Oracle Database 11g Release 2: Database Manageability Overview

Oracle Database 11g Release 2: Database Manageability Overview
An Oracle White Paper
September, 2011
Oracle Database 11g Release 2: Database
Manageability Overview
Oracle Enterprise Manager Cloud Control 12c
Oracle Database 11g Release 2: Database Manageability Overview
Executive Overview ........................................................................... 2
Introduction ....................................................................................... 2
Manageability Challenges.................................................................. 3
Performance Management ................................................................ 3
Performance Diagnostics............................................................... 3
Application Tuning ......................................................................... 8
Testing and Test Data Management................................................ 13
Throughput Testing using Database Replay ................................ 14
Response Time Testing using SQL Performance Analyzer ......... 16
Protecting Sensitive Data in Test Environments .......................... 18
Reducing Storage Costs with Data Subsetting ............................ 19
Database Lifecycle Management and Ongoing Administration ........ 19
Database Lifecycle Management................................................. 19
Resource Management ............................................................... 20
Exadata Management and Cloud Consolidation .............................. 26
Integrated System Monitoring ...................................................... 26
Manage Many as One ................................................................. 26
Consolidation Planning ................................................................ 27
Database as a Service................................................................. 27
Metering and Chargeback ........................................................... 28
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Oracle Database 11g Release 2: Database Manageability Overview
Executive Overview
Oracle Enterprise Manager is Oracle’s integrated enterprise IT management product line and
provides the industry’s first complete cloud lifecycle management solution. Oracle Enterprise
Manager’s Business-Driven IT Management capabilities allow you to quickly set up, manage
and support enterprise clouds and traditional Oracle IT environments from applications to disk.
Enterprise Manager allows customers to achieve:
Best service levels for traditional and cloud applications through management from a
business perspective including Oracle Fusion Applications
Maximum return on IT management investment through the best solutions for intelligent
management of the Oracle stack and engineered systems
Unmatched customer support experience through real-time integration of Oracle’s
knowledgebase with each customer environment
Oracle Database is the market-leader and preferred database for hundreds of thousands of
businesses as well as for application developers and database administrators worldwide. Over
the years, enterprises have come to rely on the Oracle database to provide unparalleled
performance and reliability. In Oracle Database 10g, Oracle delivered a self-managing
database with breakthrough manageability that dramatically increased IT productivity and
reduced management costs. Oracle is ready to raise the bar once again with the release of
Oracle Enterprise Manager Cloud Control 12 to manage Oracle Database. Designed for data
center environments that are rapidly evolving and changing to keep up with the demands of
the business, Oracle Database 11g and Oracle Enterprise Manager Cloud Control 12 allow
organizations to adopt new technologies quickly while minimizing risk. In addition, building on
its industry-leading self-managing capabilities, Oracle Database 11g has made significant
advances in the areas of manageability, testing and test data management and fault
diagnostics that address many of the top challenges facing businesses today.
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Oracle Database 11g Release 2: Database Manageability Overview
Manageability Challenges
The areas that continue to pose the biggest management challenges to database administrators include:
Performance diagnostics and tuning: How to maintain production databases at their peak
performance to maintain committed service levels.
Testing and test data management: How to reduce the risk of rolling out changes through testing and
managing test data in Oracle database environments at lower costs.
Database lifecycle management and ongoing administration: How to automate the day-to-day
repetitive tasks so that labor can be freed up to focus on more strategic requirements, such as
security, data center consolidation and high availability.
Cloud consolidation and Exadata management: How to consolidate databases onto a common
infrastructure to reduce data center costs and increase server efficiency.
To address these challenges, Oracle Database 11g has made significant advances in performance,
change assurance and self-management to make Oracle Database 11g easier to manage than ever
Performance Management
Performance management has traditionally been a major challenge for database administrators. With
the self-managing database, Oracle Database 11g, managing database performance is easier than ever.
Oracle Database 11g continues to expand its self-managing capabilities in all areas, including the two
main areas of database performance management: performance diagnostics and application tuning.
Performance Diagnostics
The steps to achieve good performance are to gather the right data, make a proper analysis and to then
derive an effective action plan.
The Oracle database self management framework performs these tasks for the DBA, making
performance diagnostics simple and routine. The Automatic Workload Repository gathers the
required data and the Automatic Database Diagnostics Monitor analyzes the data and makes targeted,
concrete and actionable recommendations. Let us look at them in more detail.
Automatic Workload Repository
The Automatic Workload Repository (AWR) is a built-in repository within every Oracle database that
contains operational statistics about that particular database and other such information. At regular
intervals, the Oracle database makes a snapshot of all its vital statistics and workload information and
stores them in AWR. By default, the snapshots are made every 60 minutes and are stored in the AWR
for an 8 day period after which they are automatically purged. The administrator can easily change
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these defaults. AWR is designed to be lightweight and manage itself completely in order to ensure that
it does not impose any additional management burden on administrators.
The data captured allows both system level and user level analysis to be performed, again reducing the
requirement to repeat the workload in order to diagnose problems. Optimizations have been
performed to ensure that the capture of data is performed efficiently to minimize overhead.
