Powering Microservices with Docker, Kubernetes, Kafka, and MongoDB
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The document discusses the benefits of microservices architecture utilizing Docker, Kubernetes, Kafka, and MongoDB, highlighting speed, scalability, and ease of deployment. It covers why MongoDB is suitable for microservices due to its flexible data model and monitoring capabilities, as well as how to implement microservices with containers. Additionally, it describes orchestration with Kubernetes and offers examples and resources for further learning.
![# M D B l o c a l
FROM debian:jessie-slim
RUN groupadd -r mongodb && useradd -r -g mongodb mongodb
...
ARG MONGO_PACKAGE=mongodb-org
ENV MONGO_VERSION 3.4.9
...
RUN echo "deb http://$MONGO_REPO/apt/debian jessie/${MONGO_PACKAGE%-unstable}/$MONGO_MAJOR main" | tee "/etc/apt/sources.list.d/${MONGO_PACKAGE%-unstable}.list”
RUN set -x
&& apt-get update
&& apt-get install -y ${MONGO_PACKAGE}=$MONGO_VERSION
${MONGO_PACKAGE}-server=$MONGO_VERSION
${MONGO_PACKAGE}-shell=$MONGO_VERSION
${MONGO_PACKAGE}-mongos=$MONGO_VERSION
${MONGO_PACKAGE}-tools=$MONGO_VERSION
&& rm -rf /var/lib/apt/lists/*
&& rm -rf /var/lib/mongodb
&& mv /etc/mongod.conf /etc/mongod.conf.orig
RUN mkdir -p /data/db /data/configdb && chown -R mongodb:mongodb /data/db
/data/configdb
VOLUME /data/db /data/configdb
COPY docker-entrypoint.sh /usr/local/bin/
ENTRYPOINT ["docker-entrypoint.sh"]
EXPOSE 27017
CMD ["mongod"]
https://github.com/docker-library/mongo](https://image.slidesharecdn.com/1345-1425-powering-microservic-f9730d04-2257-4ddc-8423-71bec8bf2397-20396929-171018133400/85/Powering-Microservices-with-Docker-Kubernetes-Kafka-and-MongoDB-29-320.jpg)
![# M D B l o c a l
FROM debian:jessie-slim
RUN groupadd -r mongodb && useradd -r -g mongodb mongodb
...
ARG MONGO_PACKAGE=mongodb-org
ENV MONGO_VERSION 3.4.9
...
RUN echo "deb http://$MONGO_REPO/apt/debian jessie/${MONGO_PACKAGE%-unstable}/$MONGO_MAJOR main" | tee "/etc/apt/sources.list.d/${MONGO_PACKAGE%-unstable}.list”
RUN set -x
&& apt-get update
&& apt-get install -y ${MONGO_PACKAGE}=$MONGO_VERSION
${MONGO_PACKAGE}-server=$MONGO_VERSION
${MONGO_PACKAGE}-shell=$MONGO_VERSION
${MONGO_PACKAGE}-mongos=$MONGO_VERSION
${MONGO_PACKAGE}-tools=$MONGO_VERSION
&& rm -rf /var/lib/apt/lists/*
&& rm -rf /var/lib/mongodb
&& mv /etc/mongod.conf /etc/mongod.conf.orig
RUN mkdir -p /data/db /data/configdb && chown -R mongodb:mongodb /data/db
/data/configdb
VOLUME /data/db /data/configdb
COPY docker-entrypoint.sh /usr/local/bin/
ENTRYPOINT ["docker-entrypoint.sh"]
EXPOSE 27017
CMD ["mongod"]
https://github.com/docker-library/mongo](https://image.slidesharecdn.com/1345-1425-powering-microservic-f9730d04-2257-4ddc-8423-71bec8bf2397-20396929-171018133400/85/Powering-Microservices-with-Docker-Kubernetes-Kafka-and-MongoDB-30-320.jpg)
![# M D B l o c a l
FROM debian:jessie-slim
RUN groupadd -r mongodb && useradd -r -g mongodb
mongodb
...
ARG MONGO_PACKAGE=mongodb-org
ENV MONGO_VERSION 3.4.9
...
RUN echo "deb http://$MONGO_REPO/apt/debian jessie/${MONGO_PACKAGE%-unstable}/$MONGO_MAJOR main" | tee "/etc/apt/sources.list.d/${MONGO_PACKAGE%-unstable}.list”
RUN set -x
&& apt-get update
&& apt-get install -y ${MONGO_PACKAGE}=$MONGO_VERSION
${MONGO_PACKAGE}-server=$MONGO_VERSION
${MONGO_PACKAGE}-shell=$MONGO_VERSION
${MONGO_PACKAGE}-mongos=$MONGO_VERSION
${MONGO_PACKAGE}-tools=$MONGO_VERSION
&& rm -rf /var/lib/apt/lists/*
&& rm -rf /var/lib/mongodb
&& mv /etc/mongod.conf /etc/mongod.conf.orig
RUN mkdir -p /data/db /data/configdb && chown -R mongodb:mongodb /data/db
/data/configdb
VOLUME /data/db /data/configdb
COPY docker-entrypoint.sh /usr/local/bin/
ENTRYPOINT ["docker-entrypoint.sh"]
EXPOSE 27017
CMD ["mongod"]
https://github.com/docker-library/mongo](https://image.slidesharecdn.com/1345-1425-powering-microservic-f9730d04-2257-4ddc-8423-71bec8bf2397-20396929-171018133400/85/Powering-Microservices-with-Docker-Kubernetes-Kafka-and-MongoDB-31-320.jpg)
![# M D B l o c a l
FROM debian:jessie-slim
RUN groupadd -r mongodb && useradd -r -g mongodb mongodb
...
