JAVA APPLICATION PERFORMANCE MONITORING

Every Transaction.
Fully Diagnosed.

Transaction tracing, JVM diagnostics, and database intelligence in a single Java agent — including tenant-aware traces and zero-touch Kubernetes injection.

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dynaperf · agent · trace detail
▶ trace 019f262f · tenant=acme-prod · web · 842ms
jdbc query: [testdb.public]=>/* dynamic */ ... t.id => 2,164 rows
⚠ connection pool leak detected — hikari-cp-2 held 47s past threshold
✓ K8s pod auto-instrumented — zero manifest edits, webhook injection
Analysis complete. 1 leak flagged · 1 index recommendation · tenant-filtered
OUR MISSION

Optimize. Save. Sustain.

Improve performance, reduce IT costs, and support sustainable IT operations.

Distinctive Features

Built for Production Java.
Verified in Our Own Agent.

Every capability listed below is implemented and available in the Dynaperf agent.

🔍
Tracing & Query Intelligence
Every JDBC, Hibernate and Redis call rendered inline with full query text — no drill-down required.
  • Full query text + bind variables + rows affected, per trace entry
  • Flame graphs & on-demand thread/CPU profiling
  • Slow-query stack trace capture (configurable threshold)
  • Table health checks — bloat, dead tuples, missing indexes
🏢
Multi-Tenant Observability
Every trace and slow query is automatically attributed to the originating tenant.
  • Automatic tenant tagging on traces (config-driven, zero code changes)
  • Tenant-filterable trace list
  • Seeded Viewer / Admin RBAC roles + forced password reset
  • LDAP authentication
⚙️
Pool & Resource Intelligence
Thread pools and connection pools are automatically discovered and visualized, requiring no manual configuration.
  • Auto-discovery of thread & connection pools
  • Utilization % charts for multiple pools, busy vs. max
  • Configurable JDBC connection pool leak detection
  • Custom gauges from any discovered MBean attribute
☸️
Kubernetes-Native Deployment
The agent can be deployed across a cluster without manual manifest edits.
  • Mutating admission webhook — zero-touch injection
  • Pod metrics — CPU throttling, cgroup v1/v2 aware
  • Self-hosted / fully offline embedded mode
  • Pod → node → namespace → cluster rollup hierarchy
APM Landscape

Feature Comparison
Dynaperf and New Relic APM

This comparison reflects capabilities currently implemented in the Dynaperf agent, evaluated against publicly documented New Relic APM features.

Capability New Relic Dynaperf
Tracing & Diagnostics
Full query text + bind variables + rows affected, inline per trace entry obfuscated by default ✓
Slow-query stack trace capture (configurable threshold) ✓ ✓
Trace-detail timeline correlated with JVM/pod/host metrics on the same screen separate dashboards ✓
Thread/CPU profiling on demand ✓ ✓
Database & Query Intelligence
Table health checks (bloat, dead tuples, missing indexes) ✗ ✓
Avg rows returned in aggregated query stats ✗ ✓
JDBC connection pool leak detection (configurable) ✗ ✓
Multi-Tenancy & Access
Automatic tenant tagging on traces (config-driven, no code changes) ✗ manual NRQL faceting ✓
Tenant-filterable trace list ✗ ✓
Multi-tenant RBAC (seeded Viewer/Admin roles, forced password reset) ✓ ✓
LDAP authentication ✓ ✓
Pools, Gauges & Infrastructure
Thread pool utilization % charts (multiple pools, busy vs. max) requires custom dashboard ✓
Connection pool utilization % charts (multiple pools) requires custom dashboard ✓
Auto-discovery of thread & connection pools (zero manual config) timing only ✓
Custom gauges from any discovered MBean attribute ✓ ✓
Thread CPU / Process CPU / Process Mem, out of the box ✓ ✓
Platform & Deployment
Kubernetes zero-touch injection (mutating admission webhook, no manifest edits) requires sidecar configuration ✓
K8s pod metrics (CPU throttling, cgroup v1/v2) ✓ ✓
Self-hosted / fully offline embedded mode (no SaaS dependency) ✗ SaaS-only ✓
Anomaly detection & dynamic baselines ✓ ✓
Synthetic monitoring (multi-location HTTP checks) ✓ ✓
Alert routing (Slack, PagerDuty, HealthChecks.io, email, webhook) ✓ ✓
Where New Relic Leads
Browser / RUM monitoring ✓ ✗
Mobile agent SDKs ✓ ✗
OpenTelemetry / OTLP ingestion ✓ ✗ proprietary protobuf
Formal SLO management UI ✓ ✗ alert thresholds only
New Product

Dynaperf PGINSIGHT
PostgreSQL Monitoring & Optimization

Purpose-built visibility into your PostgreSQL fleet — identifying high-cost queries, missing indexes, and bloat before they affect production performance.

