Performance Metrics

Performance metrics are quantitative measurements that provide visibility into Geode’s operational behavior, resource utilization, and query performance. Geode exposes hundreds of metrics covering every aspect of database operations, from query execution times and transaction throughput to memory consumption and disk I/O patterns. By collecting and analyzing metrics, you can identify performance bottlenecks, detect anomalies, optimize resource allocation, and ensure your Geode deployment meets service level objectives (SLOs). Metrics form the foundation of observability, enabling data-driven decisions about scaling, tuning, and capacity planning. This guide covers Geode’s metrics architecture, key performance indicators (KPIs), collection strategies, and metrics-driven optimization techniques. <h3 id="metrics-architecture" class="position-relative d-flex align-items-center group"> Metrics Architecture <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="metrics-architecture" aria-haspopup="dialog" aria-label="Share link: Metrics Architecture"> Share link </button> </h3><div id="headingShareModal" class="heading-share-modal" role="dialog" aria-modal="true" aria-labelledby="headingShareTitle" hidden> <div class="hsm-dialog" role="document"> <div class="hsm-header"> <h2 id="headingShareTitle" class="h6 mb-0 fw-bold">Share this section</h2> <button type="button" class="hsm-close" aria-label="Close"> </button> </div> <div class="hsm-body"> <label for="headingShareInput" class="form-label small text-muted mb-1 text-uppercase fw-bold" style="font-size: 0.7rem; 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if(!icon) return; const prev=copyBtn.getAttribute('data-prev')||icon.className; if(!copyBtn.getAttribute('data-prev')) copyBtn.setAttribute('data-prev',prev); icon.className= ok ? 'fa-duotone fa-clipboard-check':'fa-duotone fa-circle-exclamation'; setTimeout(()=>{ icon.className=prev; },1800); } function handleShareClick(e){ e.preventDefault(); const btn=e.currentTarget; const id=btn.getAttribute('data-share-target'); if(id) openModal(id); } function bindShareButtons(){ document.querySelectorAll('.h-share').forEach(btn=>{ if(!btn.dataset.hShareBound){ btn.addEventListener('click', handleShareClick); btn.dataset.hShareBound='1'; } }); } bindShareButtons(); if(document.readyState==='loading'){ document.addEventListener('DOMContentLoaded', bindShareButtons); } else { requestAnimationFrame(bindShareButtons); } document.addEventListener('click', function(e){ const shareBtn=e.target.closest && e.target.closest('.h-share'); if(shareBtn && !shareBtn.dataset.hShareBound){ handleShareClick.call(shareBtn, e); } }, true); document.addEventListener('click', e=>{ if(e.target===modal) closeModal(); if(e.target.closest && e.target.closest('.hsm-close')){ e.preventDefault(); closeModal(); } if(copyBtn && (e.target===copyBtn || (e.target.closest && e.target.closest('.hsm-copy')))) { e.preventDefault(); copyCurrent(); } }); document.addEventListener('keydown', e=>{ if(e.key==='Escape' && isOpen()) closeModal(); }); function trapFocus(){ if(trapBound) return; trapBound=true; modal.addEventListener('keydown', f=>{ if(f.key==='Tab' && isOpen()){ const focusable=[...modal.querySelectorAll('a[href],button,input,textarea,select,[tabindex]:not([tabindex="-1"])')].filter(el=>!el.hasAttribute('disabled')); if(!focusable.length) return; const first=focusable[0]; const last=focusable[focusable.length-1]; if(f.shiftKey && document.activeElement===first){ f.preventDefault(); last.focus(); } else if(!f.shiftKey && document.activeElement===last){ f.preventDefault(); first.focus(); } } }); } if(closeBtn) closeBtn.addEventListener('click', e=>{ e.preventDefault(); closeModal(); }); })(); </script>Geode implements a multi-layered metrics system built on industry standards: Prometheus Exposition Format: Metrics are exposed at <code>/metrics</code> endpoint in Prometheus-compatible format, making integration with monitoring stacks straightforward. Hierarchical Organization: Metrics are organized by subsystem (queries, transactions, storage, memory, connections) with consistent naming conventions. Low Overhead: Metrics collection uses lock-free data structures and sampling techniques to minimize performance impact. Rich Labels: Metrics include dimensional labels for filtering and aggregation (e.g., query