
Explore a devops toolchain using AWS ECS for Kubernetes, Ghost deployment with Helm and Argo CD, and monitoring with Prometheus and Grafana, plus Splunk and Fluentbit for logs.
Install chocolatey, helm, kubectl, and aws cli to provision an EKS cluster; configure IAM user, and set up EBS and EFS storage with kubeconfig for local access.
Create EFS and EBS storage classes for the EKS cluster, configure the EFS file system and security groups, and establish Argo and app namespaces for GitOps deployment.
Deploy a Ghost blog with a Helm chart using Argo CD, enabling git-synced, self-healing deployments and monitoring Ghost MySQL metrics with Prometheus, Grafana, and Slack alerts.
Map your Ghost app running on AWS ELB to a custom domain using No-ip’s free subdomain, create a CNAME pointing to the Ghost ELB, and test DNS propagation.
Explore Ghost features, access the admin dashboard, create posts with the editor, collaborate with a team, customize themes, and optimize SEO with analytics and email newsletters.
Install and configure Prometheus on EKS to scrape MySQL metrics on port 9104 using a Bitnami Prometheus helm chart, with Grafana, Argo CD, and GitOps integration.
Learn to integrate Grafana with Slack for real-time alerts by creating a Slack app, obtaining a bot token, and testing a Grafana contact point in the DevOps SRE project channel.
Set up a real-time alert in Grafana to detect drop table events in MySQL and notify via Slack, enabling proactive observability and defensive response.
Deploy Splunk in Kubernetes by using Helm charts for the Splunk operator and Splunk Enterprise, configure GP2 CSI storage with EBS, and expose a public load balancer for user access.
Update fluentbit to stream ghost logs from the shared NFS volume to Splunk using a tail input, ghost tag, Splunk output with TLS and token, and a JSON filter.
Analyze json logs in Splunk to search Ghost CMS post updates, using automatic field extraction, filtering http put requests with status 200 to confirm health.
Explore advanced Splunk queries against ghost logs shipped by Fluentbit to classify errors with eval on status codes 400+ and create dashboards and alerts for application traffic.
Build a Splunk dashboard named ghost application health dashboard with a status-code pie chart (200, 400, 404, 500) and a top URLs table to monitor application health and spot anomalies.
Configure a dedicated Splunk alerts Slack app and incoming webhook to send real-time alerts to the DevOps SRE project channel, then restart the Splunk pod to apply changes.
Decommission the environment by cleaning up Argo CD apps, PVC data, Helm remnants, and resources; verify with kubectl, remove AWS volumes, and delete the EKS cluster to prevent cost leaks.
Are you ready to level up your DevOps skills and build a real-world DevOps project using modern tools and cloud-native best practices?
In this hands-on course, you'll go beyond theory and walk through a complete end-to-end DevOps project — from provisioning infrastructure on AWS EKS to building a CI/CD pipeline with Argo CD, and implementing production-grade observability with Fluent Bit, Splunk, Prometheus, Grafana, and OpenTelemetry.
Whether you're aiming to become a DevOps engineer/SRE, learn Kubernetes the practical way, or showcase a solid DevOps portfolio project to land job interviews — this course will help you stand out.
What You’ll Build
A fully deployed Ghost blog application on Amazon AWS, Kubernetes/EKS with persistent storage and GitOps-powered delivery.
Fluent-bit logging pipeline: Ghost application logs streamed via Fluent Bit, transformed, and visualized in Splunk.
Live dashboards in Grafana using Prometheus and OpenTelemetry metrics.
A CI/CD workflow powered by GitHub, Helm, and Argo CD.
Realistic alerts sent to Slack — just like in production!
Technologies You'll Use
Kubernetes (EKS) on Amazon AWS
Docker, Helm, and GitHub
ArgoCD for GitOps-based deployments
Prometheus, Grafana, and custom Grafana dashboards
Splunk, Fluent Bit, and OpenTelemetry for logging and observability
Git for version control workflows
By the end of this course, you’ll be able to:
Set up and deploy Kubernetes apps using modern DevOps tools
Design and automate CI/CD pipelines with Argo CD
Monitor and troubleshoot microservices using observability best practices
Deploy real-time logging and metrics dashboards
Confidently speak to DevOps architecture and tools in interviews
This course is ideal for aspiring DevOps Engineers, SREs, and developers looking to bridge the gap between theory and production-ready workflows.