Data Visualization with Kibana

5h 16m 55s
English
Paid

Course description

Are you a software developer, and do you want to learn Kibana? Then look no further — you have come to the right place! This course is the best way for you to quickly learn Kibana and put your knowledge to use within just a few hours. Forget about watching countless of YouTube tutorials, webinars, and blog posts; this course is the single resource you need to learn Kibana. In fact, this is by far the most comprehensive course on Kibana you will find!

Read more about the course

So what is Kibana, and why should you take the time to learn it? Kibana is part of the ELK stack (Elasticsearch, Logstash, Kibana) and the Elastic Stack. It's often referred to as the window into Elasticsearch. With Kibana, you can visualize the data stored within an Elasticsearch cluster. This includes everything from running ad hoc queries, creating visualizations such as line charts and pie charts, and displaying data on dashboards. Kibana enables you to easily interact with your data, providing a much better experience than writing Elasticsearch queries. Slicing and dicing data is easy, and navigating between different datasets can be done without losing context. As such, Kibana is an excellent tool for data analysis, exploration, and investigation. Dashboards are a key feature, enabling us to provide ourselves and teams with overviews of relevant data. For instance, we could create a dashboard for a sales department, and another for software engineers.

Kibana is also commonly used for monitoring data, for instance in the context of observability. By using Kibana and the Elastic Stack for observability, you can gain insight into the performance of applications (APM), monitor service uptime, keep an eye on hardware and service utilization, etc. Apart from that, Kibana is also frequently used for security analysis and managing machine learning jobs.

Needless to say, Kibana is an incredibly powerful tool for visualizing, analyzing, and monitoring Elasticsearch data.

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#1: Introduction to the course

All Course Lessons (56)

#Lesson TitleDurationAccess
1
Introduction to the course Demo
05:31
2
Introduction to Kibana
04:09
3
Overview of installation options
02:43
4
Running Elasticsearch & Kibana in Elastic Cloud
05:42
5
Installing Kibana on macOS and Linux
04:00
6
Activating trial license
02:09
7
Console tool
03:42
8
Adding index templates
04:55
9
Importing test data
06:03
10
Introduction to the test data
08:50
11
Creating index patterns
07:13
12
Overview of apps
15:44
13
Setting the time filter
03:46
14
Kibana Query Language (KQL)
09:21
15
Discover app
12:46
16
Saving queries
03:19
17
Inspecting requests
02:28
18
How Kibana handles time zones
06:31
19
Changing Kibana’s time zone
02:35
20
Introduction to visualizations
01:13
21
Introduction to aggregations
04:11
22
Metric visualization
10:09
23
Formatting numbers
02:57
24
Vertical Bar
06:46
25
Area chart
06:04
26
Line chart
06:13
27
Changing the chart type
02:30
28
Pie chart
06:38
29
Splitting with KQL filters
03:49
30
Working with numeric ranges
02:38
31
Working with dynamic ranges (histograms)
07:59
32
Customizing visualizations
06:06
33
Data tables
09:31
34
Heat maps
09:00
35
Tag clouds
04:04
36
Goals & Gauges
09:02
37
Linking visualizations to saved searches
04:36
38
Applying saved queries to visualizations
01:49
39
Introduction to dashboards
01:40
40
Creating a dashboard
06:38
41
Editing visualizations
04:35
42
Filtering documents
01:52
43
Inspecting panels
02:11
44
Creating the access logs dashboard
02:38
45
Interactivity
04:38
46
Drilldowns
10:12
47
Introduction
01:22
48
Enabling security features
07:11
49
Introduction to spaces
09:05
50
Copying objects between spaces
10:11
51
Creating and managing users
03:29
52
Introduction to roles
06:32
53
Configuring privileges with custom roles
09:50
54
Combining space and role privileges
11:27
55
How role privileges are merged
05:20
56
Wrap up
01:22

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