Comprehensive bundle:Mi-Services,Istio,Lab,Docker,Kubernetes

Set up a virtual data center and a Docker-based cluster with a master and nodes, install the Docker engine, verify the kernel version, and configure networking and hosts files.

Configure the kube api server by editing configuration files, copy the binary to the required folder, and restart the docker service to bring up the master and node services.

Define and compare optimizer functions, including gradient descent, to minimize a regression loss. Run a training loop to track mean squared error and r-squared as the model improves.

Create and manage Kubernetes jobs that run one or more parts and track completion until the specified number of successful runs is reached, using a template named PVI.

This lecture demonstrates ridge regularization techniques to train a model on the Boston housing data. It compares loss and R-squared across iterations and visualizes results with plots and code.

Explore logistic regression for binary and multiclass classification, using sigmoid and softmax functions to model probabilities, optimize log-likelihood, and apply gradient descent.

Learn how Kubernetes services provide a single IP and DNS name, enabling load balancing, scaling, and traffic routing through endpoints, selectors, cluster IPs, and external load balancers.

Create pods with single or multi-container configurations using images from a Docker registry and yaml files, via kubectl. Explore replication controllers, replica sets, and deployments with rolling updates and rollbacks.

Explore how Kubernetes volumes mount diverse storage into pods, from emptyDir and hostPath to GCE persistent disk, AWS EBS, NFS, and secret volumes, and learn PV/PVC provisioning.

Learn how to create Kubernetes secrets from text files or YAML manifests, and deploy them as environment variables or as volumes in pods.

Explore how the Kubernetes api uses EPA objects as declarative configuration, enabling create, update, delete, and get operations via the Kuban bill cli, while balancing backward compatibility and stable versions.

Master kubectl to manage Kubernetes clusters, including deploying resources, inspecting configurations, scaling deployments, and viewing logs. Explore commands for context, file operations, create, delete, expose, rollout, get, describe, and debugging.

Explore autoscaling with the horizontal pod autoscaler in Kubernetes and set up the dashboard, including cluster creation and app deployment with prerequisites like Docker, Go, npm, Java, Gulp, and Kubernetes.

Explore monitoring large Kubernetes clusters with Prometheus components and node exporter, and centralize logs using Elasticsearch, Logstash, Kibana, or Fluentd in a Docker-based deployment.

Master advanced Kubernetes networking concepts, including virtual IPs, iptables, and kube-proxy routing. Explore external and internal services, load balancers, and node port configurations for container communication.

Explore how a proxy routes traffic to the correct service port even if pods are down, using node ports and custom port mappings for multi-port exposure.

This lesson covers cluster service addressing, including cluster IP and none for headless services, and explains service discovery via environment variables and DNS, noting creation-time limitations.

Learn how dns enables service discovery by name and by namespace in Kubernetes. The lecture covers namespaces, default versus custom namespaces, and basic resource quotas and isolation for multi-tenant clusters.

Expose and stabilize pod networking with Kubernetes services by using labels and selectors to provide a stable IP, DNS, and load balancing, accessible inside and outside the cluster.

Explore how services in a cluster use label selectors to dynamically track parts and expose a stable endpoint with DNS mapping for internal and external access.

Deploy a Kubernetes service imperatively and declaratively, linking a replica set to network access and load balancing. Explore cluster IP, node port, and load balancer options.

Learn how Kubernetes services are exposed and discovered with endpoints, deploy declaratively, and use service selectors and load balancing for blue-green updates that route traffic to new app versions.

Configure a virtual private cloud with public and private subnets, an internet gateway, and a NAT gateway with elastic IP to enable internet access and high availability.

Configure security groups for ingress and egress; link public and private subnets, enable SSH, use elastic block store, Route 53 DNS, and elastic load balancer with S3.

Set up Cuban Nitti on the blue using cops, configure VPCs, subnets, and Route 53 DNS, and deploy with a load balancer, ingress, and EBS storage.

Modify the instance group and machine type in the public cloud, save changes, and perform a rolling update to reflect the new instances.

Pause here to cover firewall rules in the next lecture and set up expectations for the upcoming topics.

Compare gcp firewall rules to traditional security groups, noting that firewall rules are loosely coupled to virtual machine instances, enabling flexible, tag-based access and subnet testing.

Configure a private host running tomcat behind subnets, then set up a gcp load balancer with firewall rules and health checks to route traffic to private and public backends.

Learn to set up a Kubernetes cluster on Google Cloud Platform with GCP VMs, VPC subnets, zones, and load balancers; resize node pools and place pods with node selectors.

Learn to perform rolling upgrades of Kubernetes clusters on Google Cloud, upgrade the master first, provision storage with persistent disks, and configure L4 load balancer and ingress with GCP integration.

Create and manage Kubernetes deployments with a declarative controller to rollout updates, scale replicas, rollback when unstable, pause rollouts, and clean up obsolete replica sets.

Update a Kubernetes deployment by changing the spec.template.containers.image and monitor the rollout, applying max unavailable and max surge to maintain availability.

Explore zero downtime deployments with rolling updates, readiness probes, and connection draining to finish in-flight requests, while using a proxy to manage TCP keepalive during updates.

Explore deployment theory, detailing rollouts and seamless rollbacks via deployment objects, replica sets, and manifest-driven updates through the API server and deployment controller for zero-downtime releases.

