Containing Chaos with Kubernetes

Why Kubernetes

  • Scenario: Many Dockerfiles and containers needed to power application (Frontend/services container and DB container)
  • Splitting the containers down, as is best practice, to make them more ephemeral
  • Many containers on same machine = single point of failure

What is Kubernetes

  • Container orchestration system
  • Open source
  • Started by Google
  • Contributed to by others (Redhat, Docker etc)

Cattle not Pets

  • Pet
    • Has a name
    • Unique
    • Personal attention
    • If it gets ill you make it better
  • Cattle
    • Has a number
    • If it gets ill you make a burger (or a jacket)



  • Atomic component of Kubernetes
  • Made from one or more containers
  • Share
    • IP address
    • Namespace
  • Ok to have just one container
  • Examples
    • Webserver & file sync
    • All web available services
    • Converting an all-in-one box


  • Subatomic particles of Kubernetes
  • Dockerfiles just like you are used to


  • Handle turning current state into desired state
  • Example
    • Replication Controllers

Replica Set

  • Everything that Replication Controllers do
    • Can do set-based selector
  • Recent change so a lot of the docs will refer to Replication Controllers but you can use Replica Sets


  • An improvement over previous rolling updates
  • Allow for easy updates to application pieces


  • Define a set of pods that work together for a common purpose
  • Gets a virtual IP address
  • Used for exposing an application to non Kubernetes clients

Labels & Selectors

  • Metadata for Objects
  • Select sections of your infrastructure


  • Pod IPs are routable
    • Docker default is private IP
  • Pods can reach each other without NAT