ARG MONGO_PACKAGE=mongodb-org
ENV MONGO_VERSION 3.4.9
...
RUN echo "deb http://$MONGO_REPO/apt/debian jessie/${MONGO_PACKAGE%-unstable}/$MONGO_MAJOR main" | tee "/etc/apt/sources.list.d/${MONGO_PACKAGE%-unstable}.list”
RUN set -x
&& apt-get update
&& apt-get install -y ${MONGO_PACKAGE}=$MONGO_VERSION
${MONGO_PACKAGE}-server=$MONGO_VERSION
${MONGO_PACKAGE}-shell=$MONGO_VERSION
${MONGO_PACKAGE}-mongos=$MONGO_VERSION
${MONGO_PACKAGE}-tools=$MONGO_VERSION
&& rm -rf /var/lib/apt/lists/*
&& rm -rf /var/lib/mongodb
&& mv /etc/mongod.conf /etc/mongod.conf.orig
RUN mkdir -p /data/db /data/configdb && chown -R mongodb:mongodb /data/db /data/configdb
VOLUME /data/db /data/configdb
COPY docker-entrypoint.sh /usr/local/bin/
ENTRYPOINT ["docker-entrypoint.sh"]
EXPOSE 27017
CMD ["mongod"]
https://github.com/docker-library/mongo](https://image.slidesharecdn.com/1345-1425-powering-microservic-f9730d04-2257-4ddc-8423-71bec8bf2397-20396929-171018133400/85/Powering-Microservices-with-Docker-Kubernetes-Kafka-and-MongoDB-32-320.jpg)
![# M D B l o c a l
FROM debian:jessie-slim
RUN groupadd -r mongodb && useradd -r -g mongodb mongodb
...
ARG MONGO_PACKAGE=mongodb-org
ENV MONGO_VERSION 3.4.9
...
RUN echo "deb http://$MONGO_REPO/apt/debian jessie/${MONGO_PACKAGE%-unstable}/$MONGO_MAJOR main" | tee "/etc/apt/sources.list.d/${MONGO_PACKAGE%-unstable}.list”
RUN set -x
&& apt-get update
&& apt-get install -y
${MONGO_PACKAGE}=$MONGO_VERSION
${MONGO_PACKAGE}-server=$MONGO_VERSION
${MONGO_PACKAGE}-shell=$MONGO_VERSION
${MONGO_PACKAGE}-mongos=$MONGO_VERSION
${MONGO_PACKAGE}-tools=$MONGO_VERSION
&& rm -rf /var/lib/apt/lists/*
&& rm -rf /var/lib/mongodb
&& mv /etc/mongod.conf /etc/mongod.conf.orig
RUN mkdir -p /data/db /data/configdb && chown -R mongodb:mongodb /data/db
/data/configdb
VOLUME /data/db /data/configdb
COPY docker-entrypoint.sh /usr/local/bin/
ENTRYPOINT ["docker-entrypoint.sh"]
EXPOSE 27017
CMD ["mongod"]
https://github.com/docker-library/mongo](https://image.slidesharecdn.com/1345-1425-powering-microservic-f9730d04-2257-4ddc-8423-71bec8bf2397-20396929-171018133400/85/Powering-Microservices-with-Docker-Kubernetes-Kafka-and-MongoDB-33-320.jpg)
![Volume
name:
mongo-persistent-storage1
pdName: mongodb-disk1
mongodb
-disk1
Container
name: mongo-node1
image: mongo
command: mongod –replSet my_replica_set
containerPort: 27017
volumeMounts:
name: mongo-persistent-storage1
mountPath: /data/db
Docker Hub Registry
Pod
labels: [name: mongo-node1; instance: rod]
ReplicationController
name: mongo-rc1
labels: [name: mongo-rc]
replicas: 1
selector: [name: mongo -node1]
Service: LoadBalancer
name: mongo-svc-a
labels: [name: mongo-svc-a]
ports: [port: 27017, targetPort: 27017]]
selector: [name: mongo-node, instance: rod]
ExternalIP
Address
104.1.1.1
App
104.1.1.1:27017](https://image.slidesharecdn.com/1345-1425-powering-microservic-f9730d04-2257-4ddc-8423-71bec8bf2397-20396929-171018133400/85/Powering-Microservices-with-Docker-Kubernetes-Kafka-and-MongoDB-48-320.jpg)
![# M D B l o c a l
ReplicationControler
name: mongo-rc-europe
labels: [name: mongo-europe]
replicas: 1
selector: [name: mongo -node]
Volume
name:
mongo-persistent-storage
pdName: mongodb-disk-europe
mongodb-
disk-europe
Container
name: mongo-node
image: mongo
command: mongod –replSet my_replica_set
containerPort: 27017
volumeMounts:
name: mongo-persistent-storage
mountPath: /data/db
Pod
labels: [name: mongo-node]
Service: LoadBalancer
name: mongo-svc-europe
labels: [name: mongo-svc-europe]
ports: [port: 27017, targetPort: 27017]]
selector: [name: mongo-node]
ReplicationControler
name: mongo-rc-asia
labels: [name: mongo-asia]
replicas: 1
selector: [name: mongo -node]
Volume
name:
mongo-persistent-storage
pdName: mongodb-disk-asia
mongodb-
disk-asia
Container
name: mongo-node
image: mongo
command: mongod –replSet my_replica_set
containerPort: 27017
volumeMounts:
name: mongo-persistent-storage
mountPath: /data/db
Pod
labels: [name: mongo-node]
Service: LoadBalancer
name: mongo-svc-asia
labels: [name: mongo-svc-asia]
ports: [port: 27017, targetPort: 27017]]
selector: [name: mongo-node]
ReplicationControler
name: mongo-rc-us
labels: [name: mongo-us]
replicas: 1
selector: [name: mongo -node]
Volume
name:
mongo-persistent-storage
pdName: mongodb-disk-us
mongodb-
disk-us
Container
name: mongo-node
image: mongo
command: mongod –replSet my_replica_set
containerPort: 27017
volumeMounts:
name: mongo-persistent-storage
mountPath: /data/db
Pod
labels: [name: mongo-node]
Service: LoadBalancer
name: mongo-svc-us
labels: [name: mongo-svc-us]
ports: [port: 27017, targetPort: 27017]]
selector: [name: mongo-node]
Loosely Coupled Replica Set](https://image.slidesharecdn.com/1345-1425-powering-microservic-f9730d04-2257-4ddc-8423-71bec8bf2397-20396929-171018133400/85/Powering-Microservices-with-Docker-Kubernetes-Kafka-and-MongoDB-49-320.jpg)
Powering Microservices with Docker, Kubernetes, Kafka, and MongoDB
