VirtualMetric DataStream + Elasticsearch: A Smarter Way to Send Logs to Elastic

Elasticsearch has long been the backbone of security analytics for organizations that need fast search, flexible dashboards, and scalable visibility across massive datasets. It powers everything from threat hunting to compliance reporting and real-time investigation. But anyone who has operated Elasticsearch at scale also knows a quiet truth: 

Elasticsearch is only as strong as the data you feed it. And getting clean, consistent, usable telemetry into Elastic is often the hardest part. 

Different vendors use different formats, high-volume logs overwhelm pipelines, and analysts often spend more time fixing ingestion issues than investigating threats. For many teams, even the basic task of sending logs to Elasticsearch becomes an ongoing source of friction.

Today, there’s finally a better way to close that gap. 

VirtualMetric DataStream now integrates directly with Elasticsearch and Elastic Security, delivering normalized, enriched, schema-aligned data from any source – cloud, network, endpoint, identity, or application – without custom scripts, manual parsing, or brittle ingestion pipelines.  

This integration gives SOC teams clean data from day one, predictable operations, and the freedom to route security telemetry wherever it’s needed. 

Security analysts like Elasticsearch for speed and flexibility. But the platform assumes the arriving data is structured, normalized, and consistent. In reality, almost no organization has this by default. 

Most security ecosystems generate massive volumes of logs from firewalls, EDRs, DNS servers, authentication systems, cloud platforms, SaaS tools, and identity providers – each with its own schema, naming conventions, and formatting quirks. As your environment grows, so does the entropy of your telemetry, making it increasingly difficult to send logs to Elasticsearch reliably.

The consequences are: 

Over time, it creates a growing operational tax on SOC teams who must not only manage alerts but also manage data pipelines. 

Most ingestion tools simply forward data as-is, making it hard to send logs to Elasticsearch in the right state. They don’t reconcile field inconsistencies, apply schema mapping, or enrich events before indexing. As a result, Elasticsearch receives raw, heterogeneous telemetry that still requires extensive manual cleanup. 

The only way to prevent downstream ingestion issues is to apply normalization and enrichment upstream before logs reach Elasticsearch’s pipelines or indices. 

The new integration connects VirtualMetric DataStream directly to Elasticsearch and Elastic Security, enabling security teams to ingest data that is normalized, enriched, reliable, and multi-destination from the moment logs enter the pipeline. 

DataStream resolves the issues traditional pipelines leave unsolved by: 

It eliminates much of the complexity organizations traditionally accept as inevitable. 

Simplified onboarding and data routing 

DataStream provides simple, no-code onboarding for all log sources, whether logs enter through agents or agentless collectors such as Syslog, API, Windows, Linux, firewalls, EDR tools, or cloud applications. Administrators choose exactly which data flows to Elasticsearch, Elastic Security, or other SIEMs or storage targets, all managed from one interface. 

This alone simplifies onboarding, removing the need for multiple ingestion systems or ad-hoc routing logic. 

Normalization and Enrichment built in 

Before Elasticsearch receives any event, DataStream parses raw fields, applies vendor-aware normalization, performs enrichment, and maps each record into ECS or intermediate schemas such as CSL or ASIM. The upstream processing prevents index conflicts, keeps dashboards stable, and ensures newly onboarded sources align with existing analytics. 

Enrichment with GeoIP, threat intelligence, and asset context provides analysts with more context per event, directly improving triage and detection workflows. 

Optimized performance and storage 

By delivering clean, pre-filtered, structured data, DataStream significantly reduces index bloat, improves search speed, and minimizes storage overhead. This stabilization of index mappings results in faster dashboards and more reliable queries. 

Multi-platform correlation with unique event IDs 

Every event processed by DataStream receives a unique correlation ID. This allows analysts to trace a single activity, such as a failed login or a suspicious network connection, across Elasticsearch, Microsoft Sentinel, Amazon Security Lake, and any other connected destination using the same identifier.  

For multi-cloud or multi-SIEM organizations, this capability eliminates blind spots and dramatically simplifies multi-system investigations. 

Enterprise-grade reliability 

DataStream includes built-in buffering, retry logic, and Write-Ahead Logging (WAL), ensuring no logs are lost during network interruptions or platform outages. Transformation lineage is retained for audit and compliance use cases.  

Ingest once, deliver anywhere 

One of the most powerful aspects of the integration is DataStream’s ability to deliver the same event in different formats to multiple destinations simultaneously: 

It eliminates duplicated agents, duplicated pipelines, and duplicated engineering work. Instead of maintaining multiple ingestion routes, teams use one clean, unified pipeline. 

The integration uses VirtualMetric’s new Elastic target with support for: 

Event flow 

This ensures that when you send logs to Elasticsearch, they arrive clean, consistent, and ready for dashboards or correlation rules.

Enabling the VirtualMetric DataStream integration with Elasticsearch takes only a few steps: 

2. Decide which logs should flow to Elasticsearch or Elastic Security. 

3. Configure route and enable normalization, enrichment, or filtering as needed. 

4. Start streaming data in real time: with no agent updates or custom parsing scripts. 

Elasticsearch is one of the most capable analytics engines available, but only when it receives high-quality telemetry. For too long, SOC teams have carried the burden of transforming, fixing, and normalizing data just to make Elastic usable. 

VirtualMetric DataStream removes that burden completely. 

By normalizing telemetry at the source, guaranteeing delivery, enabling multi-SIEM routing, and giving analysts clean data from day one, the integration unlocks a faster, more reliable, more predictable Elasticsearch experience. 

Want to explore how DataStream can be integrated into your Elasticsearch environment? Visit our documentation to get started, run a free trial with your own infrastructure, or schedule a technical session with our engineers to assess DataStream’s impact.