OneFS MetadataIQ Automatic Directory Rename Propagation

Since OneFS 9.10, MetadataIQ has provided PowerScale clusters with a global metadata namespace, by exporting file system metadata to an off-cluster Elasticsearch database. The ability to index and query metadata across geo-distributed clusters, without resorting to time-consuming tree walks, has proven invaluable for data discovery, lifecycle management, and increasingly for AI-driven workflows such as intelligent chunking and retrieval-augmented generation (RAG).

However, in OneFS 9.14 and earlier, when a directory was renamed on the cluster, MetadataIQ dutifully recorded the new directory entry in Elasticsearch, but every child path beneath that directory remained indexed under the old prefix. This resulted in stale entries: the database reported the files living under /ifs/data/A/B/C, but the file system had them under /ifs/data/A/Bx/C. Until the release of OneFS 9.15, the only remedy was a full resync — a brute-force re-indexing of the entire dataset that is neither performant nor automation-friendly.

The new OneFS 9.15 releases addresses this MetadataIQ shortcoming with automatic directory rename propagation. Specifically, when a directory rename is detected, the system now tracks both the old and new paths and runs a dedicated rename phase that updates all descendant entries in the Elasticsearch index, eliminating stale data without a full resync. Additionally, the schema encoding for hardlinks has been redesigned to remove path sensitivity entirely.

To understand the solution, it helps to be clear about the problem. MetadataIQ’s Elasticsearch index uses a primary key (_id) for each document. In releases prior to 9.15, this ‘_id’ was encoded as a combination of the file’s LIN (logical inode number) and a hash of its full path: <LIN>#<path_hash>.

This encoding has two consequences when a parent directory is renamed:

  • Every child entry in the database retains its old path. A directory rename from /ifs/data/projects to /ifs/data/projects_2026 leaves every file and subdirectory under it still indexed with the /ifs/data/projects prefix. The database and the file system disagree, and queries return incorrect results.
  • For hardlinks, the path_hash component of the _id changes when a parent is renamed, even though the file itself has not changed. This creates duplicate or orphaned entries in the index.

Pre-OneFS 9.15 this required an expensive resync, effectively re-indexing the full dataset.

However, to avoid this overhead, the directory rename feature in OneFS 9.15 operates within MetadataIQ’s existing transfer agent (‘isi_metadataiq_transfer’), adding a post-processing rename phase that runs after the normal changelist transfer is complete. As such, the 9.15 workflow has two distinct phases:

Phase 1: Primary Processing

During normal MetadataIQ processing, the transfer agent iterates through the changelist entries and pushes them to the Elasticsearch database. When a directory rename event is detected, the following occurs:

  • The changelist entry is pushed to the database as usual, with the old path and path depth preserved.
  • The new directory path is recorded in a special rename_path field on the renamed directory’s document in Elasticsearch.
  • Metadata fields such as timestamp, disk pool, and node pool are updated to reflect the current file system state.

At this stage, the children of the renamed directory still have their old paths in the database. The rename_path field is a breadcrumb that tells Phase 2 which directories have pending renames.

Phase 2: Rename (Post-processing)

After all primary changelist processing is complete, the transfer agent enters the rename phase. This is where the descendant path updates happen:

  • The script queries Elasticsearch for all documents that have a non-empty rename_path field — these are the directories with pending renames.
  • For each rename candidate, the script identifies all descendant entries whose path begins with the old directory prefix. These are processed in descending order by path depth, ensuring that deeply nested renames are handled correctly before their parents.
  • The actual path update is performed atomically using an Elasticsearch Painless script execution. A single Painless script replaces the old path prefix with the new directory path and recomputes associated metadata for all descendants. This atomic update includes:

–  Path depth: adjusted by calculating the depth difference between the new and old paths.

–  Snapshot generation number: updated atomically so that parent-level renames can skip entries already modified by a child-level rename.

–  Other metadata fields: all relevant metadata is refreshed for every descendant entry.

  • Once the root rename document and all its descendants are updated, the rename_path field is cleared, marking that rename as complete.
  • This process iterates until all pending renames have been resolved.

Above, Phase 1 (blue) records rename candidates during normal changelist processing, while phase 2 (green) iterates through candidates and atomically updates all descendant paths.

Note that the descendant prefix search in Elasticsearch requires the ‘allow_expensive_queries’ setting to be enabled, which it is by default. This setting should not be disabled on MetadataIQ’s Elasticsearch instance.

The MetadataIQ transfer agent uses batched, checkpointed processing throughout both phases. An interrupted transfer resumes from the last recorded checkpoint rather than restarting from the beginning. The various stages of the transfer workflow are as follows:

Stage Description
Fetch batch Fetch changelist entries batchwise from the PAPI server (maximum 2,048 entries per fetch)
Detect rename Detect directory rename events within the batch
Record rename_path Record the new path in the rename_path field; preserve the old path and path depth
Checkpoint Refresh object metadata, update ‘tail_cookie’, and record a checkpoint at batch end
Iterate candidates In the rename phase, iterate over each recorded directory rename candidate
Find descendants Identify descendants by old path prefix, processed in descending depth order
Update child paths Replace the old prefix with the new directory path and update child metadata
Reconcile Clear the rename_path field, marking the subtree as fully reconciled
Failure exit On crash or ElasticSearch connection failure, exit and resume from the last checkpoint

If the transfer script exits during the rename phase, for example, in the event of a node failover, service restart, or a network interruption, the ‘rename_path’ fields in Elasticsearch remain set on any unprocessed rename candidates. When the transfer agent is next invoked, it detects these pending rename entries, skips the primary processing phase entirely, and proceeds directly to the rename phase to complete the outstanding work. No manual intervention is required. This is a significant improvement over the old full-resync approach, where an interrupted resync would simply need to be restarted from the beginning.

