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Use Kubernetes to deploy a Microservice architecture. Try Udemy for Business. Deploy containers to a Kubenetes Cluster. Run Kubernetes in AWS using the Kops management tool.
Use Kubernetes to deploy a Microservice architecture. You'll deploy, manage and monitor a live Kubernetes cluster. Monitor a live Kubernetes cluster using Prometheus and Grafana. Handle Alerts in a Kubernetes cluster by notifying Slack Channels. Understand how Requests and Limits work in Kubernetes. Use Kubernetes Horizontal Pod Autoscaling.
Manage and deploy containers in Kubernetes. Explore Kubernetes platforms such as pods, deployments, replica sets and secrets. This video shows the very first steps on deploying a microservice on Kubernetes and also covers some required core principles. Learn about Pods and Nodes. Use both the kubectl (CLI) and Kubernetes dashboard. Set up and use a modern DevOps workflow that takes care of updating existing deployments when new code is checked into the source code repo. Configure and update services after they've been deployed. Define a Pod using a YAML definition. Use kubectl to list and manage Pods. Deploying a Microservice.
Try Udemy for Business. Create And Configure Kubernetes Cluster Using Kops. Deploying A Sample Microservice Application On Kong And Kubernetes. Setup Microservices Using Kong, Docker And Kubernetes. Expand all24 lectures 02:56:08.
Scalable Microservices with Kubernetes. Deploying Microservices. Go beyond the theoretical concepts and try out Kubernetes so that you can use it to manage real world apps. Prerequisites and Requirements. by. Enhance your skill set and boost your hirability through innovative, independent learning.
Much like microservices themselves, containers have been gaining ground in recent years as an indispensable part of the modern scalable architecture. As with microservices, containers have caught on because they provide real benefits to the development process: they’re dependable, scale easily, and provide a nice abstraction that isolates the core component of your web services. In particular, one containerization technology has taken off far above the rest
Kubernetes Microservices. By FCL Last updated Sep 1, 2019. Get hands-on experience of deploying and monitoring production quality Microservice architectures to the AWS cloud.
Kubernetes Microservices. Monitor a live cluster using Prometheus and Grafana. CFFJune 2, 2019November 16, 20190. The system is a Microservice based architecture, and along the way we’ll look at design decisions and trade-offs you need to make when managing these complex systems
Kubernetes Microservices. The system is a Microservice based architecture, and along the way we’ll look at design decisions and trade-offs you need to make when managing these complex systems. Note the course isn’t about how to design Microservices (although we’ll certainly be talking about that); the development work is done and we need to get the system running on a production cluster.
Kubernetes Microservices (Udemy). If you are interested in gaining one of the one of the most sought after skills nowadays then this certification is worth a look. Throughout the classes, you will have the opportunity to work on realistic requirements. Learn to deploy containers to a cluster, monitor a live cluster using Prometheus and Grafana, handle alerts and much more. The lessons have been designed in such a way so that they can be useful for both experienced as well as new learners. The lectures guide you through all the necessary topics required to handle the tools used.
The objective of this course of Introduction to Microservices for Data Science is to introduce you to the new DevOps tools .
The objective of this course of Introduction to Microservices for Data Science is to introduce you to the new DevOps tools for deploying Machine Learning models in a Big Data productive environment. In this course you will learn both the theory and the basic practice that will allow you to understand and apply these new methodologies. We will work with Python, Scikit-Learn, Flask, Docker, Kubernetes and Jenkins, but no previous knowledge is necessary to enjoy this course.
Kubernetes (also known as “K8S”) is one of the hottest topics right now, and engineers with K8S skills are in big demand.
Get those skills with this course! It’s is a great chance to work on a real K8S project, and to get yourself to a high professional standard on real projects.
All the way through the course you’ll be working on realistic requirements – but you don’t need to be a coder or know any particular programming language – I’ve prepared for you a set of Docker images, and your job is to use Kubernetes to get these images running.
The system is a Microservice based architecture, and along the way we’ll look at design decisions and trade-offs you need to make when managing these complex systems. Note the course isn’t about how to design Microservices (although we’ll certainly be talking about that); the development work is done and we need to get the system running on a production cluster.
We’ll also discover that the developers have made some bad mistakes in their code, by analysing the run time performance of the cluster!
You can do the first part of the course on your local development computer (PC/Mac/Laptop). The second part (from Chapter 13 onwards) moves to the cloud. You’ll use a real AWS account, and we go ahead to set up monitoring with the ELK/Elastic Stack and monitor with Prometheus and Grafana.
I’ve designed this course for a wide audience – whether you’re a DevOps engineer, a developer or if you’re quite new to the whole field, I’ll explain everything along the way. Just some basic knowledge of working with computers, and maybe a bit of command line experience will suffice.
You will need an AWS account for chapters 13-17 if you want to work on the system yourself. If you’re new to AWS then don’t worry, I’ve got you covered -but Amazon will charge you for running the system (as with all/most cloud providers). Expect to pay no more than around 10USD for this (this is a safe overestimate), but you are expected to manage this spend yourself and you must delete your Kubernetes cluster at the end of your session. Don’t let that put you off, it’s a great investment.
Who this course is for:
Anyone wanting to use Kubernetes on live production projects
We will be using AWS in the later sections of the course (optional); all AWS concepts are explained so this is a great start if you’re new to the cloud, but be aware that AWS do charge for usage.
Some previous knowledge of Docker is useful, but an overview is provided as part of the course
Previous knowledge of AWS is useful for the later sections of the course; however all the concepts are explained in detail and this would serve as a great first project on AWS
We’ll be using the terminal throughout the course so some (basic) familiarity of terminal operations is assumed
Last updated 12/2018