- 1. # M D B l o c a l Andrew Morgan Powering Microservices with Docker, Kubernetes, Kafka, & MongoDB MongoDB London @andrewmorgan
- 2. # M D B l o c a l Agenda Microservic es What, Why, When MongoDB Why Containers Docker Messaging Kafka Orchestrati on Kubernetes Deploying MongoDB Options, How 1 2 3 4 5 6
- 3. # M D B l o c a l Microservices
- 4. # M D B l o c a l Why Use Microservices? (tl;dr WebScale) Speed Change Maintain Scale Empower Build MVP quickly Rapid iterations Simple components Product Team == Component React to market Isolated impact Team Committees
- 5. # M D B l o c a l Why Use Microservices? (tl;dr WebScale) Speed Change Maintain Scale Empower Build MVP quickly Rapid iterations Simple components Product Team == Component React to market Isolated impact Team Committees
- 6. # M D B l o c a l Why Use Microservices? (tl;dr WebScale) Speed Change Maintain Scale Empower Build MVP quickly Rapid iterations Simple components Product Team == Component React to market Isolated impact Team Committees
- 7. # M D B l o c a l Why Use Microservices? (tl;dr WebScale) Speed Change Maintain Scale Empower Build MVP quickly Rapid iterations Simple components Product Team == Component React to market Isolated impact Team Committees
- 8. # M D B l o c a l Why Use Microservices? (tl;dr WebScale) Speed Change Maintain Scale Empower Build MVP quickly Rapid iterations Simple components Product Team == Component React to market Isolated impact Team Committees
- 9. # M D B l o c a l Why Use Microservices? (tl;dr WebScale) Speed Change Maintain Scale Empower Build MVP quickly Rapid iterations Simple components Product Team == Component React to market Isolated impact Team Committees
- 11. # M D B l o c a l Microservices Example Twitter IngestGoogle+ Ingest Snapchat Ingest Feed merge Facebook Ingest
- 12. # M D B l o c a l Microservices Example Twitter Ingest Snapchat Ingest Feed merge Facebook Ingest
- 13. # M D B l o c a l Microservices Example Twitter Ingest Snapchat Ingest Feed merge Facebook Ingest
- 14. # M D B l o c a l Microservices Example Twitter Ingest Snapchat Ingest Feed merge Facebook Ingest Whatsapp Ingest
- 15. # M D B l o c a l Microservices Example Twitter Ingest Snapchat Ingest Feed merge Facebook Ingest Whatsapp Ingest Snapchat Ingest Snapchat Ingest
- 16. # M D B l o c a l When to use Microservices
- 17. # M D B l o c a l When to use Microservices
- 18. # M D B l o c a l Why MongoDB & Microservices
- 19. # M D B l o c a l Why MongoDB is a Good Fit For Microservices Monitoring & Automation Flexible Data Model Redundancy Scalability Simplicity
- 20. # M D B l o c a l Why MongoDB is a Good Fit For Microservices Monitoring & Automation Flexible Data Model Redundancy Scalability Simplicity
- 21. # M D B l o c a l Why MongoDB is a Good Fit For Microservices Monitoring & Automation Flexible Data Model Redundancy Scalability Simplicity
- 22. # M D B l o c a l Why MongoDB is a Good Fit For Microservices Monitoring & Automation Flexible Data Model Redundancy Scalability Simplicity
- 23. # M D B l o c a l Why MongoDB is a Good Fit For Microservices Monitoring & Automation Flexible Data Model Redundancy Scalability Simplicity
- 24. # M D B l o c a l Why MongoDB is a Good Fit For Microservices Monitoring & Automation Flexible Data Model Redundancy Scalability Simplicity
- 25. # M D B l o c a l Containers
- 26. # M D B l o c a l Software containers • 1 image -> Many containers • Laptop, DC, cloud • Dev, QA, production, support • Efficient • Isolation • Constraints Containers – Powering Microservices
- 27. # M D B l o c a l • Simple to use • 100K+ images on Docker Hub • Build images from images • Platforms • Linux, OS X, Windows • Laptop, VM, Cloud,… • Cloud services Docker
- 28. # M D B l o c a l docker run -d mongo Run MongoDB
- 29. # M D B l o c a l FROM debian:jessie-slim RUN groupadd -r mongodb && useradd -r -g mongodb mongodb ... ARG MONGO_PACKAGE=mongodb-org ENV MONGO_VERSION 3.4.9 ... RUN echo "deb http://$MONGO_REPO/apt/debian jessie/${MONGO_PACKAGE%-unstable}/$MONGO_MAJOR main" | tee "/etc/apt/sources.list.d/${MONGO_PACKAGE%-unstable}.list” RUN set -x && apt-get update && apt-get install -y ${MONGO_PACKAGE}=$MONGO_VERSION ${MONGO_PACKAGE}-server=$MONGO_VERSION ${MONGO_PACKAGE}-shell=$MONGO_VERSION ${MONGO_PACKAGE}-mongos=$MONGO_VERSION ${MONGO_PACKAGE}-tools=$MONGO_VERSION && rm -rf /var/lib/apt/lists/* && rm -rf /var/lib/mongodb && mv /etc/mongod.conf /etc/mongod.conf.orig RUN mkdir -p /data/db /data/configdb && chown -R mongodb:mongodb /data/db /data/configdb VOLUME /data/db /data/configdb COPY docker-entrypoint.sh /usr/local/bin/ ENTRYPOINT ["docker-entrypoint.sh"] EXPOSE 27017 CMD ["mongod"] https://github.com/docker-library/mongo
