AI-RDS-Ops · Persona Bee · RDS reliability

Database slowdowns and failures, root-caused before they reach a developer

NudgeBee's AI-RDS-Ops works beside DBAs, application developers, on-call engineers and FinOps across Amazon RDS and Aurora.

Every root cause arrives with the evidence attached
Blocking chains, deadlocks and plan regressions, explained
Read-only by default; production changes ask first

Scope a pilot See how it runs

Runs inside your VPC
Credentials stay in AWS Secrets Manager

Run · orders-db · SQL Server on RDS · prod

Alarm fired: blocked processes on orders-db

CloudWatch

A run, step by step Gate in prod

1Read sessions and the blocking chain from DMVsHead blocker SPID 87wait LCK_M_Xquery hashRuns
2Correlate Performance Insights load and RDS events, last 24hLoad by query and userdeploy at 01:52Runs
3Post the RCA to #orders-oncall, masked; open a ticket for the owning teamMessage linkticket IDRuns
4Propose killing session 87 transaction open 42 minSession detailapprover namedAsk me first
5Create the missing blocked-process alarm on three sibling instancesAlarm ARNsAsk me first

Shared RDS core, every engine

SQL Server
PostgreSQL
MySQL
MariaDB
Oracle

Pilot targets

Measured against your own baseline. For the leader, three numbers: escalations avoided, mean time to root cause, savings identified.

50%+of database incidents root-caused before they reach a dev team
Under 10 minmean time to root cause, from alert to RCA posted where the alert fired
Agree in pilotsavings found and actioned: monthly savings identified, and the share applied

Today

An RDS alarm fires at 02:10.

With AI-RDS-Ops, the escalation arrives with the evidence already gathered.

Today 02:10

The same triage, by hand

On-call sees CPU, not the blocking chain behind it
A DBA is paged to rerun last week’s DMV and pg_stat_activity queries
Then writes up the cause for a developer who can’t see production

Meanwhile, across the fleet

Three instances with no blocked-process alarm
Half the fleet still on gp2
An Enterprise Edition license running a Standard Edition workload

With AI-RDS-Ops

Each benefit comes from a named bee

The DBA gets the escalation with the blocking chain, plan and wait type already gathered Alarm Triage
Developers see which query is slow and why, without production access Conversationmasked parameters
Problems are found on the sweep, before the first user report SweepAnomalyPlan Regression
Every deadlock is explained, not just counted Deadlock
Licence and storage savings arrive as a gated change, not a spreadsheet RDS Cost

What it does

What it is made of

Nine bees and skills, each with its own trigger, from a CloudWatch alarm to an 08:00 digest.

On an event

RDS Alarm Triage
CloudWatch alarmRDS event
- Reads live sessions, waits, blocking chains and Performance Insights load
- Correlates recent RDS events and parameter group changes
- Posts a cited root cause
Deadlock
Deadlock eventschedule
- Captures every deadlock graph
- Explains the two queries and the lock order
- Keeps the history
Conversation
SlackTeamsGitHub Copilot via MCP
- “@NudgeBee why is orders-db slow?”
- Answers with live sessions, top waits and load by query, user and host
- Parameter values masked

Watching continuously

Blocking & Long-Query Sweep
Every 5 minutes
- Finds head blockers and long-running queries
- Finds idle-in-transaction sessions
- Before users notice
Plan Regression
Query Storepg_stat_statementsschedule
- Scores plan and latency changes per critical query
- Flags regressions with the before/after plan
Anomaly
Continuous
- Flags abnormal metric and query latency
- Against each instance’s own baseline

On a schedule

Alarm Coverage
Daily
- Finds instances missing core alarms
- Creates them from your standard set
RDS Cost
Weekly
- Idle and oversized instances, gp2 to gp3
- RI coverage gaps
- Edition-aware SQL Server right-sizing
Daily Digest
08:00
- Fleet health and open findings
- Per-query trends and savings found

Coverage by engine

Shared RDS core, every engine

Every engine gets the same RDS core, then its own reads, root causes and cost levers.

