Datadog Monitoring – A Full Basic to ADVANCE Datadog guide

Datadog Monitoring – A Full Basic to ADVANCE Datadog guide, available at $99.99, has an average rating of 4.58, with 135 lectures, 8 quizzes, based on 845 reviews, and has 6055 subscribers.

You will learn about Learn In & Out of Datadog monitoring tool with proper HANDS-ON examples from Basic to Advance level. Datadog Agent setup & configuration in Windows Host and Docker containers. Datadog core concepts like Datadog Architecture, Pricing, Datadog Agent manager, Understanding installation root directory etc. Infrastructure Monitoring for Hosts, Processes, Containers, Events, Serverless function (AWS lambda). Understand the Tagging concept in Datadog and its benefits. Implement Tagging in Container and Non-container environments. Create Custom Metrics using Custom Agent check and a Python application (DogStatsD). Tailored Datadog Dashboards to get overview of Host's health using Timeseries, Query Value, Table, Group, Summaries, Stream widgets and Template variables. Build Datadog Notebooks using Timeseries, Text, Table cells. Configure Datadog Monitors & Alerts using Tag, Template, Conditional variables and Notification, Re-notification messages. EXCLUSIVE – Datadog Log Management including Log collection, LOG PIPELINE, Log Explorers & Views in Datadog. Application Performance Monitoring (APM) and Continuous Profiling for a Python Flask web application. EXCLUSIVE – Instrument Flask application for Traces, TRACE PIPELINE for Ingestion Control (Sampling), Datadog APM Views & Explorers. Datadog Account Management for Administrators – Grant Roles & Permissions, API keys, SAML Group mappings, Audit Trail, Sensitive Data Scanner. This course is ideal for individuals who are Monitoring engineers who want to add Datadog monitoring tool in their skillset. or DevOps Engineers or Application Developers It is particularly useful for Monitoring engineers who want to add Datadog monitoring tool in their skillset. or DevOps Engineers or Application Developers.

Enroll now: Datadog Monitoring – A Full Basic to ADVANCE Datadog guide

Summary

Title: Datadog Monitoring – A Full Basic to ADVANCE Datadog guide

Price: $99.99

Average Rating: 4.58

Number of Lectures: 135

Number of Quizzes: 8

Number of Published Lectures: 135

Number of Published Quizzes: 8

Number of Curriculum Items: 143

Number of Published Curriculum Objects: 143

Original Price: $99.99

Quality Status: approved

Status: Live

What You Will Learn

Learn In & Out of Datadog monitoring tool with proper HANDS-ON examples from Basic to Advance level.
Datadog Agent setup & configuration in Windows Host and Docker containers.
Datadog core concepts like Datadog Architecture, Pricing, Datadog Agent manager, Understanding installation root directory etc.
Infrastructure Monitoring for Hosts, Processes, Containers, Events, Serverless function (AWS lambda).
Understand the Tagging concept in Datadog and its benefits. Implement Tagging in Container and Non-container environments.
Create Custom Metrics using Custom Agent check and a Python application (DogStatsD).
Tailored Datadog Dashboards to get overview of Host's health using Timeseries, Query Value, Table, Group, Summaries, Stream widgets and Template variables.
Build Datadog Notebooks using Timeseries, Text, Table cells.
Configure Datadog Monitors & Alerts using Tag, Template, Conditional variables and Notification, Re-notification messages.
EXCLUSIVE – Datadog Log Management including Log collection, LOG PIPELINE, Log Explorers & Views in Datadog.
Application Performance Monitoring (APM) and Continuous Profiling for a Python Flask web application.
EXCLUSIVE – Instrument Flask application for Traces, TRACE PIPELINE for Ingestion Control (Sampling), Datadog APM Views & Explorers.
Datadog Account Management for Administrators – Grant Roles & Permissions, API keys, SAML Group mappings, Audit Trail, Sensitive Data Scanner.

Who Should Attend

Monitoring engineers who want to add Datadog monitoring tool in their skillset.
DevOps Engineers
Application Developers

Target Audiences

Monitoring engineers who want to add Datadog monitoring tool in their skillset.
DevOps Engineers
Application Developers

“Datadog is an observability service for cloud-scale applications, providing monitoring of servers, databases, tools, and services, through a SaaS-based data analytics platform.”

What’s included in the course ?

Complete Datadog monitoring tool’s features explained from Scratch to In-depth Advance level.
Covers a wide scope of almost all the Datadog features listed in Datadog’s official documentation.
Datadog Agent setup & configuration, Metrics, Events, Infrastructure Monitoring, Log Management, Application Performance Monitoring, Continuous Profiling, UI Monitoring, Dashboards, Notebooks, Monitors and many more.
Each Datadog monitoring feature and the associated concepts are demonstrated with proper Theory and Real-time Hands-On examples.
Interact with Multiple integrationssupported by Datadog monitoring tool.
Build and Instrument a Python Flask application for Application Performance Monitoring and Continuous Profiling.
Exclusive Datadog Topicslike End-to-End Log Pipeline (LMS), Trace Pipeline (APM), Datadog Containerized Agent, Application Instrumentation etc.
This course is useful for Application developers too as there are multiple sections in the course that involves Instrumenting Applications to generate Custom Metrics, Custom Events, Traces etc.
For Datadog Administrators, there is a section for Datadog Account Management that involves Granting Roles & Permissions, API keys, SAML Group mappings, Audit Trail, Sensitive Data Scanner etc.
Course is packed with many Datadog Tips & Tricks that can be very helpful in your day to day interaction with Datadog monitoring tool in Real projects.