AWR forms the foundation for all self-management functionality of Oracle Database. It is the source
of information that gives the Oracle database an historical perspective on how it is being used and
enables it to make decisions, which are accurate and specifically tailored for the environment that
system is operating in.
Automatic Database Diagnostics Monitor (ADDM)
Building upon the data captured in AWR, Oracle Database includes a self-diagnostic engine called the
Automatic Database Diagnostic Monitor (ADDM). ADDM makes it possible for the Oracle database
to diagnose its own performance and determine how any identified problems could be resolved.
ADDM runs automatically after each AWR statistics capture and makes the performance diagnostic
data available immediately.
ADDM examines data captured in AWR and performs analysis to determine the major issues on the
system on a proactive basis, recommends solutions and quantifies expected benefits. ADDM takes a
holistic approach to the performance of the system, using time as a common currency between
components. The goal of ADDM is to identify those areas of the system that are consuming the most
‘DB time’. ADDM drills down to identify the root cause of problems rather than just the symptoms
and reports the impact that the problem is having on the system overall. If a recommendation is made
it reports the benefits that can be expected, again in terms of time.
The use of a metric such a db time throughout allows the impact of several problems or
recommendations to be compared. Previously many problems have been identified based on value
judgments and experience rather than quantifiable impacts. A good example of this is a system that is
experiencing a high logon rate. A rule of thumb might have said that a logon rate of greater than 10 per
seconds was a problem and should be fixed. However many systems can run significantly higher logon
rates without it noticeably affecting performance. Using the time distribution data in AWR, ADDM
can report quantitatively that logons are taking 20% of time spent in the database. This quantified value
can make it much easier to convince whoever needs to do the work to fix the problem or arrange for it
to be fixed, rather than just making a statement such as ‘I think that you are doing too many logons’.
ADDM starts its analysis by focusing on the activities that the database is spending most time on and
then drills down through a sophisticated problem classification tree. The problem classification tree
used by ADDM encapsulates decades of performance tuning experience in the Server Technologies
Performance Group at Oracle Corporation and other performance experts.
In developing the classification tree, the prime intent was to handle the most frequently seen problems
and to drill down to the root causes of problems rather than just reporting symptoms. Some of the
common problems detected by ADDM include:
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CPU bottlenecks
Poor connection management
Excessive parsing
Lock contention
I/O capacity
Under sizing of Oracle memory structures e.g. PGA, buffer cache, log buffer
High load SQL statements
High PL/SQL and Java time
High checkpoint load and cause e.g., small log files
RAC-specific issues
Besides reporting the potential performance issues, ADDM also documents the non-problem areas of
the system. The sub-components, such as I/O, memory, etc, that are not significantly impacting the
performance of the system are pruned from the classification tree at an early stage and are listed so that
the DBA can quickly see that there is little to be gained by performing actions in those areas. Again this
saves time and wasted effort (both human and hardware) fixing things that will not impact the system
performance overall.
Oracle Database 11g extends ADDM by greatly enhancing cluster-wide performance analysis for Real
Application Clusters (RAC) databases. For RAC environments ADDM analyses the RAC cluster and
reports on issues that are affecting the entire database as well as its individual instances. DBAs can now
use ADDM to perform database-wide analysis of global resources, such as high-load SQL, global cache
interconnect traffic, network latency issues, skew in instance response times, and I/O capacity.
Oracle Database was the first database product to introduce such a revolutionary self-diagnostic
capability and has completely redefined the database administration landscape. Administrators no
longer need to first collect huge volume of diagnostic data and spend endless hours analyzing them in
order to find out answers to performance issues. With the Oracle Database 11g, they can simply ask the
database what the performance issues are and ADDM does the rest. They can sit back, relax, and
follow the recommendation made by ADDM using just a few mouse clicks.
Real-Time ADDM for Diagnosing Unresponsive Databases
Oracle Enterprise Manager Cloud Control 12c introduces Real-Time ADDM, an innovative way to
analyze problems in extremely slow or hung databases, which would have traditionally required a
database restart. Real-Time ADDM can help resolve issues like deadlocks, hangs, shared pool
contentions and many other exception situations without resorting to a restart of the database.
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Figure 1: SQL Performance Analyzer report
Real-Time ADDM uses two different types of connection modes to connect to the target instance. The
normal JDBC connection is intended to perform extensive performance analysis when some
connectivity is available. The diagnostic mode which makes a latch-less connection is useful for
extreme hang situations when normal connection is not possible. The database administrator can then
use the diagnostic mode connection to execute analysis using Real-Time ADDM and get
recommendations on how to resolve the hang situation.
Compare Period ADDM for Comparative Performance Analysis
Compare Period ADDM is a new feature in Oracle Enterprise Manager Cloud Control 12c that allows
the administrator to answer the age-old question of why performance is slower today compared to
yesterday. The administrator can choose from either an AWR baseline or the older AWR snapshot
period or any calendar period of choice to determine why database performance during a particular
period is slower than another period. Compare Period ADDM checks both the base period and the
comparison period and lists out a set of findings pinpointing the root cause for the difference in
performance. Compare Period ADDM also indicates whether the two periods are comparable, i.e. have
similar SQL running in the same period, by the use of the SQL Commonality index for the two
AWR Baselines and Adaptive Thresholds
The usefulness and value of AWR continues to expand with every new release of Oracle Database.