status, client type, operation type). <h3 id="core-metric-types" class="position-relative d-flex align-items-center group"> Core Metric Types <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="core-metric-types" aria-haspopup="dialog" aria-label="Share link: Core Metric Types"> Share link </button> </h3> <h4 id="counter-metrics" class="position-relative d-flex align-items-center group"> Counter Metrics <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="counter-metrics" aria-haspopup="dialog" aria-label="Share link: Counter Metrics"> Share link </button> </h4>Counters track cumulative totals that only increase over time. Use rate functions to convert to per-second rates: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># Total queries executed geode_queries_total{status="success"} 1,284,372 # Query rate (queries per second) rate(geode_queries_total[5m]) </code></pre></div>Key Counters: <ul> <li><code>geode_queries_total</code> - Total queries by status (success/error)</li> <li><code>geode_transactions_total</code> - Total transactions by outcome</li> <li><code>geode_connection_errors_total</code> - Failed connection attempts</li> <li><code>geode_disk_io_operations_total</code> - Disk I/O operations by type</li> <li><code>geode_cache_misses_total</code> - Cache miss count</li> </ul> <h4 id="gauge-metrics" class="position-relative d-flex align-items-center group"> Gauge Metrics <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="gauge-metrics" aria-haspopup="dialog" aria-label="Share link: Gauge Metrics"> Share link </button> </h4>Gauges represent point-in-time measurements that can increase or decrease: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># Current active connections geode_active_connections 127 # Memory usage in bytes geode_memory_used_bytes 2,147,483,648 # Active transactions geode_active_transactions 15 </code></pre></div>Key Gauges: <ul> <li><code>geode_active_connections</code> - Current client connections</li> <li><code>geode_active_queries</code> - Currently executing queries</li> <li><code>geode_memory_used_bytes</code> - Total memory consumption</li> <li><code>geode_disk_used_bytes</code> - Disk space used</li> <li><code>geode_connection_pool_size</code> - Connection pool utilization</li> </ul> <h4 id="histogram-metrics" class="position-relative d-flex align-items-center group"> Histogram Metrics <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="histogram-metrics" aria-haspopup="dialog" aria-label="Share link: Histogram Metrics"> Share link </button> </h4>Histograms track distributions of values across predefined buckets, enabling percentile calculations: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># Query duration buckets geode_query_duration_seconds_bucket{le="0.01"} 45,234 geode_query_duration_seconds_bucket{le="0.05"} 89,432 geode_query_duration_seconds_bucket{le="0.1"} 112,847 geode_query_duration_seconds_bucket{le="1.0"} 125,234 geode_query_duration_seconds_bucket{le="+Inf"} 125,847 # Calculate p95 latency histogram_quantile(0.95, rate(geode_query_duration_seconds_bucket[5m])) </code></pre></div>Key Histograms: <ul> <li><code>geode_query_duration_seconds</code> - Query execution time distribution</li> <li><code>geode_transaction_duration_seconds</code> - Transaction duration distribution</li> <li><code>geode_checkpoint_duration_seconds</code> - Checkpoint time distribution</li> <li><code>geode_index_build_duration_seconds</code> - Index creation time distribution</li> </ul> <h4 id="summary-metrics" class="position-relative d-flex align-items-center group"> Summary Metrics <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="summary-metrics" aria-haspopup="dialog" aria-label="Share link: Summary Metrics"> Share link </button> </h4>Summaries pre-calculate percentiles on the client side: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql">geode_query_latency{quantile="0.5"} 0.012 geode_query_latency{quantile="0.9"} 0.087 geode_query_latency{quantile="0.99"} 0.342 </code></pre></div> <h3 id="query-performance-metrics" class="position-relative d-flex align-items-center group"> Query Performance Metrics <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="query-performance-metrics" aria-haspopup="dialog" aria-label="Share link: Query Performance Metrics"> Share link </button> </h3>Track query execution characteristics to