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Docker and kubernetes
Docker allows building portable software that can run anywhere by packaging an application and its dependencies in a standardized unit called a container. Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery. Kubernetes can replicate containers, provide load balancing, coordinate updates between containers, and ensure availability. Defining applications as Kubernetes resources allows them to be deployed and updated easily across a cluster.
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Introduction of presenter and organization. Focus on Docker and Kubernetes as technologies.
Overview of Big Data Tech. Lab's groups and cloud technologies like Docker, Kubernetes, AWS, etc.
Docker allows portable software development and deployment using Kubernetes for orchestration.
Explains Docker’s advantages in avoiding dependency issues during software development.
Details on Docker containers, images, and isolation through Linux namespaces and file systems.
Explains layer sharing in Docker images and the example of stacking Docker images.
Wrap up on technologies enabling Docker and mention of topics not covered in the presentation.
Introduction to Kubernetes, its functions, and the benefits of using it with Docker.
Utilizing Kubernetes for service deployment to minimize human effort and ensure scalability.
Detailed explanation on how to replicate services and manage container health checks with Kubernetes.
Example of a PdM Kubernetes cluster and the overall conclusion of Docker and Kubernetes benefits.
Presentation closure and key takeaways from Docker and Kubernetes technology discussion.
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Docker and kubernetes
- 1. Docker & Kubernetes DongwonKim, PhD Big Data Tech. Lab SK Telecom
- 2. Big Data Tech.Lab in SK telecom • Discovery Group • Predictive Maintenance Group • Manufacturing Solution Group • Groups making own solutions • Technology and Architecture Leading Group • Big data processing engine • Advanced analytics algorithms • Systematize service deployment and service operation on cluster • Docker • Kubernetes
- 3. Prepare for anera of cloud with Docker and Kubernetes oracle ubuntu cloud Major technologies Docker Kubernetes Amazon Web Service Microsoft azure Cloud technologies for service providers icloud Cloud services for users one drive dropbox google drive Trend - Buy both SW & HW - Buy HW and DIY - Run your SW on cloud Ubiquitous cloud services around us Enabling technologies for custom cloud services * technology trend in USA (2004-2017)
- 4. Overview & Conclusion •Docker to build portable software • Build your software upon Docker • Then distribute it anywhere (even on MS Azure and Amazon Web Service) • Kubernetes to orchestrate multiple Docker instances • Start using Docker and Kubernetes before too late! • Google has been using container technologies more than 10 years Docker Kubernetes Hadoop The Enterprise IT Adoption CyclePopularity of Docker and Kubernetes
- 5. Docker Motivation Enabling technologies forDocker How to use Docker
- 6. Docker came tosave us from the dependency hell Docker Dependency hell Portable software
- 7. Dependency hell Development environment Production environment Your program program1 v2 program2 v2 program3 v2 dependson Your program program1 v2 program2 v2 program3 v2 depends on depends on Customer program program1 v1 program2 v1 program3 v1 conflict! Package manager Package manager
- 8. Few choices leftto you 1. Convince your customer (a.k.a. 甲) 2. Install all the dependencies manually (without the package manager) 3. Modify your program to make it depend v1
- 9. Docker container Package managerin host OS Use Docker for isolating your application Package manager in guest OS Your program program1 v2 program2 v2 program3 v2 depends ondepends on Customer program program1 v1 program2 v1 program3 v1 Host operating system Linux kernel must be ≥3.10 (such as Ubuntu 14.04 and CentOS 7) Docker engine (daemon)
- 10. Virtual machines anddocker containers Host Operating System Kernel Hypervisor Docker engine Virtual machines Docker containers Device drivers Host Operating System Kernel Device drivers CentOS-like container yum Libraries App Ubuntu-like container apt App Libraries CentOS virtual machine Kernel Device drivers yum Libraries App Ubuntu virtual machine Kernel apt App Libraries Device drivers Containers share the kernel in the host
