The insidious slowdowns in Oracle… and how to see them coming

Jean-Michel Alluguette – OP&S
Dec 17, 2025
4 min read

The most costly Oracle slowdowns don't start with a failure.

They are gradually being established:

a slightly slower request each week.
a batch that slips from 45 minutes to 1 hour 10 minutes,
an I/O latency that drifts,
a load that increases without a “red” alert.

And that's precisely what makes them dangerous: on a daily basis, it's acceptable.

Then one day, the batch window explodes, users complain, and the analysis becomes urgent.

The good news: to detect these deviations, you do not need to organize a benchmark over several weeks .

If you collect Oracle metrics correctly and continuously, the baseline already exists — and deviations become immediately visible.

That's exactly the point of OP&S: to collect data on time, store it over time, and make deviations visible.

Why progressive slowdowns escape the teams

1) Traditional thresholds trigger too late

The “CPU > 90%” or “disk < 10%” alerts detect the emergency, not the drift.

But a drift often starts with +5%, +10%, +15%... which doesn't trigger anything.

2) Real-time data masks trends

When you look at a real-time Oracle database, you mainly see:

peaks,
hollows,
noise.

This insidious trend is particularly noticeable when comparing:

“Tuesday 10am” with “Tuesday 10am”,
“Night batch” of the last 10 executions,
“Monthly closing” month after month.

3) “Nothing has changed” is often false

Even though the application hasn't changed, the system itself is drifting:

volumetry,
statistics,
competition,
storage,
progressive saturation
patches,
new flows…

Without usable historical data, you cannot prove what is happening.

The most frequent causes of slow drift on Oracle

Insidious delays rarely have a single cause. The most common are:

Volumetric growth (tables, indexes, historical data)
Statistics and execution plans that are gradually changing
I/O drift (latency, saturation, storage performance lower than before)
Controversy/competition that increases with use (locks, restraints)
Parameters that no longer match (TEMP/UNDO, redo, SGA/PGA…)
Infrastructure/app changes without "before/after" measurements

The important point: these factors rarely produce an immediate incident.

They produce a slow degradation… until the breaking point.

The real difficulty: “seeing” the deviation without doing a benchmark

In a company, when you say "you need a tagline", many people hear:

“We need to launch a testing campaign, measure for 3 weeks, benchmark…”

In reality, this isn't necessary if you have a tool that:

collect regularly (for example, hourly),
preserves the history,
and allows for the comparison of similar periods.

In other words: the baseline is built automatically by continuous collection.

Request a free PoC (1 month)

What changes when hourly data is kept over years

With historical time data collection, you can immediately answer piloting questions:

Is this batch slower today than it was 1 month ago? 3 months ago? 1 year ago?
Does I/O latency drift under comparable load?
Is one type of wait (I/O / Concurrency / Configuration) taking up more and more space?
Does the volume increase linearly or at an accelerated rate?
Does a base gradually "slide" towards the red zone?

This is precisely what allows us to identify insidious delays:

not a manual benchmark, but a comparison of historical data .

How OP&S makes these abuses visible (in concrete terms)

OP&S collects Oracle metrics hourly , maintains historical data over time, and allows visualization:

the trend in key metrics,
deviations from comparable periods,
the signature of slowdowns (CPU, I/O, concurrency, configuration),
and the deteriorating environments.

The goal is simple: to go from “it’s slowing down” to:

“This has been going on for X weeks”,
“This is particularly evident in certain time slots”,
“the cause resembles I/O / containment / configuration”,
“These are the environments that need to be addressed as a priority.”

The 6 indicators that most quickly reveal a drift (without drowning)

You don't need 50 KPIs. You need a few metrics that are stable over time:

Overall load / DB Time (and its evolution)
Distribution of waits (I/O / Concurrency / Configuration / Commit)
I/O latency (and its trend)
CPU consumption at comparable load
Volume (DATA / index / TEMP / UNDO) and growth
Key processing times (batches, ERP flows, critical processes)

These metrics, collected regularly and recorded historically, are sufficient to make a large part of the abuses visible.

Checklist: Detect a drift in a few minutes (with history)

Does the time for a key process increase over multiple executions?
Does the database show an increase in waits with comparable load?
Is a new type of wait becoming dominant (I/O, concurrency, configuration…)?
Does I/O latency drift over the weeks?
Is the volume increasing faster than expected?
Are TEMP/UNDO/redo close to their limits during peaks?
Are any regressions observed after an action (patch, migration, parameter)?
Do user complaints correspond to recurring patterns?
Is a database gradually shifting into the top category of "at-risk" databases?
Do you have an immediate comparison “this month vs last month” for the same time slots?

If several answers are “yes”, you are facing a drift, not an isolated incident.

Costly mistakes

Mistake #1: Managing everything at the threshold (and ignoring trends)

The thresholds detect the urgency.

Trends detect drift before an emergency .

Mistake #2: analyzing only after the crisis

When the crisis hits, you have no room for error.

While correcting a drift early is often simple (parameter, index, purge, storage, stats…).

Mistake #3: Not keeping the history long enough

Many systems lose context after a few days/weeks.

However, these abuses often extend over months.

Conclusion

Oracle's insidious slowdowns are difficult to detect when only looking at real-time data.

But with regular collection and a long history, they become visible :

You observe the drift,
You qualify it (I/O, concurrency, configuration…),
You prioritize the actions,
and you avoid the crisis.

This is precisely the advantage of OP&S: no need to set up a manual benchmark , the baseline already exists thanks to continuous collection and history.

Audit service to identify slowdowns before they become critical

To help you spot insidious slowdowns before they become critical, we offer a free one-month Oracle audit with a detailed report.

You will know exactly where to intervene to maintain optimal performance… before users complain.