Top 8 Recommended Datadog Self-Study Materials! [June 2023]

This course will help you to:

1. Understand basic and advanced concepts of Application Performance Management and Datadog tool usage

2. To build APM for your application with Datadog from scratch.

3. To visualize the entire request path and determine exactly where a bottleneck or error occurred.

To Be able only with a few mouse clicks to track errors inside your application and find slow queries.

4. Perform datadog Agent installations, configurations and query basic metrics.

5. Analyze datadog APM Service monitoring, Trace searches and Code Profiling.

This includes .NET Core API monitoring with the SQL service layer.

6. Create dashboards with different widgets like timeseries, query values and toplists.

We will create widgets together for:

- Latency in Timeseries and Query value graph

- Error rate in Timeseries and Query value graph

- Top List Endpoints in List/Table/Pie Chart

- Host graph usage

- Service map usage

- Applying Formulas

7. Create Monitors/Alerts for host, services, endpoints, iis and watchdog.

We will create alerts together for::

- monitor for request latency

- monitor for error rate

- monitor for specific api endpoint

- monitor for sql query duration

- monitor for host data reporting

- watchdog monitors

8. Understand SLA, SLO, SLI and Error Budget by creating Datadog SLO for success rate

9. Integrate monitors with Slack and PagerDuty

10. Synthetic Monitoring with API and Browser Tests creation using Get/Post requests with Authorization Bearer Tokens

11. Log Management and how to save/view logs using NLog in Datadog

12. Notebook

- how to investigate an issue using notebook and collaborate with team members using comments

- how to use templates and create custom ones

13. Monitor application key aspects like availability, reliability, scalability and duration.

14. How to setup and monitor NodeJS application with MongoDB in Datadog - with custom metrics and traces

1. Introduction
2. Welcome and Introduction to course
3. What is Application Performance Management?
4. Get started with Datadog: Registration, Pricing, and Agent installation
5. What is Datadog and why do we need it?
6. Pricing Information - free and paid options
7. Basic Definitions - host, agent and tags
8. Registration and Agent Installation
9. Quiz For Datadog - Section 2
10. Datadog Agent: Definitions, Configuration and Integrations
11. Datadog Agent - definitions and configurations
12. Datadog Agent - display host basic metrics and default host dashboards
13. Datadog Agent - integration with Internet Information Server (IIS)
14. Quiz for Datadog Agent
15. Datadog Infrastructure: Host maps and Infrastructure List
16. Datadog Infrastructure: Host maps and Infrastructure List
17. Datadog Metrics: Explorer, Summary and Metric Types
18. Metrics Explorer
19. Metrics Summary and Metrics Types
20. Quiz on Datadog Metrics - Explorer, Summary and Metric Types
21. Datadog APM: Download, Installation, Services, Traces and Error Tracking
22. APM will monitor our DogsWorld application based on .NET Core
23. APM - download, installation and basic configuration (Windows)
24. APM Services and Service Map
25. APM Traces - Transactions, Basic search, Search pane and Facets
26. APM Traces - Flame graph, Span list and System Tags
27. APM Traces - Error Tracing
28. APM - Profiling
29. Quiz for APM
30. Datadog APM: Custom Tags, Exception Handling and Facets
31. APM - Custom Tags and Sending custom tags using .NET Tracer Nuget Package
32. APM - Custom Tags, Search, Filter and Facet usage
33. Quiz for Datadog Tags
34. Datadog Dashboards: Create (with Graphs), Import, Export and Variable Usages
35. Dashboard List and Definitions
36. Dashboard - Create a New Dashboard with many Widgets
37. Dashboard - Import widgets/graphs into Dashboard from Services and Metrics Page
38. Dashboard - Import and Export as JSON
39. Dashboard - Variables usage
40. Quiz for Datadog Dashboards
41. Datadog Monitors (Alerts) and Notifications by Email, Slack and PagerDuty
42. Monitors - Create Monitors
43. Monitors - Suggested Monitors
44. Monitors - Management
45. Monitors - Integration with Slack
46. Pager Duty - Account Creation
47. Monitors - Integration with Pager Duty
48. Quiz for Datadog - Monitors
49. Datadog: SLA, SLO, SLI and Error Budget (DevOps)
50. Datadog - SLA, SLO, SLI and Error Budget (DevOps)
51. Datadog - SLO Creation, Date Correlation and Setup Alerts
52. Datadog: SLA, SLO, SLI and Error Budget Quiz
53. Synthetic Monitoring: API Tests and Browser Tests
54. What is a Synthetic Monitoring
55. Create API Tests
56. Create Browser Tests
57. Quiz for Datadog - Synthetic Monitoring
58. Log Management: Basics, Log Entries, Log Exceptions, NLog usage
59. What is a Log Management System
60. How to Log Data using NLog
61. Log Explorer and Log Exceptions
62. Quiz for Dataog - Log Management
63. Notebook: Creation, Issue Investigation, Documentation and Templates Usage
64. What is a Notebook in Datadog?
65. How to create Documentation Type of Notebook
66. How to Investigate an Exception using Notebook and collaborate with other users
67. Notebook Templates (Custom and Built in)
68. Questions for Datadog Notebook
69. NodeJS with MongoDB application monitoring in Datadog
70. Setup NodeJS application with MongoDB locally from GitHub
71. Configure NodeJS Custom Metrics
72. Configure NodeJS Services and Traces
73. NodeJS and MongoDB Service Catalog
74. NodeJS Traces
75. Datadog - Account
76. Account Summary
77. Account Collaboration
78. Final

