A deploy changes a database migration. Global metrics stay green, but one enterprise customer's queries slow 10x. Firetiger's release verification agent detects the per-tenant latency spike, correlates it with the deploy, and drafts a root-cause report before the customer complains.
Using Firetiger for DBA: Watch Customer Outcomes, Not Just Server Metrics.
Traditional database monitoring aggregates metrics across all tenants. Your P99 looks fine while your largest customer hits deadlocks nobody else sees. Firetiger's AI agents watch each customer's database experience individually.
What Is Firetiger for DBA?
AI agents that monitor every customer's database experience continuously.
Firetiger for DBA is an outcome-focused observability platform. You define objectives in plain language. AI agents translate them into continuous per-tenant database monitoring, investigation, and root-cause reporting.
Per-Customer Query Health
Agents baseline each tenant's query patterns and alert on deviations.
Automatic Root-Cause Reports
When a database issue emerges, agents investigate and draft actionable reports.
Release Regression Detection
Agents verify every deploy for per-customer database regressions.
High-Cardinality Data Lake
Store unsampled logs in Apache Iceberg for precise per-tenant analysis.
Why Traditional Database Monitoring Fails DBAs
Aggregate metrics hide the customers who are actually suffering.
DBAs spend 68% of their week in firefighter mode reacting to escalations. Legacy tools sample data and summarise across tenants, so a single customer's database failure stays invisible until executives get involved.
Challenge
Legacy Tools
Firetiger
Query visibility
Sampled aggregates
Every query, every tenant
Alert quality
Threshold noise
Investigated reports
Customer isolation
Global averages
Per-tenant baselines
Root-cause analysis
Manual correlation
Autonomous agents
Cost at scale
Explodes with cardinality
Iceberg data lake
How Firetiger Works for Database Administration
Define database objectives in plain language, agents handle the rest.
1. Connect Your Telemetry
Point database logs via OpenTelemetry, Vector, or CloudWatch to your Firetiger data lake.
2. Set Objectives
Write goals like 'Monitor query latency for our top 10 accounts' in plain English.
3. Agents Investigate
AI agents baseline each customer, detect anomalies, and produce root-cause reports.
4. Act on Insights
Receive actionable briefs with proposed fixes before customers notice problems.
DBA Use Cases
Real scenarios where agents protect database-dependent revenue.
How does Firetiger catch silent query regressions after a deploy?
How does Firetiger detect per-customer deadlocks that dashboards miss?
Your database reports 99.9% uptime. But one VIP tenant's complex workflow triggers lock contention invisible in averages. Firetiger's agent monitors per-tenant lock patterns and alerts your team with the exact query chain causing the issue.
Can Firetiger help DBAs protect revenue by catching billing logic errors?
A metering service silently undercounts billable events. The API returns 200 OK, but usage logs don't match billing records. Firetiger agents correlate infrastructure logs with business events and flag the discrepancy immediately.
Firetiger vs. Legacy Database Monitoring
Traditional tools watch servers, Firetiger watches customer outcomes.
68%
Average DBA week spent firefighting (SolarWinds)0.1%
Of failing requests that matter most to revenue>10%
Revenue leakage caught by Firetiger in case studyLegacy tools force DBAs to sample data and set static thresholds. Firetiger uses an Apache Iceberg data lake to store unsampled, high-cardinality data. AI agents do the investigation that used to cost your team hours at 3 AM.
Getting Started with Firetiger for DBA
From first connection to first catch in under 24 hours.
Connect in Minutes
Deploy via OpenTelemetry, Vector, or CloudWatch. Your data stays in your VPC.
First Insight in Hours
Agents scan telemetry, map services, and establish per-customer baselines automatically.
See Firetiger in Action for Your Database Stack
Start monitoring per-customer database health with AI agents today.
