Space and Segment Health Went Unchecked
Tablespace utilisation, invalid objects, and redo log status were never reviewed on a schedule — problems were discovered only after they had already begun affecting scheduling transactions.
Case Study · Oracle Production Support
Catching a Capacity Crisis Before It Became an Outage
A manufacturing operation's Oracle database supporting plant scheduling and inventory was heading toward a production-halting capacity failure. OptiSol's AWR/ASH-based proactive monitoring surfaced the warning signs weeks in advance — and capacity planning prevented the outage entirely.
Unplanned outages since rollout
~3 Weeks
Advance warning before threshold breach
~60 Days
To fully stand up monitoring baseline
The Challenge
Growing Blind Spots in a Database Nobody Was Watching Proactively
Plant scheduling and inventory ran on an Oracle database with no dedicated monitoring — only reactive support after something broke. Tablespace growth, redo log pressure, and segment health were never reviewed until they caused a visible slowdown on the shop floor.
Support Began After the Slowdown Started
Without baseline monitoring or alerting thresholds tied to production shift patterns, the team only engaged support once plant operators were already reporting delays.
Growth Trends Were Never Forecast
Storage and compute provisioning followed no trend analysis — the database was heading toward a hard capacity ceiling with no forecast in place to catch it before impact.
The Approach
Building Visibility Before Building Anything Else
OptiSol treated the first weeks of the engagement as an observability project — establishing what "normal" looked like against real production-shift patterns before setting any alerting thresholds.
AWR/ASH Dashboard Build-Out
Stood up custom AWR and ASH-based dashboards tracking tablespace growth, wait events, and session activity aligned to the plant's shift schedule and batch scheduling windows.
Scheduled Proactive Health Checks
Introduced recurring reviews of tablespace headroom, invalid objects, and redo log status — replacing "wait for it to break" with a defined weekly review cadence.
Capacity Trend Analysis & Forecasting
Modelled storage and compute growth trends against historical AWR data, projecting when key tablespaces would hit critical thresholds under current growth rates.
4 Early-Warning Alerting Thresholds Set
Configured alerting to fire on meaningful deviation from the established baseline — early enough for L2 to plan a change-managed fix, not scramble during a live incident.
Runbooks & Handoff
Documented the monitoring setup, thresholds, and response procedures, and handed them off — so the client's own team could interpret the dashboards going forward.
A Capacity Failure Caught ~3 Weeks Early
Trend-based forecasting flagged a tablespace on track to hit its critical threshold during a peak production run — giving time to provision ahead of impact instead of firefighting during it.
Zero Unplanned Outages Since Rollout
With health checks and capacity forecasting in place, the client has had no unplanned production-halting database outages since the monitoring baseline went live.
Alerts Tuned to Real Shift Patterns
Thresholds are set against the plant's actual batch and shift schedule, so alerts reflect genuine risk rather than generic default noise.
Visibility the Client's Own Team Now Owns
Documented runbooks and dashboard handoff mean the client's team can interpret warning signs independently, not just rely on OptiSol to notice them.
The Impact
From Reactive Firefighting to Forecasted Stability
- Custom AWR/ASH dashboards aligned to actual plant shift and batch scheduling patterns
- Weekly proactive health checks replaced a purely reactive support posture
- A capacity threshold breach identified roughly three weeks ahead of impact
- Zero unplanned database outages recorded since the monitoring baseline went live
- Capacity trend forecasting now informs storage and compute provisioning decisions
- Monitoring setup and runbooks fully documented and handed off to the client's team
"We used to find out about problems when the plant floor called. Now we see the trend line weeks before it would ever have become their problem." — OptiSol Oracle Engineering Lead