The second component of the directory rename feature addresses the hardlink problem at the schema level. In pre-9.15 releases, the Elasticsearch document ‘_id’ is encoded as ‘<LIN>#<path_hash>’. Since a hardlink is an additional directory entry pointing to the same inode, renaming a parent directory changes the ‘path_hash’ for every hardlink entry beneath it, creating duplicates or orphans in the index.

In OneFS 9.15, the ‘_id’ encoding for hardlinks is changed to use the parent LIN and filename rather than a full path hash. Because the filename itself does not change when a parent directory is renamed, hardlink entries are no longer sensitive to parent path changes. This eliminates an entire class of stale-entry scenarios.

The OneFS 9.14 and earlier encoding includes a hash of the full path, which changes when any ancestor is renamed. Conversely, the 9.15 encoding uses only the filename, making hardlinks immune to parent renames.

Architecturally, the rename phase is built directly into the existing MetadataIQ transfer agent. No new daemons, services, or ports are introduced. The transfer agent (‘isi_metadataiq_transfer’) already handles the mechanics of reading changelist entries, batching them, and uploading them to Elasticsearch. The rename phase simply adds a post-processing step after the draining loop completes.

There are two paths into the rename logic:

Path Details
Normal path After the primary processing phase completes and all changelist entries have been drained to Elasticsearch, the rename phase is triggered automatically.
Recovery path If the transfer script was interrupted during a previous rename phase (leaving unprocessed rename_path entries in Elasticsearch), the next invocation skips primary processing and goes directly to the rename phase.

No separate installation or configuration is required for the directory rename feature. It is built into OneFS 9.15 and follows the same installation, configuration, and scheduling as the existing MetadataIQ capability. If MetadataIQ is already configured and running on a pre-9.15 cluster, upgrading to 9.15 enables directory rename propagation automatically after the upgrade commit and subsequent resync.

The existing MetadataIQ CLI commands remain unchanged:

# isi metadataiq settings view

# isi metadataiq settings modify --schedule "every day every 5 minutes"

# isi metadataiq resync

When it comes to upgrading OneFS and MetadataIQ, the directory rename feature introduces a change to the ‘_id encoding’ in the main Elasticsearch index in order to eliminate the path dependency for hardlinks. This encoding change is not backward compatible with pre-9.15 indices, which means that a full resync is required after the NDU (non-disruptive upgrade) commit.

The important details:

  • The resync is triggered automatically by the system after the upgrade commit when incompatible versions are detected. Administrators do not need to initiate it manually.
  • During the resync, do not interact with or interrupt the MetadataIQ service. Manual intervention during this process may cause the resync to fail, potentially requiring a manual reset and restart.
  • The resync duration depends on the size of the indexed dataset. Plan accordingly when scheduling the upgrade window.

In the event of an upgrade rollback, the producer and consumer services return to their pre-upgrade behavior automatically, resuming operation on the older version with the original schema.

Understanding how MetadataIQ’s services behave during each stage of a non-disruptive upgrade is helpful for planning:

It’s also worth understanding how the producer and consumer components behave through the upgrade lifecycle:

Phase Details
Pre-upgrade Both producer and consumer run on the older version. The producer continues generating changelists as normal, and the consumer transfers data using the existing pre-upgrade schema.
Post-upgrade (mixed version): The producer is disabled for the duration of the mixed-version window. The consumer adapts per node version — old schema on not-yet-upgraded nodes, updated logic on upgraded nodes — and transfers may pause or continue based on compatibility checks.
Post-commit After the automatic resync completes, the producer is re-enabled and resumes generating changelists, while the consumer updates the database mapping and begins transferring under the new schema.
Post-rollback If the upgrade is rolled back, both components simply return to their pre-upgrade behavior on the older version and the original schema.

To illustrate the behavior, consider two scenarios that demonstrate how the rename phase handles common directory operations.

Scenario 1: Simple nested renames

Starting from a nested directory structure:

# mkdir -p /ifs/data/A/B/C/D/E/F/G/H

After the initial MetadataIQ cycle, all eight directories are indexed in Elasticsearch with their full paths. Now, two renames are performed:

# mv /ifs/data/A/B /ifs/data/A/Bx

# mv /ifs/data/A/Bx/C/D/E /ifs/data/A/Bx/C/D/Ex

In prior releases, the descendants of those directories would have retained their old paths in the index. Instead, in OneFS 9.15, when the next MetadataIQ cycle runs, the transfer agent detects both rename events during primary processing and records the new paths in the rename_path field. Then, in the rename phase, it processes the renames in depth-descending order:

  • First, E → Ex is processed: /ifs/data/A/Bx/C/D/Ex/F, /ifs/data/A/Bx/C/D/Ex/F/G, and /ifs/data/A/Bx/C/D/Ex/F/G/H are all updated.
  • Then, B → Bx is processed: all remaining descendants under the old /ifs/data/A/B prefix are updated to /ifs/data/A/Bx.

The outcome is that all child paths are correctly updated in the database, and no stale entries remain.