- 30. # M D B l o c a l FROM debian:jessie-slim RUN groupadd -r mongodb && useradd -r -g mongodb mongodb ... ARG MONGO_PACKAGE=mongodb-org ENV MONGO_VERSION 3.4.9 ... RUN echo "deb http://$MONGO_REPO/apt/debian jessie/${MONGO_PACKAGE%-unstable}/$MONGO_MAJOR main" | tee "/etc/apt/sources.list.d/${MONGO_PACKAGE%-unstable}.list” RUN set -x && apt-get update && apt-get install -y ${MONGO_PACKAGE}=$MONGO_VERSION ${MONGO_PACKAGE}-server=$MONGO_VERSION ${MONGO_PACKAGE}-shell=$MONGO_VERSION ${MONGO_PACKAGE}-mongos=$MONGO_VERSION ${MONGO_PACKAGE}-tools=$MONGO_VERSION && rm -rf /var/lib/apt/lists/* && rm -rf /var/lib/mongodb && mv /etc/mongod.conf /etc/mongod.conf.orig RUN mkdir -p /data/db /data/configdb && chown -R mongodb:mongodb /data/db /data/configdb VOLUME /data/db /data/configdb COPY docker-entrypoint.sh /usr/local/bin/ ENTRYPOINT ["docker-entrypoint.sh"] EXPOSE 27017 CMD ["mongod"] https://github.com/docker-library/mongo
- 31. # M D B l o c a l FROM debian:jessie-slim RUN groupadd -r mongodb && useradd -r -g mongodb mongodb ... ARG MONGO_PACKAGE=mongodb-org ENV MONGO_VERSION 3.4.9 ... RUN echo "deb http://$MONGO_REPO/apt/debian jessie/${MONGO_PACKAGE%-unstable}/$MONGO_MAJOR main" | tee "/etc/apt/sources.list.d/${MONGO_PACKAGE%-unstable}.list” RUN set -x && apt-get update && apt-get install -y ${MONGO_PACKAGE}=$MONGO_VERSION ${MONGO_PACKAGE}-server=$MONGO_VERSION ${MONGO_PACKAGE}-shell=$MONGO_VERSION ${MONGO_PACKAGE}-mongos=$MONGO_VERSION ${MONGO_PACKAGE}-tools=$MONGO_VERSION && rm -rf /var/lib/apt/lists/* && rm -rf /var/lib/mongodb && mv /etc/mongod.conf /etc/mongod.conf.orig RUN mkdir -p /data/db /data/configdb && chown -R mongodb:mongodb /data/db /data/configdb VOLUME /data/db /data/configdb COPY docker-entrypoint.sh /usr/local/bin/ ENTRYPOINT ["docker-entrypoint.sh"] EXPOSE 27017 CMD ["mongod"] https://github.com/docker-library/mongo
- 32. # M D B l o c a l FROM debian:jessie-slim RUN groupadd -r mongodb && useradd -r -g mongodb mongodb ... ARG MONGO_PACKAGE=mongodb-org ENV MONGO_VERSION 3.4.9 ... RUN echo "deb http://$MONGO_REPO/apt/debian jessie/${MONGO_PACKAGE%-unstable}/$MONGO_MAJOR main" | tee "/etc/apt/sources.list.d/${MONGO_PACKAGE%-unstable}.list” RUN set -x && apt-get update && apt-get install -y ${MONGO_PACKAGE}=$MONGO_VERSION ${MONGO_PACKAGE}-server=$MONGO_VERSION ${MONGO_PACKAGE}-shell=$MONGO_VERSION ${MONGO_PACKAGE}-mongos=$MONGO_VERSION ${MONGO_PACKAGE}-tools=$MONGO_VERSION && rm -rf /var/lib/apt/lists/* && rm -rf /var/lib/mongodb && mv /etc/mongod.conf /etc/mongod.conf.orig RUN mkdir -p /data/db /data/configdb && chown -R mongodb:mongodb /data/db /data/configdb VOLUME /data/db /data/configdb COPY docker-entrypoint.sh /usr/local/bin/ ENTRYPOINT ["docker-entrypoint.sh"] EXPOSE 27017 CMD ["mongod"] https://github.com/docker-library/mongo
- 33. # M D B l o c a l FROM debian:jessie-slim RUN groupadd -r mongodb && useradd -r -g mongodb mongodb ... ARG MONGO_PACKAGE=mongodb-org ENV MONGO_VERSION 3.4.9 ... RUN echo "deb http://$MONGO_REPO/apt/debian jessie/${MONGO_PACKAGE%-unstable}/$MONGO_MAJOR main" | tee "/etc/apt/sources.list.d/${MONGO_PACKAGE%-unstable}.list” RUN set -x && apt-get update && apt-get install -y ${MONGO_PACKAGE}=$MONGO_VERSION ${MONGO_PACKAGE}-server=$MONGO_VERSION ${MONGO_PACKAGE}-shell=$MONGO_VERSION ${MONGO_PACKAGE}-mongos=$MONGO_VERSION ${MONGO_PACKAGE}-tools=$MONGO_VERSION && rm -rf /var/lib/apt/lists/* && rm -rf /var/lib/mongodb && mv /etc/mongod.conf /etc/mongod.conf.orig RUN mkdir -p /data/db /data/configdb && chown -R mongodb:mongodb /data/db /data/configdb VOLUME /data/db /data/configdb COPY docker-entrypoint.sh /usr/local/bin/ ENTRYPOINT ["docker-entrypoint.sh"] EXPOSE 27017 CMD ["mongod"] https://github.com/docker-library/mongo
- 34. # M D B l o c a l Many small, focused containers -> sophisticated services • Well defined APIs • Independent languages & libraries • Modular: easy maintenance + reuse • Fault tolerant • Scalable Microservice Architectures Built on Containers
- 35. # M D B l o c a l Apache Kafka
- 36. # M D B l o c a l Connecting the Microservices – Kafka Producer 987 123... Topic A Consumer New Old
- 37. # M D B l o c a l Connecting the Microservices – Kafka Producer 987 123... Topic A Consumer Producer Consumer
- 38. # M D B l o c a l Connecting the Microservices – Kafka Producer 987 123... Partition 0 Topic A Consumer Producer Consumer 435 123... Partition 1
- 39. # M D B l o c a l Connecting the Microservices – Kafka Producer LEADER Topic A / Partition 0 Broker 1 FOLLOWER Topic A / Partition 1 FOLLOWER Topic A / Partition 0 Broker 2 LEADER Topic A / Partition 1
- 40. # M D B l o c a l Connecting the Microservices – Kafka Producer Producer Producer 9 8 7 123 ... Partition 0 4 3 5 123 ... Partition 1 7 3 2 123 ... Partition N Topic A Topic B 7 6 5 123 ... Partition 0 Consumer Consumer
- 41. # M D B l o c a l Orchestration – Kubernetes
- 42. # M D B l o c a l Created by Google, feature-rich and widely adopted • Deployment and ‘replication’ • On-line scale out/in • Rolling upgrades • High Availability • Persistence • Ports • Load balancing • Google Compute Engine Kubernetes