🐘
Query & Index Advisor
Cost-ranked index and rewrite recommendations sourced from real production query patterns.
🧹
Bloat & Vacuum Health
Table and index bloat, dead tuples, and autovacuum lag surfaced before they degrade performance.
🔗
Replication & Backup Monitoring
Streaming replication lag, WAL growth, and backup health tracked across your whole cluster.
📈
Capacity & Cost Insights
Right-size instances and connection pools with usage-driven recommendations that cut cloud spend.
🔒
Lock & Deadlock Detection
Real-time visibility into blocking sessions, long-running transactions, and deadlocks.
☸️
Kubernetes-Native
Auto-discovers Postgres instances across pods and namespaces — zero manual target config.
Why Dynaperf PGINSIGHT
100%
Purpose-built for PostgreSQL, not a generic add-on
30%
Average compute cost reduction from index & query tuning
5 min
Setup time — read-only connection, no schema changes required
Request PGINSIGHT Early Access →
Expert Services

Deep Java & APM
Performance Expertise

In addition to the platform, Dynaperf provides hands-on consulting from engineers experienced in tuning distributed Java systems in production environments.

🔍
APM Health Assessment
Deep-dive into your tracing coverage, JVM tuning, pool sizing and query performance. Full report delivered.
🚑
Emergency Triage
Same-day response for production incidents from senior engineers specializing in flame graph and heap dump analysis.
🔄
APM Migration
For organizations migrating from New Relic, Dynatrace, or Datadog APM, Dynaperf manages agent rollout and dashboard parity end to end.
🏗️
Architecture Review
Service topology, connection pool sizing, and Kubernetes deployment review for scale.
📊
Capacity Planning
Data-driven growth forecasting, JVM fleet sizing and cloud instance recommendation for your workload.
🎓
Engineering Training
Hands-on distributed tracing and JVM performance workshops for your engineering team.
Why Dynaperf Consulting
25+
Years of hands-on Java/JVM performance engineering
28
Out-of-the-box instrumentation plugins — JDBC, Kafka, Redis, Spring & more
100s
Production APM rollouts delivered on-site
Zero
Generic, templated reports — every engagement is tailored to the client
Talk to an Expert →
Expert Services

Database Performance
Tuning Consulting

Hands-on performance tuning engagements covering the databases most commonly deployed alongside Java applications — from query plan analysis to replication topology.

