Building a Technology Stack for Your Kubernetes-Based Platform

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Building a Technology Stack for your Kubernetes-Based Platform Daniel Bryant Product Architect, Datawire

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tl;dr ● Adopting a “cloud native” approach is the new norm ● This requires new technologies and new workflows ● Creating a supporting cloud platform is essential ○ Container orchestration ○ Progressive delivery ○ Edge management ○ Observability ● Consciously design your platform. Watch for antipatterns

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@danielbryantuk

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A quick recap... ● Going “cloud native” oﬀers benefits, but requires changes ● Successful cloud native organisations have ○ Created a self-service application platform ○ Adopted new tools and (full cycle) developer workflows ● Recognised four core platform capabilities

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1. Container management 2. Progressive delivery 3. Edge management 4. Observability A quick recap...

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A quick recap... https://blog.getambassador.io/enabling-full-cycle-development-are-y ou-benefiting-from-your-move-to-kubernetes-d9eab2e94e7

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Avoiding Platform Antipatterns

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Avoiding Platform Antipatterns Centralized Design and Ownership: One Size Doesn’t Fit All Fragmented Platform Implementation Slow Development Loops: Less Time Coding, More Time Toiling

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Antipattern: Centralized Design and Ownership ● Economies of scale ● Overzealous guardrails ● Modification is ticket-driven

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Antipattern: Fragmented Platform Implementation https://speakerdeck.com/stilkov/microservice s-patterns-and-antipatterns-1?slide=12

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Antipattern: Slow Development Loops https://mitchdenny.com/the-inner-loop/

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Exploring the Platform Capabilities

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1. Container management 2. Progressive delivery 3. Edge management 4. Observability Four Core Platform Capabilities

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Container Management: Kubernetes

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Manage and run container-based applications at scale and on a variety of infrastructures ● Developers ○ Self-service interactions: automated and observable ● Platform team ○ Set policies around access, control, and auditability Container Management

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● Kubernetes is the de facto container orchestrator ● Cloud agnostic fabric(?) ○ Google Anthos, Azure Stack ● Kubernetes provides: ○ Declarative configuration and control loops ○ A shared abstraction Kubernetes

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Kubernetes Decisions ● To self-host, or not to self-host? ● Which distro? ● Going all-in on a cloud?

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Kubernetes Challenges ● Open for extension, closed for modification ○ Helm for deployment ○ Operators for automation ● Developer productivity ○ Local-to-remote dev and test

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Progressive Delivery: Delivery Pipelines

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Progressive Delivery Supporting the creation of pipelines that enable the automated build, verification, deployment, release, and observability ● Developers ○ Self-service interactions: automated and observable ● Platform team ○ Centralize verification of quality and security properties https://redmonk.com/jgovernor/2018/08/06/towards-progressive-delivery/

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● Deliver any and all application changes into production as rapidly and as safely as the organisation requires ● Includes experiments, new features, configuration, and bug fixes ● Deployments should be routine and drama free Continuous/progressive delivery pipelines

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Progressive Delivery Decisions ● Pipeline practices ● Pipeline technology https://www.infoq.com/news/2020/03/reimagining-cicd-pipelines/

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Progressive Delivery Challenges ● Collaboration between dev, QA, and ops ● Balance one-size-fits-all vs chaos ● Make it easy to do the right thing

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Edge Management: Ingress and API Gateways

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Edge Management Enable the self-service release of new functionality by developers, while maintaining stability ● Developers ○ Decentralized traﬀic management ○ Support NFRs e.g. authn/z, retries, and circuit breaking ● Platform ○ Centralized configuration of sane defaults ○ TLS, authn/z, and rate limiting for DDoS protection

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● First contact between users and biz services ● The edge stack is focused on: ○ Controlled release of new functionality; ○ Cross-functional edge requirements: security and reliability ○ Supporting developer onboarding ● Separate deploy and release The Edge Stack

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Edge Stack Decisions ● Edge technologies ● Deploy/release workflows ○ Declarative ○ Self-service ○ Scalable (more microservices, more APIs)

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Edge Stack Challenges ● Scaling edge management ● Supporting multiple protocols and NFRs https://www.getambassador.io/resources/challenges-api-gateway-kubernetes/

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Observability: Metrics, Logging, Tracing

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Observability Support the collection and analysis of end user and application feedback directly by developers and the platform team. ● Developers ○ Enable product teams to observe and iterate against business goals and KPIs ● Platform ○ Observe and managing infrastructure, and ensure their service level objectives (SLOs) are met

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● Infer what is occurring within a software system ○ Gradually improving an SLI ○ Rapidly restoring an SLI ● Monitoring, logging, and tracing ○ UX Observability

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Observability Decisions ● Adoption (monitor all-the-things?) ● Technology selection ○ Metrics ○ Logging ○ Distributed tracing ● Joining the dots (open standards)

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Observability Challenges ● Self-service config and dashboards ● Increasing signal-to-noise ● Fault location https://medium.com/@copyconstruct/monitoring-and-observability-8417d1952e1c

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Wrapping Up

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In Summary ● Adopting a “cloud native” approach is the new norm ● This requires new technologies and new workflows ● Creating a supporting cloud platform is essential ○ Container orchestration ○ Progressive delivery ○ Edge management ○ Observability ● Consciously design your platform. Watch for antipatterns

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