Implementing Splunk Data Stream Processor (DSP)

Implementing Splunk Data Stream Processor (DSP)ISDSPSPSplunkSP-ISDSP1.2<ul> <li>Introduction to Splunk Data Stream Processor</li><li>Deploying a DSP cluster</li><li>Prepping Sources and Sinks</li><li>Building Pipelines - Basics</li><li>Building Pipelines - Deep Dive</li><li>Working with 3rd party Data Feeds</li><li>Working with Metric Data</li><li>Monitoring DSP Environment</li></ul>Required: <ul> <li><a class="fl-href-prod" href="/swisscom/en/course/splunk-sesa"><svg role="img" aria-hidden="true" focusable="false" data-nosnippet class="cms-linkmark"><use xlink:href="/css/img/icnset-linkmarks.svg#linkmark"></use></svg>Splunk Enterprise System Administration (SESA)</a></li><li><a class="fl-href-prod" href="/swisscom/en/course/splunk-seda"><svg role="img" aria-hidden="true" focusable="false" data-nosnippet class="cms-linkmark"><use xlink:href="/css/img/icnset-linkmarks.svg#linkmark"></use></svg>Splunk Enterprise Data Administration (SEDA)</a></li></ul>Recommended: <ul> <li><a class="fl-href-prod" href="/swisscom/en/course/splunk-ased"><svg role="img" aria-hidden="true" focusable="false" data-nosnippet class="cms-linkmark"><use xlink:href="/css/img/icnset-linkmarks.svg#linkmark"></use></svg>Architecting Splunk Enterprise Deployments (ASED)</a></li><li>Working knowledge of:<ul> <li>Distributed system architectures</li><li>Apache Kafka (user level)</li><li>Apache Flink (user level)</li><li>Kubernetes (admin level)</li></ul></li></ul>This 4-day module is designed for the experienced Splunk administrators who are new to Splunk DSP.This hands-on module provides the fundamentals of deploying a Splunk DSP cluster and designing pipelines for core use cases. It covers installation, source and sink configurations, pipeline design and backup, and monitoring a DSP environment. Please note that this class may run across four days, in 4.5 hour sessions each day and contains 18 total hours of content.Topic 1 – Introduction to DSP <ul> <li>Review Splunk deployment options and challenges</li><li>Describe the purpose and value of Splunk DSP</li><li>Understand DSP concepts and terminologies</li></ul>Topic 2 – Deploying a DSP Cluster <ul> <li>List DSP core components and system requirements</li><li>List DSP core components and system requirements</li><li>Describe installation options and steps</li><li>Check DSP service status</li><li>Learn to navigate in DSP UI</li><li>Use scloud</li></ul>Topic 3 – Prepping Sources and Sinks <ul> <li>Ingest data with DSP REST API service</li><li>Configure DSP source connections for Splunk data</li><li>Configure DSP sink connections for Splunk indexers</li><li>Create Splunk-to Splunk pass-through pipelines</li></ul>Topic 4 – Building Pipelines - Basics <ul> <li>Describe the basic elements of a DSP pipeline</li><li>Create data pipelines with the DSP canvas and SPL2</li><li>List DSP pipeline commands</li><li>Use scalar functions to convert data types and schema</li><li>Filter and route data to multiple sinks</li></ul> Topic 5 – Building Pipelines - Deep Dive <ul> <li>Manipulate pipeline options:</li><li>Extract</li><li>Transform</li><li>Obfuscate</li><li>Aggregate and conditional trigger</li></ul> Topic 6 – Working with 3rd party Data Feeds <ul> <li>Read from and write data to pub-sub systems like Kafka</li><li>List sources supported with the collect service</li><li>Transform data from Kafka and normalize</li><li>Write to S3</li></ul> Topic 7 – Working with Metric Data <ul> <li>Onboard metric data into DSP</li><li>Transform metric data for Splunk indexers and SignalFx</li><li>Send metric data to Splunk indexers</li><li>Send metric data to Splunk SignalFx</li></ul> Topic 8 – Monitoring DSP Environment <ul> <li>Back up DSP pipelines</li><li>Monitor DSP environment</li><li>Describe steps to isolate DSP service issues</li><li>Scale DSP</li><li>Replace DSP master node</li><li>Upgrade DSP cluster</li></ul>- Introduction to Splunk Data Stream Processor - Deploying a DSP cluster - Prepping Sources and Sinks - Building Pipelines - Basics - Building Pipelines - Deep Dive - Working with 3rd party Data Feeds - Working with Metric Data - Monitoring DSP EnvironmentRequired: - Splunk Enterprise System Administration (SESA) - Splunk Enterprise Data Administration (SEDA) Recommended: - Architecting Splunk Enterprise Deployments (ASED) - Working knowledge of: - Distributed system architectures - Apache Kafka (user level) - Apache Flink (user level) - Kubernetes (admin level)This 4-day module is designed for the experienced Splunk administrators who are new to Splunk DSP.This hands-on module provides the fundamentals of deploying a Splunk DSP cluster and designing pipelines for core use cases. It covers installation, source and sink configurations, pipeline design and backup, and monitoring a DSP environment. Please note that this class may run across four days, in 4.5 hour sessions each day and contains 18 total hours of content.Topic 1 – Introduction to DSP - Review Splunk deployment options and challenges - Describe the purpose and value of Splunk DSP - Understand DSP concepts and terminologies Topic 2 – Deploying a DSP Cluster - List DSP core components and system requirements - List DSP core components and system requirements - Describe installation options and steps - Check DSP service status - Learn to navigate in DSP UI - Use scloud Topic 3 – Prepping Sources and Sinks - 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 Topic 4 – Building Pipelines - Basics - 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 Topic 5 – Building Pipelines - Deep Dive - Manipulate pipeline options: - Extract - Transform - Obfuscate - Aggregate and conditional trigger Topic 6 – Working with 3rd party Data Feeds - 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 Topic 7 – Working with Metric Data - Onboard metric data into DSP - Transform metric data for Splunk indexers and SignalFx - Send metric data to Splunk indexers - Send metric data to Splunk SignalFx Topic 8 – Monitoring DSP Environment - Back up DSP pipelines - Monitor DSP environment - Describe steps to isolate DSP service issues - Scale DSP - Replace DSP master node - Upgrade DSP cluster18 hours2000.002600.00200.00200.00200.00200.00