Scenario 2: Subtree moves within the same tree

Starting from the same structure, this time with more complex operations:

# mkdir -p /ifs/data/A/B/C/D/E/F/G/H

# mv /ifs/data/A/B/C/D/E /ifs/data/A/

# mv /ifs/data/A/E/F/G /ifs/data/A/B/C/D/

# mv /ifs/data/A/B /ifs/data/A/Bx

Here, subtree E is moved up to become a direct child of A, subtree G is moved into D, and B is renamed to Bx. After the MetadataIQ cycle, the database reflects all three operations correctly:

  • E and its child F are now under /ifs/data/A/E and /ifs/data/A/E/F.
  • G and its child H are now under /ifs/data/A/Bx/C/D/G and /ifs/data/A/Bx/C/D/G/H.
  • B’s rename to Bx is propagated to all remaining descendants: /ifs/data/A/Bx/C, /ifs/data/A/Bx/C/D.

So, this results in no stale entries, nor a need for manual resync. The depth-descending processing order and the snapshot generation number atomicity ensure that even compound operations within the same tree are resolved correctly.

After a MetadataIQ cycle involving directory renames has completed, the following CLI utilities can be used to monitor and verify operation. This includes:

Checking the MetadataIQ services:

# isi services -a | grep -i metadataiq

Monitoring the ChangelistCreate job:

# isi job jobs list | grep -i ChangelistCreate

Confirming the MetadataIQ snapshot count (which should be <= 2 under healthy operating conditions):

# isi snapshot snapshots list | grep -i metadataiq

Additionally, to verify that rename propagation has completed successfully, the Elasticsearch index can be queried for any documents with a non-empty ‘rename_path’ field. In normal operation, the following query should return zero results after the transfer agent completes:

GET isi_metadata_index/_search

{

  "query": {

    "exists": {

      "field": "rename_path"

    }

  }

}

A non-zero result count indicates that rename processing was interrupted and will be completed on the next transfer agent invocation.

OneFS SmartSync Failover and Failback

Data replication is only half the equation. The other part, which often gets tested at the worst possible moment, is what happens when the primary cluster goes dark and storage administrators need to redirect clients to the secondary site with minimum disruption and maximum confidence in data integrity.

OneFS 9.15 introduces SmartSync failover and failback capabilities to ensure uninterrupted operations and fast recovery when a primary PowerScale cluster becomes unavailable. Rather than relying on time‑consuming restores from traditional backups, SmartSync enables rapid redirection of client access to a secondary cluster. By keeping data and metadata immediately available, it significantly reduces Recovery Time Objectives (RTO).

When the primary cluster is restored, SmartSync efficiently performs failback by syncing only the incremental changes generated during the failover period, preserving data integrity and enabling a seamless return to normal replication operations.

Together, these capabilities deliver a robust, high‑availability data mobility solution that strengthens business continuity and lowers operational risk.

SmartSync Failover/Failback provides the following capabilities:

·         Converts a read‑only SmartSync target path into a writeable path.

·         Switches a writeable SmartSync source path to read‑only.

·         Restores a SmartSync base path to a previous dataset state.

·         Enables reverse incremental synchronization to transfer client‑written data from a failover cluster back to the original source.

With OneFS SyncIQ, the allow-writes > resync-prep > redirect > reverse flow is generally well understood. In contrast, OneFS SmartSync has some notable variations to this theme, and it’s worth understanding how the SmartSync process differs before it’s actually required. This article walks through the full SmartSync failover and failback lifecycle, including what the commands do, why the sequence matters, and where the behavior diverges from what seasoned SyncIQ administrators will expect.

SmartSync replication is built on the Datamover service (isi_dm_d) and operates exclusively on Global Snapshots, referred to in its vernacular as ‘datasets’.

A dataset is an immutable, point-in-time view of the file system created via SnapshotIQ. Unlike a SyncIQ-replicated path, where the target is a live, writable mirror held read-only by convention, a SmartSync target path is backed by a series of versioned, lineage-aware datasets. This lineage is what makes efficient failback possible without re-baselining.

First, there are a few caveats to consider before getting into the workflow:

  • Failover and failback are supported only by file-to-file replication (PowerScale cluster to PowerScale cluster). File-to-object cloud copy does not support either operation.
  • The prerequisite state is a working repeat-copy relationship: a dataset creation policy running on the source and a repeat-copy policy replicating incrementally to the target. The baseline run must have completed successfully.
  • Both clusters must have mutual TLS trust established and replication accounts configured in both directions. Trust is symmetric by design, which is what makes role reversal possible without reconfiguring certificates.
  • The required privilege is ISI_PRIV_DATAMOVER. SmartSync also requires active SyncIQ and SnapshotIQ licenses on both clusters.

Workflow-wise, SmartSync failover and failback entails a seven-step process:

Steps 1 and 2 constitute the failover. Steps 3 through 5 constitute the failback. Steps 6 and 7 restore the original replication direction.

Step Action Details
1 Failover (part i) Make the target writeable; optionally revert to a clean dataset.
2 Failover (part ii) Client writes occur on the target; create a dataset to capture changes.
3 Failback (part i) Prepare the original source by reverting to the matching dataset.
4 Failback (part ii) Perform the reverse incremental sync from target back to source.
5 Failback (part iii) Make the original source writeable and redirect clients.
6 Reset (part i) Prepare the original target for forward replication (revert and make read-only).
7 Reset (part ii) Resume the original-direction repeat-copy policy.

In practice, a planned failover may compress some steps. Similarly, an unplanned failover may skip others depending on the state of the source cluster.

Step 1: Making the Target Writeable (and Optionally Reverting)

Under normal repeat-copy operation, the target base path is read-only. SmartSync enforces this to prevent data written on the target from conflicting with incoming incremental updates from the source. The failover action unlocks the path with a single command:

target-1# isi dm setup-dir client-access --base-path /ifs/tgt

Are you sure you would like to make base path /ifs/tgt writable? (yes/[no]): yes

Created job: 1.