Are you preparing to be Datadog certified on APM & Distributed Tracing Fundamentals? Taking the practice exams here will help you in two ways:

1. Test the coverage of your knowledge - Most Datadog users master the features that they use in their day-to-day work but are less familiar with functionalities that they need less frequently. You can use the practice exam to test how much you already know and which topics you need to learn more about. Each question in the practice exams includes an explanation and/or points to the relevant Datadog documentation for you to review.

2. Familiarize you with the question patterns - Getting certified through a multiple choice exam is a skill on top of your Datadog product knowledge. You can use the practice exam to help anticipate how questions are phrased and how wrong choices are presented to distract you from the correct answer. The questions are designed to mimic the tone and style of the official Datadog exam to simulate the testing experience.

Note: This is a practice exams course only so there will be no lectures. Although there are no lectures, you can master Datadog concepts by reviewing the explanation on each question.

This course contains multiple practice exams with 90 questions each. Each practice exam should be taken in under 2 hours.

The practice exam only contains multiple choice type of question similar to the real Datadog exam. There's one correct response and two or more incorrect responses. You need to select the response that best answers the question posed. There are no deductions for choosing incorrect answers.

The practice exams will test your knowledge on the following topics:

General APM and distributed tracing knowledge

• Justifying the rationale for application monitoring

• Understanding Datadog's approach to tracing, retention, and tagging

• Recognizing the instrumentation differences of programming languages

Instrumenting applications

• Configuring tracing libraries with different instrumentation methods

• Understanding the Datadog Agent architecture

• Understanding data sampling, retention, and security

• Enabling correlation across traces, logs, and real-user monitoring

• Enabling continuous profiling and deployment tracking

Discovering insights using APM

• Searching live and retained traces

• Using services, resources, and span summary views

• Using APM and profiler flame graphs

• Using deployment tracking and error tracking

• Identifying slow endpoints and other performance issues

Visualizing insights using APM

• Reading service performance dashboards

• Generating metrics from APM spans

• Calculating Apdex scores for web services

Troubleshooting application performance

• Applying trace search during incidents

• Setting up alerting on key APM data

Other related features

• Using the Continuous Profiler

• Creating Anomaly Monitors

• Defining SLOs

• Instrumenting with the Lambda Extension

• Applying advanced usage of ddtrace library

1. APM & Distributed Tracing Fundamentals Practice Test 1
2. APM & Distributed Tracing Fundamentals Practice Test 2

Are you preparing to be Datadog certified on Log Management Fundamentals? Taking the practice exams here will help you in two ways:

1. Test the coverage of your knowledge - Most Datadog users master the features that they use in their day-to-day work but are less familiar with functionalities that they need less frequently. You can use the practice exam to test how much you already know and which topics you need to learn more about. Each question in the practice exams includes an explanation and/or points to the relevant Datadog documentation for you to review.

2. Familiarize you with the question patterns - Getting certified through a multiple choice exam is a skill on top of your Datadog product knowledge. You can use the practice exam to help anticipate how questions are phrased and how wrong choices are presented to distract you from the correct answer. The questions are designed to mimic the tone and style of the official Datadog exam to simulate the testing experience.

Note: This is a practice exams course only so there will be no lectures. Although there are no lectures, you can master Datadog concepts by reviewing the explanation on each question.

This course contains multiple practice exams with 90 questions each. Each practice exam should be taken in under 2 hours.