- 11. Linux namespaces –what makes isolated environments in a host OS Host Operating System Docker engine Container pid ipc uts net mnt user Various ipc objects - POSIX message queue - SystemV IPC objects (mq, sem, shm) System identifiers - hostname - NIS domain name Network devices - Network devices - IPv4, IPv6 stacks - Routing tables, Firewall Mount points (directory hierarchy) Security-related identifiers - User IDs - Group IDs Process ID number space (staring from 1) Container pid ipc uts net mnt user Container pid ipc uts net mnt user Six namespaces are enough to give an illusion of running inside a virtual machine
- 12. Analogy between programand docker Dockerfile Docker image (read-only layers) Docker container (read-only layers + writable layer) Source code Byte/machine code (read only) Process (read only) text data heap stack compile execute build run Program Docker
- 13. How to definean image and run a container from it? 1) Write Dockerfile - Specify to install python with pip on ubuntu - Tell pip to install numpy 2) Build an image from Dockerfile - Execute each line of Dockerfile to build an image 3) Execute a Docker container from the image
- 14. 1 to Nrelationship between image and container Execute five containers from an image Q) Five containers take up 2,445MB (=489MB*5) in the host? A) No due to image layering & sharing
- 15. Images consists oflayers each of which is a set of files • Instructions (FROM, RUN, CMD, etc) create layers • Base images (imported by “FROM”) also consist of layers • If a file exists in multiple layers, the one in the upper layer is seen Dockerfile Base ubuntu image Layer (apt-get install python-dev python-pip) Layer (pip install numpy) Layer Layer (files) Layer (files) Layer (files) Image
- 16. Docker container • Acontainer is just a thin read/write layer • base images are not copied to containers • Copy-On-Write (COW) • When a file in the base image is modified, • copy the file to the R/W layer • and then modify the copied file
- 17. Image sharing betweencontainers ubuntu:15.04 image (~188MB) does not copied to all containers
- 18. Layer sharing betweenimages If multiple Dockerfiles 1. start from the same base image 2. share a sequence of instructions (one RUN instruction in a below example) , then docker engine automatically reuses existing layers numpy Dockerfile matplotlib Dockerfile
- 19. Example of stackingdocker images Kafka broker PdM engine kafka (with scala) Zookeeper container Kafka container PdM engine (librdkafka, avro, flask) cuda PdM engine (librdkafka, avro, flask) scipy (numpy, scipy, matplotlib, ipython, jupyter, pandas, scikit-learn, h5py) theano-gpu (theano, keras) theano-cpu (theano, keras) openjdk:8 zookeeper buildpack-deps:jessie python:2.7 buildpack-deps:jessie-curl official official official official Zookeeper cluster zk zk zkzk zk broker broker broker Kafka consumer Kafka producer Web server scipy libraries has nothing to do with GPU, so share it theano compiles its expression graphs into CPU/GPU instructions PdM container (cpu) PdM container (gpu) buildpack-deps:jessie-scm debian:jessie official official jessie is the latest, stable Debian release buildpack-deps contains essential tools to download/compile softwares
- 20. Enabling technologies fordocker (wrap-up) • Linux namespaces (covered) • To isolate system resources • pid, net, ipc, mnt, uts, user • It makes a secure & isolate environment (like a VM) • Advanced multi-layer unification File System (covered) • Image layering & sharing • Linux control groups (not covered) • To track, limit, and isolate resources • CPU, memory, network, and IO * https://mairin.wordpress.com/2011/05/13/ideas-for-a-cgroups-ui/
- 21. Docker topics notcovered here • How to install Docker engine • What are the docker instructions other than FROM, RUN, and CMD • ENV / ADD / ENTRYPOINT / LABEL / EXPOSE / COPY / VOLUME / WORKDIR / ONBUILD • How to push local Docker images to docker hub • How to pull remote images from docker hub • ... Consult with https://docs.docker.com/engine/getstarted/
- 22.
