Performance Audit for Production Systems

Find the real constraint.

Fix what moves P95/P99 and throughput.

Not an SEO review. Not a PageSpeed score.

A system-level diagnostic to identify bottlenecks, improve observability signal quality, and produce a decision-ready roadmap for scale.

Output

Dashboards + reports + execution backlog

Focus

Tail latency (P95/P99), saturation, throughput

Access

Read-only production telemetry (default)

Tool-agnostic by default. We work with Datadog, Grafana/Prometheus, New Relic, Elastic, CloudWatch, and OpenTelemetry. We’ll align to what you already run—and improve signal quality before adding complexity.

01

P95/P99 worsens even when averages look stable

02

Throughput plateaus while CPU stays “fine” (hidden saturation: pools/IO/locks)

03

Scaling instances increases instability (DB contention, cache stampedes, retry amplification)

04

Timeouts feel random (queueing delay + dependency bottlenecks)

05

Costs climb faster than performance (nonlinear scaling inefficiency)

What you get

A defensible diagnosis + dashboards + a roadmap you can execute safely.

What you avoid

Random tuning, refactors without impact, and “maybe it’s the DB?” guesswork.

Request lifecycle

Edge → Application → Data → Dependencies → Response. Where time is actually spent, not where we hope it is.

Data & contention

Query shapes, connection pooling limits, lock contention, hot rows, N+1 chains, and wait amplification.

Tail latency

P50/P95/P99 distributions, outliers, and the user experience that averages hide.

Caching & amplification

Real hit rates under load, eviction behavior, stampedes, thundering herd, and dependency amplification.

Saturation & queues

Pools, queues, IO limits, retries, and bottlenecks that appear only at higher concurrency.

Cost/performance

Inefficiencies that scale your cloud bill instead of your throughput and tail latency.

Important

We don’t require new tooling to start. If tracing is limited, we begin with logs/metrics triage—then deliver the minimum instrumentation plan needed to confirm the constraint with confidence. Deeper observability setup is included in Deep Audit / Proof Pack.

Learn how the audit process works step-by-step →

Deliverable

Dashboards & alerts

A standardized dashboard pack (and alert baseline in higher tiers) so tail latency, saturation, and regressions are visible—not guessed.

Deliverable

Constraint map

A one-page map of the system’s constraint chain: where time is spent, what saturates first, and what breaks at 2x–5x traffic.

Deliverable

Reports that match the stage

Sprint gets a Decision Brief + Evidence Appendix. Deep/Proof get an Engineering Dossier (architecture-grade) plus an executive summary.

Tooling note

We’ll align to your stack (Datadog / Grafana / New Relic / Elastic / CloudWatch / OpenTelemetry). If you have no tracing today, we won’t "force a platform migration" in a Sprint—Deep Audit/Proof Pack include bounded tracing enablement for the critical flow where feasible.

Understand the difference between monitoring and audits →

Capability	Audit Sprint	Deep Audit	Proof Pack
Price (typical)	$4,800	$9,000	$25,000
Primary constraint identification + impact quantification	●	●	●
Professional dashboards pack (tail latency + saturation)	●	●	●
Alert baseline (noise-controlled)	—	●	●
Tracing enablement for the critical flow (bounded)	⚠︎ Limited	●	●
Full constraint chain (end-to-end, multi-service)	⚠︎ Limited	●	●
Database deep dive (query plans, contention, pool model)	⚠︎ Limited	●	●
Cache/queue failure modes (stampede, backpressure, retries)	—	●	●
Capacity & bottleneck model (headroom + growth scenarios)	—	●	●
Rollout/validation playbook (canary, rollback triggers, guardrails)	⚠︎ Limited	●	●
Micro-PoC(s) with before/after evidence	—	—	● Comprehensive
Regression tripwire (tail latency drift detection)	—	—	●
Workshop + follow-up support window	●	●	●

Pricing shown is for the audit engagement only (one-time). Implementation work, if desired, is scoped separately after findings (except bounded micro-PoCs and guardrails included in the Proof Pack).

Process & Timeline

Step 1: Intake & Alignment

Confirm scope, define the critical flow(s), and establish access to telemetry. You’ll know what we’ll measure (P95/P99, saturation, throughput) and which artifacts you’ll receive.

Step 2: Production Analysis + Tracking Upgrades

Map the request lifecycle, isolate constraints, validate with evidence, and ship dashboards (and alerts / tracing enablement by package) so bottlenecks and regressions are observable.

Step 3: Readout, Handoff, and Validation

Walk through findings and the roadmap. Execute internally—or engage us for implementation. Deep/Proof includes structured handoff, follow-up, and validation guardrails.