DevOps - Big Data Trunk

https://project.bigdatatrunk.com Quality Corporate and Classroom Training in Bay Area CA Fri, 21 Feb 2025 05:29:32 +0000 en-US hourly 1 https://wordpress.org/?v=7.0 Beginner’s Course in React.js https://project.bigdatatrunk.com/courses/beginners-course-in-react-js/ https://project.bigdatatrunk.com/courses/beginners-course-in-react-js/#respond Wed, 11 Oct 2023 05:28:20 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=44538 This course will introduce you to React.js, a popular JavaScript library for building user interfaces.

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Overview
Prerequisites
Audience
Curriculum

Description:

This course will introduce you to React.js, a popular JavaScript library for building user interfaces. You will learn the fundamentals of React.js, including components, state management, and routing. By the end of this course, you will be able to build interactive and dynamic web applications using React.js

Duration: 1 Day

Course Code : BDT308

Learning Objectives:

With this course, you will have the opportunity to

Understand the core concepts and principles of React.js.
Create and manage React components.
Implement state management in React applications.
Use React Router for navigation and routing in a single-page application.
Build a small React application as a hands-on project.

Participants should have a basic understanding of HTML, CSS, and JavaScript

This course is suitable for web developers, front end and Java Script developers who want to add React.js to their skill set. It's suitable for both beginners and those with some experience in web development (HTML, CSS, and JavaScript).

Course Outline:

Session 1: Introduction to React.js

What is React.js?
Setting up a development environment (Node.js, npm, and Create React App).
Creating your first React component.
JSX (JavaScript XML) and how it works.
Understanding React components.
Creating functional and class components.
Using props to pass data between components
Component lifecycle methods.

Session 2: State and Events, Hands-On

Managing component state with `useState` and `useEffect`.
Handling user events (e.g., onClick, onChange).
Conditional rendering based on state.
Building interactive components.
Introduction to React Router.
Setting up routes in a React application.
Creating a multi-page application with navigation.
Building a small project (e.g., a simple task management app) using React.js and React Router.

Training Material Provided: Yes (Digital Format)

Additional Information that can be included on Overview Page

SETUP

A computer with a code editor (e.g., Visual Studio Code).
Node.js and npm installed.
Internet access for downloading dependencies and resources.

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]]> https://project.bigdatatrunk.com/courses/beginners-course-in-react-js/feed/ 0 Introduction to Jenkins and CI/CD https://project.bigdatatrunk.com/courses/introduction-to-jenkins-and-ci-cd/ https://project.bigdatatrunk.com/courses/introduction-to-jenkins-and-ci-cd/#respond Wed, 16 Aug 2023 06:41:40 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=42473 The Introduction to Jenkins and CI/CD training course explores how to effectively configure and use Jenkins to increase code quality through continuous builds, code coverage and quality tools, and testing suites.

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Overview
Prerequisites
Audience
Curriculum

Description:

Discover the world of continuous integration and continuous deployment (CI/CD) in our 'Intro to Jenkins and CI/CD' training course. This program is designed to help software developers and engineers, including those in quality assurance roles, effectively configure and utilize Jenkins to enhance code quality through continuous builds, code coverage, quality tools, and testing suites. In this course, you will gain essential knowledge in CI/CD, master Jenkins configuration, effectively manage plugins, and learn to create and manage jobs. Elevate your skills in software development and quality assurance, and become a CI/CD expert with our hands-on training.

Duration: 2 Days

Course Code: BDT295

Learning Objectives:

After this course, you will be able to:

Describe Continuous Integration
Configure Jenkins to support jobs and builds
Setup and measure code quality
Create alerting / notifications for builds

Development and Testing knowledge
The course will be taught using Jenkins 2, Java 11, Maven 3 and a GitHub repository.

Software Build and Release Engineers
Software Developers
DevOps Practitioners

Course Outline:

Introduction to Continuous Integration

What is CI? How does CI help improve software quality? Build Automation Basics Common types of builds Common CI Environments Expected outcomes when moving to CI

What is Jenkins?

