© Copyright VLR Training | 2020
VLR Training provides DevOps in GCP online Training in Hyderabad by Industry Expert Trainers. We provide DevOps live projects to the students and also Every day Recorded sessions.
A career in DevOps within Google Cloud Platform (GCP) offers exciting opportunities in the rapidly evolving field of cloud computing and software development. DevOps professionals in GCP are responsible for orchestrating the development, testing, and deployment of applications while ensuring efficient collaboration between development and operations teams.
DevOps in Google Cloud Platform (GCP) encompasses a set of practices and tools aimed at streamlining and automating the software development and deployment lifecycle. This approach facilitates collaboration between development and IT operations teams to deliver applications more efficiently, reliably, and at scale.
GCP offers a range of services and features that support DevOps principles. Google Kubernetes Engine (GKE) allows for containerized application deployment and management, enabling teams to quickly deploy, scale, and manage applications using Kubernetes. Continuous Integration and Continuous Deployment (CI/CD) pipelines can be built using tools like Cloud Build, which automates the process of building, testing, and deploying code changes to GCP services.
Infrastructure as Code (IaC) is promoted through tools like Google Cloud Deployment Manager and Terraform, enabling teams to define and manage infrastructure using code. This leads to consistent and reproducible environments.
Monitoring and observability are vital in DevOps, and GCP provides tools like Stackdriver (now part of Google Cloud Operations) for real-time monitoring, logging, and alerting. These tools aid in detecting issues and ensuring the reliability of applications.
Automated testing and security scanning help maintain the quality and security of applications. GCP’s integrated security features, like Identity and Access Management (IAM), VPC Service Controls, and Security Command Center, contribute to securing the DevOps process.
Overall, DevOps in GCP empowers teams to deliver software more efficiently through automation, collaboration, and standardized practices. It leverages GCP’s services to streamline development, testing, deployment, monitoring, and security, resulting in faster delivery of reliable applications to end-users.
45 Days
Online
Everyone can get DevOps training.
A Google Cloud Platform (GCP) DevOps course aims to equip individuals with the skills and knowledge necessary to effectively implement DevOps practices using Google Cloud services. The course typically covers a range of topics related to both DevOps principles and GCP-specific tools. While the specific objectives can vary depending on the course content.
Learning a Google Cloud Platform (GCP) DevOps course can bring a range of valuable benefits to both individuals and organizations.
1.1 Objectives of the Course
1.2 Pre-requisites
2.1 EC2
2.2 S3
2.3 VPC
2.4 CloudWatch
2.5 CloudTrail
2.6 RDS
2.7 CloudFormation
3.1 OS Structure
3.2 Linux Commands
3.3 File Structure
3.4 Tar & Zip
3.5 Users and groups
3.6 Hard link & softlink
4.1 Installation
4.2 Configuration
4.3 Variables
4.4 Outputs
4.5 Modules
5.1 Installation
5.2 Configuration
6.1 Gitlab installation,
6.2 Git commands
6.3 Repo structure
7.1 Installation
7.2 pipeline configuration.
7.3 Groovy scripting.
7.4 Jenkins plugins
7.5 Password management and secrets.
8.1 Installation and running Nexus
8.2 Configuring maven to use nexus
9.1 Configuration Management
9.2 History
9.3 Advantages of CM tool
9.4 Why Ansible, Ansible Advantages
9.5 Ansible Architecture setup
9.6 Install & configure Ansible
9.7 Ansible Inventory
9.8 Test Environment setup
9.9 Host Patterns
9.10 Ad-Hoc commands
9.11 Modules
9.12 Gathering facts
9.13 Playbooks
9.14 YAML Language
9.15 Target section
9.16 Variable section
9.17 Task section
9.18 Handle section
9.19 Dry run
9.20 Loops
9.21 Conditionals
9.22 Ansible Roles
10.1 Build management
10.2 Advantages of Build tool
10.3 Build tools
10.4 Architecture of Maven
10.5 Maven build life-cycle
10.6 Maven directory structure
10.7 Maven repositories
10.8 Pom.xml
10.9 Multi module project
11.1 Installation, Configuration
11.2 Tomcat manager
11.3 Application management
11.4 App deployment methods
12.1 Container
12.2 Docker history
12.3 Docker usage
12.4 OS-Level-Virtualization
12.5 Layered file system
12.6 VM Ware vs Docker
12.7 Docker components, Docker workflow
12.8 Docker benefits, Docker images
12.9 Docker Container, Docker file
12.10 Docker hub/registry
12.11 Docker daemon
12.12 Docker Install & Configure
12.13 Docker all commands
12.14 Docker Volumes
12.15 Volume (container-container)
12.16 Volume (Host- Container)
12.17 Port mapping
12.18 Registry server
12.19 Pull/push images from /to registry
12.20 CMD, RUN, ENTRYPOINT
13.1 What is kubernetes
13.2 Features of kubernetes
13.3 Architecture of kubernetes
13.4 Kubernetes Master
13.5 Kubernetes nodes
13.6 Kubernetes components
13.7 Kube-api server
13.8 etcd (cluster store)
13.9 Kube-scheduler
13.10 Node
13.11 Kube-proxy
13.12 Kubelet
13.13 pods
13.14 Multi container pod
13.15 Pod limitations
13.16 Replica sets
1. Deploy a Jenkins pipeline using Terraform: (Require a project with Organization)
2. Create 1 Host Project
3. Create 2 Service Projects (Frontend and Backend)
4. Attach Billing to all these projects
5. Create a Linux VM (Frontend Project)
6. Install LAMP stack in Linux box using Ansible
7. Create MySQL database in Cloud SQL (Backend Project)
8. Deploy a WordPress application
1. Deploy all the below tasks using Jenkins or Cloud Build
2. Create VPC and Private Subnets (Terraform)
3. Create a Private EKS cluster with 3 nodes. (Terraform)
4. Create a Testing GitHub account (Push sample code in Git Repository)
5. Create a Sample Application using Dockerfile
6. Push Docker image into Docker Hub)
7. Deploy any sample application. ( EKS using Helm Chart)
8. Setup Load Balancer (Terraform)
Access the Sample Application.
1. Setup Centralize Logging and Monitoring into separate monitoring project
2. Setup Logging and Monitoring for the above tasks (Linux, SQL, EKS)
a. CPU, Memory, Disk, Uptime
3. Create a custom Dashboard to monitor all important metrics (like CPU, Memory, Disk
Available, Uptime etc.) for VM, SQL (in single Dashboard)
4. Setup log-based metrics and alerting and notifications
a. Firewall Rule if anyone modified notify to related stakeholders
b. In case anyone add anyone as Project Owner (Primitive Role) – Not recommended
c. Notify to related stakeholders in case anyone Stopped/Deleted the VMs
© Copyright VLR Training | 2020