AWR baselines allow DBAs to capture and save system performance data over time periods with
interesting or representative workloads.
In addition, baselines can also be used in setting alert thresholds on system performance metrics. Most
metrics can be viewed in Oracle Enterprise Manager against statistical aggregates of those same metrics
observed over the baseline period. This helps users set baseline-informed thresholds rather than
selecting thresholds without the context of actual data. In addition, adaptive thresholds are available for
certain key performance metrics. Adaptive thresholds are performance alert thresholds that are
automatically set and periodically adjusted by the system using the System Moving Window Baseline
data as the basis for threshold determination. For customers who want to get started with adaptive
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thresholds immediately, the new “Quick Configure” option can setup a starter kit of thresholds based
on common workload profiles using a few mouse clicks.
AWR baselines provide powerful capabilities for defining dynamic and future baselines and
considerably simplify the process of creating and managing performance data for comparison
Active Session History
Another key component of AWR is the Active Session History (ASH).
All active database sessions are automatically sampled once every second and stored in the Active
Session History. The ASH data shows where the database is currently spending its time and highlights
any performance bottlenecks.
Oracle Database 11g Release 2 extends ASH by gathering additional RAC information. The
information is used by advisors, such as ADDM for RAC. This information can be seen in new RACspecific sections to the ASH report. The ASH report now lists events that account for the highest
percentage of session activity in the cluster wait class along with the instance numbers of the affected
instance. This information gives further visibility into potential RAC-specific issues.
ASH has also been extended to run on even on standby databases to assist in analysis of the
performance of queries executed on Active Dataguard instances.
ASH Analytics
Oracle Enterprise Manager Cloud Control 12c includes ASH Analytics, a new tool to explore ASH data
that allows the administrator to rollup, drilldown, and slice or dice performance data across various
performance dimensions. Using ASH Analytics the database administrator can explore the different
performance attributes of a database session at any point in time.
With the ability to create filters on various dimensions, the DBA can not only identify performance
issues but also get a good understanding of various performance patterns and resource usage of the
system. The ASH Analytics view is also available as an active report that can be used for offline
analysis of any performance issues at a later point in time. The built-in treemap view allows
administrators to explore performance data using predefined performance dimension hierarchies.
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Figure 2: ASH Analytics
Application Tuning
Application design issues are the most predominant cause of performance problems. All the tuning
wisdom of developers, DBAs and system administrators cannot make up for the slowdown caused by
architectural and design deficiencies of the application. One important part of database system
performance tuning is, therefore, the tuning of SQL statements.
The query optimizer takes crucial decisions which have a tremendous impact on the performance of a
query, such as whether to use an index or not, which join techniques to use if the query involves
joining multiple tables, etc. Oracle Corporation has invested considerable development effort in
making the cost-based optimizer the industry's most sophisticated, mature, and thoroughly-tested
query optimizer. The cost-based optimizer is also used extensively by the major packaged applications
such as Oracle eBusiness Suite, SAP, PeopleSoft, etc. Since the Oracle database is the platform for the
vast majority of customers using these applications, this demonstrates the success of the Oracle
optimizer in a huge number of real application settings. Consequently, starting with Oracle Database
10g, the rule based optimizer (RBO) is no longer available and the cost-based optimizer is the only
supported optimizer mode.
While Oracle Database provides best possible query optimization technology, which maximizes the
application/query performance without any administrator intervention in the majority of cases, there
may still be a few cases where the nature of the application or uniqueness of data distribution may
cause certain SQL statements to consume an unusually high percentage of total system resources. In
such situations, the SQL tuning process normally involves three basic steps:
Identifying high load or top SQL statements that are responsible for a large share of the application
workload and system resources, by looking at the past SQL execution history available in the system
(e.g., the cursor cache statistics stored in the V$SQL dynamic view)
Verifying that the execution plans produced by the query optimizer for these statements perform
reasonably well
Taking possible corrective actions to generate better execution plans for poorly performing SQL
The three steps are repeated until the system performance reaches a satisfactory level or no more
statements can be tuned. Besides being extremely time consuming, the SQL tuning process outlined
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above also requires a high degree of expertise. Only a person with a deep knowledge of the application
and database system can undertake this task.
SQL Tuning and Access Advisors
Starting with Oracle Database 10g the SQL tuning process has been completely automated. ADDM
identifies SQL statements that are consuming unusually high system resources and are therefore
causing performance problems. In addition, the top SQL statements in terms of CPU and shared
memory consumption are automatically captured in AWR. Thus, the identification of high load SQL
statements happens automatically in the new tuning framework and requires no intervention from the
After the top resource consuming SQL statements have been identified, the Oracle database can
automatically analyze them and recommend solutions using newly added automatic tuning capability of
the query optimizer, called the automatic tuning optimizer. The automatic tuning optimizer is exposed
via an advisor called the SQL Tuning Advisor. The SQL Tuning Advisor takes one or more SQL
statements, and produces well-tuned plans along with tuning advice. The administrator does not need
to do anything other than just invoking the SQL Tuning Advisor so that it can recommend a solution.
