Protocol Data Inputs

Overview

Details

This is a Splunk Add-On for receiving data via a number of different data protocols such as TCP , TCP(s) ,HTTP(s) PUT/POST/File Upload , UDP , Websockets , SockJS. The event driven , non blocking , asynchronous architecture is designed to handle connections and data at scale. The polyglot event bus allows you to declaratively plug in custom data handlers in numerous different languages(Java , Javascript , Python, Groovy , Scala , Clojure , Ruby etc..) to pre-process raw data before indexing in Splunk. Secure transport channels also allow for client certificate authentication.

Protocol Data Inputs v1.6.3

Overview

This is a Splunk Add-On for receiving data via a number of different data protocols.

Protocols

TCP
TCP w/ TLS , optional client certificate authentication
UDP (unicast and multicast)
HTTP (PUT and POST methods only , data in request body & file uploads)
HTTPS (PUT and POST methods only , data in request body & file uploads) , optional client certificate authentication
Websockets
SockJS

But we already have TCP/UDP natively in Splunk

Yes we do. And by all means use those. But if you want to perform some custom data handling and pre-processing of the received data before it gets indexed (above and beyond what you can accomplish using Splunk conf files) , then this Modular Input presents another option for you.

Furthermore , this Modular Input also implements several other protocols for sending data to Splunk.

Implementation

This Modular Input utilizes VERTX.IO version 2.1.4 under the hood.http://vertx.io/vertx2/manual.html#what-is-vertx.

This framework provides for an implementation that is :

asynchronous
event driven (reactive)
polyglot (code custom data handlers in java , javascript , groovy , scala , clojure , ruby , python , any JVM lang with a vertx module)
non blocking IO
scales over all your available cores
can serve high volumes of concurrent client connections

Polyglot Custom Data Handling / Pre Processing

The way in which the Modular Input processes the received raw data is entirely pluggable with custom implementations should you wish.

This allows you to :

pre process the raw data before indexing
transform the data into a more optimum state for Splunk
perform custom computations on the data that the Splunk Search language is not the best fit for
decode binary data (encrypted , compressed , images , proprietary protocols , EBCDIC etc....)
enforce CIM compliance on the data you feed into the Splunk indexing pipeline
basically do anything programmatic to the raw byte data you want

To do this you code a Vertx "Verticle" to handle the received data. http://vertx.io/vertx2/manual.html#verticle

These data handlers can be written in numerous JVM languages. http://vertx.io/vertx2/manual.html#polyglot

You then place the handler in the $SPLUNK_HOME/etc/apps/protocol_ta/bin/datahandlers directory.

On the Splunk config screen for the Modular Input there is a field where you can then specify the name of this handler to be applied.

If you don't need a custom handler then the default handler com.splunk.modinput.protocolverticle.DefaultHandlerVerticle will be used.

To get started , you can refer to the default handler examples in the datahandlers directory.

Supported languages and file extensions

Javascript .js
CoffeeScript .coffee
Ruby .rb
Python .py
Groovy .groovy
Java .java (compiled to .class)
Scala .scala
Clojure .clj
PHP .php
Ceylon .ceylon

Note : experimental Nashorn support is included for js and coffee (requires Java 8). To use the Nashorn JS/Coffee engine rather than the default Rhino engine , then edit protocol_ta/bin/vertx_conf/langs.properties

SSL / TLS

This is provisioned using your own Java Keystore that you can create using the keytool utility that is part of the JDK.

Refer to http://vertx.io/vertx2/core_manual_java.html#ssl-servers

Authentication

Client certificate based authentication can be enabled for the TLS/SSL channels you setup.

VERTX Modules and Repositorys

Any required Vertx modules , such as various language modules for the polyglot functionality (JS , Scala , Groovy etc...) will be dynamically downloaded from online repositorys and installed in your protocol_ta/bin/vertx_modules directory.

You can edit your repository locations in protocol_ta/bin/vertx_conf/repos.txt

Performance tuning tips

Due to the nature of the async/event driven/non blocking architecture , the out of the box default settings may just well suffice for you.

But there are some other parameters that you can tune to take more advantage of your underlying computing resource(ie: cpu cores) available to you.

These are the "server_verticle_instances" and "handler_verticle_instances" params.

Refer to http://vertx.io/vertx2/core_manual_java.html#specifying-number-of-instances for an explanation of how increasing the number of instances may help you.

