Apouc 2014-enterprise-manager-12c

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• Principle Architect | Oracle Greater China

• Joined Oracle in 2004

• Now Focusing on Database, Security, EM

• Father of 2

• Interested in Photography, Traveling, Movie, Book

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Automate Your DB Lifecycle Mgmt to Respond to the On-demand Requirements of DBaaS using

Oracle Enterprise Manager 12c

APOUC Leaders’ Meeting 2014 @ Hong Kong Vincent P. Chan | Principal Architect, Oracle Greater China


Agenda

Oracle Confidential – Internal/Restricted/Highly Restricted 4

• New Architecture Leads to New Challenges!

• How Does EM12c Help?

• Case Study


IOUG Report Shows that Demands of DBaaS Increased…


Source: 2012-2013 IOUG Cloud Computing Survey


New Architecture Leads to New Challenges …


Virtual Machines

Share Servers

Dedicated Databases

Share Servers and OS

Schema/Pluggable DB

Share Servers, OS and Database


IOUG Report Shows that the Private Cloud Challenges are …


Source: 2012-2013 IOUG Cloud Computing Survey


And the Leading Database Administrative Challenges are …


Source: 2013 IOUG Survey on Database Manageability


So, How Do You Work?




EM12c helps new employees get familiar with our environment quickly with industry standardized interface, and helps us offload our workload to application team.

– Lead DBA, a Global Bank



How Does EM12c Help? Automate Your Database Lifecycle Management



Oracle EM12c

User Interaction:

WebCenter

Infrastructure as a Service

Oracle Database

Oracle Fusion Middleware

Platform as a Service

Integration: SOA Suite

Security: Identity Mgmt

Process Mgmt: BPM Suite

Oracle Apps 3rd Party Apps ISV Apps

Applications and Business Services

Oracle VM for x86

Operating Systems: Oracle Enterprise Linux Oracle Linux Oracle Solaris

Oracle VM for SPARC (LDom) Solaris Containers

Servers

Storage

Applications and Business Services

Platform as a Service

Database as a Service

Infrastructure as a Service

Meter & Charge

Optimize

Manage

Plan

Setup

Build

Test

Deploy

Monitor

User Interaction: Web Center


How Does EM12c Help?


• Create a Database in Minutes with Dramatically Reduced Storage

• Automate & Track Your Patch Process

• Find Out Regressed SQL from Millions of Statements to Ensure Database Performance

• Keep with Standard and Security Best Practices


Scenarios & Problems to Solve

• 12 TB database in production for an internal application

• The production DB is running on Exadata, while a standby database is running on ZFSSA

• Agile development is used for the internal app with 7 sprints running in parallel

• Each sprint requires a clone of the production DB

• Each sprint lasts for a month, and clones need to be refreshed monthly as well

Case 1: Telecom Industry

Storage requirements

using traditional cloning

Prod DB = 12 TB

Standby DB = 12 TB

7 Clones (7 * 12 TB)

= 84 TB

------------------

Total 108 TB

Time = days/weeks



• 5 production databases total 30 TB of storage

• All 5 production DBs have a standby

• Clones of the production database are required for data analysis and reporting

• 6 total clones across different teams every quarter

• For security reasons, sensitive data has to be masked prior to cloning

Case 1: Banking Industry

Storage requirements

using traditional cloning

5 Prod DB = 30 TB

5 Standby DB = 30 TB

5 Masked DB = 30 TB

6 Clones (6 * 30 TB)

= 180 TB

------------------

Total 270 TB

Time = days/weeks


Database-Aware Snap Clone

• Leverage storage level snap clone feature

• Out-of-box self service portal

• Resource quota based on role

• Integrated monitoring, snapshot/rollback, etc


Continuous Replication using:

Golden Gate or Dataguard

Standby Database [on ZFS Storage Appliance]

Production Database [Exadata or any commodity hardware]

Snap Clones using Standby

Private backups (snapshots) for SSA user

Scenario 1: SnapClone Using Standby

DR Database [Exadata or any commodity hardware]


Discrete Replication using: RMAN

backups, Netapp SnapMirror, etc

Test Master Production Database [Exadata or any commodity hardware]

Masking and Subsetting using EM

Snap Clones using Test Master

Private backups (snapshots) for SSA user

Benefit: Massage data before cloning

Scenario 2: SnapClone Using Test Master

DR Database [Exadata or any commodity hardware]


Customer Scenarios with Snap Clone

Customer Scenario 1 [Telecom Industry]

Prod DB = 12 TB

Standby DB = 12 TB

7 Clones (7 * 2 GB of writable space)

= 84TB 14 GB

-------------------

Total 108 ~24 TB

Time = days/weeks minutes

Customer Scenario 2 [Banking Industry]

5 Prod DB = 30 TB

5 Standby DB = 30 TB

5 Masked DB = 30 TB

6 Clones (6 * 5 * 2 GB of writable space) = 180TB 60 GB

---------------------

Total 270 ~90 TB

Time = days/weeks minutes



Difficult to Identify Suitable Patches

Time Consuming For Patching

No Automation Not Predictable

Oracle 10gR2 on Solaris

Oracle 11gR2 on Linux Oracle 11gR2 with RAC on Linux

Exadata


Automating DB Infrastructure Patching Fully Integrated with My Oracle Support

• Proactive advisories, recommendations, and analysis

– One-off patches, patch set updates, and critical patch updates

• Zero downtime for patching

• Integrated patch management & deployment automation

• Patch intelligence and community

• Streamlined conflicts and merge patch process

• Cell patching done through “patchmgr”

Analyze

Test

Patch

Report Provision

Stage


With KM, Bugs Fixed, Trends of Downloads

1) Proactively Recommend Patches


With Multiple Patches to Multiple Targets

2) Mass Deploy to Avoid Time Constraints


By Out of Place Patching

3) Allow Switchback & Reduce Downtime


With Comprehensive Pre-flight Checks

4) Automatically Detect Patch Conflicts


5) Automatically Rollout & Track Patch


• Concern on performance degrading (i.e. SQL regression) after database changes, i.e.

