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Implementing Splunk Data Stream Processor (DSP) 1.2 Course Overview

Splunk Data Stream Processor (DSP) 1.2 is a comprehensive course designed to provide hands-on training in the use of Splunk’s data processing engine. The main objective of this course is to give you a broad understanding of the key concepts and operational functions of Splunk’s powerful data processing engine. The course will teach you how to build and deploy real-time applications with the Splunk Data Stream Processor (DSP) 1.2 engine. You will learn how to implement monitoring, alerting, and anomaly detection applications in Splunk and create a secure, cloud-native environment to process big data streams in the cloud. You will gain an understanding of the power of Splunk’s data processing engine, how to construct user interfaces for data delivery, and how to monitor applications using data stream processor. You will also learn about the Splunk management components and how to develop custom Splunk data processing applications. The course content is designed to help you quickly have a deep understanding of Splunk’s powerful data streaming processing engine, and to learn how to use it to get valuable business insights. The hands-on assignments in this course are designed to help you gain a fuller understanding of the basics of applying data stream processing with Splunk Data Stream Processor (DSP) 1.2.

This is a Rare Course and it can be take up to 3 weeks to arrange the training.

The 1-on-1 Advantage


Flexible Dates

  • • Choose Start Date
  • • Reschedule After Booking
  • • Weekend / Evening Option

4-Hour Sessions

You will learn:

Module 1: Introduction to DSP
  • Review Splunk deployment options and challenges
  • Describe the purpose and value of Splunk DSP
  • Define DSP concepts and terminologies
  • List DSP core components and system requirements
  • Describe installation options and steps
  • Check DSP service status
  • Learn to navigate in DSP UI
  • Use scloud
  • Ingest data with DSP REST API service
  • Configure DSP source connections for Splunk data
  • Configure DSP sink connections for Splunk indexers
  • Create Splunk-to Splunk pass-through pipelines
  • Describe the basic elements of a DSP pipeline
  • Create data pipelines with the DSP canvas and SPL2
  • List DSP pipeline commands
  • Use scalar functions to convert data types and schema
  • Filter and route data to multiple sinks
  • Review Splunk lookups
  • Enrich data with DSP lookups
  • Populate KV Store lookups from DSP streams
  • Manipulate pipeline options
  • Introduce the DSP Plugins SDK
  • Read from and write data to pub-sub systems like Kafka
  • List sources supported with the collect service
  • Transform data from Kafka and normalize
  • Write to S3
  • Onboard observability data (log, metric, and trace) into DSP
  • Transform metric data for Splunk indexers and Splunk SignalFx
  • Transform trace data for Splunk Infrastructure Monitoring
  • Route metric data to Splunk indexers and SignalFx
  • Send trace data to Splunk SignalFx
  • Describe the advantage of using DSP Streaming ML plugin
  • Enable the Streaming ML plugin in DSP
  • List the DSP Streaming ML functions
  • Practice DSP ML algorithms with the ML datagen
  • Back up DSP pipelines
  • Monitor DSP environment
  • Describe steps to isolate DSP service issues
  • Scale DSP
  • Replace DSP master node
  • Upgrade DSP cluster
Live Online Training (Duration : 32 Hours) 2800 + If you accept merging of other students. Per Participant
We Offer :
  • 1-on-1 Public - Select your own start date. Other students can be merged.
  • 1-on-1 Private - Select your own start date. You will be the only student in the class.

4 Hours
8 Hours
Week Days

Start Time : At any time

12 AM
12 PM

1-On-1 Training is Guaranteed to Run (GTR)
Group Training
Date On Request
Course Prerequisites

• Basic Splunk Administration and Administration (including Splunk Search Processing Language [SPL])
• Familiarity with SPL commands such as stats,eval,ifx and transaction
• Experience with data processing operations, common scripting languages such as JavaScript, Python, and shell scripting
• Understanding of streams, pipelines, and distributed processing architectures such as Apache Storm or Hadoop
• Experience working with open-source distributed intelligence platforms such as Apache Spark or Apache Flink
• Understanding of data sources such as databases, message queues, log files, and others
• Understanding of data transformation and enrichment operations such as filtering, sorting, join operations, and others
• Knowledge of security and compliance for data handling, including the regulations and privacy laws around such topics

Target Audience

The target audience for Splunk Data Stream Processor (DSP) 1
2 training would include IT professionals, administrators, and developers who need to be able to use DSP for real-time streaming analytics and data monitoring
System architects, DevOps engineers, and analytics professionals may also benefit from the training
The training would cover the components of DSP, including the streaming analytics engine, its high-performance architecture, and the components used to build streaming applications
The goal of the training is to enable participants to build high-performance analytics applications that enable real-time insights and streamline operations
Additionally, the training covers best practices and use cases to ensure participants are well-equipped to use DSP in the most beneficial way

Learning Objectives of Implementing Splunk Data Stream Processor (DSP) 1.2

1. Learn to identify the components and architecture of Splunk’s Data Stream Processor (DSP) 1.2.
2. Understand how to deploy and configure DSP 1.2 components and productionize the processing pipelines.
3. Master the ability to develop data stream pipelines and flow graphs.
4. Become proficient in creating and maintaining custom processors, productionizing data collection for existing pipelines, and troubleshooting processing issues.
5. Learn the DSP’s special features, such as creating and using custom processors, dealing with massive amounts of incoming data streams, and performing clustering as well as stream-based analytics.
6. Master the techniques to effectively work with data streams and create powerful streaming applications.

Student Feedback  (Check Koenig Feedback on Trustpilot)

Q1 Say something about the Trainer? Q2 How is Koenig different from other training Companies? Q3 Will you come back to Koenig for training ?

Student Name Feedback
United States
A1. Yes, she was very clear & a strong mastery of both English & Azure platforms hence following was easy. She was also patient and was answering every question asked, she also shared material & tips on how to pass the exam, Well done, and keep it up.
Nick Barker
United States
A1. Calm and understanding, she not only kept the course running well but also took time to help those with lots of questions. Very well done.
Robin Johnson
United States
A2. Individual attention during training, excellent customer service and coordination. Neha has been ever so helpful and is definitely an asset to Koenig.
Shivani Prasad
United States
A1. The trainer was great and his teaching methods were incredible. He used different teaching methods to ensure I was learning well. A fun trainer with lots of patience and understanding.
United States
A1. The trainer was very knowledgeable and well prepared about the presentation/training subject, with a positive attitude towards students and making every effort in answering questions during the training session. Top-notch service!
United States
A1. Exceptional... recommend to everyone!
Shyam Vaddakapett
United States
A1. My trainer, Mohit Kakkar was excellent as he focused on hands-on assignments to supplement the concepts of AZ 900. The training coordinator Jasmeet as well as the ops manager Sheshadri are also very professional and customer-centric. I recommend Koenig for training courses, and I will take some more courses with them soon.
Gilles Chirlias
United States
A1. Chavi was a great teacher, I have learned a lot from her. I would like to have her for the next training, which would be the AZ 301 and AZ 500.
Abdulrahman Saad Alshahrani
United States
A1. Excellent trainer. I will take another course with him someday. He deserves a good appreciation from his Manager.
United States

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1-on-1 Public - Select your start date. Other students can be merged.
1-on-1 Private - Select your start date. You will be the only student in the class.
Yes, course requiring practical include hands-on labs.
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Schedule for Group Training is decided by Koenig. Schedule for 1-on-1 is decided by you.
In 1-on-1 you can select your own schedule, other students can be merged but you select the schedule. Choose 1-on-1 if published schedule do not meet your requirement. If you also want a private session, opt for 1-on-1 Public.
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