You can also tune the TCP accept queue settings (also requires OS tweaks) , particularly if you are receiving lots of connections within a short time span.

Refer to http://vertx.io/vertx2/manual.html#improving-connection-time

Data Output

By default data will be output to STDOUT in Modular Input Stream XML format.

However you can bypass this if you wish and declare that data is output to a Splunk TCP port or via Splunk's HTTP Event Collector.

Dependencies

Splunk 5.0+
Java Runtime 1.7+
Supported on Windows, Linux, MacOS, Solaris, FreeBSD, HP-UX, AIX

Setup

Optionally set your JAVA_HOME environment variable to the root directory of your JRE installation.If you don't set this , the input will look for a default installed java executable on the path.
Untar the release to your $SPLUNK_HOME/etc/apps directory
Restart Splunk
If you are using a Splunk UI Browse to Settings -- Data Inputs -- Protocol Data Inputs to add a new Input stanza via the UI
If you are not using a Splunk UI (ie: you are running on a Universal Forwarder) , you need to add a stanza to inputs.conf directly as per the specification in README/inputs.conf.spec. The inputs.conf file should be placed in a local directory under an App or User context.

Activation Key

You require an activation key to use this App. Visit http://www.baboonbones.com/#activation to obtain a non-expiring key

Logging

Any log entries/errors will get written to $SPLUNK_HOME/var/log/splunk/splunkd.log

These are also searchable in Splunk : index=_internal error protocol.py

JVM Heap Size

The default heap maximum is 256MB.
If you require a larger heap, then you can alter this in $SPLUNK_HOME/etc/apps/protocol_ta/bin/protocol.py on line 95

JVM System Properties

You can declare custom JVM System Properties when setting up new input stanzas.
Note : these JVM System Properties will apply to the entire JVM context and all stanzas you have setup

Troubleshooting

JAVA_HOME environment variable is set or "java" is on the PATH for the user's environment you are running Splunk as
You are using Splunk 5+
You are using a 1.7+ Java Runtime
You are running on a supported operating system
Look for any errors in $SPLUNK_HOME/var/log/splunk/splunkd.log
Run this command as the same user that you are running Splunk as and observe console output : "$SPLUNK_HOME/bin/splunk cmd python ../etc/apps/protocol_ta/bin/protocol.py --scheme"

Contact

This project was initiated by Damien Dallimore , damien@baboonbones.com

Release Notes

Version 1.6.3

May 10, 2019

cosmetic fixes

Version 1.6.2

April 23, 2019

updated docs

Version 1.6.1

April 19, 2019

added trial key functionality

Version 1.6

March 28, 2019

docs updated

Version 1.5.1

June 3, 2018

minor manager xml ui tweak for 7.1

Version 1.5

May 27, 2018

Added an activation key requirement , visit http://www.baboonbones.com/#activation to obtain a free,non-expiring key
Docs updated
Splunk 7.1 compatible

Version 1.3

Nov. 17, 2016

Added the latest jython jar to the main classpath because the jython language module that
is dynamically installed is missing some useful jython modules ie:json

Version 1.2

July 28, 2016

Added an example handler for decompressing gzip content
com.splunk.modinput.protocol.handlerverticle.GZipHandler

Version 1.1

Nov. 24, 2015

Minor HEC data handling tweaks

Version 1.0

Sept. 22, 2015

Added support to optional output to Splunk via a HEC (HTTP Event Collector) endpoint

Version 0.7

Feb. 11, 2015

Enabled TLS1.2 support by default.
Made the core Modular Input Framework compatible with latest Splunk Java SDK
Please use a Java Runtime version 7+
If you need to use SSLv3 , you can turn this on in bin/protocol.py
SECURE_TRANSPORT = "tls"
#SECURE_TRANSPORT = "ssl"

Version 0.6

Nov. 15, 2014

Abstracted the output transport logic out into verticles.
So you can choose from STDOUT (default for Modular Inputs) or bypass this and output
data to Splunk over other transports ie: TCP.
This also makes it easy to add other output transports in the future.
Futhermore , this makes the implementation of custom data handlers much cleaner as you don't have
worry out output transport logic or formatting Modular Input Stream XML for STDOUT transports.

Version 0.5.1

Nov. 11, 2014

Added langs.properties and repos.txt to the classpath

Version 0.5

Nov. 10, 2014

Initial beta release

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BaboonBones Ltd

Contributors

BaboonBones Ltd

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App Contents: Inputs