Container Scheduling Without the Hype: Why Bother?

Transcript

1. Container Scheduling Without
   the Hype: Why Bother?
   DevOpsDays Boise 2018
   Tyler Langlois
   Software Engineer, Elastic
   

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2. $ whois tylerjl
   ● Infrastructure/software/devops-y
   things @ Elastic
   ● Lots of recent work on
   dynamic/containerized
   environments
   Come talk to me about Arm SBCs (or
   if you want to yell about the Elastic
   Puppet modules)
   ____________________
   < angry at computers >
   --------------------
   \ ^__^
   \ (oo)\_______
   (__)\ )\/\
   ||----w |
   || ||
   

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3. Who is This For?
   ● Why care about container
   schedulers?
   ● What can they offer
   operations and
   development?
   ● Real-world achievements
   made possible by these
   solutions (or, new ideas
   for current practitioners)
   

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4. Where We’ve Been
   ???
   /var/log/?
   tcp:localhost:???
   statsd?
   prometheus?
   graphite?
   ...
   Dependent:
   ● Libraries
   ● Packages
   ● Runtime
   ● Distro
   ● etc.
   

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5. Where We Can Go
   ???
   /var/log/?
   tcp:localhost:???
   statsd?
   prometheus?
   graphite?
   ...
   Dependent:
   ● Libraries
   ● Packages
   ● Runtime
   ● Distro
   ● etc.
   Let’s talk about:
   ● Runtime
   ● Monitoring
   ● Persistence
   ● Services
   

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6. Runtime (Traditional)
   ● Without containers
   ○ Don’t even - dependencies are separate from code,
   messy
   ● With just containers
   ○ Where are you running them? Cloud instances?
   ○ How are you scheduling and running them?
   

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7. Runtime
   ---
   image: org/app:1.0
   env:
   FOO: bar
   count: 3
   ● Nodes are cattle
   ● Contract
   w/consumers is
   clear:
   ○ Build
   instructions
   ○ Runtime
   instructions
   FROM python:3
   COPY app.py app.py
   CMD python app.py
   

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8. Runtime
   ---
   image: org/app:1.0
   env:
   FOO: bar
   count: 3
   ● Nodes are cattle
   ● Contract
   w/consumers is
   clear:
   ○ Build
   instructions
   ○ Runtime
   instructions
   FROM python:3
   COPY app.py app.py
   CMD python app.py
   ● Deployments are always the same bits - repeatability
   ● Updates are hands-off for both dev and ops - rolling
   container upgrades
   ● Application changes async from backend (container build
   instructions)
   

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9. Monitoring (Traditional)
   Logs
   ● Format? Path?
   ● Opt-in
   ● Accessibility?
   Metrics
   ● System metrics
   != app metrics
   ● Scrape from
   app?
   Alerts
   ● Metrics are
   good;
   deployment
   statistics as
   well?
   

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10. Monitoring
    stdout stderr
    

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11. Monitoring
    stdout stderr
    ● Zero-config for generic logs/metrics out of the box
    ● Easily build custom tools atop this data for out of the box
    alerting as well
    ● Logs/metrics become self-service with appropriate
    visualization solutions
    

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12. Persistence (Traditional)
    ● Shared mass storage (ceph, gluster) in traditional setups
    ● Dynamically attached storage in the case of cloud environments (EBS)
    ● Works, but:
    ○ What ties them together, provisions them, migrates them, backs up?
    big ol’
    data
    ?
    

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13. Persistence
    ---
    volume:
    size: 50G
    ● Like runtime
    definitions, the
    underlying impl.
    Isn’t a concern
    ● Carve off a hunk of
    storage as needed
    ● Scheduling is
    happening all the
    time, storage
    follows
    big ol’
    data
    

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14. Persistence
    ---
    volume:
    size: 50G
    ● Like runtime
    definitions, the
    underlying impl.
    Isn’t a concern
    ● Carve off a hunk of
    storage as needed
    ● Scheduling is
    happening all the
    time, storage
    follows
    big ol’
    data
    ● Nobody cares where or what the persistence base is, we
    just have space now
    ● Infra can develop tools to enhance storage for everyone
    (automated backups, snapshotting, etc.)
    ● Backend-agnostic - GCP, AWS, Azure, etc.
    

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15. Services (Traditional)
    ● Both internal and external:
    ○ Spin up an app, add it to a pool
    of servers
    ○ Health checks sometimes
    ○ Typically, the “expose this”
    process very loosely coupled
    with “provision this”
    

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16. ● Tie service endpoints to groups
    of containers and let the
    router/proxy handle it for you
    Services
    pods
    

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17. ● Load balancers become a
    by-product of naturally selecting
    endpoints from a pool of healthy
    endpoints
    Services
    pods
    

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18. Services (+MORE)
    Traefik/Envoy/Fabio are solving neat
    problems:
    ● Automatic Let’s Encrypt TLS
    ● Automatic Host/app name
    routing
    ● Networking ACLs
    

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19. Better Processes
    Runtime
    Monitoring
    Persistence
    Services
    ● Contracts are clear - no one needs to
    learn another team’s tools if they don’t
    want to
    ● Improvements and iteration are
    completely unblocked on either side
    ● Infra tooling becomes immediately
    useful for everyone on the platform
    

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20. Thank you!
    github.com/tylerjl
    irc/twitter: leothrix
    tjll.net
    Additional Information:
    ● Google for:
    ○ Kubernetes
    ○ Nomad
    ○ Mesos
    ○ Traefik
    ○ Envoy
    Let’s talk about monitoring/metrics
    at the Elastic booth
    

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