The practice exam only contains multiple choice type of question similar to the real Datadog exam. There's one correct response and two or more incorrect responses. You need to select the response that best answers the question posed. There are no deductions for choosing incorrect answers.

The practice exams will test your knowledge on the following topics:

• General log management knowledge

  • Justifying the rationale of logging systems

  • Understanding logging sources and formats

  • Addressing common logging use cases

• Collecting logs

  • Enabling log collection

  • Filtering logs to be collected

  • Obfuscating sensitive data in logs

• Parsing and processing logs

  • Using log processors and log pipelines

  • Using standard attributes

  • Understanding the composition of a log

• Searching and filtering logs

  • Understanding the Live Tail and Log Explorer views

  • Applying log explorer functionalities

  • Using the Datadog log search syntax

• Visualizing and analyzing logs

  • Filtering and/or excluding logs for analysis

  • Using different log aggregations

  • Visualizing and communicating information from logs

  • Exporting logs out of Datadog

• Operating with log management features

  • Ingesting and indexing logs

  • Archiving and rehydrating logs

  • Creating monitors and alerts

  • Generating metrics from logs

  • Handling sensitive data in logs

  • Controlling access to logs

• Troubleshooting logs setup issues

  • Troubleshooting Datadog Agent issues

  • Troubleshooting log ingestion issues

1. Log Management Fundamentals Practice Test 1
2. Log Management Fundamentals Practice Test 2

"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.

• 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 integrations supported by Datadog monitoring tool.

• Build and Instrument a Python Flask application for Application Performance Monitoring and Continuous Profiling.

• Exclusive Datadog Topics like 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.

1. Introduction
2. Introduction to Monitoring in SDLC
3. What is Datadog monitoring tool
4. Key functionalities of monitoring tools
5. Announcement
6. Monitoring Terminologies
7. Architecture of Datadog
8. Pricing and Setup
9. Datadog Pricing
10. Datadog Setup and account creation
11. Datadog Agent
12. Datadog Agent Manager
13. Datadog Agent's Directory Tour
14. Datadog Agent Manager continued
15. Quiz 1
16. Infrastructure Monitoring - Host
17. Host Map
18. Agent, System, Ntp metrics in Host Map
19. Tags in Datadog
20. Introduction to Tagging
21. Unified Service Tagging (Reserved Tags) in Datadog
22. Filtering, Grouping on Tags
23. Assigning Tags from datadog.yaml file
24. Host Map Options
25. Quiz 2
26. Infrastructure Monitoring - Processes
27. Process Explorer - Part 1
28. Process Explorer - Part 2
29. Scrubbing Sensitive data
30. Create Custom Process metrics
31. Infrastructure Monitoring - Containers
32. Introduction
33. Docker Setup
34. Containerized Docker Agent Setup
35. Container Map and Live Containers
36. Realistic approach to run Docker agent
37. Environment Variables Translation rules
38. Run Docker Agent from Docker Compose file
39. Quiz 3
40. Metrics and Metric Views in Datadog
41. What are Metrics ?
42. Why Datadog Agent aggregates metrics
43. Count, Rate, Gauge, Set Metric types
44. Histogram Metric type
45. Distribution Metric type
46. Datadog's Summary View for Metrics
47. Metric Explorer
48. Custom Metrics - Agent Check
49. Custom Metrics Fundamentals
50. Custom Metrics submission types
51. Create Custom Check for COUNT metric type
52. Custom Agent check running
53. Metric Without Limits
54. Create Custom Check for GAUGE metric type
55. Create Custom Check for RATE metric type
56. Create Custom Check for HISTOGRAM metric type
57. Custom Metrics - DogStatsD & Python app
58. Python application code to instrument
59. increment() & decrement() functions for COUNT metric type
60. Instrument Python app for COUNT metric type
61. Instrument Python app for GAUGE metric type
62. Instrument Python app for HISTOGRAM & DISTRIBUTION
63. Quiz 4
64. Events
65. Introduction to Events
66. Event Log Check to capture Windows Events
67. Create Custom events
68. Event Explorer
69. Notebooks
70. Create notebook - Add Timeseries Cell
71. Add Text, Table cells in notebook
72. Notebook Settings
73. Notebook Templates
74. Quiz 5
75. Dashboards
76. Introduction to Dashboards
77. Timeseries widget
78. Find Correlations in metrics
79. Query values, Table, Top list widgets
80. Groups, Annotations, Summaries, List, Stream widgets
81. Template Variables
82. Dashboard Settings
83. Monitors & Alerts
84. Create Host Monitor
85. Tag, Template, Conditional Variables
86. Draft Notification messages
87. Draft Renotification message
88. EVAL function
89. Trigger Monitor & Test notifications
90. Manage Monitors View
91. Downtime
92. Quiz 6
93. Logs Collection
94. Introduction to Datadog's Log Management
95. Configurations required to collect logs from Python App
96. Python application to generate logs
97. Containerized Log collection
98. Logs Preprocessing - Datadog Log Pipelines
99. Introduction to Log pipelines
100. Create Custom Processor in Pipeline using Grok Parser
101. Create Custom Pipeline
102. Standard Attributes
103. Generate Log based metrics
104. Create Custom Index
105. Exclusion Filter in an Index
106. Archive Logs to Google Cloud
107. Log Rehydration
108. Log Explorers
109. Live Tail view
110. Group logs by Fields, Patterns, Transactions
111. Create Facet in Facet panel
112. Create Measure in Facet panel
113. Quiz 7
114. Datadog Integrations
115. Datadog Integrations Types
116. Supported Datadog Integrations with default Dashboards
117. Application Performance Monitoring (APM) - Instrument Flask App
118. Understanding Flask application
119. What are Traces & Spans
120. APM Setup & Configuration
121. Run app with ddtrace instrumentation
122. APM - Trace Pipeline
123. Introduction to Trace pipeline
124. Sampling - Agent & Library level
125. Trace Metrics
126. Sever side components of Trace pipeline
127. Ingestion Control - Usage Dashboard
128. Ingestion Control - Manage Agent & Library Sampling
129. Ingestion Control - Library Sampling
130. Ingestion Control - Custom metrics & Retention filters
131. APM Views & Explorers
132. Live Search
133. Trace View - Flame graph, Span list, Dependency Map
134. Introduction to Service Catalog
135. Service catalog - Ownership, Reliability, Performance, Security views
136. Service page
137. Resource page
138. Deployments tab & Service Map view
139. Instrument application for Error Tracking
140. Error Tracking page
141. Connect Traces to Logs
142. Service Registration
143. Quiz 8
144. Continuous Profiling
145. Instrumentation for Profiling
146. Endpoint Profiling & Code hotspots
147. UI Monitoring
148. Introduction to Real User Monitoring (RUM)
149. Instrument application for RUM
150. Event types collected by RUM
151. Customize & Enrich RUM data
152. Session & Replays
153. View Panel
154. Dashboards and Generate Custom RUM Metrics
155. Account Management for Admins
156. Personal Settings
157. Organization settings
158. SAML Group mappings
159. API and Application keys
160. Login methods
161. Audit Trail
162. Sensitive data scanner
163. Plan and usage
164. Additional Learnings
165. Docker Installation on Ubuntu
166. VM Ubuntu Installation