History Features Overview of Jenkins Architecture Understanding the Jenkins build infrastructure

Setting up Jenkins

Download and Install Getting the initial password Installing Suggested plugins Creating first user Jenkins Home Directory Uninstall

Configuring Jenkins

Manage Jenkins Configure System:

Understanding Quiet Period
Project naming restrictions
Setting up Jenkins Location and Admin Email
Email Configuration
Email Setup
Manage Plugins
Installing Plugin
Plugin Versions
Uninstalling plugins
Global Tool Configuration
Setup JAVA_HOME and Setup MAVEN_HOME

All about Jobs

Types of Jobs Creating Freestyle Project

Use Custom Workspace
Configuring SCM
Setting up a git-based (github) project
Build Triggers
Build Periodically
Cron Syntax Tricks
Build Environment Parameters
Email Notifications
Building other Projects
Archiving artifacts
Obtaining artifacts
Understanding Upstream/Downstream Projects
Updating an existing job
Cloning an existing job
Importing/Exporting jobs
Creating Maven Project

Plugin Management

Notable plugins and their functionalities
Recommended Plugins and their functionalities
EC2 plugin for Jenkins Autoscaling

Creating Pipelines

Blue Ocean
Declarative vs Scripted Pipeline
Pipeline Syntax Generator
Understanding Jenkinsfile
Creating scripted pipeline job
Creating declarative pipeline job
Simple to complex examples
Creating and storing artifacts

Jenkins Post Build and Reporting

Setting up Post-Build Actions
Setting up Test Reporting

Code Coverage

What is code coverage
Why is code coverage important?
Measuring code coverage
Configuring Cobertura (for Java)

10. Code Quality – Sonarqube

Code Quality and CI Checkstyle

11. Setting up Notifications

Email Notification Slack Notification
Other type of notifications

12. Advanced Build Configuration

Parameterized Builds and Triggers
Master/Slave Distributed Builds

13. Advanced Build Management

Joins
Parallel
Build Trigger
Builds based on REST API

Jenkins Security

Global security setting
JNLP Port Management
Remember Me
Forgeries
Authentication
Security Realms
Configuring LDAP

Authorization

Active Directory
Jenkins own user database
Unix User/group database
Configuring job-level permissions in Jenkins
Matrix Based Security
Role Based Strategy
Project Based Matrix Authorization Strategy
People vs Manage Users

Jenkins Agents/Nodes

Creating Node
Configuring Node
Launch Methods
Node Properties
Setting up Node
Tools
Using node in your jobs/pipelines

Best Practices for Jenkins

Training material provided: Yes (Digital format)

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]]> https://project.bigdatatrunk.com/courses/introduction-to-jenkins-and-ci-cd/feed/ 0 Advanced Apache Airflow https://project.bigdatatrunk.com/courses/advanced-apache-airflow/ https://project.bigdatatrunk.com/courses/advanced-apache-airflow/#respond Wed, 16 Aug 2023 06:10:56 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=42426 The Apache Airflow Next Steps course is intended for either of two audiences: 1) data engineers that already work with Apache Airflow on a daily basis and want to understand the new changes that Airflow 2 brings; or 2) data engineers that have taken the Apache Airflow Fundamentals course and want to expand their knowledge of the advanced topics of Apache Airflow.

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Overview
Prerequisites
Audience
Curriculum

Description:

The Apache Airflow Next Steps course is intended for either of two audiences: 1) data engineers that already work with Apache Airflow on a daily basis and want to understand the new changes that Airflow 2 brings; or 2) data engineers that have taken the Apache Airflow Fundamentals course and want to expand their knowledge of the advanced topics of Apache Airflow.

The course begins by revisiting topics that are often not taught in an Airflow fundamentals class, such as connections, variables, templating, and Pools. Then, we reformulate how we create DAGs under the new paradigms of Apache Airflow 2.x.

