Python in Containers

Focused View

Kris Celmer

23:47:16

6 View

1-Introduction

01-Course Introduction and Agenda Overview.mp4

10:46

02-The Concept of Linux Containers.mp4

10:08

03-Containers Explained.mp4

15:11

04-Build, Ship, Run.mp4

08:45

05-Introduction to Docker.mp4

11:48

06-Ecosystem of Container Technologies.mp4

05:12

07-Introduction to Container Orchestration.mp4

08:49

08-Python App in Docker Container.mp4

11:06

09-Shipping the Image to Docker Hub.mp4

01:47

10-Running our App in Various Environments.mp4

12:36

2-Docker Deep Dive

11-Installing Docker for a Developer.mp4

04:41

12-Create Docker ID.mp4

01:33

13-Play with Docker.mp4

07:33

14-Install Docker on Ubuntu.mp4

09:16

15-Install Docker on CentOS.mp4

08:58

16-Docker on Linux - Security Warning.mp4

05:44

17-Docker Desktop on Windows Pro.mp4

13:38

18-Introduction to Windows Containers.mp4

03:52

19-Docker Desktop on MacOS.mp4

13:17

20-Docker Toolbox for Windows Home.mp4

07:24

21-Running Containers with Docker.mp4

10:37

22-Integrating Containers with a Host System.mp4

15:50

23-Container Images.mp4

13:40

24-Managing Containers.mp4

14:06

25-Running Multiple Containers.mp4

15:04

26-Container Networking.mp4

14:03

27-Data Persistency - Volumes.mp4

08:40

28-Dockerfile Introduction.mp4

10:17

29-Docker Hub Introduction.mp4

10:32

30-Python Base Images.mp4

07:54

31-Docker GUIs Part 1 - Kitematic.mp4

07:14

32-Docker GUIs Part 2 - Portainer.mp4

27:54

33-Docker Machine Overview.mp4

02:55

34-Docker Machine with VirtualBox.mp4

20:25

35-Docker Machine with Hyper-V.mp4

07:33

36-Docker Machine on AWS Cloud Hosts.mp4

19:23

37-Docker Machine on Google Cloud Hosts.mp4

11:16

3-Build Container Images

38-Elements of Containerized Python Project.mp4

07:36

39-Lifecycle of Containerized Python Project.mp4

17:38

40-Design Principles for Containerized Python Apps.mp4

20:46

41-Manual Image Build Process.mp4

09:25

42-Dockerfile - Automation of Image Build.mp4

13:39

43-Dockerfile Commands - Introduction and FROM.mp4

09:10

44-Dockerfile Commands - WORKDIR, COPY, ADD.mp4

11:14

45-Dockerfile Commands - RUN.mp4

12:44

46-Dockerfile Commands - ENV, LABEL, USER.mp4

08:26

47-Dockerfile Commands - VOLUME and EXPOSE.mp4

13:10

48-Dockerfile Commands - ENTRYPOINT and CMD.mp4

21:47

49-Parametrizing Dockerfiles with ARG.mp4

09:22

50-Building and Running Reusable Images.mp4

09:12

51-Build time versus Run time Execution.mp4

18:10

52-Building smaller Images.mp4

11:59

53-Multistage Image Build.mp4

14:14

54-Building Custom Python Images.mp4

08:25

55-Build Base Images from Scratch.mp4

17:57

56-Dockerizing PyTest and Pdb - Simple Case.mp4

12:46

57-Django Containerization for Development.mp4

08:11

58-Django Containerization for Production.mp4

15:20

59-Application Servers to Run Django and Flask.mp4

08:28

60-Production--grade Database Engine - PostgreSQL.mp4

19:07

61-Production--grade Database Engine - MariaDB.mp4

07:57

62-Implementing Proxy Server.mp4

15:41

63-The need of Automation.mp4

05:14

4-Ship Containers

64-Shipping Images.mp4

13:12

65-Image Registries and Repositories.mp4

21:20

66-Review of Key Cloud Registries.mp4

09:05

67-Review of Local Registry Technologies.mp4

19:47

68-GitHub and Docker Hub Integration.mp4

19:35

69-GitLab Container Image Build Workflow.mp4

11:07

70-Vulnerability Scanning of Images.mp4

11:57

5-Run Containers in Docker

71-Running Production Containers in Docker.mp4

06:45

72-Docker Compose - Introduction.mp4

15:54

73-Docker Compose File - Version and Volumes.mp4

11:18

74-Docker Compose File - Networks.mp4

10:45

75-Docker Compose File - Services.mp4

23:20

76-Managing Images with Docker Compose.mp4

14:48

77-Application Lifecycle with Docker Compose - Part 1.mp4

10:59

78-Application Lifecycle with Docker Compose - Part 2.mp4

17:48

79-Introduction to Docker Swarm.mp4

14:00

80-Provisioning Swarm with Docker Machine.mp4

05:56

81-Standalone Containers in Swarm.mp4