Path will become writable.

In an unplanned failover where the source is simply unavailable, take the last replicated dataset and make it available for writes. However, in a ransomware or data-corruption scenario, the latest dataset on the target may itself be compromised. SmartSync addresses this with the ‘–dataset-revert’ option, which simultaneously makes the path writeable and rolls it back to a specific earlier dataset:

target-1# isi dm setup-dir client-access --base-path /ifs/tgt --dataset-revert 1

Are you sure you would like to revert base path /ifs/tgt to dataset ID 1? (yes/[no]): yes

Created job: 1.

Dataset will revert and path will become writable.

The dataset ID to revert to is identified beforehand using the ‘isi dm datasets list’ command, inspecting creation timestamps to find the last known-clean point in time. Once the revert completes, the target dataset that was reverted away from is removed from the dataset list, and the base path reflects the contents of the chosen dataset, ready for clients.

Step 2: Capturing Changes on the Failover Cluster

With clients now writing to the former target, a dataset creation policy is needed to capture those changes as Global Snapshots. This is necessary for Step 4 (failback sync) to have a reference point to sync from, and is created with a one-shot ‘run-now’ execution to immediately capture the current state, then configure recurrence for ongoing snapshots:

target-1# isi dm policies create fo_creation CREATION \

    --priority NORMAL \

    --run-now true \

    --creation-account-id local \

    --creation-base-path /ifs/tgt

Created policy: 1.

At this point, if the original source is to be permanently decommissioned, the workflow stops here. The former target is now a fully independent source cluster. A new repeat-copy policy can be defined pointing at a fresh target, and normal forward replication resumes from this cluster with no re-baselining required anywhere downstream.

Step 3: Preparing the Original Source for Failback

Failback mandates that the original source be in a state the reverse-direction incremental sync can build upon. Specifically, the source must contain no datasets under the base path that post-date the dataset the target was using when it became writeable. If the source was still receiving new datasets from a running dataset creation policy at the moment of failover, those newer datasets must be removed before failback can proceed.

The ‘isi dm setup-dir replication-target’ CLI command handles this. It always requires a dataset revert and makes the base path read-only, transforming the cluster from an active source into a replication target ready to receive data:

source-1# isi dm setup-dir replication-target --base-path /ifs/src --dataset-revert 2

Are you sure you would like to revert base path /ifs/src to dataset 2? (yes/[no]): yes

Created job: 1.

Dataset will revert and path will become read-only

Dataset IDs are cluster-local, not globally synchronized, so the dataset ID on the source cluster will generally differ from the corresponding ID on the target. The preferred approach is to match by dataset revision and tree ID, not by the local integer ID. Running ‘isi dm dataset view <id>’ on both clusters and comparing the Dataset Revision and Dataset Global ID fields allows the match to be confirmed before the revert is issued.

Note that, if the final dataset creation policy on the source is configured with the ‘–creation-dataset-make-read-only true’ argument, the source base path is automatically made read-only as soon as that dataset is created. Combined with a scheduled dataset creation immediately before the planned maintenance window, this eliminates the need to manually run replication-target on the source, and ensures no writes land between the last sync and the failover.

Step 4: Reverse Incremental Sync

This is where SmartSync’s re-baselining elimination pays off in the failback scenario. A reverse-direction repeat-copy policy is created from the failover cluster (now acting as source) back to the original source (now acting as target). The ‘–reconnect true’ flag instructs SmartSync to resume from the last shared dataset rather than initiating a full baseline copy. Without it, the first run would transfer the entire dataset unnecessarily.

target-1# isi dm policies create failback_rc REPEAT_COPY \

    --priority NORMAL \

    --run-now true \

    --repeat-copy-source-base-path /ifs/tgt \

    --repeat-copy-base-source-account-id local \

    --repeat-copy-base-target-account-id <source-cluster-account-id> \

    --repeat-copy-base-target-base-path /ifs/src \

    --reconnect true \

    --repeat-copy-base-target-dataset-type FILE

Created policy: 1025.

After the run completes, the job type can be verified in the ‘isi dm reports list’ command output. The type should be marked as ‘DATASET_INCREMENTAL’, confirming that SmartSync found the shared lineage and performed an incremental transfer rather than a full baseline. If it shows ‘DATASET_BASELINE’, the dataset revision match between the two clusters was incorrect and the revert (step 3) needs revisiting.

Step 5: Redirecting Clients Back to the Original Source

Once the failback sync has completed and the original source base path is current, the clients can be redirected. The ‘isi dm setup-dir client-access’ CLI command makes the path writeable without requiring a dataset revert, which is appropriate when the source is known-clean and the reverse sync is current:

source-1# isi dm setup-dir client-access --base-path /ifs/src

Are you sure you would like to make base path /ifs/src writable? (yes/[no]): yes

Created job: 1.

Path will become writable.

Following this, any pertinent DNS entries, SmartConnect zone configuration, or NFS mount points can be updated as appropriate to redirect client traffic. The original source is now serving live client workloads again.

Step 6: Prepare the Original Target for Forward Sync

With clients back on the original source, the final pair of steps (steps 6 & 7) restores the normal A-to-B replication direction. First, the former failover cluster (B) is prep’d to become a replication target again. As such, any datasets created on it since the last successful reverse sync are reverted away, and the path is made read-only.

target-1# isi dm setup-dir replication-target \

    --base-path /ifs/tgt \

    --dataset-revert <latest-shared-dataset-id>
Step 7: Resume the Original Replication Direction

With the original target read-only and aligned to the same dataset revision as the source, the original forward repeat-copy policy is resumed with a manual ‘run-now’ trigger. SmartSync uses the shared lineage to perform an incremental update, again with no re-baseline:

source-1# isi dm policies modify <original-policy-id> --run-now true

Once this job completes successfully, the relationship is back to its pre-failover state: Source writeable, target read-only, incremental replication running on schedule. As such, the full cycle is complete.