Next, we expand on a fundamental topic for any Airflow in Production: Security in Airflow. Finally, we teach Airflow in Kubernetes and how to scale within Kubernetes.

This course focuses on the practical aspects of how to use Airflow and is 70% hands-on, 30% lecture, demo, and discussion.

This Apache Airflow Next Steps course is taught using Python > 3.5 and Airflow > 2.1.

Duration: 3 Days

Course Code: BDT292

Learning Objectives:

After this course, you will be able to:

Secure your Apache Airflow installation
Create highly concurrent DAGs in Kubernetes
Leverage most of the new functionality Airflow 2 brings

All attendees must have prior Apache AIrflow experience, either from their own work or from Accelebrate’s Apache Airflow Fundamentals training.

Data Engineers
Data Scientists
Python Developers Interested in Data Engineering
Data Analysts with Python Programming Knowledge

Course Outline:

Creating DAGs the right way

Secrets, connections and variables
Demo: Creating connections on startup
Using Pools for long running and demanding tasks
Demo: Simulating long running tasks
DAG serialization
DAG versioning
Testing DAGs
Demo: CI/CD in Airflow
Capstone Lab

Modularize your DAGs

TaskGroups vs subDAGs
TaskFlowAPI and XComs
Demo: Modularizing
Dynamic and Functional DAGs
SmartSensors and timeouts
Capstone Lab

Airflow Security

RBAC in Airflow
Setting up OAuth authentication
Demo: Add Google oauth
Adding SSL certs
Default Roles and custom roles
Demo: Creating a custom role

Airflow in Kubernetes

The Helm chart
Demo: Deploying Airflow with Helm
Deploying single tasks to Kubernetes: KubernetesPodOperator
Demo: Adding a task in Kubernetes
Scaling Airflow with Kubernetes executor
Demo: Changing the Helm charts values
KEDA autoscaler
Preparing DAGs for Kubernetes
Demo: Creating a DAG fully in Kubernetes
The CeleryKubernetes executor for extreme scalability

A note on upgrading from Airflow 1.10

Training material provided: Yes (Digital format)

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]]> https://project.bigdatatrunk.com/courses/advanced-apache-airflow/feed/ 0 Apache Airflow Fundamentals https://project.bigdatatrunk.com/courses/apache-airflow-fundamentals/ https://project.bigdatatrunk.com/courses/apache-airflow-fundamentals/#respond Wed, 16 Aug 2023 05:44:44 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=42418 Enhance your Apache Airflow proficiency through our 'Advanced Apache Airflow' course. Designed for experienced data engineers, this program covers Airflow 2 updates and dives into advanced topics, including connections, DAG creation, security, Kubernetes, and scaling. This hands-on course (70%) combines practical exercises with informative lectures, demos, and discussions (30%). It's conducted using Python versions exceeding 3.5 and Airflow versions surpassing 2.1. Join us to take your Airflow skills to the next level and excel in data engineering and workflow orchestration."

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Overview
Prerequisites
Audience
Curriculum

Description:

Enhance your Apache Airflow proficiency through our 'Advanced Apache Airflow' course. Designed for experienced data engineers, this program covers Airflow 2 updates and dives into advanced topics, including connections, DAG creation, security, Kubernetes, and scaling. This hands-on course (70%) combines practical exercises with informative lectures, demos, and discussions (30%). It's conducted using Python versions exceeding 3.5 and Airflow versions surpassing 2.1. Join us to take your Airflow skills to the next level and excel in data engineering and workflow orchestration.

Duration: 3 Days

Course Code: BDT292

Learning Objectives:

After this course, you will be able to:

Create production-ready data pipelines in Airflow that are able to scale to hundreds of tasks
Enforce modularization and reusability of Airflow Tasks across projects
Scale Airflow in Kubernetes

Python Programming
Basic Understanding of Workflow Management

People being curious about data engineering.
People who want to learn basic and advanced concepts about Apache Airflow.
People who like hands-on approach.