Shared RDS core

CloudWatch metrics and alarms
Performance Insights
Enhanced Monitoring
RDS events
Parameter group change tracking
Alarm gap-fill
Right-sizing
gp2 to gp3
RI coverage
Escalation routing to a named owner

SQL Server

On RDS, EC2 or on-premises

Reads

DMVs
Query Store
system_health Extended Events
SQL Agent history

Root-causes

Blocking chains
Deadlocks
Plan regressions
SQL Agent job failures
TempDB and log growth
Memory grants

Cost levers

Edition-aware right-sizing (Enterprise → Standard)
License-included vs BYOL
Instance class

Also runs without the RDS core

SQL Server on EC2
SQL Server on-premises

PostgreSQL

On RDS, plus Aurora PostgreSQL

Reads

pg_stat_statements
pg_stat_activity
pg_locks
pg_stat_user_tables

Root-causes

Lock waits
Idle-in-transaction
Vacuum and bloat
Autovacuum lag
Connection saturation
XID wraparound risk
Replication lag

Cost levers

Instance class
Storage type
Read replica sizing

Aurora PostgreSQL

Reads Aurora cluster metrics too
Aurora replica lag, buffer cache hit ratio, failover events
I/O-Optimized vs Standard, Serverless v2 capacity

MySQL

On RDS, plus Aurora MySQL

Reads

Slow query log
performance_schema
InnoDB status

Root-causes

InnoDB lock waits
Deadlocks
Replica lag
Connection exhaustion
Temp table spills

Cost levers

Instance class
Storage type

Aurora MySQL

Reads Aurora cluster metrics too
Aurora replica lag, failover events
I/O-Optimized vs Standard, Serverless v2 capacity

MariaDB

On RDS

Reads

Slow query log
performance_schema
InnoDB status

Root-causes

Lock waits
Deadlocks
Replica lag

Cost levers

Instance class
Storage type

Oracle

On RDS

Reads

V$ session views
V$ wait views
V$ SQL views

Root-causes

Blocking sessions
Top SQL by wait
Long-running transactions

Cost levers

Instance class
License model

Gates

Read-only by default. Production changes ask first.

Runs through the NudgeBee agent inside your VPC; credentials stay in AWS Secrets Manager.

Runs

Observe and Records steps

Reading DMVs and stats views
Posting findings
Opening tickets

Ask me first in prod

Four kinds of change

Alerting changes: creating missing alarms
Workload: killing a session
Config: forcing a plan, changing a parameter group
Capacity: resizing an instance, changing storage type

Off by default

One-way changes

Deleting an idle instance or snapshot

Every finding cites its evidenceSQL parameter values are masked in chat
When confidence is low, it says soAnd escalates to the named owner
Starts in Analyze onlyNever exceeds the RBAC of the engineer who owns it

ROI

The buyer’s KPI scorecard

Baselines are measured in the first two weeks, before the agent acts. Targets are agreed with you on day one.

How the score is weighted

Escalations25%
Speed25%
Early detection20%
Cost15%
Trust and adoption15%

Escalations

25%

Escalation avoidanceDB incidents root-caused before reaching a dev team (ticket routing)50%+
DBA hours returnedHours per month on routine DB triage, before vs afterAgree in pilot

Speed

25%

Mean time to root causeAlert to RCA posted (investigation timestamps)Under 10 min
Mean time to resolveDB ticket open to close (Jira, ServiceNow)30% lower

Cost

15%

Savings found and actionedMonthly savings identified, and the share appliedAgree in pilot

Early detection

20%

Proactive detectionIncidents flagged before the first user report60%+
Deadlock captureDeadlocks explained, out of all deadlocks recorded100%
Alarm coverageInstances with every core alarm in place100%

Trust and adoption

15%

RCA usefulnessRCAs engineers rate useful80%+
Alert precisionProactive alerts not dismissed as noise85%+
Developer self-serviceDB questions answered without granting production accessAgree in pilot

Green at or better than target
Amber within 20%
Red more than 20% off
Overall score is the weighted share of KPIs at Green

Extensibility

Your runbooks, your scripts, your stack.