It is important to bear in mind here that the solution is coming right from the optimizer and not from
any external tools using some pre-defined heuristics. This provides several advantages:
the tuning is done by the system component that is ultimately responsible for the execution plans
the tuning process is fully cost-based and naturally accounts for any changes and enhancements done
to the query optimizer
the tuning process takes into account the past execution statistics of a SQL statement and
customizes the optimizer settings for that statement
it collects auxiliary information in conjunction with the regular statistics based on what is considered
useful by the query optimizer.
The recommendation of the automatic tuning optimizer can fall into one of the following categories:
Statistics Analysis: The automatic tuning optimizer checks each query object for missing or stale
statistics, and makes recommendation to gather relevant statistics. It also collects auxiliary information
to supply missing statistics or correct stale statistics in case recommendations are not implemented.
SQL Profiling: The automatic tuning optimizer verifies its own estimates and collects auxiliary
information to remove estimation errors. It also collects auxiliary information in the form of
customized optimizer settings (e.g., first rows vs. all rows) based on past execution history of the SQL
statement. It builds a SQL profile using this auxiliary information and makes a recommendation to
create it. When a SQL profile is created it enables the query optimizer (under normal mode) to
generate a well-tuned plan. The most powerful aspect of SQL profiles is that they enable tuning of
queries without requiring any syntactical changes and thereby proving Oracle administrators with a
solution to tune the SQL statements embedded in packaged applications.
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Access Path Analysis: The automatic tuning optimizer explores whether a new index can be used to
significantly improve access to each table in the query, and when appropriate makes recommendations
to create such indexes.
SQL Structure Analysis: The automatic tuning optimizer tries to identify SQL statements that lend
themselves to bad plans, and makes relevant suggestions to restructure them. The suggested
restructurings can be syntactic as well as semantic changes to the SQL code.
Both access path and SQL structure analysis can be immensely useful in tuning the performance of an
application under development or a homegrown production application where the
administrators/developers have access to application code.
The SQL Access Advisor is yet another major component of Oracle Database manageability. It can
automatically analyze the schema design for a given workload and recommend indexes, materialized
views, and materialized view logs to create, retain or drop as appropriate for the workload. While
generating recommendations, the SQL Access Advisor considers the impact of adding new access
structures on data manipulation activities, such as insert, update and delete, in addition to the
performance improvement they are likely to provide for queries. The SQL Access Advisor provides a
very easy to use interface and requires very little system knowledge. It can also be run without affecting
production systems since the data can be gathered from the production system and taken to another
machine where the SQL Access Advisor can be run.
The SQL Access Advisor has been enhanced in Oracle Database 11g to provide partition advice as a
part of SQL access structure recommendations.
Automatic SQL Tuning
In Oracle Database 11g, the SQL tuning process was further enhanced and automated to keep
databases running at their peak performance. The SQL Tuning Advisor now runs automatically during
the system maintenance windows as a maintenance task. In each run, it automatically selects high-load
SQL queries in the system, and generates recommendations on how to tune them.
To validate the recommendation, SQL Tuning Advisor in Oracle Database performs a test-execute of
the SQL statements with the new execution plan for which a SQL profile is recommended. This
dramatically increases the accuracy and reliability of SQL profile recommendations.
The SQL Tuning Advisor can be configured to automatically implement SQL profile
recommendations. If you enable automatic implementation, the advisor will create SQL profiles for
only those SQL statements where the performance improvement would be at least three-fold. Other
types of recommendations, such as the ones to create new indexes or refresh optimizer statistics or the
ones that restructure SQL, can only be implemented manually. DML statements are not considered for
tuning by the automatic SQL Tuning Advisor. By default, the automatic SQL Tuning Advisor is
configured to run nightly and only report recommendations but not automatically implement them.
You can view a summary of the results of automatic SQL tuning over a specified period (such as the
previous seven days), as well as view a detailed report on recommendations made for all SQL
statements processed. The recommendations can then be selectively implemented through a manual
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process. You can also view the recommendations that were automatically implemented. The automatic
SQL Tuning Advisor can be configured to run in any maintenance window or can be disabled
altogether if desired.
Real Time SQL Monitoring
The Real Time SQL Monitoring feature of Oracle Database 11g enables monitoring of the
performance of SQL statements while they are executing. Live execution plans of long running SQL
are automatically displayed on the SQL Monitor page in Oracle Enterprise Manager using new, finegrained SQL statistics that are tracked out-of-the-box.
By default, SQL monitoring is automatically started when a SQL statement runs in parallel, or when it
has consumed at least 5 seconds of CPU or I/O time in a single execution. The DBA can observe the
SQL statement step through the execution plan, displaying statistics for each step as it executes. Row
source information at each step of the execution plan is tracked by means of key performance metrics,
including elapsed time, CPU time, number of reads and writes, I/O waits and other wait time. SQL
monitoring gives the DBA information on what steps long running SQL are executing and allows the
DBA to decide if additional tuning action needs to be taken.
