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Shift Observability Left

Closing the gap on missing data in current observability tools

Granular
Telemetry

Provides breakdown specific function calls and individual performance.

Real-Time
Monitoring

Predicts traceable points, achieving 90% of data acquisition compression.
Avail. Q2, 25

Contextualized System overview

Builds visualization of full systems' contextualization, CPUs and GPUs.

HW Specific
Insights

Provides CPU-bound vs. HW acceleration operation, providing APIs to ensure optimal workload placement.

Detection of Performance Degradation

Shift left Symbolic execution prediction for static data execution, automatically identifies performance degradation.

Granular Telemetry

Provides breakdown specific function calls and individual performance.

Real-Time Monitoring

Predicts traceable points, achieving 90% of data acquisition compression.
Avail. Q2, 25

Contextualized System overview

Builds visualization of full systems' contextualization, CPUs and GPUs.

HW Specific Insights

Provides CPU-bound vs. HW acceleration operation, providing APIs to ensure optimal workload placement.

Detection of Performance Degradation

Shift left Symbolic execution prediction for static data execution, automatically identifies performance degradation.

Shift observability Left with LOCI

LOCI, Line-of-Code Intelligence platform, transforms observability and shift-left approach by extracting deep performance insights from compiled binary files, without requiring source code. Traditional static analysis and observability tools fail to detect performance issues in compiled BIN files due to missing execution context, hardware interactions, and real-time software behavior analysis.

LOCI bridges this gap by modeling compiled binaries with real-world execution data, enabling it to:

  • Predict performance impacts
  • Detect degradations across software versions
  • Identify power-hungry functions
  • Optimize resource efficiency
  • Provide test coverage references
  • Enhance testing & validation
Converge static and dynamic analysis for early-stage optimizations

Unlock R&D Productivity & Reduce Time to Resolution

Designed for companies developing performance-critical infrastructure, LOCI provides actionable insights on CPU/GPU workloads, power consumption, CPU usage, and performance degradation—complete with precise root cause evidence spanning both software and hardware domains.

LOCI dramatically reduces Mean Time to Resolution (MTTR) and enhances key performance indicators (KPIs) by shifting performance analysis left in the development cycle.

Key Benefits:

  • Detects issues immediately after build
  • Minimizes costly late-stage performance issues
  • Faster performance debugging & fixes
  • Power efficiency gains
  • Rapid root cause analysis
  • Enhance testing optimization

Seamless CI/CD Integration for Early Optimization

LOCI integrates directly into CI/CD pipelines, providing real-time feedback post-build and eliminating the need for extensive post-deployment profiling. This ensures continuous monitoring, early anomaly detection, and reduced rollbacks/hotfixes, leading to a more stable and efficient release software cycle.

Seamless CI/CD Integration

Shift observability Left Key capabilities:

Performance Degradation Mitigation

LOCI predicts symbolic execution cycles for each software component across cloud, server, and embedded hardware systems. This deep analysis protects against cold startups, timeouts, and time-event deviations by analyzing atomic cycles and program counter-branching mechanisms, ensuring optimal system performance:
Performance Indicators:

  • Latency: Time to process requests
  • Throughput: Number of requests processed per second
  • Response Time: Time taken to respond to an end-user query
  • Execution Time: Time taken to execute a module
  • Model Inference Time: Time taken for a model to produce output

Energy and Power Optimization

LOCI predicts power hungry workload tasks per application and service, providing actionable recommendations for optimizing system performance and efficiency.
Power indicators:

  • Energy distribution, Max, Mean, Min. per
  • service, and workloads
  • Prediction on static data
  • Monitoring and trend prediction in real time
  • Root cause - where to optimize

Quality analysis

Quality indicators:

  • Branch Coverage - indicates all branch execution possibilities for designing all possible test scenarios  to achieve the minimal risk of untested paths.
  • Behavior Impacts - indicates if the system is functioning within a “safe zone” of acceptable parameters, with negligible or no noticeable impact on performance 
  • Test strategy - enabling analysis of unforeseen consequences among interconnected symbols,  symbol influencers and influenced symbols behavior analysis identified butterfly effect meaning which symbol to include into unit test and test scenarios

LOCI examines both source code and compiled binary files to uncover root cause evidence, enabling teams to anticipate and prevent potential unforeseen consequences before production deployment. This shift-left proactive approach significantly enhances software reliability and reduces post-deployment issues.

Observability in action with LOCI: Embedded and HPC for Automotive

Shift left - Performance degradation between Versions

Full Systems Real-Time Monitoring, New trends with root cause

Inference, Downtime Prediction

Shift left - Power hungry workload prediction, Compiled BIN

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