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SPLK-2002 Exam Format | SPLK-2002 Course Contents | SPLK-2002 Course Outline | SPLK-2002 Exam Syllabus | SPLK-2002 Exam Objectives

Length: 90 minutes

Format: 85 multiple choice questions

Delivery: Exam is given by our testing partner Pearson VUE



- Introduction

- Describe a deployment plan

- Define the deployment process



- Project Requirements

- Identify critical information about environment, volume, users, and requirements

- Apply checklists and resources to aid in collecting requirements



- Infrastructure Planning: Index Design

- Understand design and size indexes

- Estimate non-smart store related storage requirements

- Identify relevant apps



- Infrastructure Planning: Resource Planning

- List sizing considerations

- Identify disk storage requirements

- Define hardware requirements for various Splunk components

- Describe ES considerations for sizing and topology

- Describe ITSI considerations for sizing and topology

- Describe security, privacy, and integrity measures



- Clustering Overview

- Identify non-smart store related storage and disk usage requirements

- Identify search head clustering requirements

- Forwarder and Deployment Best Practices 6%

- Identify best practices for forwarder tier design

- Understand configuration management for all Splunk components, using Splunk deployment tools



- Performance Monitoring and Tuning

- Use limits.conf to improve performance

- Use indexes.conf to manage bucket size

- Tune props.conf

- Improve search performance



- Splunk Troubleshooting Methods and Tools

- Splunk diagnostic resources and tools



- Clarifying the Problem

- Identify Splunks internal log files

- Identify Splunks internal indexes



- Licensing and Crash Problems

- License issues

- Crash issues



- Configuration Problems

- Input issues



- Search Problems

- Search issues

- Job inspector



- Deployment Problems

- Forwarding issues

- Deployment server issues



- Large-scale Splunk Deployment Overview

- Identify Splunk server roles in clusters

- License Master configuration in a clustered environment



- Single-site Indexer Cluster

- Splunk single-site indexer cluster configuration



- Multisite Indexer Cluster

- Splunk multisite indexer cluster overview

- Multisite indexer cluster configuration

- Cluster migration and upgrade considerations



- Indexer Cluster Management and Administration

- Indexer cluster storage utilization options

- Peer offline and decommission

- Master app bundles

- Monitoring Console for indexer cluster environment



- Search Head Cluster

- Splunk search head cluster overview

- Search head cluster configuration



- Search Head Cluster Management and Administration

- Search head cluster deployer

- Captaincy transfer

- Search head member addition and decommissioning

- KV Store Collection and Lookup Management

- KV Store collection in Splunk clusters



- Splunk Deployment Methodology and Architecture

- Planning and Designing Splunk Environments:

- Understand Splunk deployment methodologies for small, medium, and large-scale environments.

- Design distributed architectures to handle high data volumes efficiently.

- Plan for redundancy, load balancing, and scalability.



- Indexers: Store and index data for search and analysis.

- Search Heads: Manage search requests and distribute them across indexers.

- Forwarders: Collect and forward data to indexers (e.g., Universal Forwarder, Heavy Forwarder).

- Deployment Server: Manages configurations for forwarders and other Splunk components.

- Cluster Master: Oversees indexer clustering for replication and high availability.

- Distributed Deployment:

- Configure indexer and search head clustering for redundancy and performance.

- Implement high availability (HA) through failover mechanisms.

- Design scalable systems with horizontal scaling (adding more indexers or search heads).

- Terminologies:

- Indexer Clustering: Grouping indexers to replicate data for redundancy.

- Search Head Clustering: Grouping search heads for load balancing and HA.

- Replication Factor: Number of data copies maintained in an indexer cluster.

- Search Factor: Number of searchable data copies in an indexer cluster.

- Bucket: A storage unit for indexed data (hot, warm, cold, frozen).



- Data Ingestion and Indexing

- Data Inputs Configuration:

- Configure data inputs (e.g., files, directories, network inputs, scripted inputs).

- Manage source types and ensure consistent event formatting.

- Handle data from various sources (syslog, HTTP Event Collector, etc.).

- Indexing Processes:

- Understand data parsing, indexing, and storage processes.

- Configure indexes for performance and retention policies.

- Optimize indexing pipelines for high-throughput environments.

- Data Integrity and Compression:

- Ensure data integrity during ingestion and indexing.

- Understand Splunks data compression (e.g., rawdata and tsidx files).

- Estimate disk storage requirements (e.g., rawdata ~15%, tsidx ~35% for syslog data).