Real Time SQL Monitoring has been enhanced in Oracle Database 11g Release 2 to support execution
plans that are being executed in part by the Oracle Database machine, Exadata.
Figure 3. Real Time SQL Monitoring execution plan
In addition to being able to monitor SQL statements in real time in Oracle Database 11g Release 2, the
DBA can also save all the execution details in an active report - an interactive report that can be used
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for offline analysis. It offers the same level of interactivity as the live screens, with drill-downs to
various levels of detail.
SQL Plan Management
SQL plan management prevents performance regressions resulting from sudden changes to the
execution plan of a SQL statement by providing components for capturing, selecting, and evolving
SQL executions plans. SQL performance can be affected by various changes, such as a new optimizer
version, changes to optimizer statistics and/or parameters, or creation of SQL profiles. SQL plan
management is a preventative mechanism that records and evaluates the execution plans of SQL
statements over time, and builds SQL plan baselines composed of a set of existing plans known to be
efficient. The SQL plan baselines are then used to preserve performance of the corresponding SQL
statements, regardless of changes occurring in the system.
Common usage scenarios where SQL plan management can improve or preserve SQL performance
A database upgrade that installs a new optimizer version may result in plan changes for a small
percentage of SQL statements, with most of the plan changes resulting in either improvement or no
performance changes. However, certain plan changes may cause performance regressions. The use
of SQL plan baselines significantly minimizes potential performance regressions resulting from a
database upgrade.
Ongoing system and data changes can impact plans for some SQL statements, potentially causing
performance regressions. The use of SQL plan baselines can also help to minimize performance
regressions and stabilize SQL performance.
Deployment of new application modules means introducing new SQL statements into the system.
The application software may use appropriate SQL execution plans developed under a standard test
configuration for the new SQL statements.
SQL plan baselines evolve over time to produce better performance. During the SQL plan baseline
evolution phase, Oracle Database 11g routinely evaluates the performance of new plans and integrates
plans with better performance into SQL plan baselines. A successful verification of a new plan consists
of comparing its performance to that of a plan selected from the SQL plan baseline and ensuring that
it delivers better performance.
Migration of Stored Outlines to SQL Plan Baselines
Before SQL plan baselines were introduced as part of SQL plan management, stored outlines served a
similar function. However, stored outlines lack the flexibility and adaptability of SQL plan
Stored outlines cannot automatically evolve over time. Consequently, a stored outline may be good
when it is created, but become a bad plan after a database change, leading to performance
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Hints in a stored outline can become invalid - for example, an index hint on a dropped index. In
such cases, the database still uses the outlines but excludes the invalid hints, producing a plan that is
often worse than the original plan or the current best-cost plan generated by the optimizer.
For a SQL statement, the optimizer can only choose the plan defined in the stored outline in the
currently specified category. The optimizer cannot choose from other stored outlines in different
categories or the current cost-based plan even if they improve performance.
Oracle Database 11g Release 2 provides the capability of migrating stored outlines to SQL plan
baselines. The benefits of migrating to SQL plan baselines include:
SQL plan baselines enable the optimizer to use the same good plan and allow this plan to evolve
over time. For a specified SQL statement, you can add new plans as SQL plan baselines after they
are verified not to cause performance regressions.
SQL plan baselines prevent plans from going bad because of invalid hints. If hints stored in a plan
baseline become invalid, the plan may not be reproducible by the optimizer. In this case, the
optimizer selects an alternative reproducible plan baseline or the current best-cost plan generated by
the optimizer.
For a specific SQL statement, the database can maintain multiple plan baselines. The optimizer can
choose from a set of good plans for a specific SQL statement instead of being restricted to a single
plan per category, as required by stored outlines.
By utilizing the migration path in Oracle Database 11g Release 2, old applications using stored outlines
can be transparently migrated and can instantaneously take advantage of the enhanced functionality of
SQL plan management.
Testing and Test Data Management
Oracle Enterprise Manager’s Application Quality Management (AQM) solutions provide high quality
testing for all tiers of the application stack. Thorough testing can help users identify application
quality and performance issues prior to deployment. Testing is one of the most challenging and time
consuming parts of successfully deploying an application, but it is also one of the most critical to the
project’s success. The testing and secure test data management capabilities in Oracle Enterprise
Manager provide a unique combination of test capabilities for Oracle databases which enable users to:
Test infrastructure changes: Real Application Testing is designed and optimized for testing database
tier infrastructure changes using real application production workloads to validate database
performance in your test environment.
Manage your test data and enable secure production-class testing: Oracle Data Masking and Oracle
Test Data Management solutions helps enterprises achieve security & compliance objectives by
obfuscating sensitive data from production in test databases and scale down production data into
right-sized databases so production data can be used securely in test and development environments.