- 43. # M D B l o c a l MongoDB & Kubernetes
- 44. # M D B l o c a l How to use MongoDB with Containers Twitter Ingest Snapchat Ingest Feed merge Facebook Ingest Whatsapp Ingest Snapchat Ingest Snapchat Ingest MongoDB Atlas
- 45. # M D B l o c a l How to use MongoDB with Containers Twitter Ingest Snapchat Ingest Feed merge Facebook Ingest Whatsapp Ingest Snapchat Ingest Snapchat Ingest Kubernetes Ops Mgr agent Ops Mgr agent Ops Mgr agent
- 46. # M D B l o c a l How to use MongoDB with Containers Twitter Ingest Snapchat Ingest Feed merge Facebook Ingest Whatsapp Ingest Snapchat Ingest Snapchat Ingest Kubernetes mongod mongod mongod
- 47. # M D B l o c a l Kubernetes Building Blocks POD Host Host Service
- 48. Volume name: mongo-persistent-storage1 pdName: mongodb-disk1 mongodb -disk1 Container name: mongo-node1 image: mongo command: mongod –replSet my_replica_set containerPort: 27017 volumeMounts: name: mongo-persistent-storage1 mountPath: /data/db Docker Hub Registry Pod labels: [name: mongo-node1; instance: rod] ReplicationController name: mongo-rc1 labels: [name: mongo-rc] replicas: 1 selector: [name: mongo -node1] Service: LoadBalancer name: mongo-svc-a labels: [name: mongo-svc-a] ports: [port: 27017, targetPort: 27017]] selector: [name: mongo-node, instance: rod] ExternalIP Address 104.1.1.1 App 104.1.1.1:27017
- 49. # M D B l o c a l ReplicationControler name: mongo-rc-europe labels: [name: mongo-europe] replicas: 1 selector: [name: mongo -node] Volume name: mongo-persistent-storage pdName: mongodb-disk-europe mongodb- disk-europe Container name: mongo-node image: mongo command: mongod –replSet my_replica_set containerPort: 27017 volumeMounts: name: mongo-persistent-storage mountPath: /data/db Pod labels: [name: mongo-node] Service: LoadBalancer name: mongo-svc-europe labels: [name: mongo-svc-europe] ports: [port: 27017, targetPort: 27017]] selector: [name: mongo-node] ReplicationControler name: mongo-rc-asia labels: [name: mongo-asia] replicas: 1 selector: [name: mongo -node] Volume name: mongo-persistent-storage pdName: mongodb-disk-asia mongodb- disk-asia Container name: mongo-node image: mongo command: mongod –replSet my_replica_set containerPort: 27017 volumeMounts: name: mongo-persistent-storage mountPath: /data/db Pod labels: [name: mongo-node] Service: LoadBalancer name: mongo-svc-asia labels: [name: mongo-svc-asia] ports: [port: 27017, targetPort: 27017]] selector: [name: mongo-node] ReplicationControler name: mongo-rc-us labels: [name: mongo-us] replicas: 1 selector: [name: mongo -node] Volume name: mongo-persistent-storage pdName: mongodb-disk-us mongodb- disk-us Container name: mongo-node image: mongo command: mongod –replSet my_replica_set containerPort: 27017 volumeMounts: name: mongo-persistent-storage mountPath: /data/db Pod labels: [name: mongo-node] Service: LoadBalancer name: mongo-svc-us labels: [name: mongo-svc-us] ports: [port: 27017, targetPort: 27017]] selector: [name: mongo-node] Loosely Coupled Replica Set
- 50. # M D B l o c a l Beta in Kubernetes 1.5+ • Stable, predictable, unique network identifiers • IP addresses may change • Stable, persistent storage • Ordered, graceful deployment and scaling (0 N-1) • Ordered, graceful deletion and termination (N-1 0) StatefulSets
- 51. # M D B l o c a l MongoDB Replica Set as StatefulSet rs.initiate() rs.add('mongo-1.mongo:27017') rs.add('mongo-2.mongo:27017')
- 52. # M D B l o c a l • Enabling Microservices: Containers & Orchestration Explained https://www.mongodb.com/collateral/microservices-containers-and-orchestration-explained • Microservices: The Evolution of Building Modern Applications https://www.mongodb.com/collateral/microservices-the-evolution-of-building-modern-applications • Data Streaming with Apache Kafka & MongoDB https://www.mongodb.com/collateral/data-streaming-with-apache-kafka-and-mongodb • Guidance and examples http://k8smongodb.net/ References
- 53. # M D B l o c a l MongoDB & Microservices in the Wild
- 54. # M D B l o c a l
Editor's Notes
- #3: 1 min
- #4: 2 mins A microservice architecture is one where you break an application down into multiple processes; where each one: Is self-contained Has a single, well defined role The microservices communicate with each other using network technologies (even if running on the same host)
- #5: 3 min. Web & Mobile Apps => Enterprise Micro Web Services Microservices were pioneered in the web and then mobile App worlds; at one time called micro-web-services. Now other enterprises are looking for the same benefits. Microservice architectures implement applications as a series of small, self-contained, loosely coupled software components. Each has a specific and well understood role. Benefits of microservices: - Development Speed - Rapid Iteration Evolve quickly, continuous deployment Isolate impact of changes to existing functions or just add a new one Reactive development Maintainable Independent, empowered work teams
