Docker How and Why
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Docker for Full Stack Developers
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Docker How and Why
- 1. Docker Why and How for Development
- 2. Foundations of a Container
- 3. Like a VM Own Process Space Own Network Interface Can run stuff as Root Can Install Packages Can Run Services Can manipulate routing, iptables, etc.
- 4. Not VM Uses the Host Kernel Can’t Boot a different OS Can’t have its own modules Does not need init as PID 1 Does not need, or usually have, syslogd, cron, etc. Processes are visible on the host machine
- 5. Why
- 6. Development Environments Runtimes and dependencies are consistent with production Build and test applications on platforms different than the one you use for development Build and test for multiple environments Run backend services
- 7. Build/Test Environments Checkout multiple branches, run tests simultaneously Increase parallelism of worker/test nodes Isolate different tests running on a node Provide multiple test and build environments Optimize utilization level of CI nodes Make environments available for local development match those used for testing and deployment
- 8. Production Code runs with dependencies and needed libraries bundled Operations teams can provide base images with consistent starting points Create clusters of services Scale service stacks horizontally with multiple nodes running multiple containers
- 9. How
- 10. Development of NodeJS Example Nginx Container serves connections /src/public mounted into nginx container to serve static files Can run locally on development machine, or spin up the NodeJS container to execute tests or run the application in “production” environment Redis container provides Redis connectivity Mock PuppetDB, LDAP, Sensu, and OpenTSDB services run in additional containers Locally running NodeJS combined with Webstorm provides great development experience Supporting services and infrastructure provided by Docker Compose, effortless testing and integration
- 11. Build and Test with CI Tools Unit tests are run in same environment as production. Isolated resources allow simulation of various constraints and prevent CPU/Memory intense test from impacting other tests Build artifacts can be written to host with mounted volumes Logging and test results shipped via Syslog or other logging drivers Network can be built up and isolated to ensure multiple stacks can run on a host but not interact Failure scenarios and network segmentation can be tested also
- 12. Deploying OpenTSDB Example 10x Query Nodes in Docker Containers Host runs Docker, HBase, OpenTSDB Write Node, HAProxy Query node resources limited, high number of isolated query slots improves average query response time, prevents long queries from impacting general population Docker containers specified by Puppet Configuration written to host /etc/opentsdb/opentsdb.conf Uses volume to place it into container at runtime HAProxy balances incoming connections across container nodes
- 13. Data Processing Pipeline Example Service 1 is a lightweight ingest container, parses lines into structured JSON Service 2 is a Redis cache, to prevent incoming data from overwhelming backend services or outage on backend from impacting incoming data Service 3 reads from Redis lists and processes incoming data. Handle more ingest customers with more Docker hosts, handle larger streams per connection with larger hosts, t2.large vs m4.16xlarge
- 15. ● http://www.slideshare.net/jpetazzo/anatomy-of-a-container-namespaces-cgroups-some- filesystem-magic-linuxcon ● https://github.com/veggiemonk/awesome-docker ● http://www.slideshare.net/SteveBargelt/automated-build-system-with-docker-jenkins- and-azure-intro