DevOps On AWS and AI - Real Projects - All In One

Launch an ec2 instance on aws by naming an Ubuntu server, selecting g2media, creating a key pair, configuring a default vpc security group, and increasing storage to 20 gb.

Copy the published IP, save it to a folder, and connect to the server via ssh to verify internet access by updating Istio packages.

Install docker on a jupyter server using a script to automate the setup, then verify the installation by checking the docker version and granting docker user permissions.

Install kubectl on an Ubuntu server by following the step-by-step commands from the website, compiling and executing them to complete the installation.

Learn to understand and construct dockerfiles for Python, Node.js, and Java apps by stepwise copying dependencies, installing packages, running unit tests, and configuring multi-stage builds and ports.

Learn how to use docker compose to build images, configure services like mongodb and mysql, set up volumes, networks, and environments, and run step-by-step deployments.

Clone the reboot story repository via git clone, follow the workspace, generate and use an authentication token, then set permissions and verify the reboot workflow.

Run a microservices project with Docker Compose to run the bookinform microservice application, building and launching services such as product page, detail, MongoDB, writing, and review, then verify containers.

Run the container and open the security group to expose the app online. The setup involves Azure VCI, CIDR, and GitHub Salesforce; paste the public ID into your browser.

Set up ECR to store a versioned image on AWS, configure permissions, build and test the image, and verify login success.

Build, tag, test, and push a docker image to an html repository, then verify the pushed image details in the repository.

Create a GKE cluster and a VPC with Terraform, then verify the deployment. Check the VPC dashboard, subnets, root tables, internet gateway, cluster resources, IAM, and routes like DksMathRoute.

Connect to an EKS cluster by running setup commands and use kubectl to inspect nodes, pods, deployments, services, ingress, and other resources in the cluster.

Deploy a simple Nginx application on an EKS cluster by creating and applying deployment and service, forwarding ports, and enabling internet access on port 8080.

Deploy the main application with MongoDB database by pushing updates to GitHub, pulling on an Ubuntu server, and testing versioned MongoDB containers.

Deploy the main application with a MySQL database by configuring secrets for the MySQL password, applying configuration changes, and testing access via kubectl port-forward across versions.

Set up MongoDB Atlas free tier, create a database and collection, configure a database user with a username and password, and save the connection string.

Connect to MongoDB Cloud, manage sequences, and insert documents with 5 and 2 stars; configure IP allowlists to run the app.

Push a CI/CD workflow to the project and run it with GitHub Actions, push images to ECR, and deploy to EKS to verify the running app.

Set up Istio and kube-ctl, download and export config files, install Istioctl, deploy and test a book info gateway, and forward ports to access the product page.

Create a gateway and http route, then access the app through the load balancer domain using the address from kubectl get gateway, and verify status across versions 1 to 3.

Set up a service and its route for a single version, then create three preview versions of the service to observe the results.

Direct traffic from the three circuits to version 1, create an http route for version 1, relog multiple times to confirm stability, and verify with other versions later.

Configure an http route to serve any reviews version and switch between version 1, 2, and 3. Observe logs to verify the active version and ensure correct routing.

Set up QAly to monitor MySQL traffic and verify deployment status, including port forwarding. Use Grafana and Prometheus to visualize traffic data while testing 1 to 100 requests.

This lecture demonstrates horizontal autoscaling and monitoring, simulating traffic to trigger replica scaling based on CTQ target utilization, with a 60-second stabilization window.

Build and edit Grafana dashboards to monitor real-time cpu usage and application performance, using simulated traffic to visualize bot cpu metrics across configurable time windows.

Set up a Grafana to Slack alert workflow by creating a cdqbot app with an incoming webhook, linking it to the cdqmonitoring channel, and testing notifications.

learn how to test alerting with a 50% threshold, observe autoscaling from 1 to 5 replicas as cpu rises, and trigger slack notifications and monitoring messages.

Set up a domain namespace in Cloudflare, connect your domain, and enable SSL, choosing the Korean namespace plan to manage the domain. Expect time for certification, from minutes to hours.

Install cert-manager to issue and manage SSL certificates, securing your domain, data, and traffic, then enable guest-wide APIs to route traffic and advance to the next step.

Set up a domain with ssl for Grafana and configure an http route with notifications. Add records, issue and install the Grafana certificate, and verify access at grafana.andguru.site.

Scale the cluster to three nodes by applying Terraform to add compute and pods, using a horizontal autoscaler for testing across platforms on Nextstack.

Set up ArgoCD and a custom domain by configuring Agostini deployment and enabling qt with qtctl. Test http defaults, verify CloudFlare CNAME, and confirm certificate readiness to access Agostini.

Use ArgoCD to deploy and sync an application by configuring repository access, generating and managing private keys, and creating a sample 'book info' app in ArgoCity.