Turn-key Kubernetes with data visualization and analytics
(Ed.–This post covers 1 of 3 related tutorials you can do around Kubernetes-based application development. The author mentions the other two–on creating a highly scalable web app, and on establishing a DevOps pipeline–after discussing the tutorial on setting up visualization of app log data.)
Monitoring or diagnosing performance or errors with your applications, containers, Kubernetes pods or workers doesn’t have to be challenge. IBM Cloud delivers a set of integrated tools to remove this hurdle, even for a user that has little experience managing clusters. These tools provide a single pane of glass to manage application activity and health across multiple clusters, compute options and/or regions.
Follow this tutorial to go from scratch to having an application running in a cloud-hosted Kubernetes cluster with built-in industry standard open source tools for log aggregation, data visualization, monitoring and alerting.
Once you’ve created your cluster on IBM Cloud (you can do that here), this tutorial should take you no more than 30 minutes.
Along with this current tutorial, there are two others that build on each other:
Scalable web app on Kubernetes gets guides you through deploying and scaling a web app. While you’re at it, consider what’s involved in adding a chatbot to that web experience; here’s how online-only banker UBank did it.
Continuous deployment on Kubernetes sets you up with a DevOps pipeline.
You can start with any of them but, if you have no other preference, I would recommend doing them in sequence, top to bottom.
This current solution starts off by using the IBM Cloud Developer Tools to generate a starter application. No need to program your own yml files or Helm Charts. The starters come preconfigured ready to use as-is or customize them to your liking. Push the containerized application image to a IBM Cloud Container Registry and create a Kubernetes deployment in one single command.
Then, stand up your Log Analysis and Monitoring services which ingests data from your cluster. These services are meant to be used with Kubernetes clusters, Cloud Foundry or Virtual Servers. When your application architecture is composed of several microservices, this provides a single dashboard to analyze logs or metrics across all your microservices. Keep in mind that data can also be sent from outside of IBM-Cloud. This scales well to architecture that span across multi-clouds or hybrid environments.
Try it today
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