MongoDB World 2016: MongoDB + Google Cloud
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The document discusses MongoDB and its integration with Google Cloud Platform. It provides a brief history of SQL and NoSQL databases, noting that NoSQL is essential for highly available cloud applications. It describes how containers and pods allow for continuous evolution of production systems through incremental changes. It also discusses how stateful services in Kubernetes support persistent resolvable names, initialization, and volumes to maintain state across restarts. Finally, it mentions that MongoDB Atlas will soon support Google Cloud Platform to enable continuous evolution of stateful services through automated data conversion during schema/API upgrades.
MongoDB World 2016: MongoDB + Google Cloud
- 1. Confidential & ProprietaryGoogle Cloud Platform 1 MongoDB + Google Cloud Eric Brewer VP Infrastructure, Google
- 2. Confidential & ProprietaryGoogle Cloud Platform 2Confidential & ProprietaryGoogle Cloud Platform 2 Brief History of SQL/NoSQL 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 Today Pre-SQL • Programming and data are tightly integrated • One kind of developer • More control SQL • Strong data model • Two kinds of developers • Invariants first (ACID) NoSQL • Back to tight integration • One kind of programmer • Both models make sense
- 3. Confidential & ProprietaryGoogle Cloud Platform 3Confidential & ProprietaryGoogle Cloud Platform 3 NoSQL is essential to the rapid evolution of cloud native datasets & applications. The Rise of NoSQL Delivers required control for Highly Available Applications Bottom-up Layering: Unix systems view applied to data management
- 4. Confidential & ProprietaryGoogle Cloud Platform 4Confidential & ProprietaryGoogle Cloud Platform 4 Continuous Evolution High availability makes continuous evolution extremely challenging. The ability to continuously improve and modify a production application, through many, small changes...without taking it down.
- 5. Confidential & ProprietaryGoogle Cloud Platform 5Confidential & ProprietaryGoogle Cloud Platform 5 Continuous Evolution Drive incremental improvements to a production system In-Production Change Rollback In-Production Change TIME VERSION
- 6. Confidential & ProprietaryGoogle Cloud Platform 6Google Cloud Platform 6 Building block: Sets of Containers Containers ● Handle package dependencies ● Different versions, same machine ● No “DLL hell” Pods ● Co-locate containers ● Shared volumes ● IP address, independent port space ● Unit of deployment, migration /data Pod MyService python 3.4.2 glibc 2.21 MySQL python 2.7.9 glibc 2.19
- 7. Confidential & ProprietaryGoogle Cloud Platform 7Google Cloud Platform Unit of deployment: Services Service: ● Replicated pods • Source pod is a template ● Auto-restart member pods ● Abstract name (DNS) • IP address for the service ● Load balancing among replicas Load Balancer Service IP
- 8. Confidential & ProprietaryGoogle Cloud Platform 8Google Cloud Platform replicas: 1replicas: 0replicas: 3replicas: 2replicas: 4 Example: Rolling Upgrade with Labels Pods: Labels: frontend v1.3 frontend v1.3 frontend v1.3 Replication Controller v1.3 replicas: 1 v1.2 Replication Controller frontend replicas: 2replicas: 3 frontend v1.3 frontend v1.2 frontend v1.2 frontend v1.2 frontend v1.2 replicas: 4 Load Balancer
- 9. Confidential & ProprietaryGoogle Cloud Platform 9Confidential & ProprietaryGoogle Cloud Platform 9 How do we do the same for stateful that we’ve done for stateless?
- 10. Confidential & ProprietaryGoogle Cloud Platform 10Google Cloud Platform Stateful Services (in Kubernetes 1.3) Persistent resolvable name: e.g. UserDB-Mongo-2 ● Persistent ⇒ Name stays as pod comes/goes ● Resolvable ⇒ other replicas can find this one Clean initialization: ● An init hook — recover or initialize state ● Staggered start for replica groups Persistent volumes and claims ● Persistent volumes reliably keep state (magic disks!) ● Claim ensures you mount the same volume on restart
- 11. Confidential & ProprietaryGoogle Cloud Platform 11Google Cloud Platform Driving Continuous Evolution for Stateful Services Core idea: schema/API upgrade must be a reality ● Easy: API, schema version numbers ● Clients need version awareness/negotiation Servers require automated way to convert data to new version ● Atomically ● Partition data by key (to enable incremental conversion) ● Must be able to roll back partial changes ● Ideally this would be automated
- 12. Confidential & ProprietaryGoogle Cloud Platform 12Confidential & ProprietaryGoogle Cloud Platform 12 Today: Deployment Manager support for MongoDB Cloud Manager. Just Announced: Google Cloud Platform support in MongoDB Atlas coming soon! MongoDB and Google Cloud Platform Atlas
- 13. Confidential & ProprietaryGoogle Cloud Platform 13Confidential & ProprietaryGoogle Cloud Platform 13 MongoDB in the Google Cloud Ecosystem BigQuery Cloud ML
- 14. Confidential & ProprietaryGoogle Cloud Platform 14 At MongoDB World: Learn More ‣ ‣ Attend Sandeep’s Talk Running MongoDB on GCP – Sandeep Parikh Wednesday 3:10 - 3:50 PM, Nassau Learn More About GCP Services Codelabs
- 15. Confidential & ProprietaryGoogle Cloud Platform 15 Thank You