MongoDB Evenings DC: Get MEAN and Lean with Docker and Kubernetes
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This document discusses running MongoDB and Kubernetes together to enable lean and agile development. It proposes using Docker containers to package applications and leverage tools like Kubernetes for deployment, management and scaling. Specifically, it recommends: 1) Using Docker to containerize applications and define deployment configurations. 2) Deploying to Kubernetes where services and replication controllers ensure high availability and scalability. 3) Treating databases specially by running them as "naked pods" assigned to labeled nodes with appropriate resources. 4) Demonstrating deployment of a sample MEAN stack application on Kubernetes with MongoDB and discussing future work around experimentation and blue/green deployments.
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MongoDB Evenings DC: Get MEAN and Lean with Docker and Kubernetes
- 1. Getting MEAN and Lean with MongoDB and Kubernetes MongoDB Evenings DC 2016 4/12/2016
- 2. Golden Age of Software Development { } Developer : ) User DeploymentTesting www. Native
- 3. About Me Inovalon - R&D, Enterprise Architecture, Software Dev, Healthcare AOL Advertising - High volume transactions, Big Data 3 Startups – Healthcare and Financial Services FIRST Robotics Mentor https://www.linkedin.com/in/vadimpolyakov
- 4. Impedance mismatch metaphor “Lossless” transmission line Impedance mismatch
- 5. Database impedance mismatch Existing concept: Database or Object-relational impedance mismatch ORM Tools/code (Hibernate, Entity Framework) Database technology • Object Databases • Document Databases Application and database schema are unified
- 7. This talk - tie the stack together How do we maximally leverage tools like MongoDB to deliver the right thing quickly? Tie together a “thin line architecture” of tools that support agility and leanness.
- 8. 11 The stack
- 9. Stack Impedance Client HTML, CSS, JS Server .Net, Java Database SQL
- 10. Browser (HTML, JS, CSS) Server REST API Data MEAN - Single Page App Routable Components [Service, contoller, direcrive] Routable Components [Middleware] JSON Flexible/Composable Flexible schema Collections JavaScript/TypeScript
- 11. JSON and JS Pipeline URL View – HTML template Controller – Manage the view Service – Manage the model URL Business Logic Injectable Abstract Data Store MongoDB
- 12. Schema – Service granularity Schema modeling ⇔ Service Design granularity Overnormalized ⇔ Chatty services or joins Giant documents ⇔ Network overhead, client resources (mobile)
- 13. Gettting the most of MEAN Adopt “Architecturally evident” coding style George Fairbanks, AgileRoots 2010 Architectural styles Components Layers Service orientation
- 15. Beyond development Dev QA UAT Prod
- 16. Docker “Docker containers wrap up a piece of software ... This guarantees that it will always run the same, regardless of the environment it is running in.” (https://www.docker.com/what-docker) Opinionated configuration of cgroups and namespaces Management API Git-like semantics (push, pull, diff…) Repository of existing images (public, private) Starts in milliseconds (it’s a process) Dev QA UAT Prod
- 17. A “right” choice Managed as code – Dockerfile Simple and fast to build images Simple deployment Retain prior version images for rollback and quick troubleshooting
- 18. Application – multiple containers and nodes nginx nginx Static content volume (HTML, JS, CSS) nginx Nginx nginx API Node /data/db volumenginx Data MongoDB nginx nginx Static content volume (HTML, JS, CSS) nginx Nginx nginx API Node /data/db volumenginx Data MongoDB MongoDB backup Git Sync nginx nginx Static content volume (HTML, JS, CSS) nginx Nginx nginx API Node /data/db volumenginx Data MongoDB MongoDB backup Git Sync nginx nginx Static content volume (HTML, JS, CSS) nginx Nginx nginx API Node /data/db volumenginx Data MongoDB MongoDB backup Custer Config Kubernetes Git Sync
- 19. Kubernetes Components - Node Node - physical resources Registers with the master Resource capacity Labels - tags used to filter the environment e.g. has kernel config for MongoDB
- 20. Kubernetes Components - Pod Pod - One or more co-located components with shared context (cgroups, namespaces)
- 21. Kubernetes Components - Replication Controller Replication Controller - Keep certain number of pod replicas running
- 22. Kubernetes Components - Services Services - Set of pods - Typically selected using labels - Virtual IP External Services Headless Service