Course Outline:

Introducing Apache Airflow

What Airflow is and what does it solve?
Airflow architecture
How do we represent a Pipeline?
Demo: Our first DAG
Tasks, TaskFlow and Operators
Demo: First Pipeline
Capstone Lab

Mastering scheduling

execution_date, start_date and schedule_interval
Handling non-default schedule_intervals
Demo: Playing with time
Capstone Lab

Abstracting functionality

Using custom operators
Creating TaskGroups vs subDAGs
Sharing data with xCOMs
Branching and Triggers
Sensors and SmartSensors
Capstone Lab

Executors and Scaling Airflow

Abandoning SQLite to PostgreSQL
Executors: Debug, Local, Celery
Concurrency and parallelism
Demo: Concurrency with Celery
Airflow in Kubernetes, the old and new ways
KEDA and HA scheduler
Demo: Deploying a highly availability fault-tolerant Airflow

Hackathon

Training material provided: Yes (Digital format)

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]]> https://project.bigdatatrunk.com/courses/apache-airflow-fundamentals/feed/ 0 Apache Airflow For Machine Learning Operations https://project.bigdatatrunk.com/courses/apache-airflow-for-machine-learning-operations/ Wed, 16 Aug 2023 05:07:16 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=42406 The Apache Airflow for Machine Learning Operations course is intended for machine learning engineers interested in leveraging Apache Airflow to generate training, validation, and test sets in a reproducible manner.

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Overview
Prerequisites
Audience
Curriculum

Description:

Empower your machine learning operations with our 'Apache Airflow Training for Machine Learning Operations' course. Tailored for machine learning engineers, this program equips you to create reproducible training sets, build and validate models, and deploy them confidently. Explore the complexities of reproducible CI/CD pipelines in machine learning and how Apache Airflow simplifies batch training workflows using Directed Acyclic Graphs (DAGs). You'll gain a solid understanding of Airflow's foundations, applying them to real-world machine learning challenges, including sentiment prediction in tweet streams. This course offers a hands-on learning approach, with a focus on creating reproducible pipelines with Airflow. Join us to elevate your machine learning operations with Apache Airflow.

Duration: 3 Days

Course Code: BDT291

Learning Objectives:

After this course, you will be able to:

Migrate their Machine Learning training workflows to scalable pipelines in Apache Airflow
Take a raw dataset and a model architecture and be able to take the project to the end deploying it in the cloud
Enforce reusability and modularization of pipelines for easy collaboration.

Although there is no background needed except basic Python knowledge or object-oriented programming experience, any knowledge of Machine Learning can help boost your learning.

People being curious about data engineering.
People who want to learn basic and advanced concepts about Apache Airflow.
People who like hands-on approach.

Course Outline:

The scalable problem of Machine Learning Pipelines

What problems arise when trying to create a Machine Learning model?
The components of a Machine Learning platform
Introducing Apache Airflow
Airflow architecture
How do we represent a Machine Learning Pipeline?
Demo: Our first DAG
Tasks, TaskFlows, and Operators
Demo: First Pipeline
Capstone Lab: Cresting the datasets for training

Creating our Machine Learning Pipeline

Using custom operators
Demo: Creating a Train Operator
Creating TaskGroups vs subDAGs
Sharing data with xCOMs
Branching and Triggers
Sensors and SmartSensors
Demo: Adding a sensor to validate enough new data
Capstone Lab: Adding training, validation and delivery steps to our pipeline

Mastering scheduling

Execution_date, start_date and schedule_interval
Handling non-default schedule_intervals
Demo: Playing with time
Capstone Lab: Using Sensors with a correct schedule_interval

Enabling concurrency and scalability

Abandoning SQLite to PostgreSQL
Executors: Debug, Local, Celery
Concurrency and parallelism
Demo: Concurrency with Celery

Hackathon: Sentiment Prediction from Twitter

Software Required

This Apache Airflow for Machine Learning Operations course is taught using Python > 3.5, Apache Airflow > 2.1, scikit-learn > 1.1, and PyTorch > 1.8. On request, we can provide either a remote VM environment for the class or directions for configuring this environment on your local PCs.

