SPLK-2002 Exam Information and Guideline
Splunk Enterprise Certified Architect - 2025
Below are complete topics detail with latest syllabus and course outline, that will help you good knowledge about exam objectives and topics that you have to prepare. These contents are covered in questions and answers pool of exam.
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 Splunk’s internal log files
- Identify Splunk’s 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 Splunk’s 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: Splunk’s 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 Splunk’s REST API for programmatic access.
- HDFS: Hadoop Distributed File System.
- REST API: Splunk’s 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.