Adaptive Data Collector

Adaptive Data Collector captures context‑aware diagnostic data after a performance degradation event. This targetted data collection provides relevant insights while avoiding continuous, high‑volume data collection, minimizing system impact.

With Adaptive Data Collector, BMC Helix Operations Management adopts a precision-on-demand telemetry that has the following key features:

Resting state: This state triggers low-frequency polling to establish baseline health and trends, minimizing data volume and cost.
Active state: This state automatically enables high-frequency telemetry when a trigger occurs. Examples: deployment events, latency deviations, or alerts
Self-optimizing pipeline: This feature dynamically scales data collection up or down without manual intervention, ensuring that observability aligns with operational reality.

Adaptive Data Collector capabilities

Prevent cost leaks by eliminating waste during the steady state
Capture specific, targetted data during change and risk
Reduce the mean time to resolve (MTTR)
Treat observability as a business-aware capability rather than a passive data list

Scenario

Monitoring specific metrics with context-aware data collection

Apex Global operates Apex‑Retail, an online service for selling pharmaceutical products. The Apex‑Retail service has recently begun responding slowly, and the performance degradation is not related to any ongoing maintenance activity.

Sarah, the administrator at Apex Global, needs to respond to the Apex-Retail service health incident. To achieve a quicker turnaround time, Sarah does not want to waste time collecting data for all available metrics. She wants to collect data for only the affected metrics.

Adaptive Data Collector identifies the issue and increases data collection only for the affected metrics. By running Adapative Data Collector, Sarah achieves the following results:

Analyze the collected metrics to correctly understand the issue
Take corrective action faster to resolve the issue
Avoid high-frequency polling for data collection and save on operational costs

Agent types, skills, and prompts

Adaptive Data Collector supports the following agent types, skills, prompts, and supported models.

Agent types

Health Breach Analyzer: Identify and analyze a health breach in the infrastructure system
Process Correlation: Identify the process that is affected because of the health breach
Deep Monitor Trigger: Identify the subprocesses that are affected because of the health breach
Policy Mapping: Converts selected actionable metrics into deployment-ready policy mappings to enable monitoring

Out-of-the-box skills

Parsing a four-row hierarchy as shown below:
Monitor type > instance > attribute > data
Detecting breaches by using percentile thresholds
Establishing a correlation between health, process, and deep monitoring as shown below:
Health > Process > Deep-monitor
Detecting the lag relation. The following types are valid:
- process_leads
- process_lags
- simultaneous
Estimating causal strength by using causation-scoring heuristics
Recommending an adaptive poll interval. The following values are valid:
- 10s
- 1m
- 10m
Grouping and deduplication of actionable attributes
Performance reporting and scale extrapolation

Out-of-the-box prompts

Detect breached health attributes and windows
Correlate process metrics with breached health signals
Trigger deep monitor selection when SQL/MSSQL context appears
Generate policy mappings for monitor enablement
Recommend polling intervals from volatility/anomaly patterns

Supported models

Azure OpenAI deployment (configured in config.json, current gpt-5-mini)
For more information, see https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/reasoning?tabs=csharp%2Cgpt-5.

User roles and permissions

Make sure that you have the following roles and permissions to configure and use Adaptive Data Collector:

Role	Description
BMC Helix Operations Managementadministrator	Runs Adaptive Data Collector.

Process overview

The following diagram explains how Adaptive Data Collector works:

An administrator observers performance degradataion in the infrastructure system.
The administrator runs Adaptive Data Collector.
Data is collected only for the affected metrics.

Adaptive Data Collector use case

The following table lists the task that you can perform by using Adaptive Data Collector:

Task	Description	Reference
Collect data for specific metrics	After a performance degradation in the infrastructure system, collect data only for the affected metrics instead of continuous, high-volume data collection.	Investigating a sudden performance degradation by using the Adaptive Data Collector