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Series Week 8/52 — Database consolidation : Key to managing rising applications to curtail OCI cloud costs

{ Abhilash Kumar Bhattaram : Follow on LinkedIn }

In my earlier blogs I have explained about automation on how handling multiple parallel patching improves operational efficiency.

More databases , more the operational overhead , so consolidation is the key

But seldom do oraganizations reliaze that you are slow piling up databases which backups , DR's and the entire lifecycle systems will have operational overhead. In other words consolidation is the key.


   BEFORE CONSOLIDATION (20 Individual DB Systems)
   ------------------------------------------------
       • 20 Separate DB Servers
       • 20 Database Patches Every Cycle
       • 20 GI Patches Every Cycle
       • 20 Backup Schedules
       • 20 DR Replications
       • 20 Monitoring Configurations
       • Higher Cloud OCPU + Storage Cost [Fixed]
       • Fragmented Performance & Capacity

                   ▼  CONSOLIDATE  ▼

   AFTER CONSOLIDATION (1 ExaCS + 10 Databases)
   ---------------------------------------------
       • 1 ExaCS Platform Hosting All Workloads
       • 10 Database Patches (≈50% Reduction)
       • 1 GI Patch for Entire Platform
       • Unified Backup & DR Strategy , though 20 DB's are still have individual DR setup
       • Centralized Monitoring - Using Ops Insights 
       • Better Capacity Utilization - ExaCS Dynamic Scaling for reduced CPU resources 
       • Optimized OCPU/Storage = Lower Costs
       • Streamlined Performance Management


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1. Ground Zero: Where Challenges Start

Understand which applications and database are running , a DBA cant just be a systems guy - he should help the bussiness operations

+--------------------------------------------------------------------------------------+
| 1. Ground Zero: Where Challenges Start                                               |
|--------------------------------------------------------------------------------------|
| - Every new application demands its own database — duplication becomes the default.  |
| - Cloud provisioning is too easy → systems are created without clear ownership.      |
| - Backups multiply per environment: Prod, Dev, QA, DR — unchecked.                   |
| - No visibility into which systems are active vs abandoned.                          |
| - Many databases are oversized and underutilized.                                    |
| - Cloud invoices increase month after month — but nobody knows which DB drives cost. |
|                                                                                      |
+--------------------------------------------------------------------------------------+

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2. Underneath Ground Zero: Finding the Real Problem

Understand and question why operations are increasing with number of databases.

+--------------------------------------------------------------------------------------+
| 2. Underneath Ground Zero: Finding the Real Problem                                  |
|--------------------------------------------------------------------------------------|
| - No governance model for lifecycle: creation, consolidation, retirement.            |
| - Application managers request isolation instead of sharing resources.               |
| - DR environments are costly but often underused or misclassified.                   |
| - Retention policies are not standardized — stale data lives forever.                |
| - No right-sizing: sizes set once, never revisited.                                  |
| - Cloud cost attribution is missing — infra teams can’t link DBs to business units.  |
| - The issue is not “too many DBs”—it’s invisible debt.                               |
| - 20 DB systems = 20 GI patches, 20 DB patches, 20 outages.                          |
| - Backup + DR multiplied 20 times (FRA, snapshots, RMAN).                            |
| - Idle capacity everywhere: some DBs 10% used, some choking.                         |
| - Fragmented performance insight—each DB is a silo.                                    |
| - Architecture grows by project decisions, not platform plan.                        |
| - Reliability cannot scale when the foundation is fragmented.                        |
+--------------------------------------------------------------------------------------+


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3. Working Upwards: From Understanding to Solution

Consolidate - Build and Manage with that in mind

+--------------------------------------------------------------------------------------+
| 3. Working Upwards: From Understanding to Solution                                   |
|--------------------------------------------------------------------------------------|
| - Build a live, automated catalog of your DB estate (size, owner, usage).             |
| - Tag and classify databases (active, inactive, critical, archive).                   |
| - Consolidate databases logically — reduce count without sacrificing isolation.      |
| - Right-size everything: CPU, memory, storage — based on real usage.                  |
| - Rationalize DR and backup systems — align to actual business risk.                  |
| - Implement policies for lifecycle management: retire or archive unused DBs.          |
| - Measure cost per DB and map it to business value — create accountability.           |
|                                                                                      |
+--------------------------------------------------------------------------------------+

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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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