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Throughput Testing using Database Replay
Database Replay provides DBAs and system administrators with the ability to faithfully, accurately and
realistically rerun actual production workloads, including online user and batch workloads, in test
environments. By capturing the full database workload from production systems, including all
concurrency, dependencies and timing, Database Replay enables you to realistically test system changes
by essentially recreating production workloads on the test system – something that a set of scripts can
never duplicate. With Database Replay, DBAs and system administrators can test
Database upgrades, patches, parameter, schema changes, etc.
Configuration changes such as conversion from a single instance to RAC, ASM, etc.
Storage pool, network, and interconnect changes
Operating system and hardware migrations, patches, upgrades, and parameter changes
Lower Test Infrastructure Cost
DBAs now have a test infrastructure at their disposal to test their changes without the overhead of
having to duplicate an entire application infrastructure. Database Replay does not require the set up
overhead of having to recreate a middle-tier or a web server tier. Thus, DBAs and system
administrators can rapidly test and upgrade data center infrastructure components with the utmost
confidence, knowing that the changes have truly been tested and validated using production scenarios.
Faster Deployment
Another major advantage of Database Replay is that it does not require the DBA to spend months
getting a functional knowledge of the application and developing test scripts. With a few point and
clicks, DBAs have a full production workload available at their fingertips to test and rollout any
change. This cuts down testing cycles from many months to days or weeks and brings significant cost
savings to businesses as a result.
Database Replay consists of four main steps:
Workload capture - When workload capture is enabled, all external client requests directed to
the Oracle database are tracked and stored in binary files, called capture files, on the file
system. The user specifies the location of the capture files and the workload capture start and
end time. During this process, all information pertaining to external database calls is written to
the capture files.
Workload processing - Once the workload has been captured, the information in the capture
files has to be processed. This processing transforms the captured data into replay files and
creates all necessary metadata needed for replaying the workload. The capture files would
typically be copied to another system for processing. This must be done once for every
captured workload before they can be replayed. After the captured workload is processed, it
can be replayed repeatedly on a replay system. As workload processing can be time consuming
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and resource intensive, it is generally recommended that this step be performed on the test
system where the workload will be replayed.
Workload replay - After the captured workload has been processed, it is now ready for replay.
A client program, called Replay Client, then processes the replay files and submits calls to the
database with the exact same timing and concurrency as in the capture system. Depending on
the captured workload, you may need one or more replay clients to properly replay the
workload. A calibration tool is provided to help determine the number of replay clients
needed for a workload. It should be noted that since the entire workload is replayed including
DML and SQL queries, it is important that the data in the replay system be identical to that in
the production system, whose workload was captured, to enable reliable analysis for reporting
Analysis and Reporting - Extensive reports are provided to enable detailed analysis of the
capture and replay. Any errors encountered during replay are reported. Any divergence in
rows returned by DML or queries is shown. Basic performance comparisons between capture
and replay are provided. For advanced analysis, Replay Compare Period and other AWR
reports are available to allow detailed comparison of various statistics between capture and
Both the workload capture and replay process support a filtering capability that is useful for targeting
workload of interest, such as by service, action, module to name a few. Oracle Enterprise Manager
significantly enhances the value of Real Application Testing by supporting end-to-end Database Replay
automation. This simplifies the process of saving and transferring the workload capture and
performance data to the test system, setting up the test system and replay clients correctly, and
orchestrating the entire replay through the Oracle Enterprise Manager interface.
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Figure 4: Database Replay Workflow
Response Time Testing using SQL Performance Analyzer
Changes that affect SQL execution plans can severely impact application performance and availability.
As a result, DBAs spend enormous amounts of time identifying and fixing SQL statements that have
regressed due to the system changes. SQL Performance Analyzer (SPA) can predict and prevent SQL
execution performance problems caused by environment changes.
SPA provides a granular view of the impact of environment changes on SQL execution plans and
statistics by running the SQL statements serially before and after the changes. SPA generates a report
outlining the net benefit on the workload due to the system change as well as the set of regressed SQL
statements. For regressed SQL statements, appropriate executions plan details along with
recommendations to tune them are provided.
SPA is well integrated with existing SQL Tuning Set (STS), SQL Tuning Advisor and SQL plan
management functionality. SPA completely automates and simplifies the manual and time-consuming
process of assessing the impact of change on extremely large SQL workloads (thousands of SQL
statements). DBAs can use SQL Tuning Advisor to fix the regressed SQL statements in test
environments and generate new plans. These plans are then seeded in SQL plan management baselines
and exported back into production. Thus, using SPA, businesses can validate with a high degree of
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confidence that a system change to a production environment in fact results in net positive
improvement at a significantly lower cost.
Examples of common system changes for which you can use SPA include:
Database upgrade, patches, initialization parameter changes
Configuration changes to the operating system, hardware, or database
Schema changes such as adding new indexes, partitioning or materialized views
Gathering optimizer statistics—
SQL tuning actions, for example, creating SQL profiles
Using SPA involves the following 5 main steps:
Capture the SQL workload that you want to analyze with SPA. The Oracle database offers
ways to capture SQL workload from several sources, such as cursor cache and Automatic
Workload Repository, into a SQL tuning set (STS). This would typically be done on a
production system and the STS would then be transported to the test system where SPA
analysis will take place.
