Transform runaway telemetry costs into predictable, controlled expenses while improving data quality and accessibility. We implement sophisticated data optimization strategies that dramatically reduce licensing costs and infrastructure load without compromising the visibility your teams need.
Our Approach
Most organizations send all telemetry data to all destinations, resulting in massive costs for storing and processing low-value data. Premium platforms charge based on data volume, making this approach economically unsustainable as systems scale. The traditional solution—reducing visibility by collecting less data—creates dangerous blind spots.
We implement intelligent optimization at the pipeline layer that solves the economic problem without sacrificing visibility. By analyzing data value, applying sophisticated filtering and sampling, and routing strategically, we reduce costs while often improving data quality. The key insight: not all data has equal value, and different use cases require different data fidelity.
Our optimization strategies combine multiple techniques—smart sampling, aggregation, filtering, enrichment, and routing—applied based on data value and intended use. High-signal data flows to premium platforms at full fidelity, while high-volume but low-signal data is aggregated, sampled, or routed to cost-effective storage. When investigations require full detail, archived data remains accessible for rehydration and analysis.
What We Deliver
Cost & Volume Analysis Comprehensive analysis of current telemetry volumes, costs, and usage patterns. We identify optimization opportunities, quantify potential savings, and prioritize improvements based on ROI and implementation complexity.
Intelligent Filtering Strategic filtering that eliminates noise without losing signal. We implement filtering rules that remove redundant data, debug logs in production, and low-value events while preserving critical telemetry for security, compliance, and troubleshooting.
Sampling Strategies Sophisticated sampling that maintains statistical accuracy while reducing volume. We design sampling approaches tailored to different data types—head sampling for high-volume logs, tail sampling for distributed traces, and adaptive sampling that responds to system conditions.
Log Aggregation Aggregation policies that collapse repetitive log patterns into summary events. Instead of indexing thousands of identical messages, we create aggregated metrics with sample preservation for detailed investigation when needed.
Smart Archival & Rehydration Archival architecture that stores full-fidelity data in cost-effective storage while routing optimized data to premium platforms. We implement rehydration workflows that enable deep-dive analysis on archived data when investigations require full detail.
Routing Optimization Multi-tier routing strategies that direct data to appropriate destinations based on value. High-priority security events flow to premium SIEM platforms, while verbose application logs route to cost-effective alternatives or archives.
Typical Results
- 40-70% reduction in telemetry platform licensing costs
- 50-80% reduction in data volumes sent to premium destinations
- 10-20% reduction in production infrastructure load
- Weeks to hours improvement in onboarding new data sources
- Maintained or improved visibility and troubleshooting capability