PowerScale cluster admins who are familiar with SyncIQ will notice both familiar patterns plus notable differences when it comes to managing SmartSync failover. The following table summarizes the key operational distinctions:

Aspect SyncIQ SmartSync
Failover command isi sync policies modify –action allow-writes isi dm setup-dir client-access
Source lock for failback Implicit: resync-prep job prepares source as target Explicit: isi dm setup-dir replication-target (always requires revert)
Re-baselining on failback Not required (changelist-based incremental) Not required (Global Snapshot lineage, –reconnect true)
Ransomware / data corruption recovery Fail over to last clean sync snapshot via isi snapshot restore Integrated: –dataset-revert in same failover command
Reverse sync direction New SyncIQ policy, source becomes target New REPEAT_COPY policy with –reconnect true from failover cluster
Restoring forward direction Disable reverse policy; re-enable original policy setup-dir replication-target on ex-target; modify original policy –run-now
Object / cloud replication Not applicable (file only) Cloud copy does not support failover or failback

 

SmartSync provides two views into replication state during and after a failover or failback operation. Running jobs appear in ‘isi dm jobs list’; completed jobs move to ‘isi dm reports list’. For granular job detail, the ‘isi dm job view <id>’ CLI command provides per-task progress, and ‘isi_datamover_job_status <id>’ gives lower-level internal state. Transfer failures write a job-specific log to ‘/ifs/data/Isilon_Support/datamover/transfer_failures/<job-id>/’, and the primary log file is ‘/var/log/isi_dm.log’.

For RPO visibility across replication relationships, particularly useful in the lead-up to a planned failover, the ‘isi dm rpo reports list’ CLI command provides a per-policy view of how current the replicated data is relative to defined recovery objectives.

SmartSync’s support for pull policies, where the target cluster initiates and pulls data from the source, adds a useful dimension to DR topology design that SyncIQ does not offer. In a resource-constrained source cluster, configuring the target to pull rather than the source to push offloads the replication compute burden to the DR site, leaving primary client I/O unaffected.

For the failback reverse sync specifically (Step 4), the policy is always issued from the cluster that holds the current writeable data, pushing to the recovering original source. There is no functional difference in the failover/failback sequence between clusters that used push versus pull in normal operations; both directions use the same commands. The key is that account IDs and base paths are swapped to reflect the reversed roles.

SmartSync failover and failback is a structured, seven-step workflow anchored on Global Snapshot lineage and three core commands: ‘isi dm setup-dir client-access’ (unlock a path for writes), ‘isi dm setup-dir replication-target’ (lock a path as a replication target and revert to a known state), and a reverse ‘REPEAT_COPY’ policy with ‘–reconnect true’ (incremental failback without re-baselining). The sequence handles both unplanned outage (fail over to last clean dataset, write locally, sync back) and planned maintenance (using the ‘–creation-dataset-make-read-only’ flag to cleanly quiesce the source before cutover).

Note the following important differences from SyncIQ: There is no equivalent of the ‘resync-prep job’, The ‘isi dm setup-dir replication-target’ CLI command, and its mandatory dataset revert, serve that function. Dataset ID matching between clusters is by revision and global ID, not by local integer. And –reconnect true on the reverse repeat-copy policy is non-negotiable for incremental failback.

Note also that SmartSync failover and failback is only supported for file-to-file replication. File-to-object cloud copy (replication to ECS, AWS, Azure, or GCP) does not support these operations and is intended for backup and archival workflows only. Verify the Job Type field in ‘isi dm reports list’ after a reconnect-mode failback sync: It must read ‘DATASET_INCREMENTAL’ to confirm that no re-baseline occurred.

PowerScale Software-Defined Exascale Platform

Building on the success of the PowerScale F910 and F710 all-flash platforms and the recently launched OneFS 9.15 release comes the debut of a fundamentally new addition to the PowerScale family: the software-defined Exascale node, based on the Dell PowerEdge R7725xd platform.

This marks a significant architectural milestone for PowerScale, introducing both the first AMD-based node in the product’s history and a notable enhancement to the traditional appliance delivery model that has defined the platform since its Isilon origins.

Predicated upon the 17th generation Dell PowerEdge R7725xd, the new Exascale node pairs dual-socket AMD EPYC SP5 processors with PCIe Gen5 all-flash NVMe storage, high-bandwidth 400GbE networking, and a generous helping of DDR5 memory — all in a standard 2RU chassis.

What makes it truly distinctive, however, is not just the hardware profile but the way it is delivered: Hardware and OneFS software are procured and shipped separately, and the node is not pre-configured as a dedicated storage appliance at the factory.

Customers purchase Exascale through standard Dell server sales channels and receive OneFS as a separate software license — meaning the same physical hardware can support PowerScale, ObjectScale, and in the future, PowerFlex, and Lightning File System workloads, depending on how the organization’s needs evolve.