Measure the performance of the workload before a change by executing SPA on the SQL
tuning set. Very short running queries are executed multiple times and their statistics are
averaged to eliminate variations due to buffer cache state and other noise factors
Make the change, such as database upgrade or optimizer statistics refresh.
Measure performance of the workload after the change by executing SPA on the SQL tuning
set again, as in step 2.
Compare performance of the two executions of the SQL tuning set to identify the SQL
statements that have regressed, improved, or were unchanged.
Figure 5: SQL Performance Analyzer Report
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This SPA comparison report shows significant performance improvement of overall SQL workload
after the proposed system change but with a few execution plan regressions. SQL Performance
Analyzer takes into account the number of executions of a SQL statement when measuring its impact.
A SQL statement that completes in seconds but is frequently executed may have a higher impact on
the system than a long running statement executed only once. SPA takes these factors into account
when predicting overall performance improvements and regressions. If any regressions are
encountered, SPA allows the user to fix them using SQL Tuning Advisor or with SQL plan baselines, a
new plan stability feature introduced in Oracle Database 11g.
SPA supports numerous other features that help assess system changes, these are briefly described
SPA helps estimate the I/O reduction that can be accomplished by migrating to an Exadata
server but without actually requiring you provision the hardware. This can be used to identify
potential workloads/systems that are good candidates for Exadata migration.
SPA supports comparing two STSs – this functionality is useful when you have mechanisms
such as load testing scripts or Oracle Application Testing Suite that can be used to test the
changes. By capturing the workload in to two different STSs (for before and after change
runs), one can use SPA to assess the impact of the system change.
With Oracle Enterprise Manager, a “one-click” STS transport mechanism can be used to
simplify the process of moving STS workloads between production and test databases.
Choosing the right solution helps DBAs absorb and manage change efficiently. Database Replay is
designed to test and improve system performance and SQL Performance Analyzer helps DBAs
improve SQL response time. Oracle 11g Real Application Testing makes it easy for database
administrators to manage and execute changes that are critical to the business and do it all at lower risk.
Protecting Sensitive Data in Test Environments
Administrators can leverage the provisioning capabilities in Oracle Enterprise Manager to roll out pretested standardized gold images of Oracle Database. This provides administrators with tremendous
labor savings instead of having to execute each step of the provisioning process manually. These gold
images can be used to provision test systems from backups or live production databases.
When enterprises copy production data into test environments for the purposes of application
development or testing, they risk falling out of compliance with regulations or incurring fines and
penalties that accompany violations of these data privacy laws. The data masking capabilities available
to administrators helps organizations comply with privacy and confidentiality laws by masking sensitive
or confidential data in development, test or staging environments. By using an irreversible process to
replace sensitive data with realistic-looking but scrubbed data based on masking rules, security
administrators can ensure that the original data cannot be retrieved, recovered or restored while
maintaining the integrity of the application.
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Reducing Storage Costs with Data Subsetting
With the growth in the number of database applications, enterprises are faced with the challenge of
provisioning non-production environments which are used for application development and testing.
They cannot afford to incur the storage expenses of provisioning the same production data in their
non-production databases; nor do they have the tools or the application knowledge to shrink
production data to a right-sized development environment. Oracle’s test data management
functionality helps enterprises shrink storage costs by creating reduced size copies of production data
for application development and testing while maintaining the referential integrity of the data set.
Through data discovery and application modeling, Oracle’s test data management functionality
automatically enforces complex business rules of enterprise applications resulting in accurate subsets of
production data.
Real Application Testing and Data Masking integration enables businesses to perform secure testing.
Typically testing is done in a non-production environment or by a different group or organization.
Sharing production data and/or the captured workload that contains sensitive information results in
breach of data privacy regulations and poses significant business risk. Real Application Testing and
Data Masking integration enables sharing of captured workload and data in the database in compliance
with data privacy regulations.
With Oracle Enterprise Manager Cloud Control 12c, the data masking functionality has been enhanced
to consistently mask sensitive not just in tables but also across all Real Application Testing artifacts
such as SQL tuning sets and Database Replay workload capture files. This allows you to perform
proper testing even after test data has been masked. With Real Application Testing and Data Masking
integration, businesses can now perform secure testing in a manner compliant with data privacy
Database Lifecycle Management and Ongoing Administration
Automating the day to day repetitive tasks that in the past have taken too much of an administrators
time is a key achievement of the self managing database, Oracle Database 11g. By relieving the
administrators of the tedious management tasks, such as provisioning or patching databases, managing
memory allocations and disk resources, they can be freed up to focus on more strategic requirements,
such as security and high availability.
Database Lifecycle Management
Database lifecycle management covers the entire lifecycle of databases, including:
Discovery and inventory tracking: the ability to discover your assets, and track them
Initial provisioning: the ability to rollout databases in minutes
Ongoing change management: end-to-end management of patches, upgrades, schema and data
Configuration management: track inventory, configuration drift and detailed configuration search
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Compliance management: reporting and management of industry and regulatory compliance
Database lifecycle management capabilities eliminate the need to manually track IT assets involving
databases. It provides non-intrusive out-of-box agentless capabilities to discover physical servers. Once
servers have been discovered, they are easily promoted to a managed state automatically discovering all
databases and other applications. This automated discovery simplifies the process of ensuring all your
servers and software are managed along with assisting in IT infrastructure consolidation and
optimization initiatives.