Training material provided: Yes (Digital format)

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]]> Mulesoft Fundamentals https://project.bigdatatrunk.com/courses/mulesoft-fundamentals/ https://project.bigdatatrunk.com/courses/mulesoft-fundamentals/#respond Wed, 16 Aug 2023 04:54:37 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=42389 Software integration is the most significant unresolved billion-dollar market in the world. The Anypoint Platform, empowered by the Mulesoft runtime, can easily create, develop, deploy, and monitor integrations.

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Overview
Prerequisites
Audience
Curriculum

Description:

Software integration is the most significant unresolved billion-dollar market in the world. The Anypoint Platform, empowered by the Mulesoft runtime, can easily create, develop, deploy, and monitor integrations. In this course, Mulesoft Fundamentals. you’ll learn the best practices to develop, deploy, manage, and monitor Mulesoft Applications within the Anypoint Platform

Our journey begins by discovering how to design API specifications in Design Center. Next, you’ll discover how to implement APIs in Anypoint Studio with the Mulesoft Runtime. Finally, you’ll learn how to deploy such Mule apps into any environment as well as monitor and secure those integrations

When you finish this course, you’ll have the skills and knowledge of Mulesoft needed to leverage the Mulesoft Runtime and the Anypoint Platform to scale your IT operations exponentially.

Duration: 3 Days

Course Code: BDT290

Learning Objectives:

After this course, you will be able to:

Build an application network using API-led connectivity and Anypoint Platform.
Use Anypoint Platform to discover, design, build, deploy, manage, and govern APIs.
Connect to databases, files, web services, SaaS applications, JMS queues, and more.
Add application logic, handle errors, and transform data using DataWeave.
Structure applications to facilitate development and deployment.

Experience with an object-oriented language
Experience with HTTP/REST/SOAP

Students
Professionals
Who looking out to start career as MuleSoft Developer

Course Outline:

One Platform to Connect Them All

Why is developing integrations so painful?
Introducing API-led connectivity
Explain what web services and APIs are
Make calls to secure and unsecured APIs

Introducing Anypoint Platform

Navigate Anypoint Platform
Locate APIs and other assets needed to build integrations and APIs in Anypoint Exchange

Designing the API Specification

The API lifecycle
Introducing RAML 2.x vs OAS 3.x
Designing the API endpoints [2 parts]
Adding examples and data types
Testing our API with the Mocking Service
How to collaborate with branches (1 minute)
Publishing the API to Exchange and editing the API Portal

Implementing the API in Anypoint Studio

Introduce Studio as the implementation point
Add Choice, Logger, Set Payload, Set Variable, Try, HTTP, and JDBC modules/connectors.
Deploy Mule Apps locally
Compare Design Center and Anypoint Studio
Introduce APIkit
Introduce Munit

Structuring Mule Applications

Create applications composed of multiple flows and subflows
Pass events between flows using asynchronous queues
Encapsulate global elements in separate configuration files
Specify application properties in a separate properties file and use them in the application
Describe the purpose of each file and folder in a Mule project
Define and manage application metadata

Triggering flows

Read and write files
Trigger flows when files are added, created, or updated
Trigger flows when new records are added to a database table
Schedule flows to run at a certain time or frequency
Persist and share data in flows using the Object Store
Publish and consume JMS messages

Deploying and Monitoring the API Implementation

Deploy to Cloudhub
Manage the API in API Management
Deployment options in Mulesoft
Promote to production
Monitor the Application with Anypoint Monitoring

Setup:

A laptop with 16 GB of RAM
Latest version of your browser of choice (Safari, Firefox or Chrome)
Postman
Anypoint Studio 7 downloaded from https://www.mulesoft.com/lp/dl/anypoint-mule-studio

Training material provided: Yes (Digital format)

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]]> https://project.bigdatatrunk.com/courses/mulesoft-fundamentals/feed/ 0 DevOps Toolkit: Docker And Kubernetes https://project.bigdatatrunk.com/courses/devops-toolkit-docker-and-kubernetes/ https://project.bigdatatrunk.com/courses/devops-toolkit-docker-and-kubernetes/#respond Sat, 20 May 2023 08:51:42 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=29595 In this course you will understand the fundamentals of DevOps and the patterns to develop, build and deploy applications.

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Overview
Prerequisites
Audience
Curriculum

Overview:

In this course you will understand the fundamentals of DevOps and the patterns to develop, build and deploy applications. You will learn key concepts behind Virtual Machines, Containers and Processes. There will be hands on labs that will help understand Docker Containers, Container Orchestration using Kubernetes.

Course Code/Duration:

BDT55 / 3 Days

Learning Objectives:

After this course, you will be able to:

Understand the steps involved in DevOps methodology
Use Docker in your daily developer and/or sysadmin roles
Deploy apps to Kubernetes
Make Dockerfiles and Compose files
Build multi-node Swarm clusters and deploying H/A containers
Make Kubernetes YAML manifests and deploy using infrastructure-as-code methods
Build a workflow of using Docker in dev, then test/CI, then production with YAML
Protect your keys, TLS certificates, and passwords with encrypted secrets
Keep your Dockerfiles and images small, efficient, and fast
Run apps in Docker, Swarm, and Kubernetes and understand the pros/cons of each
Develop locally while your code runs in a container
Protect important persistent data in volumes and bind mounts
Lead your team into the future with the latest Docker container skills!

Basic Understanding of Linux/Unix and some basic programming with python.

This course is designed for anyone interested to get started with the domain of DevOps including Data Engineers, DevOps Engineer, Release Engineer, Database Administrator, Infrastructure Engineers, Software Engineers, or System Administrator.

Topic Outline:

Understand principal concepts and practices in DevOps methodology.
How to use Docker, Compose and Kubernetes on your machine for better software building and testing.
Learn Docker and Kubernetes official tools
Gain the skills to build development environments with your code running in containers.
Build Swam and Kubernetes clusters for server deployments!
Hand’s-on with best practices for making Dockerfiles and Compose files
Build and publish your own custom images.
Create your own custom image registry to store your apps and deploy in corporate environments.
Use the practices on Cloud – GCP, AWS
References and Next steps

Structured Activity/Exercises/Case Studies:

More that 50% of the course is going to be hands-on

Training material provided:

Yes (Digital format)

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]]> https://project.bigdatatrunk.com/courses/devops-toolkit-docker-and-kubernetes/feed/ 0 Site Reliability Engineering On AWS https://project.bigdatatrunk.com/courses/site-reliability-engineering-on-aws/ https://project.bigdatatrunk.com/courses/site-reliability-engineering-on-aws/#respond Sat, 20 May 2023 08:50:36 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=29592 The Site Reliability Engineering training course is designed to demonstrate a discipline where the main goals are to create ultra-scalable and highly reliable software systems.

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Overview
Prerequisites
Audience
Curriculum

Description:

Embark on a journey of excellence with our Site Reliability Engineering (SRE) training course. Discover how SRE, born at Google in the early 2000s, combines software engineering principles with infrastructure and operations to create ultra-scalable and highly reliable software systems. Dive into the history, principles, and practices of SRE, differentiate it from DevOps, and gain hands-on experience in budgeting, planning, monitoring, and best practices. Elevate your skills and learn to make your systems run smoothly, efficiently, and reliably

Course Code/Duration:

BDT139 / 2 Days

Learning Objectives:

Understand the core principles of Site Reliability Engineering (SRE) and its origins at Google, including how it incorporates software engineering into infrastructure and operations to create highly reliable software systems.
Differentiate between SRE and DevOps, and grasp the roles and responsibilities associated with SRE.
Gain practical skills in budgeting, planning, monitoring, and implementing best practices for SRE, enabling you to enhance the scalability and reliability of software systems.