11:42

82-Services in Swarm.mp4

18:56

83-Service Modes and Ingress Routing Mesh.mp4

16:39

84-Application Stack in Swarm - Part 1.mp4

17:40

85-Application Stack in Swarm - Part 2.mp4

06:33

86-Application Environment in Swarm - Part 1.mp4

21:35

87-Application Environment in Swarm - Part 2.mp4

20:30

88-Application Lifecycle in Swarm.mp4

18:49

89-Summary of Docker Runtime Environment.mp4

03:10

6-Run Containers in Kubernetes

90-Introduction to Kubernetes.mp4

10:04

91-Helicopter View of Kubernetes as the Application Platform.mp4

17:34

92-Installing a Small Kubernetes Cluster.mp4

10:03

93-Running Simple Application in Minikube.mp4

23:07

94-Deployment of Multi-Container Application in Minikube - Part 1.mp4

14:56

95-Deployment of Multi-Container Application in Minikube - Part 2.mp4

20:33

96-Pod Controllers Part 1 - Introduction and ReplicaSet.mp4

19:22

97-Pod Controllers Part 2- Deployment.mp4

19:31

98-Pod Controllers Part 3 - StatefulSet, DaemonSet.mp4

14:05

99-Pod Controllers Part4 - Job, CronJob.mp4

16:47

100-Services.mp4

17:19

101-Volumes.mp4

24:14

102-Deploying a Multi-Container Application in Google Kubernetes Engine.mp4

24:35

103-Application Environment in Kubernetes.mp4

20:25

7-Data Science & Machine Learning in Containers

104-Section Introduction & Overview.mp4

04:07

105-Containers in Research & Experimentation.mp4

10:50

106-Machine Learning in Production.mp4

09:05

107-Jupyter Notebook in Docker.mp4

08:52

108-Run Python Code in Jupyter Container.mp4

08:04

109-Data Science in Jupyter Container.mp4

06:35

110-TensorFlow in Containers.mp4

07:15

111-MNIST Classification Models in Tensorflow Container.mp4

04:27

112-Tensorflow Serving - Prediction Example.mp4

10:23

113-Object Detection in TensorFlow Container.mp4

07:07

114-NVIDIA GPU and Docker.mp4

07:41

Description

Docker and Kubernetes are must-have skills for Python engineers these days. Whether your focus is on machine learning and data science or you use Python as a general programming language, you must understand Docker and Kubernetes, as they form the basis of modern cloud-native applications built using microservice architectures. In this course, you’ll learn to do the following: • Develop and explore machine learning, data science, and Jupyter Notebooks in Docker • Run machine learning models in production with Kubernetes and Docker Swarm • Package your Python code into containers • Publish your containers in image registries • Deploy containers to production, both in Docker and Kubernetes • Build highly modular, container-based services in a microservices way • Monitor and maintain containerized apps You can use the course in two ways: • If you use Python for machine learning and data science, go top-down - start with section 7 to quickly develop practical Docker skills and use sections 2 to 6 to delve deeper into specific container topics • If you want to use Python for building web apps and microservices, try the bottom-up approach - use the course in a linear way All the resource files are uploaded on the GitHub repository at https://github.com/PacktPublishing/Python-in-Containers

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Python

Docker

Kris Celmer

Instructor's Courses

Kris Celmer is a Cloud Architect and has worked with many companies across Europe, Asia, and Africa, helping them to shape their private, public, and Telco clouds. He supports his customers in architecting cloud solutions, but also in the business aspects of cloud transformation. He has 25+ years' experience in the IT Industry, working at companies such as Sun Microsystems, NetApp, Citrix, and Huawei.

PacktPub

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Packt is a publishing company founded in 2003 headquartered in Birmingham, UK, with offices in Mumbai, India. Packt primarily publishes print and electronic books and videos relating to information technology, including programming, web design, data analysis and hardware.