Build and automate your machine learning application with docker and jenkins
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This document discusses using Docker and Jenkins to automate machine learning application deployment. It introduces Docker as a tool to create isolated environments for applications using containers. Benefits of Docker include consistent environments, portability, and easy scaling. The document demonstrates building a ML application Docker image. It then introduces Jenkins as an open-source automation server that facilitates continuous integration and delivery. Jenkins allows automating build, test and deployment tasks through jobs and pipelines. Feedback is welcomed.
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Build and automate your machine learning application with docker and jenkins
- 1. Build and automate your machine learning application with docker and Jenkins Presented By: Shubham Goyal Data Scientist Knoldus Inc. & MachineX Intelligence
- 2. Agenda Knoldus Introduction What is docker and its benefits Deploy a ML application with Docker What is Jenkins and its benefits
- 3. We are a team of Data Scientist and engineers with a product mindset who deliver competitive business advantage. Who are we?
- 4. Our Global Presence Years of Profitable Growth Reactive products, Fast Data strategy, AI Toronto, Chicago, Singapore, New Delhi, Pune Multi-year Global Customers
- 5. Our Partners Through our strategic partnerships, we have an unwavering commitment to equip your organization with the knowledge, skills, expertise, resources and tools to succeed.
- 6. REACTIVE PRODUCTS Microservices & API ● Scala ● Functional Java ● Rust ● Elixir ● Haskell ENTERPRISE DATA PROGRAM Data Lake ● Delta ARTIFICIAL INTELLIGENCE Machine Learning Data Science Deep Learning ● Knime ● Tensorflow ● PyTorch ● Scikit BLOCKCHAIN ● Hyperledger ● DAML ● ScoreX Knoldus Practice Areas Fast Data ● Spark ● FLink ● Hadoop Agile Transformation Reactive UI/UX Test Automation Practice Reactive DevOps Product Engineering
- 7. 7 About Knoldus MachineX MachineX is a group of data wizards. We are a team of Data Scientist and engineers with a product mindset who deliver competitive business advantage.
- 8. Knoldus MachineX Offerings Natural Language Processing Computer Vision Solutions Data mining Chatbot Development Artificial intelligence research and solutions
- 9. 9 Enable organizations to capture new value and business capabilities Innovation Labs Consistently blogging, to share our knowledge, research Blogs Knime, Deeplearning, Coursera, Stanford certified professionals Certifications Insight & perspective to help you to make right business decisions TOK Sessions It’s great to contribute back to the community. We continuously advance open source technologies to meet demanding business requirements. Open Source Contribution
- 10. Problem? Ever deployed a Machine Learning model that works perfectly fine on your computer locally but then the code breaks on another machine or worse when it’s been deployed into production?
- 11. Docker
- 12. What is Docker? Docker is a tool that makes it easier to create, deploy, and run any application by using what is called a container. It’s also a software platform, which is used to create Docker images that will be referred to as a Docker container once it’s been deployed.
- 13. What is Docker container? A Docker Container is an isolated environment which contains all the required dependencies for your application to run, it is often referred to as a running instance of a Docker image.
- 14. What is Docker Image? A Docker image is a file(read-only), comprised of multiple layers, that is used to execute code in a Docker container. Docker images are found in a large hub which is referred to as Docker Hub. So you pull images from the hub or you build a custom image from a base image and when these images are being executed they serve as containers for your application.
- 15. Combine the pieces together A Software platform which makes it easier to create and deploy any application by creating a Docker image which will then be a Docker container which contains all the dependencies and packages we need for our application to work once it’s been deployed.
- 16. Benefits of docker ● Docker solves the problem of having an identical environment across various stages of development and having isolated environments in your individual applications. ● Docker allows you to run your application from anywhere as long as you have docker installed on that machine. ● Docker gives you the liberty to scale up quickly. ● Expand your development team painlessly.
- 17. Let's create our ML application with Docker
- 18. Problem? Let’s paint a scenario ● You're working on a Data Science project and at first, you had a model accuracy of 80%, you deploy that application to production serving it as an API using Flask. ● Your make some changes in the model’s parameters for better accuracy. ● Now you plan to deploy this model and you have to go through the trouble of building, testing and deploying the model to production again
- 19. What is Jenkins? Jenkins is a free and open-source automation server. It helps automate the parts of software development related to building, testing, and deploying, facilitating continuous integration and continuous delivery - Wikipedia
- 20. Benefits of Jenkins ● It is Open Source ● Easy to use and install ● A large number of plugins that fit into a DevOps environment ● Spend more time on your code and less time on deployment ● Massive community
- 21. Jenkins Job A Jenkins job simply refers to runnable tasks that are controlled by Jenkins.
- 22. Jenkins Pipeline A pipeline is running a collection of jobs following a particular order or sequence Types of Jenkins Pipeline: ● Declarative pipeline ● Scripted pipeline