{ Abhilash Kumar Bhattaram : Follow on LinkedIn }
Monitoring is only as good as its context.
While traditional systems track CPU, I/O, and wait events, few DBAs (for that matter any support engineer) map these to actual business activities — like Diwali flash sales, quarterly closing, or year-end reconciliations. The result? Perfectly tuned systems that fail under predictable business load.
I have seen the following situations
DB Support for Thanksgivig sale for systems in North America , however most people support in Asian support teams are not aware how how much regional load to expect to scale the systems.
Diwali sale for a retail enterprise , there are only 2 DBA's available and both are granted Diwali leave without anyone understanding that systems monitoring are needed. There needs to be understanding that IT support is needed for Diwali.
Every month end there will be performance problems , very few DBA's dig into the systems to address the business part of the load.
Monitoring is only as good as its context. Business-aware monitoring bridges this gap — making database operations anticipate business, not just react.
Global support models add another layer of complexity — teams spread across regions may not understand local workload rhythms. A quiet Tuesday in London could mean a high-traffic festival sale in Mumbai. Without awareness of when and why systems peak, even the best monitoring setups miss the real business pulse.
1. Ground Zero: Where Challenges Start
Understand the business rythym
+--------------------------------------------------------------------------------------+
| 1. Ground Zero: Where Challenges Start |
|--------------------------------------------------------------------------------------|
| - Monitoring focuses purely on infrastructure metrics (CPU, I/O, Memory). |
| - Alerts flood during business peaks with no correlation to user activity. |
| - Lack of understanding of “when” business spikes actually occur. |
| - Year-end or Diwali loads handled reactively through firefighting. |
| - No load correlation between business events and DB resource spikes. |
| - ASM, AWR, and OEM data collected — but not analyzed in business context. |
| - Global support teams unaware of local business patterns and workload surges. |
| - No proactive scaling or throttling before predictable surge events. |
| |
| >> When DBAs monitor systems without business rhythm, performance issues feel random.|
2. Underneath Ground Zero: Finding the Real Problem
Bussiness peaks and lows benchmark them - track them
+--------------------------------------------------------------------------------------+
| 2. Underneath Ground Zero: Finding the Real Problem |
|--------------------------------------------------------------------------------------|
| - Monitoring thresholds set uniformly — not per business cycle. |
| - No event tagging (e.g., “Month-End Close”, “Festive Sale”, “Payroll Run”). |
| - DB growth projections ignore seasonal data ingestion (e.g., billing cycles). |
| - Lack of collaboration between business teams and database ops. |
| - Infrastructure scaling planned for averages, not business peaks. |
| - No predictive analytics for trending transaction surge behavior. |
| - Global NOC and L2 teams work off fixed alerting windows, missing regional peaks. |
| - Monitoring tools don’t surface business-event context with alerts. |
| |
| >> The problem isn’t database load — it’s lack of awareness about *why* it happens. |
+--------------------------------------------------------------------------------------+
3. Working Upwards: From Understanding to Solution
Business benchmarks and technical benchmarks need to go together
+--------------------------------------------------------------------------------------+
| 3. Working Upwards: From Understanding to Solution |
|--------------------------------------------------------------------------------------|
| - Establish business–IT sync calendars (sales peaks, closures, cutovers). |
| - Map AWR and OS metrics against business timestamps. |
| - Leverage ASM to balance I/O hotspots proactively before surge windows. |
| - Enable storage auto-scaling or extend tablespaces for high-growth workloads. |
| - Build event-based monitoring dashboards (e.g., “Festival Load Watch”). |
| - Correlate SQL response time with transaction type and time-of-day. |
| - Train DBAs and global support teams on local business patterns and workload cycles.|
| - Include business context in post-incident RCA documentation. |
| - Schedule patching and maintenance around business calendars, not fixed quarters. |
| |
| >> True monitoring maturity is when your database sees the business coming. |
+--------------------------------------------------------------------------------------+
How Nabhaas helps you
At Nabhaas, we work closely with teams to uncover dependencies, knowledge gaps, and process inefficiencies to ensure the patching cycle is smooth and predictable.
TAB ( Total Automation Box ) is how we automate patching lifecycles. https://www.nabhaas.com/tab
There is no staright answer to the points mentioned above but all of them needs to be addressed as best fits the organization.
At Nabhaas we ensure we identify all the above before beginning a patch cycle. Feel free to download our whitepaper here
Top comments (0)