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Series Week 7/52 - Optimizing Bussiness Performance with a Managed Model for Performance

{ Abhilash Kumar Bhattaram : Follow on LinkedIn }

This article is a natural extension to my earlier blog "Business - Aware DBA Monitoring"

Bussiness and Technology needs to go hand in hand at all times , one should understand each other.

The biggest barrier to predictable performance isn’t technology — it’s disconnect. When technical discussions and business planning happen in separate rooms, infrastructure bears the cost.
Predictability begins when database teams understand the rhythm of business, not just the thresholds of systems.

1. Ground Zero: Where Challenges Start

When Bussiness and Technology do not go hand in hand the Infra problems starts

┌──────────────────────────────────────────────────────────────────────────────┐
│ 1. Ground Zero: The Firefighting Mode                                        │
│------------------------------------------------------------------------------│
│ • DBAs on shift have no context of upcoming business workloads —             │
│   they react to spikes they never saw coming.                                │
│ • Business-critical SQLs (month-end, quarter-end, or compliance reports)     │
│   behave differently under changing data volumes and execution plans.        │
│ • Certain workloads cannot be tested in non-prod due to data scale,          │
│   sensitivity, or timing — leaving production history as the only guide.     │
│ • Plan changes or gathering statistics just before peak periods              │
│   often trigger unexpected regressions.                                      │
│ • No unified timeline correlating system load with business events.          │
│ • Reactive fixes dominate — session limits raised, parameters tweaked,       │
│   CPUs scaled up — without real understanding of cause or trend.             │
│                                                                              │
│    Solution: Integrate DBA operations with business calendars and load plans.│
│   Use historic workload data to forecast upcoming peaks and simulate impact  │
│   before they hit production.                                                │
└──────────────────────────────────────────────────────────────────────────────┘

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2. Underneath Ground Zero: Finding the Real Problem

Understand Bussiness and Technologgy , there must a serious guy who can bring these teams together.

┌──────────────────────────────────────────────────────────────────────────────┐
│ 2. Beneath Ground Zero: The Invisible Complexity                             │
│------------------------------------------------------------------------------│
│ • Infra and App teams operate in silos — database load doesn’t reflect       │
│   application campaign schedules or market pushes.                           │
│ • Business events like festive sales, policy renewals, or quarter-end runs   │
│   drive unpredictable spikes that no AWR trend reveals.                      │
│ • Lack of communication between business and support teams leads to          │
│   misaligned resource scaling.                                               │
│ • No pre-validated baselines for “expected load” at these known events.      │
│ • DBAs often learn about promotions or regulatory deadlines from incidents,  │
│   not from planning meetings.                                                │
│ • Global support teams fail to understand local workload rhythms —           │
│   impacting response accuracy and prioritization.                            │
│                                                                              │
│   Solution: Connect business event data (sales, launches, renewals) with     │
│   technical monitoring. Use OCI metrics, AWR baselines, and plan history to  │
│   anticipate spikes.                                                         │
└──────────────────────────────────────────────────────────────────────────────┘
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3. Working Upwards: From Understanding to Solution

When Bussinees and Infra understand each other , the company is in cruise control mode.

┌──────────────────────────────────────────────────────────────────────────────┐
│ 3. Working Upwards: From Reactive to Predictive                              │
│------------------------------------------------------------------------------│
│ • Build “business-aware” monitoring — databases that understand when and     │
│   why the load will rise, not just when CPU hits 95%.                        │
│ • Maintain workload histories for every business cycle to identify trends.   │
│ • Managed automation (TAB + OCI Observability) helps DBAs predict when       │
│   scaling or plan adjustments are required.                                  │
│ • Shift DBAs become proactive operators — armed with forecasts, not alarms.  │
│ • Performance management moves from firefighting to rhythm alignment —       │
│   database behavior tuned to business intent.                                │
│ • Technical discussions with business teams must go hand-in-hand with IT     │
│   goals — else infrastructure teams carry the consequences.                  │
│                                                                              │
│    Solution: Operationalize foresight — synchronize managed models with      │
│   business calendars so systems scale *with* the enterprise rhythm.          │
└──────────────────────────────────────────────────────────────────────────────┘
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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

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