After completing this Datadog course, you can start working on any Real-time Datadog monitoring project with full confidence.

Please go through the above Course content/Curriculum to get more details of it.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction to Monitoring in SDLC

Lecture 2: What is Datadog monitoring tool

Lecture 3: Key functionalities of monitoring tools

Lecture 4: Announcement

Lecture 5: Monitoring Terminologies

Lecture 6: Architecture of Datadog

Chapter 2: Pricing and Setup

Lecture 1: Datadog Pricing

Lecture 2: Datadog Setup and account creation

Chapter 3: Datadog Agent

Lecture 1: Datadog Agent Manager

Lecture 2: Datadog Agent's Directory Tour

Lecture 3: Datadog Agent Manager continued

Chapter 4: Infrastructure Monitoring – Host

Lecture 1: Host Map

Lecture 2: Agent, System, Ntp metrics in Host Map

Chapter 5: Tags in Datadog

Lecture 1: Introduction to Tagging

Lecture 2: Unified Service Tagging (Reserved Tags) in Datadog

Lecture 3: Filtering, Grouping on Tags

Lecture 4: Assigning Tags from datadog.yaml file

Lecture 5: Announcement1

Lecture 6: Host Map Options

Chapter 6: Infrastructure Monitoring – Processes

Lecture 1: Process Explorer – Part 1

Lecture 2: Process Explorer – Part 2

Lecture 3: Scrubbing Sensitive data

Lecture 4: Create Custom Process metrics

Chapter 7: Infrastructure Monitoring – Containers

Lecture 1: Introduction

Lecture 2: Docker Setup

Lecture 3: Containerized Docker Agent Setup

Lecture 4: Container Map and Live Containers

Lecture 5: Realistic approach to run Docker agent

Lecture 6: Environment Variables Translation rules

Lecture 7: Run Docker Agent from Docker Compose file

Chapter 8: Metrics and Metric Views in Datadog

Lecture 1: What are Metrics ?

Lecture 2: Why Datadog Agent aggregates metrics

Lecture 3: Count, Rate, Gauge, Set Metric types

Lecture 4: Histogram Metric type

Lecture 5: Distribution Metric type

Lecture 6: Datadog's Summary View for Metrics

Lecture 7: Metric Explorer

Chapter 9: Custom Metrics – Agent Check

Lecture 1: Custom Metrics Fundamentals

Lecture 2: Custom Metrics submission types

Lecture 3: Create Custom Check for COUNT metric type

Lecture 4: Custom Agent check running

Lecture 5: Metric Without Limits

Lecture 6: Create Custom Check for GAUGE metric type

Lecture 7: Create Custom Check for RATE metric type

Lecture 8: Create Custom Check for HISTOGRAM metric type

Chapter 10: Custom Metrics – DogStatsD & Python app

Lecture 1: Python application code to instrument

Lecture 2: increment() & decrement() functions for COUNT metric type

Lecture 3: Instrument Python app for COUNT metric type

Lecture 4: Instrument Python app for GAUGE metric type

Lecture 5: Instrument Python app for HISTOGRAM & DISTRIBUTION

Chapter 11: Events

Lecture 1: Introduction to Events

Lecture 2: Event Log Check to capture Windows Events

Lecture 3: Create Custom events

Lecture 4: Event Explorer

Chapter 12: Notebooks

Lecture 1: Create notebook – Add Timeseries Cell

Lecture 2: Add Text, Table cells in notebook

Lecture 3: Notebook Settings

Lecture 4: Notebook Templates

Chapter 13: Dashboards

Lecture 1: Introduction to Dashboards

Lecture 2: Timeseries widget

Lecture 3: Find Correlations in metrics

Lecture 4: Query values, Table, Top list widgets

Lecture 5: Groups, Annotations, Summaries, List, Stream widgets

Lecture 6: Template Variables

Lecture 7: Dashboard Settings

Chapter 14: Monitors & Alerts

Lecture 1: Create Host Monitor

Lecture 2: Tag, Template, Conditional Variables

Lecture 3: Draft Notification messages

Lecture 4: Draft Renotification message

Lecture 5: EVAL function

Lecture 6: Trigger Monitor & Test notifications

Lecture 7: Manage Monitors View

Lecture 8: Downtime

Chapter 15: Logs Collection

Lecture 1: Introduction to Datadog's Log Management

Lecture 2: Configurations required to collect logs from Python App

Lecture 3: Python application to generate logs

Lecture 4: Containerized Log collection

Chapter 16: Logs Preprocessing – Datadog Log Pipelines

Lecture 1: Introduction to Log pipelines

Instructors

Cstech Training
Online Instructor

Rating Distribution

1 stars: 23 votes
2 stars: 11 votes
3 stars: 73 votes
4 stars: 316 votes
5 stars: 426 votes

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