Learn deployment scaling and upgrading by bootstrapping a cluster, deploying a mean application with a custom Helm chart, and validating the deployment and release workflows.

Scale your Kubernetes deployment up or down to handle load with kubectl scale and status checks, then configure external load balancers and perform rolling updates and rollbacks.

Learn how yaml defines kubernetes configurations, using maps and lists to build apiVersion, kind, metadata, and spec for deploying containers with images and ports.

Create a pod using a yaml manifest saved as part.yaml, run it to launch containers, and troubleshoot using events to fix a missing image tag before deployment.

Create and manage Kubernetes deployments with YAML, define replicas and selectors, use templates, apply configuration, and monitor deployment status and events.

Master scalable updates with rolling upgrades and gradual rollouts, minimizing downtime. Learn to scale the cluster with scale commands and perform one-by-one replica updates for version zero point two.

Explore blue-green and canary deployments, AB testing, and rolling updates to safely release new features, test performance, and route traffic with affinity and service variants.

Scale the cluster by configuring minimum and maximum nodes and enabling auto scaling with environment variables. Use the instance group template to add or remove nodes.

Scale a Cuba Nitti cluster manually via CLI or console, adjust min and max node counts, and learn auto-scaling concepts and rollout considerations for reliable capacity.

Explore Kubernetes installation options—Minikube on a laptop, Google Cloud's GKE, and Ubuntu with kubeadm—then initialize a cluster, configure networking, and join additional nodes to a ready, multi-node setup.

Install Minikube on Mac, Windows, and Linux, explore a local Kubernetes environment, and spin up a cluster with a chosen hypervisor; ideal for learning and testing.

Learn to install and start minikube on Mac, configure shell context, list cluster nodes, switch contexts for multiple clusters, stop, delete, and run specific Kubernetes versions.

Install minikube on windows 10 using chocolaty or the browser installer, configure a Hyper-V external switch, start a local cluster, and verify kubectl version.

discover google container engine (gke) built on google compute engine and learn to create a kubernetes cluster in the google cloud console using zone, machine type, and container-optimized image.

Explore Google Kubernetes Engine (GKE) in the GCP console, viewing the container cluster and connecting via Cloud Shell to manage it. Learn kubectl installation options using a development ops tool.

Install and configure kops on AWS, create a state store in S3, supply credentials for Route 53 and S3, then create, deploy, and validate a Kubernetes cluster with kubectl.

Manually install kubernetes using kubeadm across three linux machines, initialize the cluster, configure an overlay network, and add nodes with kubectl.

Initialize a new kubernetes cluster with kubeadm, pull images, and create system components; copy kubeconfig, set the kubeconfig environment variable, then join additional nodes and verify the cluster is ready.

Understand pods as the atomic unit in Kubernetes, where one or more containers share networks, hostnames, and volumes via the pause container, with cgroup resource controls.

Define pods with manifests and deploy to the cluster; they move from pending to running, may succeed or fail, and should be managed by replica sets or deployments.

Learn to create a basic pod manifest with apiVersion, kind, metadata, and a spec for a single container with a latest image and an exposed port.

Deploy pods from a manifest with kubectl, monitor status, and access containers; pods are the atomic deployment unit on a node, defined declaratively with deployments, replica sets, and daemon sets.

Explore Kubernetes replica sets and deployments, contrasting declarative versus imperative models, and learn how reconciliation loops maintain the desired state, enabling self-healing and scalable pod management.

Understand replica sets as the next generation replication controller, using selectors and templates to maintain a desired number of pods. Deployments manage replica sets for declarative updates and rolling changes.

Explore replica sets in Kubernetes, learn horizontal scaling targets, and compare deployment, daemonset, and job options to manage scalable, resilient pod lifecycles.

Identify enterprise deployment targets for Kubernetes, ranging from managed services and container as a service to public cloud and hybrid deployments, highlighting image registries, load balancing, and lifecycle management.

Discover Kubernetes design features that enable scalable, available, secure, and portable deployments. See how microservices, stateless and stateful containers, autoscaling, persistent storage, secrets, and load balancing ensure resilient performance.

Set up a lab environment by using vagrant to provision linux virtual machines, install docker engine, and configure docker machine for local or cloud hosts.

Connect the Docker local client to an AWS remote host and manage images, containers, and networks with build, run, and cleanup commands.

Demonstrates adding an interface to a network namespace via a veth pair on localhost, assigning IPs, bringing both ends up, and testing connectivity within docker bridge networking.

Explore Docker bridge networking and the container network model (CNM) for IP address allocation and container-to-container communication. Configure bridge networks, port mappings, and iptables rules to enable external connectivity.

Explore host networking and container network namespaces, showing how a container can share the host ip and mac in host network mode, its performance and security implications.

Explore overlay networking for containers using docker bridges and vxlan, and enable host-to-host connectivity with Open vSwitch, then learn multihost overlays with flannel for subnet routing.

Set up the flannel network in a two-host lab, creating a new interface and enabling inter-host container traffic with iptables, then deploy a demo voting app using compose.

Build and scale a Docker swarm cluster, deploy a service with load balancing across replicas, monitor the swarm topology, and verify access via browser hostnames and published ports.

Build and scale a Kubernetes cluster using kubeadm and kubectl, deploy a Flask web app, create deployments and services, and perform a rolling update to illustrate architecture.