A New CPU Architecture for PowerScale

Introducing AMD to the PowerScale lineup is not a minor footnote. AMD’s EPYC architecture has become the CPU of choice across the hyperscaler and AI/ML communities, and its presence in the PowerScale portfolio provides opportunities where Intel-only offerings have historically been a limitation. Each Exascale node is equipped with two AMD EPYC SP5 9455 processors — 48 cores each, running at a base clock of 3.15 GHz with a boost to 4.4 GHz, with 300W TDP (thermal design power) and 256 MB of L3 cache per socket. That is 96 cores per node, a significant step up from the 48-core (dual 24-core Sapphire Rapids) configuration of the F910, and it brings commensurate improvements in throughput-heavy and parallel workloads such as generative AI data pipelines, EDA, and high-concurrency analytics.

Accompanying the new CPUs is a whopping 768 GB of DDR5-6400 memory per node — 24 DIMMs at 32 GB each — compared to the 512 GB DDR5 configuration of the F910. This additional memory headroom benefits caching, metadata handling, and concurrent client workload density.

Storage and Journal

Each Exascale node accommodates 24 NVMe U.2 SSDs connected via PCIe Gen5 x4 lanes per drive. Five drive capacity points are supported, spanning from 7.68 TB TLC up to 122 TB QLC, yielding raw per-node capacities from 184 TB at the entry point all the way to 2.88 PB with the highest-density QLC option. That last figure is what earns the platform its Exascale designation — at maximum density, a fully populated cluster of Exascale nodes can reach raw capacities that were previously the exclusive domain of purpose-built hyperscale infrastructure.

The journal subsystem receives an equally significant upgrade. The Exascale platform ships with a 64 GB Software Defined Persistent Memory (SDPM) module — double the 32 GB SDPM introduced with the PowerScale F-series family. This is also the first SDPM implementation on an AMD platform, requiring a new SDPM design that integrates with the AMD memory controller architecture. SDPM continues to serve its established role as the persistent storage backing for the OneFS journal, providing the durability guarantees that protect in-flight write operations without the limitations of earlier NVDIMM-n technology.

On the system boot media side, the legacy IDSDM microSD configuration is replaced by a BOSS (Boot Optimized Storage Solution) N-1 DC-MHS module — a pair of dual-mirrored 960 GB ISE SSDs — providing a more robust and higher-capacity platform for node operating system and configuration storage.

400GbE Front- and Back-End Networking

Both front-end client and back-end intra-cluster networking on the Exascale platform step up to 400 GbE, a fourfold increase over the 100 GbE back-end configuration of the F910. Each interface is delivered via an NVIDIA ConnectX-8 dual-port 400 GbE adapter running over PCIe Gen5.0 x16, paired with NVIDIA Spectrum-SN5610 switches. Unlike the F910, InfiniBand is not supported — Exascale is an Ethernet-only platform — and the management port moves from a LOM (LAN-on-Motherboard) to a dual-port OCP 3.0 NIC operating at 1 GbE.

Licensing

Consistent with the software-defined delivery model, Exascale employs a dynamic licensing approach for PowerScale: a subscription-based license with an expiration date, rather than the traditional perpetual hardware-bundled license. A new single eLicensing tier covers the Exascale nodes, which can coexist alongside traditional PowerScale F-series, H-series, and A-series nodes within the same cluster under unified licensing management.

Specs

The basic specifications for the new Exascale hardware platform are:

Component Exascale Platform
Platform Dell PowerEdge R7725xd
CPU Dual-socket AMD EPYC SP5 9455, 48c, 3.15 GHz / 4.4 GHz
Memory 768 GB DDR5-6400 (24 × 32 GB)
Journal 64 GB SDPM
NVMe drives per node 24 × NVMe U.2 (PCIe Gen5 x4)
Drive options 7.68 TB, 15.36 TB (TLC) ; 30.72 TB, 61 TB, 122 TB (QLC)
Raw capacity per node 184 TB to 2.88 PB
Front-end network 2 × 400 GbE
Back-end network 2 × 400 GbE
Management 2 × 1 GbE OCP 3.0
Data reduction Software compression and deduplication
Form factor 2RU
Minimum OneFS 9.15

Deployment and Compatibility

In its PowerScale guise, the Exascale platform requires OneFS 9.15 as the minimum software version, along with Node Firmware Package (NFP) 14.1 minimum. Deployment is supported via a manual process performed by Dell Professional Services, or through the new Exascale Phase 1 Pave — a more automated, multi-node provisioning process capable of deploying either PowerScale or ObjectScale on the same hardware. Software and firmware upgrade procedures remain consistent with prior PowerScale generations.

In a future article, we’ll take a deeper look at the Exascale platform internals and interconnects, including the storage options, SDPM implementation, PCIe topology, and network connectivity in more detail. But in summary, the PowerScale Exascale platform quite simply redefines what a PowerScale node can be: Exascale-class capacity, next-generation AMD performance, 400 GbE throughout, and the operational flexibility of a truly software-defined delivery model — all in a compact and powerful 2RU form factor.

PowerScale InsightIQ 6.4

The dog days of summer have done nothing to slow the pace over at Dell PowerScale. Hot on the heels of the OneFS 9.15 release comes the arrival of the latest and greatest PowerScale InsightIQ 6.4 monitoring and reporting release.

As a quick refresher, InsightIQ provides robust health, performance, and reporting capabilities that help maximize PowerScale cluster efficiency, including advanced analytics to optimize applications, correlate cluster events, and accurately forecast future storage requirements.

So what goodness does this InsightIQ 6.4 release add to the PowerScale metrics and monitoring mix?