– DB upgrades

– Database structure changes

– Optimizer statistics refresh

– Patching

• Problems

– Partial workload

– Large workloads (100Ks SQL statements are common)

– Non-production optimizer context

– Manual and time consuming regression testing

– SQL performance regression after production



• Test and predict impact of system changes on SQL query performance

• Analyze performance changes for improvements or regression

• Comprehensive performance analysis and reporting

• Re-execute SQL queries in test environment

• End-to-end solution: STS, SQL Plan Baselines, & SQL Tuning Advisor

RAT: SQL Performance Analyzer (SPA)

SQL Workload

STS

SQL Plans + Stats Pre-Change Trial

SQL Plans + Stats Post-Change Trial

Compare SQL Performance

Analysis Report


Regressed SQL Statements

SPA Report


Consolidation Testing using Real SQL Workload

Consolidated SQL Performance Analyzer

• Validates SQL performance

for consolidated database

• SQL workload captured for

each database in STS

• SPA executes all workloads

together in consolidated

environment

• Identifies SQL regressions

and helps remediate them

• Existing SPA capability in DB

11.1 works for schema

consolidation

• Support for Pluggable DB

consolidation in DB12c

SALES

HR

ERP

CRM

ERP STS

SALES STS

CRM STS

HR STS

SALES

HR

ERP

CRM



Time Consuming Totally Reactive Not Scalable No Detail


1) Identify and Track Assets


You can show inventory summary by type.


And roll up by location, platform, lifecycle, version, vendor, LoB, department, or cost center.


Showing host and roll up by platform.


Showing host and roll up by version.


Showing databases and roll up by version.


With Pre-Configured Templates, Ignore Differences and Notification

2) Track and Remediate Drifts from Standards

You can select/exclude these pre-configured

template from comparison:

Instance Tablesapces Control files Redologs Rollback Segments Users Database Options

Feature Usage

You can ignore the differences. You can set notification on

differences


2) Track and Remediate Drifts from Standards with Notification

Database dbm1’s listener port is 1521, while dbm2’s listener

port is 1522


With Out-of-the-Box, 400+ Security Practices

3) Adhere to Security Best Practices


With Periodically Scoring


# of Target Evolutions

# of Violations

Avg Score (%)

Compliance Standards (i.e. Best Practices)


With Real Time Dashboard



With Scoring History and Violation History


Avg. Compliance Score (%)

Avg. Violation Count Per Evaluation


Case Study Automate Your Database Lifecycle Management



Oracle Exadata and Oracle Enterprise Manager 12c:

Extreme Consolidation in Cloud

Presented in OOW

About HDFC Bank • Incorporated in

Auguest 1994 • India’s Second

Largest Private Bank with • 3,119

Branches • 11,088 ATMs

& 20 Million Customers

• Employees: 60,000

• Annual Revenue: USD 7 Billion


The Challenges • Average 3 days to provision UAT database for lending segment

• Silo’ed IT environment with average 30% utilization

• Compliance requirement consume testing resources

• SI expenses for provisioning databases manually

• Overhead in managing configuration drift between production and testing environment

• Rollout impact/delay on new business initiatives

• Challenges in managing exponential growth of data

• Database sprawl over 168 racks of real estate


The Solution: DBaaS


The Result

Plus: • Effective usage of

infrastructure leading to better ROI

• Empowered application team with self service

• Drastically cut down on support/SI costs for DBA activities

• 10x compression achieved to low CapEx requirements


1000 % faster Databases

deployment on its enterprise cloud

“Spinning up a database, a process that used to take two to three weeks, now takes us only 19 minutes, something like a 1,000% improvement in deployment time. Accelerating deployment to this degree has brought us much closer to the customer service levels

our business goals demand.”

Surren Partabh - CTO, BT Operate

BT_EM_11569193_960x540.wmv


PATCH MANAGEMENT $70 Billion revenue in 2011

75,000 employees

96 million retail customers

FOCUS ON Automation

Challenge:

• Patch and upgrade large number of databases with minimal maintenance time

• Regulations require quarterly patching for compliance management & reporting

• Mandatory to apply PSU to over 520 databases 2 time a year

• Inventory tracking and deploying changes to non-production databases was difficult

• During patching periods, DBAs worked extra hours on nights & weekends

After Oracle Enterprise Manager:

• Patching process is now automated

• 4 times reduction in man hours for patching resulting in approx 67% savings in productivity

• Application team can track changes across non-production and production environments resulting in no impact to development work providing more time for coding & testing

• DBA team now focused on database availability, scalability & performance

• IT runs like a business and adds value

Case Study


Summary



EM12c Helps You to Address These Challenges




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Safe Harbor Statement

The preceding is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.


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