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Continuous Delivery for Containerized Applications:The Trials and Tribulations
Daniel Bryant
@danielbryantuk
Setting the scene…
• Continuous delivery is a large topic
• Focusing on the process and tooling• No live coding today
• Mini-book contains more details
• “Building a CD pipeline” by Adrian and Kevin
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TL;DR – Containers and CD
• Container image becomes the build pipeline ‘single binary’
• Adding metadata to containers images is vital
• Must validate container constraints (NFRs)• Cultivate containerised ‘mechanical sympathy’
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@danielbryantuk
• Chief Scientist at OpenCredo, CTO at SpectoLabs
• Agile, architecture, CI/CD, DevOps
• Java, Go, JS, microservices, cloud, containers
• Leading change through the application of technology and teams
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Continuous Delivery
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Continuous Delivery
• Produce valuable and robust software in short cycles
• Optimising for feedback and learning
• Not (necessarily) Continuous Deployment
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Creation of a build pipeline is mandatory for continuous delivery
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The Impact of containers on CD
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Container technology (and CD)
• OS-level virtualisation• cgroups, namespaces, rootfs
• Package and execute software
• Container image == ‘single binary’
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Creating a pipeline for containers
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Make your dev environment like production
• Develop locally or copy/code in container
• Use base images from production
• Must build/test containers locally• Perform (at least) happy path tests
• All tests should be runnable locally
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Lesson learned: Dockerfile content is super important
• OS choice
• Configuration
• Build artifacts
• Exposing ports
• Java• JDK vs JRE and Oracle vs OpenJDK
• Golang• Statically compiled binary
• Python• Virtualenv
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Please talk to the sysadmin people:
Their operational knowledge is invaluable
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Different prod and test containers?
• Create “test” version of container• Full OS (e.g. Ubuntu)
• Test tools and data
• Easy to see app/configuration drift
• Use test sidecar containers instead
• ONTEST proposal by Alexi Ledenev
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http://blog.terranillius.com/post/docker_testing/
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Building images with Jenkins
• My report covers this
• Build as usual…
• Build Docker Image• Cloudbees Docker Build and Publish Plugin
• Push image to registry
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Storing in an image registry (DockerHub)
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Lesson learned: Metadata is valuable
• Application metadata• Version / GIT SHA
• Build metadata• Build date• Image name• Vendor
• Quality metadata• QA control• Security audited etc
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Metadata – Beware of “latest” Docker Tag
• Beware of the ‘latest’ Docker tag
• “Latest” simply means • the last build/tag that ran without
a specific tag/version specified
• Ignore “latest” tag• Version your tags, every time
• Danielbryantuk/test:2.4.1
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Metadata - Adding Labels at build time
• Docker Labels
• Add key/value data to image
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Metadata - Adding Labels at build time
• Microscaling Systems’ Makefile
• Labelling automated builds on DockerHub (h/t Ross Fairbanks)• Create file /hooks/build
• label-schema.org
• microbadger.com
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Metadata - Adding Labels at runtime
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$ docker run -d --label
uk.co.danielbryant.lbname=frontdoor nginx
• Can ’docker commit’, but creates new image
• Not possible to update running container
• Docker Proposal: Update labels #21721
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Component testing
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Testing: Jenkins Pipeline (as code)
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Testing individual containers
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Integration testing
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Introducing Docker Compose
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Docker Compose & Jenkins Pipeline
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Mechanical sympathy: Docker and Java
• Watch for cgroup limits (and cgroup awareness)• getAvailableProcessors issue (bugs.openjdk.java.net/browse/JDK-8140793)
• Default fork/join thread pool sizes (based from host CPU count)
• Set container memory appropriately • JVM requirements = Heap size (Xmx) + Metaspace + JVM overhead
• Account for native thread requirements e.g. thread stack size (Xss)
• Entropy • Host entropy can soon be exhausted by crypto operations
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Mechanical sympathy: Docker and security
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Containers are not a silver bullet
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Containers: Expectations versus reality
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“DevOps”
Containerise an existing (monolithic) app?
• For
• We know the monolith well
• Allows homogenization of the pipeline and deployment platform
• Can be a demonstrable win for tech and the business
• Against
• Can be difficult (100+ line scripts)
• Often not designed for operation within containers, nor cloud native
• Putting lipstick on a pig?
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Whatever you decide…
push it through the pipeline ASAP!
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Key lessons learned
• Conduct an architectural review • Architecture for Developers, by Simon Brown• Architecture Interview, by Susan Fowler
• Look for data ingress/egress• File system access
• Support resource constraints/transience• Optimise for quick startup and shutdown • Evaluate approach to concurrency• Store configuration (secrets) remotely
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Microservices…
Containers and microservices are complementary
Testing and deployment change
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https://specto.io/blog/recipe-for-designing-building-testing-microservices.html
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Microservice architectural impact on CD
• Application decomposition• Bounded context
• Change cadence
• Risk
• Performance
• Scalability
• Team location
h/t Matthew Skelton, Adam Tornhill
• Worth knowing about:• Consumer-based contracts
• Service virtualisation
• Synthetic transactions and semantic monitoring
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Using containers does not obviate the need for
good architectural practices
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https://speakerdeck.com/caseywest/containercon-north-america-cloud-anti-patterns
Summary
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In summary
• Continuous delivery is vitally important in modern architectures/ops
• Container images must be the (single) source of truth within pipeline
• Mechanical sympathy is important (assert properties in the pipeline)• We’re now bundling more responsibility into our artifact (e.g. an OS)• Not all developers are operationally aware
• The tooling is now becoming stable/mature• We need to re-apply old CD practices with new technologies/tooling
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Bedtime reading
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Thanks for listening
• Any questions?
• Feel free to contact me• @danielbryantuk
• daniel.bryant@opencredo.com
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