For strict data isolation requirements, especially under regulations, logical access controls (like RBAC) on a shared system are often insufficient. The most secure and compliant approach is physical or logical separation at the search head level. Dedicated search heads connected only to specific, isolated indexes prevent any possibility of cross-data access, meeting the core requirement. While RBAC is important, it operates within a shared system and may not satisfy all audit requirements for absolute isolation.

Heavy forwarders are designed for data pipeline processing (parsing, filtering, routing, batching) before data reaches the indexers. They are not designed or intended to function as search heads. Search heads are specialized components that handle user queries, knowledge objects, and dashboarding. Using a heavy forwarder as a search head would lead to poor performance and is an incorrect architectural pattern.

The correct, graceful process is to first stop the Splunk instance on the peer (`splunk stop`). This allows the cluster master to recognize the peer is down and trigger replication of its buckets to other peers to maintain the configured search factor. After this replication is complete and data integrity is assured, you can then formally decommission the peer by editing the cluster configuration on the master to remove it. The other options either use incorrect commands or reverse the safe order of operations.

In a multi-site cluster, `site_replication_factor` controls data placement across sites. The setting `origin:2, total:3` means: For each bucket of data, the cluster will maintain `total` 3 copies. Of those 3 copies, at least `origin` 2 copies will be stored within the same site as the indexing peer that created the data (the ‘origin’ site). The remaining copy (`total` – `origin` = 1) will be stored in one of the other available sites. This optimizes for local search performance while providing cross-site redundancy.

This is a common issue. A scheduled search has two time components: the execution schedule (e.g., `cron = */60 * * * *`) and the time range specified in the search itself (e.g., `earliest=-1h@h latest=@h`). If these are misaligned—for instance, a search runs on the hour but looks for data from `-5m` to `now`—it may consistently look in a time window where no new data has arrived yet. Manual searches succeed because you are likely picking an appropriate ad-hoc time range. Permission issues would affect both manual and scheduled runs.

Indexer RAM is critically used for two main functions: processing incoming data (indexing) and executing searches. Higher daily indexing volume requires more RAM for parsing, compression, and building indexes in memory (hot buckets). A larger number of concurrent searches also requires more RAM to handle the search pipeline, including map-reduce operations and result set management. While other factors like OS and Splunk version have baseline needs, indexing volume and search concurrency are the key variables for sizing RAM.

The deployment server’s core function is configuration management. It allows administrators to centrally define apps and configuration bundles (inputs, outputs, props, transforms, etc.) and push them out to designated groups of forwarders, indexers, and search heads. This ensures consistency, simplifies management at scale, and is essential for maintaining control over a large fleet of Splunk components. It does not handle search load balancing, clustering redundancy, or data archiving.

The Recovery Point Objective (RPO) defines the maximum acceptable amount of data loss measured in time. Indexer clustering with a `replication_factor` > 1 is the Splunk feature designed for data redundancy. It ensures multiple copies of each data bucket exist across different peers. If a peer fails, the data is still available on other peers, minimizing potential data loss. The replication process is near real-time, making it capable of supporting low RPOs like 15 minutes. Search head clustering addresses search availability (RTO), not data durability.

The symptom is slow searches due to high load on the *search head*. The search head is responsible for distributing search queries to indexers, merging results, and running post-processing. A single search head can become a bottleneck. Forming a search head cluster (SHC) distributes the user search load across multiple search head members, provides high availability, and shares knowledge objects. Adding resources to indexers or forwarders addresses ingest or indexing performance, not the search head bottleneck. Increasing replication factor impacts storage and redundancy, not search head query processing capacity.

For strict data isolation requirements, especially under regulations, logical access controls (like RBAC) on a shared system are often insufficient. The most secure and compliant approach is physical or logical separation at the search head level. Dedicated search heads connected only to specific, isolated indexes prevent any possibility of cross-data access, meeting the core requirement. While RBAC is important, it operates within a shared system and may not satisfy all audit requirements for absolute isolation.0