Add your own bees and steps, tune them per instance, and build on what they find.

Add your DBA runbooks as bees

Index maintenance windows
Failover drills
Statistics refresh
Replica rebuilds

Attach your scripts as steps

Your sp_WhoIsActive wrapper
Your vacuum script
Your parameter group Terraform module

Tune it

Sweep interval and long-query threshold, per instance
Which instances are critical
Masking rules
Dial per environment
Which model route writes the RCA

Build on its output

A plan regression can open a PR against the query
A deadlock finding can trigger your post-incident workflow

Point it at your stack

Database signals

CloudWatch
Performance Insights
Datadog Database Monitoring

Tickets and paging

Jira
ServiceNow
PagerDuty

Chat and copilots

Slack
Teams
GitHub Copilot via the NudgeBee MCP server

AI-RDS-Ops FAQ

Frequently asked questions

For the DBA evaluating it and the security team signing it off.

Scope a pilot

What is AI-RDS-Ops?

AI-RDS-Ops is NudgeBee's Persona Bee for database reliability on Amazon RDS and Aurora. It root-causes database slowdowns and failures, such as blocking chains, deadlocks and plan regressions, before they reach a developer, with the evidence attached. It is read-only by default, runs inside your VPC, and production changes ask first.

Which database engines does AI-RDS-Ops cover?

SQL Server, PostgreSQL, Aurora PostgreSQL, MySQL, Aurora MySQL, MariaDB and Oracle on Amazon RDS. Every engine shares the RDS core: CloudWatch metrics and alarms, Performance Insights, Enhanced Monitoring, RDS events, parameter group change tracking, alarm gap-fill, right-sizing, gp2 to gp3, RI coverage and escalation routing to a named owner. The SQL Server edition also runs without the RDS core, for SQL Server on EC2 or on-premises.

Can AI-RDS-Ops change anything in production?

It is read-only by default. Observe and Records steps run: reading DMVs and stats views, posting findings, opening tickets. Alerting changes, Workload, Config and Capacity changes ask first in prod. One-way changes, such as deleting an idle instance or snapshot, are off by default. It starts in Analyze only and never exceeds the RBAC of the engineer who owns it.

Where does AI-RDS-Ops run, and where do the database credentials live?

It runs through the NudgeBee agent inside your VPC. Credentials stay in AWS Secrets Manager.

Can developers use AI-RDS-Ops without production access?

Yes. Ask “@NudgeBee why is orders-db slow?” in Slack, Teams or GitHub Copilot via the NudgeBee MCP server. It answers with live sessions, top waits and load by query, user and host, with SQL parameter values masked.

What happens when AI-RDS-Ops is not sure of a root cause?

Every finding cites its evidence. When confidence is low, it says so and escalates to the named owner.

What does an AI-RDS-Ops pilot involve?

Ten production RDS instances on one engine plus their non-prod twins, with the Alarm Triage, Sweep, Deadlock and RDS Cost bees. Weeks 1–2: baselines measured, read-only. Week 3: RCAs posted to the channel and alarm gaps filled in non-prod. Week 4: a scorecard against the agreed targets. From you: read access via Secrets Manager, one channel, one DBA owner and 30 minutes a week.

How much does AI-RDS-Ops cost?

AI-RDS-Ops is included in every NudgeBee edition, alongside the other Persona Bees. The Community edition is free, and you run it yourself. Enterprise Support starts at $500 a month, billed annually and priced by environments and clusters, and Enterprise Platinum is priced on environments, clusters and accounts. Most teams start with a scoped pilot; full details are on the pricing page.

Database slowdowns and failures, root-caused before they reach a developer

Pilot targets

An RDS alarm fires at 02:10.

What it is made of

Shared RDS core, every engine

Read-only by default. Production changes ask first.

The buyer’s KPI scorecard

Your runbooks, your scripts, your stack.

Frequently asked questions

One platform, five Persona Bees

Scope a pilot on ten production RDS instances.