New functionality includes:

Feature IIQ 6.4 Functionality
Top Talkers Report New report type surfacing the top N clients slowing a cluster down, ranked by bandwidth, latency, and operation rate.
Performance Anomaly Detection On-demand anomaly detection across the Performance Reports modules, highlighting unusual behavior directly on the existing performance graphs.
Dell ESE Integration Secure, always-on connectivity to Dell support infrastructure via Connectivity Services, enabling remote troubleshooting without VPN or direct network access.
Telemetry Automated, periodic collection of system health, configuration, and feature-adoption metadata, uploaded securely over the same ESE channel. No customer PII or cluster data.
Partitioned Performance Enhancements New SmartQoS identification and workload-latency metrics, plus support for 1,024+ workloads per dataset.
AI Assistant Enhancements Bring Your Own LLM (BYO-LLM) support, multi-session chat history, and response-feedback collection.
Platform & OS Support Support for the latest OS and OneFS releases, plus N-2 version upgrade support for simplified upgrade planning.

The new PowerScale InsightIQ 6.4 release introduces a healthy crop of enhancements aimed at improving performance visibility, supportability, and day-to-day usability. Let’s take a closer look at each of them in turn.

Top Talkers Report

Top of the bill in 6.4 is the new Top Talkers report, added to the Performance Reports family. Rather than trawling through graphs to work out which client is hammering a cluster, administrators can now see the busiest clients at a glance. The report presents bar charts of the top N clients across three brand-new modules — Bandwidth, Latency, and Op Rate — making it straightforward to pinpoint the workloads that are slowing a monitored cluster down.

Because Top Talkers lives within Performance Reports, it behaves just like its siblings: the usual filters can be applied (single-value filters are supported for these new modules), and the modules can be freely mixed and matched into custom user-defined reports.

Performance Anomaly Detection

InsightIQ 6.4 also gains on-demand Performance Anomaly Detection — a built-in capability that automatically flags unusual performance patterns on your monitored clusters. Anomalies are highlighted directly on the existing performance reporting graphs, with InsightIQ computing expected upper and lower confidence bounds for each metric and marking any data point that breaches them. It works across all performance report types, with the sole exception of multiline graphs.

Two detection modes are on offer, depending on how much history is available:

Historic Mode Current View Mode
Uses past trends and seasonality (hourly, daily, weekly) to establish a baseline. Detects anomalies using only the data visible on the current graph.
Requires a minimum of one week of historical data. Works for any selected time duration.
Configurable lookback window of 1, 2, or 3 weeks (default: 2 weeks). No historical data requirement.
Best for steady-state workloads with predictable patterns. Useful when historical data is limited or the cluster is newly added.

Three sensitivity levels — Low, Medium, and High — control the strictness of the confidence bounds, with higher sensitivity flagging subtler deviations. Historic mode builds its baseline from up to three weeks of past data, learning the hourly, daily, and weekly seasonality unique to each cluster’s workload. To use Historic mode, at least one PowerScale cluster must be added, actively monitored, in a Connected state, and have a minimum of one week of collected performance data.

Dell ESE Integration (Connectivity Services)

Arguably the headline supportability feature of the release, InsightIQ 6.4 introduces integration with Dell’s backend through ESE Connectivity Services. This establishes secure, always-on connectivity between InsightIQ and Dell Technologies support infrastructure, allowing Dell support engineers to remotely access and troubleshoot an InsightIQ instance without requiring a VPN, direct network access, or customer-side coordination during the session. Once configured, a dedicated support user is automatically provisioned for those remote sessions.

Two core capabilities ride on this new channel:

  • Remote Support — Dell support engineers can initiate secure remote CLI (SSH) or Web UI sessions to the InsightIQ instance, authenticated via a time-limited RSC passcode tied to an active Service Request.
  • Auto Support Case Creation — InsightIQ can automatically open support cases with Dell when qualifying events are detected. This can be enabled in the 6.4 release, though it is not yet internally active.

Connectivity can be established in one of two modes, depending on whether the InsightIQ instance is permitted direct internet access:

Connection Mode Description
Connect Directly InsightIQ connects out over the internet directly to Dell Connectivity Services. Requires outbound internet access from the IIQ instance.
Via Secure Connect Gateway InsightIQ connects over port 9443 to a Secure Connect Gateway (SCG) appliance, which acts as a secure proxy to Dell Connectivity Services — useful when IIQ cannot have direct internet access. IIQ monitors only its connection to the gateway; the gateway-to-Dell link is not checked by IIQ. The SCG appliance must be acquired and set up independently.

From a security standpoint, the auto-provisioned support user is deliberately constrained. Via the Web UI it holds a read-only role — able to view the InsightIQ interface but unable to modify any settings or data. Via CLI (SSH) it is limited to non-disruptive operations such as log collection and diagnostics; session-disrupting operations are blocked, with the sole exception of ‘system-reboot’. All remote sessions auto-terminate after 20 minutes of inactivity, and the support user’s credentials are managed internally by InsightIQ and the Dell backend, rather than by IIQ users. Prerequisites are modest: a machine-id (/etc/machine-id) must be present on Scale setups, and an Access Key and PIN are generated up front via the Dell support portal.

Telemetry

Complementing the ESE integration, InsightIQ 6.4 adds Telemetry — the automated, periodic collection of operational metrics and configuration data from InsightIQ, securely uploaded to the Dell ESE connectivity hub. Telemetry rides on the very same connectivity channel and runs quietly in the background as long as connectivity is enabled; no customer action is required after the initial setup. Data is gathered at staggered intervals, compressed into timestamped .tar.gz archives, and uploaded with MD5 checksum integrity verification. Crucially, no customer PII or cluster data content is collected — only system health, configuration metadata, and operational counters.