identify optimization opportunities: Query Throughput: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># Total query rate sum(rate(geode_queries_total[5m])) # Success rate percentage rate(geode_queries_total{status="success"}[5m]) / rate(geode_queries_total[5m]) * 100 </code></pre></div>Query Latency: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># Median query time (p50) histogram_quantile(0.50, rate(geode_query_duration_seconds_bucket[5m])) # p95 query time (95% of queries complete faster) histogram_quantile(0.95, rate(geode_query_duration_seconds_bucket[5m])) # p99 query time (worst-case for 99% of queries) histogram_quantile(0.99, rate(geode_query_duration_seconds_bucket[5m])) </code></pre></div>Query Plan Cache: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># Cache hit rate (percentage) rate(geode_query_plan_cache_hits_total[5m]) / (rate(geode_query_plan_cache_hits_total[5m]) + rate(geode_query_plan_cache_misses_total[5m])) * 100 # Cache size geode_query_plan_cache_size_bytes </code></pre></div>Slow Queries: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># Slow query rate (queries exceeding threshold) rate(geode_slow_queries_total[5m]) # Slow query threshold (default 1 second) geode_slow_query_threshold_seconds </code></pre></div> <h3 id="transaction-metrics" class="position-relative d-flex align-items-center group"> Transaction Metrics <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="transaction-metrics" aria-haspopup="dialog" aria-label="Share link: Transaction Metrics"> Share link </button> </h3>Monitor transaction behavior and ACID guarantees: Transaction Throughput: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># Commits per second rate(geode_transactions_total{status="committed"}[5m]) # Rollbacks per second rate(geode_transactions_total{status="rolled_back"}[5m]) # Commit ratio rate(geode_transactions_total{status="committed"}[5m]) / rate(geode_transactions_total[5m]) * 100 </code></pre></div>Transaction Conflicts: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># Serialization conflict rate rate(geode_transaction_conflicts_total[5m]) # Conflict ratio (conflicts per transaction) rate(geode_transaction_conflicts_total[5m]) / rate(geode_transactions_total[5m]) </code></pre></div>Transaction Duration: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># Average transaction duration rate(geode_transaction_duration_seconds_sum[5m]) / rate(geode_transaction_duration_seconds_count[5m]) # p95 transaction duration histogram_quantile(0.95, rate(geode_transaction_duration_seconds_bucket[5m])) </code></pre></div>Long-Running Transactions: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># Transactions exceeding 60 seconds geode_long_running_transactions{threshold="60s"} # Oldest active transaction age geode_oldest_transaction_age_seconds </code></pre></div> <h3 id="connection-metrics" class="position-relative d-flex align-items-center group"> Connection Metrics <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="connection-metrics" aria-haspopup="dialog" aria-label="Share link: Connection Metrics"> Share link </button> </h3>Track client connectivity and connection pool health: Connection Utilization: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># Current active connections geode_active_connections # Connection pool utilization percentage geode_active_connections / geode_max_connections * 100 # Connections by client type sum by (client_type) (geode_active_connections) </code></pre></div>Connection Churn: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># New connections per second rate(geode_connections_opened_total[5m]) # Closed connections per second rate(geode_connections_closed_total[5m]) # Connection error rate rate(geode_connection_errors_total[5m]) </code></pre></div>QUIC Stream Metrics: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># Active QUIC streams geode_quic_streams_active # Stream errors rate(geode_quic_stream_errors_total[5m]) # Stream reset rate rate(geode_quic_streams_reset_total[5m]) </code></pre></div> <h3 id="memory-metrics" class="position-relative d-flex align-items-center group"> Memory Metrics <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="memory-metrics" aria-haspopup="dialog" aria-label="Share link: Memory Metrics"> Share link </button> </h3>Monitor memory consumption and allocation patterns: Memory Usage: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># Total memory used geode_memory_used_bytes # Memory usage percentage geode_memory_used_bytes / geode_memory_total_bytes * 100 # Memory by subsystem sum by (subsystem) (geode_memory_used_bytes) </code></pre></div>Cache Metrics: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># Query result cache size geode_query_cache_size_bytes # Buffer pool size geode_buffer_pool_size_bytes # Cache hit rate rate(geode_cache_hits_total[5m]) / (rate(geode_cache_hits_total[5m]) + rate(geode_cache_misses_total[5m])) </code></pre></div>MVCC Version Overhead: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># Total MVCC versions in memory geode_mvcc_versions_count # MVCC memory overhead geode_mvcc_memory_bytes # Version cleanup rate rate(geode_mvcc_versions_cleaned_total[5m]) </code></pre></div>Allocation Rate: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># Memory allocations per second rate(geode_memory_allocations_total[5m]) # Deallocations per second rate(geode_memory_deallocations_total[5m]) # Allocation churn rate(geode_memory_allocations_total[5m]) - rate(geode_memory_deallocations_total[5m]) </code></pre></div> <h3 id="storage-metrics" class="position-relative d-flex align-items-center group"> Storage Metrics <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="storage-metrics" aria-haspopup="dialog" aria-label="Share link: Storage Metrics"> Share link </button> </h3>Track disk usage and I/O performance: Disk Space: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># Disk space used geode_disk_used_bytes # Disk space available geode_disk_free_bytes # Disk usage percentage geode_disk_used_bytes / geode_disk_total_bytes * 100 </code></pre></div>Write-Ahead Log (WAL): <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># WAL size in bytes geode_wal_size_bytes # WAL growth rate deriv(geode_wal_size_bytes[15m]) # WAL segments geode_wal_segments_count # WAL flush rate rate(geode_wal_flushes_total[5m]) </code></pre></div>Checkpoint Metrics: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># Checkpoint duration geode_checkpoint_duration_seconds # Checkpoints per hour rate(geode_checkpoints_total[1h]) * 3600 # Data written during checkpoint geode_checkpoint_bytes_written </code></pre></div>Disk I/O: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># Read operations per second rate(geode_disk_io_operations_total{type="read"}[5m]) # Write operations per second rate(geode_disk_io_operations_total{type="write"}[5m]) # Bytes read per second rate(geode_disk_bytes_read_total[5m]) # Bytes written per second rate(geode_disk_bytes_written_total[5m]) </code></pre></div> <h3 id="index-metrics" class="position-relative d-flex align-items-center group"> Index Metrics <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="index-metrics" aria-haspopup="dialog" aria-label="Share link: Index Metrics"> Share link </button> </h3>Monitor index effectiveness and storage: Index Usage: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># Index lookups per second rate(geode_index_lookups_total[5m]) # Index hit rate rate(geode_index_hits_total[5m]) / rate(geode_index_lookups_total[5m]) * 100 # Scans vs. seeks rate(geode_index_scans_total[5m]) / rate(geode_index_seeks_total[5m]) </code></pre></div>Index Storage: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># Total index size geode_index_size_bytes # Index size by type sum by (index_type) (geode_index_size_bytes) # Index memory usage geode_index_memory_bytes </code></pre></div>Index Maintenance: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># Index build duration geode_index_build_duration_seconds # Index updates per second rate(geode_index_updates_total[5m]) # Index rebuilds geode_index_rebuilds_total </code></pre></div> <h3 id="custom-metrics-integration" class="position-relative d-flex align-items-center group"> Custom Metrics Integration <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="custom-metrics-integration" aria-haspopup="dialog" aria-label="Share link: Custom Metrics Integration"> Share link </button> </h3>Extend Geode’s metrics with application-specific measurements: Application Metrics via Labels: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-python" data-lang="python"># Track custom query categories await