- 23. App deployment Deployment as code svc-www.json rc-www.json svc-app.json rc-app.json svc-arb.json svc-mongo-db1.json svc-mongo-db2.json pod-mongo-db1.json pod-mongo-db2.json rc-arb.json www-rc nginx nginx www-svc app-svc app-rc app app app mongo1-svc mongo2-svc arbiter-svc Arbiter-rc arbitiermongo-db2mongo-db1
- 24. Application up kubectl create –f ./configdir - runs all the applications in the config Before the demo: • Start cluster, • Assign Elastic IP to the cluster • Update kubernetes security group to allow port 80 • Label the nodes Demo: • Deploy application • Configure replica set • Reload nginx config • Access the web app After the demo: • Teardown the cluster, run kube-down https://youtu.be/rOkKTUdQFGQ
- 25. MongoDB on Kubernetes “Datacenter as a Computer” Most nodes in the cluster are “cattle” not “pets” Some nodes are special Databases and DB servers are special • Working set, kernel config • Data is an asset, state of the enterprise
- 26. MongoDB on Kubernetes Replication Controller? • Restart automatically on failure • Schedule on multiple nodes Naked Pods Services • Discoverability • DNS node=mongo-db2 arbiter=true node=mongo-db2 arbiter=true mongo-db1 (naked pod) mongo-db2 (naked pod) mongo-db1-svc (service) mongo-db2-svc (service) aribiter-rc arbiter (pod) arbiter-svc (service)
- 27. MongoDB on Kubernetes: Demo MongoDB Instance MongoDB Instance MongoDB Arbiter MongoDB Instance MongoDB Instance MongoDB Instance MongoDB Arbiter Replication Controller MongoDB Instance MongoDB Instance MongoDB Arbiter Replication Controller MongoDB Instance Replication Controller MongoDB Instance MongoDB Arbiter Replication Controller MongoDB Instance Service MongoDB Arbiter Replication Controller MongoDB Instance MongoDB Instance ServiceService Service MongoDB Arbiter Manual Intervention https://youtu.be/bFnhl7QbjWg
- 28. Golden Age of Software Development { } Developer : ) User DeploymentTesting www. Native
- 29. Future work Enable experimentation/Blue-Green deployment http://martinfowler.com/bliki/BlueGreenDeployment.html
- 30. Architecting application for canary deployment Data layer for blue green deployment
Editor's Notes
- If, five years ago my sons asked me if they should build software, I would have probably said “Maybe” It’s not so bad. If they asked me today, I would say yes. The tools available are so rich that you can truly focus on solving the problem or being creative in a most satisfying way.
- About me
- Signal goes on forever - coax If there is mismatch between lines it bounces around and interferes with the signal coming from the source.
- MongoDB reduces the mismatch between datastore and web page or object. This a great starting point, but it does not the full solution.
- This is reason I wouldbn’t want my kids doing software engineering 5 years ago Bringing a new developer onto the team Deployments to QA Managing multiple versions - new release, prod fix, uat
- To get value out MongoDB we need to consider how it will play with the application stack and how that stack will be deployed
- If there is a character who embodies low impedance misamatch. It’s the dude.
- These are not terrible controversial choices, though certainly not the only ones. Applications framework: MEAN Containers: Docker Cluster management/deployment: Kubernetes Cluster: Vagrant: local, good for dev/demo Terraform: cloud
- PluggableSingle page app has come of age Angular 1 is a powerful framework, not without shortcomings for large apps Angular 2 is solves many issues (Beta, breaking change)
- TODO: Add diagram
- TODO: add screenshot Add graphic There are several competing project layout styles from varios seed projects (yoman Show how components are added independently for each other. Layers are important - we want the data layer to abstract our databases Service layer to abstract use of services be they internal or external
- Typical application will consist of many deployment steps Docker solves the issue of “Works in my machine” for one container. We want something that take the config “NoSsh” deployment - the environment has an API
- TODO: Add screen shot
- Container come and go (new IPs all the time) Service has a virtual
- If, five years ago my sons asked me if they should build software, I would have probably said “Maybe” It’s not so bad. If they asked me today, I would say yes. The tools available are so rich that you can truly focus on solving the problem or being creative in a most satisfying way.
- Now that the architecture for leannes and agility is available we can begin doing some interesting things. We all hear about facebook and other unicorns doing hundreds of deployments a day.