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01 – Introduction
0/6
Introduction to Monitoring in SDLC
05:03
What is Datadog monitoring tool
03:45
Key functionalities of monitoring tools
02:38
Announcement
01:03
Monitoring Terminologies
05:21
Architecture of Datadog
05:01
02 – Pricing and Setup
0/2
Datadog Pricing
04:26
Datadog Setup and account creation
04:36
03 – Datadog Agent
0/3
Datadog Agent Manager
03:34
Datadog Agent’s Directory Tour
06:06
Datadog Agent Manager continued
05:04
04 – Infrastructure Monitoring – Host
0/2
Host Map
05:38
Agent, System, Ntp metrics in Host Map
06:16
05 – Tags in Datadog
0/5
Introduction to Tagging
03:04
Unified Service Tagging (Reserved Tags) in Datadog
03:46
Filtering, Grouping on Tags
05:24
Assigning Tags from datadog.yaml file
03:51
Host Map Options
03:46
06 – Infrastructure Monitoring – Processes
0/4
Process Explorer – Part 1
05:00
Process Explorer – Part 2
06:06
Scrubbing Sensitive data
04:37
Create Custom Process metrics
04:58
07 – Infrastructure Monitoring – Containers
0/7
Introduction
03:33
Docker Setup
04:47
Containerized Docker Agent Setup
06:46
Container Map and Live Containers
04:19
Realistic approach to run Docker agent
03:01
Environment Variables Translation rules
02:49
Run Docker Agent from Docker Compose file
04:27
08 – Metrics and Metric Views in Datadog
0/7
What are Metrics
04:02
Why Datadog Agent aggregates metrics
03:28
Count, Rate, Gauge, Set Metric types
03:07
Histogram Metric type
02:36
Distribution Metric type
03:50
Datadog’s Summary View for Metrics
09:23
Metric Explorer
08:39
09 – Custom Metrics – Agent Check
0/8
Custom Metrics Fundamentals
02:58
Custom Metrics submission types
04:30
Create Custom Check for COUNT metric type
08:11
Custom Agent check running
03:16
Metric Without Limits
07:23
Create Custom Check for GAUGE metric type
06:25
Create Custom Check for RATE metric type
04:28
Create Custom Check for HISTOGRAM metric type
03:17
10 – Custom Metrics – DogStatsD & Python app
0/5
Python application code to instrument
04:42
increment() & decrement() functions for COUNT metric type
04:20
Instrument Python app for COUNT metric type
05:12
Instrument Python app for GAUGE metric type
05:15
Instrument Python app for HISTOGRAM & DISTRIBUTION
02:58
11 – Events
0/4
Introduction to Events
02:53
Event Log Check to capture Windows Events
10:17
Create Custom events
05:00
Event Explorer
03:04
12 – Notebooks
0/4
Create notebook – Add Timeseries Cell
06:29
Add Text, Table cells in notebook
05:20
Notebook Settings
04:39
Notebook Templates
04:19
13 – Dashboards
0/7
Introduction to Dashboards
03:31
Timeseries widget
08:34
Find Correlations in metrics
03:48
Query values, Table, Top list widgets
04:46
Groups, Annotations, Summaries, List, Stream widgets
06:35
Template Variables
05:40
Dashboard Settings
08:10
14 – Monitors & Alerts
0/8
Create Host Monitor
07:37
Tag, Template, Conditional Variables
03:37
Draft Notification messages
05:09
Draft Renotification message
04:02
EVAL function
04:03
Trigger Monitor & Test notifications
04:09
Manage Monitors View
04:37
Downtime
07:31
15 – Logs Collection
0/4
Introduction to Datadog’s Log Management
05:18
Configurations required to collect logs from Python App
05:38
Python application to generate logs
05:13
Containerized Log collection
06:17
16 – Logs Preprocessing – Datadog Log Pipelines
0/9
Introduction to Log pipelines
05:31
Create Custom Processor in Pipeline using Grok Parser
06:32
Create Custom Pipeline
05:02
Standard Attributes
04:53
Generate Log based metrics
04:10
Create Custom Index
05:19
Exclusion Filter in an Index
04:22
Archive Logs to Google Cloud
08:47
Log Rehydration
06:00
17 – Log Explorers
0/4
Live Tail view
04:10
Group logs by Fields, Patterns, Transactions
08:09
Create Facet in Facet panel
05:28
Create Measure in Facet panel
04:57
18 – Datadog Integrations
0/2
Datadog Integrations Types
04:19
Supported Datadog Integrations with default Dashboards
06:02
19 – Application Performance Monitoring (APM) – Instrument Flask App
0/4
Understanding Flask application
12:44
What are Traces & Spans
02:51
APM Setup & Configuration
05:01
Run app with ddtrace instrumentation
04:12
20 – APM – Trace Pipeline
0/8
Introduction to Trace pipeline
03:22
Sampling – Agent & Library level
05:51
Trace Metrics
04:20
Sever side components of Trace pipeline
02:31
Ingestion Control – Usage Dashboard
03:45
Ingestion Control – Manage Agent & Library Sampling
07:00
Ingestion Control – Library Sampling
05:11
Ingestion Control – Custom metrics & Retention filters
09:41
21 – APM Views & Explorers
0/11
Live Search
06:04
Trace View – Flame graph, Span list, Dependency Map
07:46
Introduction to Service Catalog
03:52
Service catalog – Ownership, Reliability, Performance, Security views
04:53
Service page
09:28
Resource page
04:23
Deployments tab & Service Map view
04:14
Instrument application for Error Tracking
05:02
Error Tracking page
05:19
Connect Traces to Logs
08:36
Service Registration
03:42
22 – Continuous Profiling
0/2
Instrumentation for Profiling
04:36
Endpoint Profiling & Code hotspots
05:01
23 – UI Monitoring
0/7
Introduction to Real User Monitoring (RUM)
04:03
Instrument application for RUM
08:53
Event types collected by RUM
04:01
Customize & Enrich RUM data
06:03
Session & Replays
04:55
View Panel
05:41
Dashboards and Generate Custom RUM Metrics
04:14
24 – Account Management for Admins
0/8
Personal Settings
06:47
Organization settings
06:20
SAML Group mappings
03:10
API and Application keys
06:45
Login methods
02:42
Audit Trail
03:52
Sensitive data scanner
07:27
Plan and usage
02:16
25 – Additional Learnings
0/1
VM Ubuntu Installation
06:06
Datadog Monitoring – A Full Basic to ADVANCE Datadog guide
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