None

Developers and developer teams are looking to incorporate the principles of SRE into practice.

Course Outline:

The course includes presentations, demonstrations, and hands-on labs.

Module 1: The Basics of Site Reliability Engineering

Reliability in Modern Applications
The Impact of Failure and Determining Your Reliability Objectives
Accepting Failure and Making It Part of the Design Process
SRE is a Mindset

Module 2: Gaining Resilience and Reliability On AWS

AWS Global, Regional, and Zonal Architecture Design
Amazon’s Global Storage Services – S3
Running Resilient Databases on AWS – RDS and DynamoDB
Fault Tolerant Computation on AWS – Lambda and EC2
Core Resilience Principles for AWS – Load Balancing and Auto Scaling

Module 3: Accepting Failure In Multi-Tier Applications

Typical Three-Tier Application Resilience and Why It Fails in Cloud
Designing in Resilience with Microservices
Managing State
Typical Application Reliability Patterns

Module 4: Deploying Applications On AWS

Optimizing and Migrating the Code
Creating Container with Code Build
The Architecture of Microservices
Using Kubernetes and ECS in AWS
Deploying ECS and RDS
The Problem with What we’ve Just Built

Module 5: Designing Applications

Overview of Failure Mode Analysis
Multi-Regional Support
Microservices Design
Authentication and Authorization
Code Deployment with Code Pipeline
Application Telemetry and Tracing
Application Analytics
Aurora and its Advantages Over MySQL

Module 6: Deploying a Resilient, Fault Tolerant Application

Running/Scaling Applications On EKS
Deploying App-Mesh

Module 7: Surviving Failure of a Global Scale

Review: AWS Global Architecture and What we have just Built
Global Tools: Route 53, CloudFront
Going Global: What does this mean for Users/Developers
Operational Changes Required for a Global Application
Course Summary

Training material provided:

Yes (Digital format)

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]]> https://project.bigdatatrunk.com/courses/site-reliability-engineering-on-aws/feed/ 0 Advanced Git For Developers https://project.bigdatatrunk.com/courses/advanced-git-for-developers/ https://project.bigdatatrunk.com/courses/advanced-git-for-developers/#respond Sat, 20 May 2023 08:49:15 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=29589 This course is well-suited for developers who are comfortable using the command line and experienced using the basics of Git.

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Overview
Prerequisites
Audience
Curriculum

Session Description:

Elevate Your Git Skills: Ideal for Developers Comfortable with Command Line and Git Basics. Master Advanced Code Management and Versioning in this Specialized Course.

Course Code/Duration:

BDT147 / 2 Days

Learning Objectives:

After this course, you will be able to:

Perform basic and advanced Git commands.
Understand how Git works under the hood.
Understand the internal structure of a Git repository.
Understand Git objects.
Understand Git trees.
Use Git features efficiently and fix issues in your development workflow.
Understand versioning and how to use Git tags to create software release versions.
Manage repositories.

Comfortable using the command line and Git basics.

Developers, DevOps, System Admin , Database administrator and anyone interested in source code management.

