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Observability & Code Profiling
for Distributed Systems

Uncover Hidden Bottlenecks with Minimal Overhead

BitDive delivers real-time code-level observability for Java-based distributed systems, enabling instant root cause analysis and performance optimization through continuous low-overhead profiling.
Ideal for developers, and performance-focused enterprises.

  • BitDive integration diagram showing simple Maven dependency addition and configuration steps

    All-in-One, Developer-Friendly Integration

    • Effortless Setup: Deploy the entire infrastructure in minutes using our Docker Compose configuration
    • Plug-and-Play Library: Simply add the BitDive Maven dependency to your pom.xml file to start profiling
    • No Code Changes: Auto-instrumentation eliminates the need to modify your application code
    • Zero Hassle: Forget assembling complex, puzzle-like solutions—everything you need is included and optimized
    • Seamless in CI/CD: Ideal for containerized environments and DevOps workflows
    Quick start guide
  • Venn diagram showing BitDive's three core capabilities: Method-Level Tracing, Distributed Tracing, and Continuous Low-overhead Profiling

    BitDive Core Capabilities

    • Runs seamlessly in production, gathering method-level data
    • Low (very low) overhead due to in-process monitoring
    • Captures method parameters, SQL queries, and errors
    • Profiles asynchronous tasks and multithreaded operations
    • Enables root cause analysis with full context data
    • Monitors large-scale distributed systems in production
    • Works with any Java code, not just common frameworks
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  • Real time performance dashboard/heatmap showing method response times, request rates, and error tracking across multiple services

    Real-Time Performance Heatmap & Observability

    • Color-coded heatmap showing system response times and changes
    • Real-time tracking of HTTP, REST, SQL and scheduler metrics
    • Module-to-method drill-down with response time details
    • Success rate monitoring with comprehensive error tracking
    • SQL performance analysis with query execution counts
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  • Call tree interface showing method execution flow with detailed parameters panel displaying input/output data, response codes and timing information

    Code-Level Call Tree & Parameter Analyzer

    • Debug production issues by tracing complete method call sequences
    • Access full method context including params and return values
    • Validate data transformations across microservices
    • Track request and response data between service boundaries
    • Identify performance bottlenecks with visual execution path analysis
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  • Timeline waterfall view showing color-coded execution spans for web requests, methods, and database operations with precise timing

    Service Call Timeline Analyzer

    • Track method execution timeline with precise timing visualizations
    • Distinguish web calls, internal methods, database and SQL operations
    • Pinpoint blocking operations and execution overlaps
    • Measure database query performance with detailed timing data
    • Identify service latency and communication bottlenecks
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  • Performance dashboard showing multiple time-series graphs for HTTP requests and SQL queries, with metrics for call count and average response time across different student service operations

    Method-Level Performance Graphs & Metrics

    • Monitor HTTP requests, methods and SQL queries in real-time metrics
    • Track service response times through interactive time-series graphs
    • Compare call counts and query volumes across different operations
    • Identify performance trends with auto-refreshing data points
    • Analyze SQL timing patterns with precise time-based visualizations
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  • JVM monitoring dashboard displaying real-time graphs of system resources including CPU usage, memory usage, thread count, and disk/swap memory utilization across multiple metrics

    Real-Time JVM Resource Monitor

    • Comprehensive system metrics tracking CPU, memory, and thread utilization
    • Live heap and non-heap memory analysis with maximum threshold monitoring
    • Thread management insights showing daemon and total thread patterns
    • Disk space allocation with used vs free space visualization
    • Swap memory tracking for system memory pressure detection
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  • Illustration showing successful deployment metrics and celebration of a smooth Friday deployment

    Easy Friday Deploy to Production

    • Full deployment visibility from service topology to method-level details
    • Compare before/after behavior instantly and asses new release performance
    • Get full contextual data with method parameters, SQL queries, and errors
    • Enables root cause analysis with full context data input/output values
    • Monitors large-scale distributed systems in production without overhead
    See More Details

How BitDive Delivers ROI

Faster Troubleshooting

Reduce MTTR by up to 70% with precise method-level tracing and automatic bottleneck detection, enabling rapid issue resolution

Improved User Experience

Detect and prevent performance degradation before users are impacted by monitoring method-level metrics continuously

Resource Optimization

Save on cloud infrastructure costs by identifying performance bottlenecks and optimizing resource utilization across services

connected world

Enterprise-Grade Scalability

Whether you’re managing monolithic applications or microservices, BitDive scales effortlessly, from single apps to complex microservices architectures

Five-Minute Setup

Start profiling with one Maven dependency and minimal YAML config - no code changes, no JVM agents required

Reduced Operational Costs

Cut support tickets and performance-related incidents through proactive monitoring and rapid root cause analysis

How BitDive Stands Out

Beyond traditional profiling

Comparison of traditional profiling tools versus BitDive's modern approach to Java application monitoring

Most APM and profiling tools force you to make difficult tradeoffs: either collect high-level metrics that miss critical details, or get comprehensive data that impacts performance.
BitDive solves this through an efficient library-based approach that captures complete method-level data—including parameters, return values, SQL queries, and async operations—while maintaining microsecond-level overhead.
This lets you run continuous profiling in production and trace requests end-to-end across distributed services, finally making distributed debugging and performance optimization practical at scale.

Detailed Comparison

Built for Modern Java Teams

Modern Profiling for Cloud-Native Era

Cloud-Native Applications
Trace requests across Kubernetes clusters and cloud services while maintaining low overhead in containerized environments.
High-Load Production
Run continuous profiling in high-throughput systems without performance impact. Catch issues early and optimize resource usage.
Microservices Architecture
Follow requests through your entire service mesh with method-level visibility. Understand distributed system behavior in production.
CI/CD Integration
Detect performance regressions early through automated deployment pipeline integration. Compare method-level metrics between releases.

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