- 23. Disclaimer • The purposeof this section is to briefly explain Kubernetes without details • For a detailed explanation with the exact Kubernetes terminology, see the following slide • https://www.slideshare.net/ssuser6bb12d/kubernetes-introduction- 71846110
- 24. What is Kubernetesfor? Container-based virtualization + Container orchestration To satisfy common needs in production replicating application instances naming and discovery load balancing horizontal auto-scaling co-locating helper processes mounting storage systems distributing secrets application health checking rolling updates resource monitoring log access and ingestion ... from the official site : https://kubernetes.io/docs/whatisk8s/
- 25. Why Docker withKubernetes? • A mission of our group • Systematize service deployment and service operation on cluster • I believe that systematizing smth. is to minimize human efforts on smth. • How to minimize human efforts on service deployment? • Make software portable using a container technology • Docker (chosen for its maturity and popularity) • Rkt from CoreOS (alternative) • Build images and run containers anywhere • Your laptop, servers, on-premise clusters, even cloud • How to minimize human efforts on service operation? • Inform a container orchestration runtime of service specification • Kubernetes from Google (chosen for its maturity and expressivity) • Docker swarm from Docker • Define your specification and then the runtime operates your services as you wish
- 26. Kubernetes architecture Server - RESTAPI server with a K/V store - Scheduler - Find suitable machines for containers - Controller manager - Current state Desired state - Make changes if states go undesirable Service specification (written in yaml) - Execute a web-server image - Two replicas for LB & HA - 3GB memory each Docker engine Node agent container (3GB) Docker engine Node agent container (3GB) Docker engine Node agent container (3GB) Ensure a specified # of replicas running all the time
- 27. Web server example node2 webserver node 1 webserver node 3 webserver Want to launch 3 replicas for high availability and load balancing How to achieve the followings? • Users must be unaware of the replicas • Traffic is evenly distributed to replicas webserver 4bp80 webserver 6dk12 webserver g1sdf a well-known address It’s a piece of cake with Kubernetes!
- 28. How to replicateyour service instances node 2 webserver 6dk12 node 1 webserver 4bp80 node 3 webserver g1sdfapp=web1 app=web1 app=web1 Server Node agent Node agent Node agent Docker engine Docker engine Docker engine Specify your Docker image and a replication factor using Deployment Specify a common label to group containers with different names
- 29. node 2node 1node 3 Define a service to do round-robin forwarding Server <service> webserver:80 webserver 6dk12 webserver 4bp80 webserver g1sdfapp=web1 app=web1 app=web1 33% 33% 33% <ingress> metatron:80 External traffic over internet Internal traffic Kubernetes runs its own DNS server for name resolution Kubernetes manipulates iptables on each node to proxy traffic
- 30. Kubernetes How to guaranteea certain # of running containers during maintenance node1 zk-0 Containers Volumes node2 zk-2 Containers Volumes node3 zk-3 Containers Volumes Drain node1 Operation is permitted because allowed-disruptions=1 Kubernetes Drain node2 3 replicas have to be running due to StatefulSet, so try scheduling zk-0 on other nodes! Oops! cannot schedule zk-0 on node2 and node3 due to anti-affinity! Operation not permitted because allowed-disruptions=0 (Note that minAvailable=2) Please wait until node1 is up and zk-0 is rescheduled! node1 zk-0 Containers Volumes node2 zk-2 Containers Volumes node3 zk-3 Containers Volumes Define disruption budget to specify requirement for the minimum available containers Hold on for a while
- 31. PdM Kubernetes cluster Zookeeperheadless service Kafka headless service PdM service QuorumPeer Main QuorumPeer Main QuorumPeer Main Pod Pod Pod Kafka (broker) Kafka (broker) Kafka (broker) Pod Pod Pod2181 2888 3888 2181 2888 3888 2181 2888 3888 9092 9092 9092 Statefulset Statefulset PdM engine Kafka consumer Kafka producer Web server Pod (Deployment) Ingress rule 8080 Persistent storage Attached volume Volume 80
- 32. Overview & Conclusion •Docker to build portable software • Build your software upon Docker • Then distribute it anywhere (even on MS Azure and AWS) • Kubernetes to orchestrate multiple Docker instances • Start using Docker and Kubernetes before too late! • Google has been using container technologies more than 10 years Docker Kubernetes Hadoop The Enterprise IT Adoption CyclePopularity of Docker and Kubernetes
- 33.