Course Outline

Course Introduction
Overview of the Git Repository Structure
- Initialization
- Git Object Types
- Blob Objects
- Tree Objects
- Hash Function
- Working Directory
- Staging Directory
- Git Repository

Milestone 1: Creating and Exploring a Git Repository

Git Branches
- Common Operations
- Current State
- HEAD in Git
- Checking Out
- Rename and Track
- Branch Management
- Merging Branches
- Merge Conflicts
Cloning, Exploring and Modifying Repositories
Git diff Command and Conflicts

Milestone 2: Working with Branches and Tracking Content

Git Tagging
- Git Tag Object
- Creating Tags
- Tag Options
- Staging vs Production
- Semantic Versioning

Aliases
Searching Git History

Git Log
- Formatting
- Filtering
- Reflogs
Git Blame

Milestone 3: Using Git History, Aliases, Tags and Versioning

Rebasing
- Merging vs Rebasing
- Rebase with Conflicts
- Rebasing Steps
Submodules
Ignoring Files in Git
- Git Ignore
- Git File Statuses
Advancing
- Git Reset
- Git Revert
- Amend Option
- Cherry-picking Commits
- Stashing

Milestone 4: Modifying, Deleting, Renaming and Stashing

Git Hooks for Extending Git Functionality
- Installing Hooks
- Common Hook Attributes
- Updating Hooks
Git Custom Commands
Git Best Practices
Conclusion: Practical Git, next steps.

Structured Activity/Exercises/Case Studies:

Milestone 1: Creating and Exploring a Git Repository
Milestone 2: Working with Branches and Tracking Content
Milestone 3: Using Git History, Aliases, Tags and Versioning
Milestone 4: Modifying, Deleting, Renaming and Stashing

Training material provided: Yes (Digital format)

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]]> https://project.bigdatatrunk.com/courses/advanced-git-for-developers/feed/ 0 DevOps For Leaders https://project.bigdatatrunk.com/courses/devops-for-leaders/ https://project.bigdatatrunk.com/courses/devops-for-leaders/#respond Sat, 20 May 2023 08:47:32 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=29586 Discover the power of DevOps in applying best software development practices, fostering collaboration, and enabling swift, quality-driven software delivery. This course is your guide to the world of DevOps, with a focus on continuous integration and continuous deployment (CI/CD) principles.

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Overview
Prerequisites
Audience
Curriculum

Description:

Discover the power of DevOps in applying best software development practices, fostering collaboration, and enabling swift, quality-driven software delivery. This course is your guide to the world of DevOps, with a focus on continuous integration and continuous deployment (CI/CD) principles. Learn how to lead your team effectively by applying DevOps principles and leveraging the tools integral to the CI/CD process. Rapid innovation is the cornerstone of any successful company, and an efficient development process is crucial to achieving it. Gain insights into the key design principles of microservices to lead your team during their development journey. Explore a range of DevOps tools, both on-premises and in the cloud, to enhance your leadership in the software development realm

Course Code/Duration:

BDT258 / 4 Hours

Learning Objectives:

Upon completing this course, you will:

Define the core principles and purpose of DevOps.
Comprehend the concepts of Continuous Integration and Continuous Development/Delivery (CI/CD).
Gain an understanding of microservices and their design principles.
Familiarize yourself with the fundamental concepts of CI/CD pipelines, including their role in modern software development practices.

Basic Understanding of Computers

This course is designed for anyone interested in understanding the DevOps domain, it includes Development managers, product managers, project managers and anyone considering transitioning to DevOps.

Course Outline:

What is DevOps?

Understand what does the term DevOps mean
Goals for DevOps
Best practices in DevOps

Understanding CI/CD

What is Continuous CI/CD?
Continuous integration and what are its benefits
Difference between Continuous Delivery and Continuous Deployment
CI/CD and DevOps

Microservices and its design

Monolithic Architecture v/s Microservices Architecture
Microservices application design for leaders
Tools involved in building microservices

Basic Concepts of CI/CD pipelines

What is a CI/CD pipeline?
Tools involved in building CI/CD pipelines
Building CI/CD pipelines on prem as well as on cloud
Demo of building a CI/CD pipeline

Leading an DevOps Organization

DevOps tools on premises and in the cloud.
Best Practices
DevOps Patterns
Hiring and Building DevOps team

Training material provided: Yes (Digital format)

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