client.execute( query, params, labels={"query_category": "recommendation", "version": "v2"} ) </code></pre></div>Custom Metric Exporter: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-python" data-lang="python">from prometheus_client import Counter, Histogram, Gauge # Define custom metrics recommendation_requests = Counter( 'app_recommendation_requests_total', 'Total recommendation requests', ['algorithm', 'status'] ) recommendation_latency = Histogram( 'app_recommendation_duration_seconds', 'Recommendation generation time', ['algorithm'] ) # Instrument application code with recommendation_latency.labels(algorithm='collaborative').time(): recommendations = await generate_recommendations(user_id) recommendation_requests.labels( algorithm='collaborative', status='success' ).inc() </code></pre></div> <h3 id="metrics-driven-optimization" class="position-relative d-flex align-items-center group"> Metrics-Driven Optimization <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="metrics-driven-optimization" aria-haspopup="dialog" aria-label="Share link: Metrics-Driven Optimization"> Share link </button> </h3>Use metrics to guide performance improvements: Identify Hot Queries: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># Queries consuming most total time topk(10, rate(geode_query_duration_seconds_sum[5m])) # Most frequently executed queries topk(10, rate(geode_queries_total[5m])) </code></pre></div>Detect Resource Bottlenecks: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># High memory pressure indicator (geode_memory_used_bytes / geode_memory_total_bytes > 0.85) and (rate(geode_cache_evictions_total[5m]) > 100) # Disk I/O bottleneck indicator rate(geode_disk_io_wait_seconds_total[5m]) > 0.1 </code></pre></div>Transaction Tuning: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-promql" data-lang="promql"># High conflict rate requiring tuning rate(geode_transaction_conflicts_total[5m]) / rate(geode_transactions_total[5m]) > 0.05 </code></pre></div> <h3 id="best-practices" class="position-relative d-flex align-items-center group"> Best Practices <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="best-practices" aria-haspopup="dialog" aria-label="Share link: Best Practices"> Share link </button> </h3>Establish Baselines: Monitor metrics under normal load to establish performance baselines for anomaly detection and capacity planning. Use Recording Rules: Pre-compute expensive metric queries in Prometheus recording rules to reduce dashboard load times. Set Meaningful Thresholds: Configure alert thresholds based on actual system behavior and SLO requirements, not arbitrary values. Monitor Metric Cardinality: Avoid high-cardinality labels (e.g., user IDs) that can explode metric storage requirements. Correlate Metrics: Analyze multiple related metrics together to understand root causes (e.g., high query latency + memory pressure). Track Trends: Monitor metric trends over time to predict capacity needs and detect gradual degradation. Validate Changes: Compare metrics before and after configuration changes to measure impact. <h3 id="related-topics" class="position-relative d-flex align-items-center group"> Related Topics <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="related-topics" aria-haspopup="dialog" aria-label="Share link: Related Topics"> Share link </button> </h3><ul> <li><a href="/tags/monitoring/" >System Monitoring</a> - Comprehensive monitoring strategies</li> <li><a href="/tags/observability/" >Observability</a> - Observability best practices</li> <li><a href="/tags/prometheus/" >Prometheus Integration</a> - Prometheus configuration</li> <li><a href="/tags/performance/" >Performance Tuning</a> - Performance optimization</li> <li><a href="/tags/alerting/" >Alerting</a> - Alert configuration</li> <li><a href="/tags/profiling/" >Profiling</a> - Query profiling techniques</li> </ul> <h3 id="further-reading" class="position-relative d-flex align-items-center group"> Further Reading <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="further-reading" aria-haspopup="dialog" aria-label="Share link: Further Reading"> Share link </button> </h3><ul> <li>Metrics Reference Documentation</li> <li>Prometheus Query Examples</li> <li>Metrics-Based Alerting Guide</li> <li>Capacity Planning with Metrics</li> <li>Custom Instrumentation Guide</li> </ul>

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