- Source Type: Metadata defining how Splunk parses incoming data.

- Rawdata: Uncompressed event data stored in buckets.

- Tsidx: Time-series index files for efficient searching.

- Event Breaking: Process of splitting raw data into individual events.

- Hot/Warm/Cold Buckets: Stages of data storage based on age and access frequency.



- Search and Reporting

- Search Processing Language (SPL):

- Write and optimize complex SPL queries for searching and reporting.

- Use commands like stats, eval, rex, and lookup for data analysis.

- Knowledge Objects:

- Create and manage knowledge objects (e.g., saved searches, reports, dashboards, field extractions).

- Understand permissions and sharing of knowledge objects.

- Search Optimization:

- Optimize search performance in distributed environments.

- Configure search pipelines and limits (e.g., limits.conf).

- Use data models and accelerated searches for faster results.



- Knowledge Objects: Reusable components like searches, dashboards, and lookups.

- Data Model: Structured dataset for pivoting and reporting.

- Accelerated Search: Pre-computed summaries for faster search results.

- Search Head: Component that executes searches and renders results.



- Security and User Management

- Authentication and Authorization:

- Configure user authentication (e.g., LDAP, SAML, Splunk native).

- Manage roles, capabilities, and access controls.

- Data Security:

- Implement data encryption for Splunk Web, splunkd, and distributed search.

- Configure certificate authentication between forwarders and indexers.

- Audit and Compliance:

- Monitor audit trails for user activity and system changes.

- Ensure compliance with security standards.



- Role: A set of permissions assigned to users.

- Capability: Specific actions a role can perform (e.g., run searches, edit indexes).

- Splunkd: The core Splunk daemon handling indexing and search.

- KV Store: Key-value store for storing application data.



- Clustering and High Availability

- Indexer Clustering:

- Configure replication and search factors for data redundancy.

- Manage bucket replication and recovery.

- Search Head Clustering:

- Set up search head clusters for load balancing and HA.

- Use splunk apply shcluster-bundle and splunk resync shcluster-replicated-config for configuration synchronization.

- High Availability:

- Ensure continuous availability through failover and redundancy.

- Increase replication factor for searchable data HA.



- Cluster Master: Manages indexer cluster operations.

- Peer Node: An indexer in a cluster.

- Search Head Cluster: Group of search heads for distributed search.

- Raft: Consensus algorithm for search head clustering.



- Performance Tuning and Troubleshooting

- Performance Optimization:

- Increase parallel ingestion pipelines (server.conf) for indexing performance.

- Adjust hot bucket limits (indexes.conf) and search concurrency (limits.conf).

- Monitor system resources (CPU, memory, IOPS) for bottlenecks.

- Troubleshooting:

- Diagnose connectivity issues using tools like tcpdump and splunk btool.

- Analyze splunkd.log for deployment server issues.

- Resolve inconsistent event formatting due to misconfigured forwarders or source types.



- IOPS: Input/Output Operations Per Second, a measure of disk performance.

- Splunk Btool: Command-line tool for configuration validation.

- KV Store: Used for storing and retrieving configuration data.

- Monitoring Console: Splunks built-in tool for monitoring deployment health.



- Integration with Third-Party Systems

- Third-Party Integration:

- Integrate Splunk with Hadoop for searching HDFS data.

- Configure Splunk to work with external systems via APIs or add-ons.

- Data Sharing:

- Enable Splunk to share data with external applications.

- Use Splunks REST API for programmatic access.



- HDFS: Hadoop Distributed File System.

- REST API: Splunks interface for external integrations.

- Add-on: Modular component for integrating with specific data sources.



- Forwarder: Collects and sends data to indexers (Universal, Heavy, Cloud).

- Indexer: Processes and stores data for searching.

- Search Head: Manages search queries and user interfaces.

- Cluster Master: Coordinates indexer clustering.

- Replication Factor: Number of data copies in an indexer cluster.

- Search Factor: Number of searchable data copies.

- Bucket: Data storage unit (hot, warm, cold, frozen).

- Source Type: Metadata for parsing data.

- Rawdata: Uncompressed event data.

- Tsidx: Time-series index for efficient searches.

- Knowledge Objects: Reusable components like searches and dashboards.

- Data Model: Structured dataset for reporting.

- KV Store: Key-value storage for configurations.

- Splunkd: Core Splunk service.

- Btool: Tool for troubleshooting configurations.

- IOPS: Disk performance metric.

- HDFS: Hadoop file system for big data.

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