- #6: Web & Mobile Apps => Enterprise Micro Web Services Microservices were pioneered in the web and then mobile App worlds; at one time called micro-web-services. Now other enterprises are looking for the same benefits. Microservice architectures implement applications as a series of small, self-contained, loosely coupled software components. Each has a specific and well understood role. Benefits of microservices: - Development Speed - Rapid Iteration Evolve quickly, continuous deployment Isolate impact of changes to existing functions or just add a new one Reactive development Maintainable Independent, empowered work teams
- #7: Web & Mobile Apps => Enterprise Micro Web Services Microservices were pioneered in the web and then mobile App worlds; at one time called micro-web-services. Now other enterprises are looking for the same benefits. Microservice architectures implement applications as a series of small, self-contained, loosely coupled software components. Each has a specific and well understood role. Benefits of microservices: - Development Speed - Rapid Iteration Evolve quickly, continuous deployment Isolate impact of changes to existing functions or just add a new one Reactive development Maintainable Independent, empowered work teams
- #8: Web & Mobile Apps => Enterprise Micro Web Services Microservices were pioneered in the web and then mobile App worlds; at one time called micro-web-services. Now other enterprises are looking for the same benefits. Microservice architectures implement applications as a series of small, self-contained, loosely coupled software components. Each has a specific and well understood role. Benefits of microservices: - Development Speed - Rapid Iteration Evolve quickly, continuous deployment Isolate impact of changes to existing functions or just add a new one Reactive development Maintainable Independent, empowered work teams
- #9: Web & Mobile Apps => Enterprise Micro Web Services Microservices were pioneered in the web and then mobile App worlds; at one time called micro-web-services. Now other enterprises are looking for the same benefits. Microservice architectures implement applications as a series of small, self-contained, loosely coupled software components. Each has a specific and well understood role. Benefits of microservices: - Development Speed - Rapid Iteration Evolve quickly, continuous deployment Isolate impact of changes to existing functions or just add a new one Reactive development Maintainable Independent, empowered work teams
- #10: Web & Mobile Apps => Enterprise Micro Web Services Microservices were pioneered in the web and then mobile App worlds; at one time called micro-web-services. Now other enterprises are looking for the same benefits. Microservice architectures implement applications as a series of small, self-contained, loosely coupled software components. Each has a specific and well understood role. Benefits of microservices: - Development Speed - Rapid Iteration Evolve quickly, continuous deployment Isolate impact of changes to existing functions or just add a new one Reactive development Maintainable Independent, empowered work teams
- #11: 5 mins. Add a new flavor independently. Chef making chocolate knows that well but need not know the others Blueberry goes out of fashion, remove them Need more green cakes, add them Improved pink frosting, throw out the old ones and the new ones. Microservices are like Cupcakes Can add new ones with different flavors, remove ones that you no longer need, add more pink ones if there’s greater demand Developers can create and activate new microservices without prior coordination with others. Their adherence to MSA principles makes continuous delivery of new or modified services possible Greater modularity, looser coupling. Started in the web and mobile app world, moving to Enterprise. Big in media and startups Plan for flexibility rather than reuse
- #12: 7 mins. Each of the ovals represents a microservice. Each source of social media feeds has its own microservice which is specialised in interfacing with the relevant API. Each of those microservices passes messages to the ‘feed merge’ microservice which can then make them available for further microservices to work with. Communication between the microservices is over the network – they can be local to the same machine or distributed. Best practice is for each microservice to be stateless and to have its own database or schema
- #13: Individual microservices can be updated in isolation or even removed if their role is no longer needed
- #14: When a new role (or even a change to an existing one) appears, best practice is to implement a new microservice rather than extending an existing one.
