Day1 part 2
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content/day1/10_lessons_learned_from_building_a_db_operator
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content/day1/10_lessons_learned_from_building_a_db_operator
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---
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title: Lessons learned from building a MoboDB Operator
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weight: 10
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---
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Another talk as part of the Data On Kubernetes Day.
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## Baseline
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### Hosting Models
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* Managed: Atlas
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* Semi: Cloud manager
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* Selfhosted: Enterprise and community operator
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### Mongo on K8s
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* Cluster Architecture
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* Control Plane: Operator
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* Data Plane: MongoDB Server + Agen (Sidecar Proxy)
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* Enterprise Operator
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* Opsmanager CR: Deploys 3-node operator DB and OpsManager
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* MongoDB CR: The MongoDB cLusters (Compromised of agents)
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* Advanced Usecase: Data Platform with mongodb on demand
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* Control Plane on one cluster (or on VMs/Hardmetal), data plane in tennant clusters
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* Result: MongoDB CR can not relate to OpsManager CR directly
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## Pitfalls
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* Storage: Agnostic, Topology aware, configureable and resizeable (can't be done with statefulset)
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* Networking: Cluster-internal (Pod to Pod/Service), External (Split horizon over multicluster)
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content/day1/11_platform_beyond_k8s.md
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content/day1/11_platform_beyond_k8s.md
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---
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title: MAtuzre platform engineering beyond Kubernetes
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weight: 11
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---
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## CNCF Platform maturity model
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* Was donated to the cncf by syntasso
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* Constantly evolving since 1.0 in november 2023
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### Overview
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> Entire matrix is available from CNCF
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* Levels (from tactical to strategic)
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* Provisional
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* Operational
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* Scalable
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* Optimizing
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* Dimensions:
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* Investment: How are funds/staff allocated to platform capabilities
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* Adoption: How and why do users discover this platform
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* Interfaces: How do users interact with and consume platform capabilities
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* Operations: How are platforms and capabilities planned, prioritzed, developed and maintained
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* Measurement: What is the process for gathering and incorporating feedback/learning?
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## Goals
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* Understand
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* Outcomes & Practices
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* Where are you at
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* Limits & Opportunities
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* Behaviours and outcome
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* Balance People and processes
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## Typical Journeys
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### Steps of the jurney
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1. What are your goals and limitations
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2. What is my current landscape
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3. Plan babysteps & iterate
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### Szenarios
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* Bad: I want to improve my k8s platform
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* Good: Scaling an enterprise COE (Center Of Excellence)
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* What: Onboard 20 Teams within 20 Months and enforce 8 security regulations
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* Where: We have a dedicated team of centrally funded people
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* Lay the foundation: More funding for more larger teams -> Switch from Project to platform mindset
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* Do your technical Due diligence in parallel
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