Logstash overview in Elasticsearch - Step-by-Step Execution

Concept Flow - Logstash overview

Start Logstash

↓

Input: Receive Data

↓

Filter: Process & Transform

↓

Output: Send Data

↓

End

Logstash takes data in, processes it, and sends it out in a flow from input to filter to output.

Execution Sample

Elasticsearch

input {
  stdin {}
}
filter {
  mutate { lowercase => ["message"] }
}
output {
  stdout { codec => rubydebug }
}

This Logstash config reads input from the keyboard, makes the message lowercase, and prints it out.

Execution Table

Step	Action	Input Data	Filter Applied	Output Data
1	Receive input	HELLO WORLD	None yet	HELLO WORLD
2	Apply filter	HELLO WORLD	Lowercase message	hello world
3	Send output	hello world	Filter done	hello world
4	Wait for next input	None	None	None

💡 Logstash waits for new input after processing current data.

Variable Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	Final
message	None	HELLO WORLD	hello world	hello world	hello world

Key Moments - 2 Insights

Why does Logstash have separate input, filter, and output sections?

Because each section has a clear job: input gets data, filter changes data, output sends data. This flow is shown in the execution_table steps 1 to 3.

What happens if no filter is defined?

Data passes from input directly to output unchanged, like step 1 to 3 but skipping filtering in the execution_table.

Visual Quiz - 3 Questions

Look at the execution_table, what is the message content after Step 2?

A "hello world"

B "Hello World"

C "HELLO WORLD"

D "HELLO world"

💡 Hint

Check the 'Output Data' column at Step 2 in the execution_table.

At which step does Logstash apply the filter to the data?

A Step 1

B Step 2

C Step 3

D Step 4

💡 Hint

Look at the 'Filter Applied' column in the execution_table.

If the filter was removed, what would be the output at Step 3?

A "Hello World"

B "hello world"

C "HELLO WORLD"

D No output

💡 Hint

Without filter, input data passes unchanged to output, see Step 1 and 3 comparison.

Concept Snapshot

Logstash processes data in three parts:
Input: where data comes in
Filter: where data is changed or enriched
Output: where data is sent out
Data flows step-by-step through these stages
Filters modify data before output

Full Transcript

Logstash is a tool that takes data from many sources, changes it if needed, and sends it somewhere else. It works in three steps: input, filter, and output. First, it gets data from input like a keyboard or file. Then it changes the data using filters, for example making text lowercase. Finally, it sends the changed data to output like the screen or a database. This flow helps organize data processing clearly and simply.

Practice

1. What is the primary role of Logstash in the Elastic Stack?

easy

A. To store data in a database

B. To visualize data with dashboards

C. To collect, process, and forward data from various sources

D. To secure the Elastic Stack with authentication

Solution

1. Step 1: Understand Logstash's function

   Logstash is designed to collect and process data from many sources before sending it to storage or analysis tools.

2. Step 2: Compare with other Elastic Stack components

   Elasticsearch stores data, Kibana visualizes it, and security features handle authentication, so these are not Logstash's main roles.

3. Final Answer:

   To collect, process, and forward data from various sources -> Option C

4. Quick Check:

   Logstash = Data collection and processing [OK]

Hint: Remember: Logstash handles data input and processing [OK]

Common Mistakes:

• Confusing Logstash with Elasticsearch or Kibana
• Thinking Logstash stores data permanently
• Assuming Logstash manages security

2. Which section in a Logstash configuration file defines where data comes from?

easy

A. filter

B. input

C. output

D. codec

Solution

1. Step 1: Identify configuration sections

   Logstash config files have three main sections: input, filter, and output.

2. Step 2: Match section to purpose

   The input section specifies data sources, filter modifies data, and output sends data elsewhere.

3. Final Answer:

   input -> Option B

4. Quick Check:

   Data source = input section [OK]

Hint: Input section = data source definition [OK]

Common Mistakes:

• Choosing filter or output instead of input
• Confusing codec with input
• Thinking output defines data source

3. Given this Logstash config snippet:

input { stdin { } } filter { mutate { add_field => { "new_field" => "value" } } } output { stdout { codec => rubydebug } }

What will happen when you type 'hello' and press enter?

medium

A. The input 'hello' is printed with an added field 'new_field' set to 'value'

B. The input 'hello' is discarded and nothing is printed

C. An error occurs because 'add_field' is not valid here

D. The input 'hello' is printed without any changes

Solution

1. Step 1: Analyze input and filter

   The input reads from standard input (stdin). The filter adds a new field named 'new_field' with value 'value' to each event.

2. Step 2: Analyze output

   The output prints the event to stdout using rubydebug codec, which shows all fields including added ones.

3. Final Answer:

   The input 'hello' is printed with an added field 'new_field' set to 'value' -> Option A

4. Quick Check:

   Filter adds field, output shows it [OK]

Hint: Filter adds fields; output shows full event [OK]

Common Mistakes:

• Thinking input is discarded
• Believing add_field causes error
• Assuming output prints raw input only

4. Identify the error in this Logstash config snippet:

input { file { path => "/var/log/syslog" } } filter { grok { match => { "message" => "%{SYSLOGTIMESTAMP:timestamp}" } } } output { elasticsearch { hosts => ["localhost:9200"] } }

medium

A. Elasticsearch output hosts must be a string, not an array

B. Missing closing brace in filter section

C. Grok pattern syntax is incorrect

D. File input path should be an array, not a string

Solution

1. Step 1: Check file input syntax

   The 'path' option for file input expects an array of strings, not a single string.

2. Step 2: Verify other sections

   Filter grok syntax and output hosts as array are correct according to Logstash documentation.

3. Final Answer:

   File input path should be an array, not a string -> Option D

4. Quick Check:

   File path = array required [OK]

Hint: File input path must be an array even for one file [OK]

Common Mistakes:

• Using string instead of array for file path
• Misreading grok pattern syntax
• Thinking output hosts must be string

5. You want to collect logs from multiple servers, add a tag with the server name, and send all logs to Elasticsearch. Which Logstash configuration approach is best?

hard

A. Use multiple input sections with file paths and add tags in filter section, then output to Elasticsearch

B. Use one input section with a wildcard path and add tags in output section

C. Use multiple output sections for each server and add tags in input section

D. Use filter section only to read files and add tags, then output to Elasticsearch

Solution

1. Step 1: Understand data collection from multiple servers

   Multiple input sections allow specifying different file paths per server.

2. Step 2: Add tags in filter section

   The filter section is the right place to add tags like server names to enrich data.

3. Step 3: Output all processed logs to Elasticsearch

   The output section sends all enriched logs to Elasticsearch for indexing.

4. Final Answer:

   Use multiple input sections with file paths and add tags in filter section, then output to Elasticsearch -> Option A

5. Quick Check:

   Input for sources + filter for tags + output to ES [OK]

Hint: Input for sources, filter for tags, output to Elasticsearch [OK]

Common Mistakes:

• Adding tags in output section
• Using filter to read files (wrong place)
• Multiple outputs instead of inputs for servers