “… running my app version 2….” • Use tags, labels, etc on your hosts and metrics to form queries. • Pull in labels from your infrastructure whether EC2, Docker or your scheduler. • Ask questions that will ring true regardless of your scale that day.
  11. Monitoring Needs and Pains • Avoid Static config files tracking

    dynamic infrastructure. • Avoid a host centric view. Focus on service level. • Use tags, labels, etc on your hosts and metrics to form queries. • Know your underlying tech. In this case Docker and how to pull metrics from it.
  12. Collecting Docker Metrics: Pseudo Files • Access via sysfs in

    /sys/fs/cgroup or /cgroup • By default do not require root access. • Fast and light weight • Limited I/O and Network metrics.
  13. Collecting Docker Metrics: stats • Continuous live stream of basic

    CPU, memory, & network metrics. • Available via API in JSON (see unix:///var/run/docker.sock) • At least version 1.5.0 of Docker (released Feb 2015)
  14. Collecting Docker Metrics: stats api • Similar to stats command

    provides a stream of metrics • More details. • Data is returned in JSON (see unix:///var/run/docker.sock)
  15. Collecting Docker Metrics: Summary CPU METRICS MEMORY METRICS I/O METRICS

    NETWORK METRICS pseudo-files Yes Yes Some Yes, in 1.6.1+ stats command Basic Basic No Basic API Yes Yes Some Yes
  16. DASHBOARDS Build Real-Time Interactive Dashboards CORRELATION Search And Correlate Metrics

    And Events See It All In One Place Your Servers, Your Clouds, Your Metrics, Your Apps, Your team. Together.
  17. COLLABORATION Share What You Saw, Write What You Did METRIC

    ALERTS Get Alerted On Critical Issues DEVELOPER API Instrument Your Apps, Write New Integrations See It All In One Place Your Servers, Your Clouds, Your Metrics, Your Apps, Your team. Together.