🐘
PostgreSQL
Performance Tuning
Query plan analysis, index strategy, vacuum & bloat management, connection pool sizing, and streaming replication tuning.
Key tuning areas
  • EXPLAIN plan and wait-event analysis
  • Index, partitioning and query rewrite strategy
  • Autovacuum, bloat and statistics maintenance
  • Shared buffers, work_mem and WAL tuning
  • Lock contention and connection pool sizing
  • Storage I/O, checkpoint and replication lag review
  • High availability, backup and failover readiness
EXPLAIN ANALYZE Autovacuum Replication
🐬
MySQL
Performance Tuning
InnoDB buffer pool sizing, index & query optimization, replication lag resolution, and schema-change strategy for high-traffic tables.
Key tuning areas
  • Slow query log and execution plan analysis
  • Composite index and join optimization
  • InnoDB buffer pool, redo log and flush tuning
  • Lock, deadlock and transaction isolation review
  • Replication lag, binlog and failover tuning
  • Schema change, partitioning and archival strategy
  • Connection, thread and storage I/O sizing
InnoDB Replication Sharding
🔶
Oracle
Performance Tuning
AWR/ASH analysis, SGA/PGA sizing, execution plan stabilization, and RAC/Data Guard performance reviews.
Key tuning areas
  • AWR, ASH and SQL Monitor deep dives
  • Execution plan, SQL profile and baseline tuning
  • SGA, PGA and buffer cache sizing
  • Index, partitioning and optimizer statistics review
  • Latch, enqueue and wait-class contention analysis
  • RAC interconnect, services and workload placement
  • Data Guard, backup and recovery performance
AWR/ASH RAC Data Guard
🗄️
SQL Server
Performance Tuning
Query Store analysis, index & statistics maintenance, TempDB contention, and Always On availability group tuning.
Key tuning areas
  • Query Store and actual execution plan analysis
  • Index, statistics and parameter sniffing fixes
  • Memory grants, buffer cache and plan cache review
  • Blocking, deadlock and isolation-level tuning
  • TempDB contention and file layout optimization
  • Storage latency, log throughput and backup tuning
  • Always On, replication and failover health checks
Query Store TempDB Always On
DB
Other Databases
Performance Tuning
Coverage for additional relational, NoSQL, cache, search, and cloud-managed database engines used in Java production stacks.
Key tuning areas
  • Workload profiling and top statement identification
  • Access path, indexing and data model review
  • Memory, cache and resource governance tuning
  • Concurrency, throttling and queue-depth analysis
  • Storage, network and cloud service limit review
  • Replication, shard, cluster and failover checks
  • Observability, alerting and runbook readiness
MongoDB Redis Cloud DBs
01
Evidence Pack
Top SQL, waits, plans, locks, I/O signals, and configuration evidence collected into a clear tuning baseline.
02
Ranked Fix Plan
Index, SQL, schema, memory, pool, and platform recommendations ordered by impact, risk, and rollout effort.
03
Before/After Validation
Measured comparison of query latency, throughput, waits, CPU, I/O, and replication health after tuning changes.
04
Operations Handoff
Runbook updates, monitoring thresholds, maintenance tasks, and rollback guidance for production teams.
Expert Services

Application Performance Tuning
Java · J2EE · App Servers

Server-specific tuning for the JVMs and application servers running your production workloads.

☕
WebLogic
Work manager tuning, JDBC data source pool sizing, and JMS/EJB container optimization.
🌐
WebSphere
JVM heap & GC tuning, thread pool sizing, and connection pool optimization for traditional and Liberty profiles.
🦋
WildFly / JBoss EAP
Subsystem & datasource tuning, Undertow thread pool sizing, and clustering/session replication tuning.
🍃
Spring Boot
Embedded container tuning, actuator-driven diagnostics, connection pool & async executor sizing.
🐈
Tomcat
Connector & thread pool tuning, session manager configuration, and NIO/APR protocol selection.
⚙️
Generic JVM Tuning
Heap sizing, GC algorithm selection (G1, ZGC, Parallel) and pause-time reduction across any Java runtime.
Generic Performance Tuning Areas
  • ✦ Heap sizing & garbage collection tuning (G1, ZGC, Parallel)
  • ✦ Thread pool & connection pool sizing
  • ✦ Class loading & deployment/startup optimization
  • ✦ Session management & clustering/replication tuning
  • ✦ Thread dump & heap dump bottleneck analysis
  • ✦ Data source & JDBC pool contention resolution
Talk to an Expert →
Dynaperf Java APM · Pricing

Dynaperf Java APM
Simple, Transparent Pricing

Priced per monitored server, with no per-user fees or data egress charges. No long-term commitment required.

FREE TRIAL AVAILABLE
Professional
$35/server/mo
Full platform for engineering teams serious about production Java performance.
  • ✓ All 28 instrumentation plugins
  • ✓ Flame graphs + thread/CPU profiling
  • ✓ 30-day trace history
  • ✓ ML anomaly detection
  • ✓ Multi-tenant RBAC
  • ✓ Kubernetes zero-touch injection
Start Free Trial
Enterprise
Custom
For organizations with large JVM fleets, compliance requirements or self-hosted needs.
  • ✓ Unlimited monitored applications
  • ✓ Self-hosted / embedded deployment
  • ✓ 1-year trace history
  • ✓ SSO / SAML / LDAP
  • ✓ SLA guarantee
  • ✓ Dedicated support engineer
  • ✓ Consulting hours included
Contact Sales