This course is for intermediate+ DevOps software engineer to learn observability in Kubernetes using Datadog (monitoring, logging, alerting).

If you are one of the below:

- what is Datadog and datadog agentg?

- how can I aggregate and analyze K8s logs?

- what is APM (App Performance Monitoring)?

- what are Datadog features/services?

Then, you will understand the basics of Datadog in 30 minutes!

Who should take this course

• at least intermediate level in DevOps, Kubernetes, and Docker

• you know how to use Helm chart

• you have setup K8s cluster in AWS EKS (or GKE etc)

Why you should take this course:

1. Instructed by a cloud DevOps engineer (with CKA and certified AWS DevOps pro) working at US company in SF

I have been pretty handson with Terraform, AWS, AWS EKS with 7+ industry experience in both North America and Europe.

My background & Education & Career experience

• Cloud DevOps Software Engineer with 7+ years experience

• Bachelor of Science in Computing Science from a Canadian university

• Knows Java, C#, C++, Bash, Python, JavaScript, Terraform, IaC

• Expert in AWS (holds AWS DevOps Professional certification) and Kubernetes (holds Certified Kubernetes Administrator, CKA)

I will see you inside!

Please note this is a free sample course for "Datadog in Kubernetes"

NOTE: This is a free intro course for "Datadog in Kubernetes".

1. Datadog Overview
2. 1.0 Datadog overview
3. 1.1 Integration
4. 1.2 Dashboard
5. 1.3 Infra
6. 1.4 Logs
7. 1.5 Events
8. 1.6 APM
9. 1.7 Synthetic tests
10. 1.8 Network
11. Deploy Guestbook App to K8s
12. Set up ESK Cluster and Deploy Guestbook App in K8s
13. BONUS lecture
14. Bonus: what is next step?