- #15: When a new role (or even a change to an existing one) appears, best practice is to implement a new microservice rather than extending an existing one.
- #16: Microservices allow scale-out. Each type of microservice can be scaled independently – add extra instances just for the functions that are being overworked. Multiple instances of each service can provide High Availability
- #17: 9 mins
- #18: Fast > Elegant Sagrada Familia –1882-2026 (144 years). Frequent, localised changes Localised scaling Upgrades Only if: Scaling team Designing for change Fast is more important than elegant. Change in the application’s functionality and usage is frequent. Change occurs at different rates within the application, so functional isolation and simple integration are more important than module cohesiveness. Functionality is easily separated into simple, isolatable components. When you have the developer/DevOps skillsets. Where development org boundaries match service boundaries. Don’t forget that you’re building a distributed system -> complexity but there are precedents to read up on. One argument is that you shouldn’t bother with microservices unless you need either: - Scale your team - Design for change Sagrada Familia – designed by Gaudi; construction started on March 19, 1882. Expected to be finished in 2026.
- #19: 11 mins
- #26: 13 mins
- #27: Software containers Build an image containing the full application stack only once Spin up many containers from the same image in multiple environments Laptop, data center, cloud Development, QA, production, support Simple to use & efficient Contents of each container isolated from the others Storage, memory, namespace Constrain resources available to each container Storage, memory, CPU, IO
- #28: 16 mins The most popular container technology Simple to use and has a rich ecosystem 100,000+ images available from Docker Hub Including mongo hub.docker.com/_/mongo/ Syncs with GitHub projects Define new images built upon base images Define interfaces between containers LINUX, (and now) Windows, and OS X Runs on bare metal, VMs, and cloud. Cloud providers supply the Docker infrastructure (e.g. Google Container Engine)
- #33: Not best practice The ARG instruction defines a variable that users can pass at build-time to the builder with the docker build command using the --build-arg <varname>=<value> flag. The ENV instruction sets the environment variable <key> to the value <value>.The environment variables set using ENV will persist when a container is run from the resulting image.
- #35: 20 mins Microservices built by combining multiple containers Build sophisticated services from many small, focused processes (containers) Well defined APIs between components Each component can use different libraries, middleware & programming languages Modular, decoupled architecture simplifies maintenance and enables reuse Fault tolerant Scalable
- #36: 21 mins
- #37: 21 mins 3,6 Change Streams To do useful work, microservices need a way of communicating – Apache Kafka Kafka provides a flexible, scalable, and reliable method to distribute streams of event data from one or more **producers** to one or more **consumers**. Examples of **events** (or **messages**) include: A periodic sensor reading such as the current temperature A user adding an item to the shopping cart in an online store A Tweet being sent with a specific hashtag A log entry generated for each click in a web application Streams of Kafka events are organized into **topics**. A producer chooses a topic to send a given event to and consumers select which topics they pull events from. For example, a financial application could pull NYSE stock trades from one topic, and company financial announcements from another in order to look for trading opportunities. Kafka actually stores all of the messages that it passes around – this makes it ideal for production microservice deployments A microservice can be upgraded and then catch up on everything it missed Or even apply its updated business logic to the full history of events A new microservice can be added and it can be brought up to speed with everything that’s gone before If one service is generating more work than another can keep up with then Kafka operates as a buffer
- #38: To do useful work, microservices need a way of communicating – Apache Kafka Kafka provides a flexible, scalable, and reliable method to distribute streams of event data from one or more **producers** to one or more **consumers**. Examples of **events** (or **messages**) include: A periodic sensor reading such as the current temperature A user adding an item to the shopping cart in an online store A Tweet being sent with a specific hashtag A log entry generated for each click in a web application Streams of Kafka events are organized into **topics**. A producer chooses a topic to send a given event to and consumers select which topics they pull events from. For example, a financial application could pull NYSE stock trades from one topic, and company financial announcements from another in order to look for trading opportunities. Kafka actually stores all of the messages that it passes around – this makes it ideal for production microservice deployments A microservice can be upgraded and then catch up on everything it missed Or even apply its updated business logic to the full history of events A new microservice can be added and it can be brought up to speed with everything that’s gone before If one service is generating more work than another can keep up with then Kafka operates as a buffer
