The challenge
Too many moving parts, too much at stake
A SIEM migration is rarely just a platform swap. The data layer is where most of the work and most of the risk lives: sources must be reconnected, parsers rebuilt, schemas mapped, and detections validated in a new environment. On top of that, ingestion costs can spike before filtering is in place, while the SOC carries two SIEMs, two data paths, and the constant risk of silent gaps. Any gap in that process is a gap in security coverage.
The solution
Take control of your SIEM migration
DataStream handles the data pipeline side of migration, reducing the effort required to rebuild integrations and validate the new SIEM.
Run old and new SIEMs in parallel
DataStream routes the same data stream to multiple destinations simultaneously. Connect your new SIEM as an additional target, validate it against live data, and switch off the old one when you’re ready without reconfiguring every log source individually.
Normalize data for any destination automatically
DataStream normalizes at ingestion and converts bidirectionally into a schema that your new SIEM expects. Field mapping is handled automatically, so out-of-the-box and ported detection content can run without waiting on manual parser work.
Filter before the new SIEM ingests
DataStream filters before ingestion, so only relevant data reaches the new SIEM. Critical logs go to analytics. Bulk telemetry routes to low-cost storage. Ingestion costs on the new platform are controlled from the first day of migration.
Carry your pipeline configuration forward
Filtering rules, enrichment logic, routing decisions – everything configured in DataStream travels with the pipeline. When the destination changes, your processing logic stays the same, and your team’s work carries over.
Full visibility into every source and destination
DataStream alerts you when a source stops sending, a destination goes offline, or volumes change unexpectedly. During migration, you know exactly what’s flowing where, with the visibility needed for monitoring and audit.
No data loss, even when a destination drops
DataStream’s Write-Ahead Log architecture persists events to disk before forwarding. If the new SIEM is unreachable, slow, or rate-limited during cutover, data is queued locally and replayed automatically when the destination recovers – with no loss or duplication.
Key benefits
Why this approach works
How it works
Four phases, one pipeline
DataStream’s capabilities map directly to the phases of a real migration. The pipeline you stand up on day one carries you all the way through decommissioning.
Shadow
Point DataStream at both SIEMs. The new platform receives live production data as an additional destination, without touching a single source. The old SIEM stays authoritative; the new one starts filling up the moment the pipeline is live.
Validate
Run the new SIEM’s detection rules against real volume and real schema. Tune filters, confirm parser coverage, and measure ingestion cost on actual data – not synthetic samples – while the old SIEM continues to protect the SOC.
Cut over
Switch the primary destination source-by-source on your schedule. There is no big-bang moment: each source flips when its detections are validated. WAL-backed buffering guarantees no events drop during the swap.
Decommission
Before the old SIEM goes dark, route a parallel copy of events to the new SIEM’s lake tier or low-cost storage. Historical data stays queryable and correlated with live detections without competing for analytics-tier budget.
The fastest security data pipeline on the market – during migration and after.
Running two SIEMs simultaneously doubles your data processing requirement. DataStream handles parallel routing at full throughput — openly and continuously benchmarked against every major security data pipeline on the market. Migration doesn’t mean degraded performance.
Frequently asked questions
How long does it take to reconnect log sources to a new SIEM?
For sources covered by DataStream’s vendor packs – which include all major security platforms – reconnecting to a new destination is a configuration change in the portal, done in minutes.
What SIEM platforms does DataStream support for migration?
DataStream supports all leading SIEM platforms as migration destinations – including Microsoft Sentinel, Splunk, Google SecOps, Elastic Security, CrowdStrike Falcon NG SIEM, LogPoint, Rapid7 InsightIDR, and others. Beyond SIEMs, it also routes to data lakes, cloud storage, and analytics platforms such as Azure Data Explorer, Amazon Security Lake, and ClickHouse. Any combination of these can run simultaneously during migration. If a specific destination isn’t covered out of the box, VirtualMetric typically delivers a new vendor pack within a day.
What happens to data if a destination goes down during migration?
DataStream uses WAL-backed buffering to persist data locally if a downstream destination becomes unavailable. Data is queued and not dropped; processing resumes automatically when the destination recovers. This applies to both the old and new SIEM during parallel routing.
Can DataStream help evaluate the new SIEM before fully committing?
Yes. Because DataStream routes data to multiple destinations simultaneously, you can send data to a new SIEM in parallel with your existing platform: test detection coverage, validate rule performance, and evaluate ingestion costs with real data before cutting over.
How do I know what’s actually sending data during migration?
DataStream’s health monitoring covers every layer of the pipeline: pipeline instances, sources, and destinations. You can set alerts for source disconnection, no data received, unexpected volume drops, or destination backpressure. During migration, you have real-time visibility into what‘s flowing to the old SIEM, what’s flowing to the new one, and where gaps might be appearing before they affect detection.
What happens to my historical data during migration?
Historical data belongs in the lake tier next to your new SIEM – Sentinel data lake, Amazon Security Lake, Azure Blob, S3, or a customer-managed data lake – not in the analytics tier built for real-time detection. DataStream handles both cases: events flowing through during the migration are forked to the lake tier as they’re processed, and data that pre-dates DataStream can be loaded from existing cloud backups the same way. In either case, historical logs stay queryable and correlated with live detections via the SIEM’s lake-tier search, without paying analytics-tier ingestion costs.
How does DataStream support SIEM migration across multiple customers or tenants?
MSSPs and multi-tenant security teams can run migrations across customers simultaneously, reusing the same pipelines, vendor packs, and routing logic. Each tenant’s pipeline runs independently with its own destinations and policies, but the engineering work is built once and applied many times – so the team isn’t rebuilding configurations per customer or coordinating a book-wide cutover.
Plan your SIEM migration with our engineering team
30-minute technical walkthrough. Bring your current SIEM setup and target platform – we’ll show you how DataStream handles your migration scenario.
Try it on your own data – for free
Connect your sources and see every relevant log flowing to your SIEM, storage, and data lake without coverage gap, data loss, or a long engineering project.
Start now