The collected data gives Dell health monitoring (IIQ health status, cluster connectivity, and critical alerts), deployment visibility (version, deployment mode, host specs, and cluster configuration across the installed base), and feature-adoption insight (which features such as FSA, Quotas, Dedupe, Performance Reporting, and the AI Assistant are actively in use). The collection cadence is pre-configured as follows:

Frequency Data Collected
Every 15 minutes Overall IIQ health; clusters with data-collection failures; critical alerts in the last 15 minutes.
Every 1 hour Cluster connectivity status; datastore usage %; node count; OneFS version; per-cluster node health (nodes up vs. nodes down).
Every 4 hours Total node count across all monitored clusters; per-cluster feature availability (FSA, Quotas, Dedupe).
Every 24 hours Alerts generated in the last 24h; storage usage (percent used, total capacity, per-cluster DB size); deployment info (version, Simple/Scale mode); host info (OS & kernel, CPU cores, RAM, IIQ storage used); alert configuration; performance-reporting configuration; and AI Assistant feedback.

Partitioned Performance Report Enhancements

Keeping step with the latest PowerScale release, InsightIQ 6.4 extends its Partitioned Performance reporting to embrace the newest SmartQoS capabilities. Three enhancements land here:

  • New identification metrics — The new Identification Metrics for performance datasets — Operation Class and File — are now displayed in the breakout values and can be filtered on as normal.
  • Workload latency metrics — The new latency metrics ReadQoSDelay, WriteQoSDelay, and OtherQoSDelay appear as three new lines in the Workload Latency graph, with breakouts displayed as normal when selected from the Breakout By dropdown — a boon for SmartQoS latency analysis.
  • More workloads per dataset — Support has been added for OneFS’s new configurable workload limit, so InsightIQ now handles 1,024+ workloads per user-defined dataset. Dell recommends bumping the deployment VM to 12 CPUs and 32 GB RAM to comfortably absorb the higher expected load.

AI Assistant Enhancements

The document-aware AI Assistant introduced in InsightIQ 6.3 — the intelligent companion that helps users find information, understand product capabilities, and troubleshoot InsightIQ and PowerScale issues directly within the interface — receives a trio of enhancements in 6.4:

  • Bring Your Own LLM (BYO-LLM) — Enables integration with an external, OpenAI-compatible LLM. User queries can be securely routed to the configured external model for response generation, rather than relying solely on the built-in assistant.
  • Chat history — Supports multiple chat sessions, letting users switch between conversations while maintaining context across interactions.
  • Response feedback — Lets users rate the AI-generated responses. That feedback is gathered through telemetry to help improve the overall experience over time.

Enabling the AI Assistant is a prerequisite for all of the above. For BYO-LLM specifically, an OpenAI-compatible API endpoint, valid API credentials, and — where applicable — the required SSL/TLS certificates are needed.

Ecosystem & Platform Support

On the platform front, InsightIQ 6.4 keeps pace with the latest operating system and OneFS releases. The headline changes since 6.3 are the move to SLES 15 SP6 for Scale deployments and extended PowerScale coverage up to OneFS 9.15. The full qualification matrix is as follows:

Qualified On InsightIQ 6.3 InsightIQ 6.4
OS (Scale deployment) RHEL 8.10, RHEL 9.6, RHEL 10.0, SLES 15 SP4 RHEL 8.10, RHEL 9.6, RHEL 10.0, SLES 15 SP6
PowerScale (OneFS) v9.7 to v9.14 v9.7 to v9.15
VMware ESXi ESXi v8.0 U3, ESXi v9.0.1 ESXi v8.0 U3, ESXi v9.0.1
VMware Workstation Workstation 17 Free Version Workstation 17 Free Version
Ubuntu Ubuntu 24.04 Online deployment Ubuntu 24.04 Online deployment
OpenStack RHOSP v21 with RHEL 10.0 RHOSP v21 with RHEL 10.0

As with prior releases, InsightIQ continues to offer the same two deployment models — the bare-metal / virtual-machine InsightIQ Scale flavour and the OVA-based InsightIQ Simple flavour on a VMware hypervisor — so existing customers can stick with the model that best suits their environment.

Upgrading to InsightIQ 6.4

One of the more welcome operational touches in this release is N-2 upgrade support, which simplifies upgrade planning by allowing a direct, in-place upgrade to 6.4 from either the 6.2.0 or 6.3.0 release — the process is identical on both Simple and Scale deployments. Beyond an existing InsightIQ Simple or Scale machine running 6.2.0 or 6.3.0, the only real prerequisite is at least 40 GB of free disk space.

At a high level, the upgrade is driven by a single script and moves through a precheck, the upgrade itself, and a post-upgrade cleanup:

  • Precheck — Docker availability, an InsightIQ version check (6.2.0 or 6.3.0), free disk space, InsightIQ service status, and OS compatibility.
  • Upgrade — EULA acceptance, extraction of the InsightIQ images, service shutdown, resource-limit updates, add-on and CIAM installation, and the InsightIQ service upgrade itself.
  • Post-upgrade — InsightIQ metadata refresh, re-enabling of the AI Assistant (if opted in), removal of old Docker images, and clean-up of the upgrade and backup folders.

The mechanics themselves are refreshingly simple — download and uncompress the bundle, extract the upgrade scripts, and trigger ./upgrade-iiq.sh. Progress can be tracked at any time with the showupg –log and showupg –status helpers, with the full detail available in the insightiq_upgrade.log under /usr/share/storagemonitoring/logs/.

All told, InsightIQ 6.4 is a hearty release: Top Talkers and Performance Anomaly Detection sharpen the day-to-day performance story, the ESE integration and Telemetry step change the supportability experience, and the SmartQoS, AI Assistant, and platform updates round things out nicely.