- #39: To do useful work, microservices need a way of communicating – Apache Kafka Kafka provides a flexible, scalable, and reliable method to distribute streams of event data from one or more **producers** to one or more **consumers**. Examples of **events** (or **messages**) include: A periodic sensor reading such as the current temperature A user adding an item to the shopping cart in an online store A Tweet being sent with a specific hashtag A log entry generated for each click in a web application Streams of Kafka events are organized into **topics**. A producer chooses a topic to send a given event to and consumers select which topics they pull events from. For example, a financial application could pull NYSE stock trades from one topic, and company financial announcements from another in order to look for trading opportunities. Kafka actually stores all of the messages that it passes around – this makes it ideal for production microservice deployments A microservice can be upgraded and then catch up on everything it missed Or even apply its updated business logic to the full history of events A new microservice can be added and it can be brought up to speed with everything that’s gone before If one service is generating more work than another can keep up with then Kafka operates as a buffer
- #40: To do useful work, microservices need a way of communicating – Apache Kafka Kafka provides a flexible, scalable, and reliable method to distribute streams of event data from one or more **producers** to one or more **consumers**. Examples of **events** (or **messages**) include: A periodic sensor reading such as the current temperature A user adding an item to the shopping cart in an online store A Tweet being sent with a specific hashtag A log entry generated for each click in a web application Streams of Kafka events are organized into **topics**. A producer chooses a topic to send a given event to and consumers select which topics they pull events from. For example, a financial application could pull NYSE stock trades from one topic, and company financial announcements from another in order to look for trading opportunities. Kafka actually stores all of the messages that it passes around – this makes it ideal for production microservice deployments A microservice can be upgraded and then catch up on everything it missed Or even apply its updated business logic to the full history of events A new microservice can be added and it can be brought up to speed with everything that’s gone before If one service is generating more work than another can keep up with then Kafka operates as a buffer
- #41: To do useful work, microservices need a way of communicating – Apache Kafka Kafka provides a flexible, scalable, and reliable method to distribute streams of event data from one or more **producers** to one or more **consumers**. Examples of **events** (or **messages**) include: A periodic sensor reading such as the current temperature A user adding an item to the shopping cart in an online store A Tweet being sent with a specific hashtag A log entry generated for each click in a web application Streams of Kafka events are organized into **topics**. A producer chooses a topic to send a given event to and consumers select which topics they pull events from. For example, a financial application could pull NYSE stock trades from one topic, and company financial announcements from another in order to look for trading opportunities. Kafka actually stores all of the messages that it passes around – this makes it ideal for production microservice deployments A microservice can be upgraded and then catch up on everything it missed Or even apply its updated business logic to the full history of events A new microservice can be added and it can be brought up to speed with everything that’s gone before If one service is generating more work than another can keep up with then Kafka operates as a buffer
- #42: 23 mins
- #43: 23 mins Cloud Native Computing Foundation Created by Google, feature-rich and widely adopted Automated container deployment and ‘replication’ On-line scale out/in Rolling upgrades HA – automatic rescheduling of failed containers Exposure of network ports to external apps Load balancing over groups of containers providing a service Provided as a service by Google Compute Engine
- #44: 25.5 mins
- #48: 27.5 mins
- #49: 29.5 mins Kubernetes. Single Pod/comtainer/mongod in a ReplicationController. Use external IP addresses (other IP addresses & hostnames are local to Kubernetes cluster and they change) Refer to white paper for details
- #50: 31 mins
- #51: 31.5 mins
- #52: 33.5 mins
- #53: 35.5 mins
- #54: 36.5 mins Gap (flexibility): Monolith -> microservice (75 days). New types of PO took just days FuboTV (scalability). Single cluster for dev, QA + production. Cope with 100x bursts. Run MongoDB on Kubernetes Otto (arch == org). Fast, iterative delivery Backcountry (> distributed dev team): Schema changes were taking 20% of dev time. Flexible schema Compare The Market (Use Docker, Kafka, MongoDB & Ops Manager). GAP moved their purchase order system from a monolith architecture to microservices. Due to MongoDB’s flexible schema, it took just 75 days to build the new system. When requirements changed and they had to add new types of purchase orders, it took days instead of months. FuboTV is a North American soccer streaming service. Using Microservices with Kubernetes, Docker & MongoDB. Isolation means that they can use a single cluster of machines (in Google Cloud) for dev, QA & production. Very birsty application – scalability lets them handle 100x increases in traffic. Otto – the key was to have an architecture that fits with their organization. Microservices empower loosely couple development teams (business, project management, IT). This is all enabling Fast test & deployment + Iterative, Continuous Delivery Backcountry.com is an online specialty retailer that sells outdoor clothing and gear. The driver to Microservices for them was a growing, distributed development team. As more and more developers joined and made contributions to the code, the schemas became convoluted and harder to maintain; contributing to 20% of the Scrum backlog. Taking advantage of MongoDB’s flexible data model, Backcountry was able to iterate faster, reduce development time, and mitigate technical debt. Compare The Market: In the cloud, each microservice, or logical grouping of related microservices, is provisioned with its own MongoDB replica set running in Encrypted storage engine to further reduce our security-related surface area. Use Docker, Kafka & MongoDB.