It comes with out-of-box deployment procedures to provision and patch Oracle Database (both single
instance database and RAC) including the underlying infrastructure. Enterprise Manager supports
segregation of duties, so that a designer can create the provisioning and patching workflows while an
operator can simply deploy the databases using those workflows. One can also provision a new
database from a reference system or from a gold image. The gold image along with configuration
details can be captured in provisioning profiles which can either be sourced from a reference system or
downloaded from Oracle.
Database Lifecycle Management supports the entire patch management lifecycle, including patch
advisories, pre-deployment analysis, rollout and reporting. It is integrated with My Oracle Support to
provide a synchronized view of available and recommended patches. Database lifecycle management
also provides complete automation for the schema change deployment process. Administrators can
also define gold standards and baselines for configurations allowing them to standardize their
environments against those definitions.
Resource Management
Automating resource management tasks, such as managing memory allocation and disk resources, has
been another key achievement of the self managing database, Oracle Database 11g. Let’s examine
these tasks in more detail.
Automatic Memory Management
Memory is a precious system resource and administrators historically have spent a significant amount
of their time optimizing its use. One of the key self-management enhancements in Oracle Database 11g
is automatic memory management. This functionality automates the management of shared memory
used by an Oracle instance and liberates administrators from having to configure the shared memory
components manually. The automatic memory management feature is based on sophisticated
heuristics internal to the database that monitors the memory distribution and changes it according to
the demands of the workload.
Oracle memory structures basically consist of shared memory – the System Global Area (SGA) – and
private memory – the Program Global Area (PGA). In Oracle Database 9i, the automatic SQL
execution memory management feature was introduced to automate management of the PGA. In
Oracle Database 10g, the same was done for the SGA by the introduction of automatic shared memory
management. This meant all the different SQL areas in the PGA were automatically sized for the
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system workload to give best performance and all the memory pools in shared memory were similarly
adjusted for optimal performance. The user was only required to specify the PGA and SGA target sizes
and Oracle would appropriately allocate memory within these targets to give the best possible
performance. PGA and SGA Advisors were also provided to help the user properly set the targets for
the SGA and PGA in Oracle Database 10g.
O /S M em ory
O /S M em ory
Figure 6. Automatic Memory Management
In Oracle Database 11g, memory management has been automated even further. All memory, PGA
and SGA, is now managed centrally with the automatic memory management feature. DBAs need to
specify a single parameter, MEMORY_TARGET, and Oracle will automatically size the PGA and
SGA based on the workload. Using indirect memory transfer, the database transfers memory from
SGA to PGA and vice versa to respond to the load. Dynamic allocation of memory is adjusted at
frequent intervals to optimize memory usage in line with workload requirements to maximize memory
utilization and avoid out-of-memory errors. Users can optionally set SGA and PGA targets when using
the automatic memory management feature. This ensures that SGA and PGA sizes will not shrink
below the values specified by their respective parameter targets in automatic tuning mode. This feature
is currently available on Linux, Solaris, HP-UX, AIX and Windows platforms.
First introduced in Oracle Database 10g, memory advisors provide graphical analyses of total memory
target settings, SGA and PGA target settings, or SGA component size settings. DBAs can use these
analyses to tune database performance and to perform what-if planning scenarios. Different memory
advisors become available depending on the memory management mode used with the database.
For instance, if automatic memory management is enabled, you can get advice for setting the target
amount of memory to allocate to the entire instance. If automatic shared memory management is
enabled, you can gain advice on configuring the target sizes of the SGA and PGA. If manual shared
memory management is enabled, you can get advice on sizing the shared pool, buffer cache, and PGA.
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Space Management
Space management can be one of the most time consuming tasks for database administrators.
Fortunately, Oracle Database 11g automatically manages its space consumption, alerts administrators
on potential space problems, and recommends possible solutions.
Proactive Space Management
Oracle Database 11g does non-intrusive and timely monitoring checks for space utilization in the
database server. Oracle Database 11g automatically monitors its space utilization during its normal
space allocation and de-allocation operations and alerts administrators if the free space availability falls
below the pre-defined thresholds. Oracle Database 11g’s space monitoring functionality is set up outof-box, causes no measurable performance impact, and is uniformly available across all tablespace
types. Since the monitoring is performed at the same time as space is allocated and freed up in the
database server, this guarantees immediate availability of space usage information whenever the user
needs it.
Notification is performed using server generated alerts mechanism. The alerts are triggered when
certain space related events occur in the database. For example when the space usage threshold of a
tablespace is crossed, an alert is raised. Another example of an alert is when a resumable session
encounters an out of space situation. An alert is sent instantaneously to the DBA to take corrective
measures. The DBA may choose to get paged with the alert information and add space to the
tablespace to allow the suspended operation to continue from where it left off.
The database comes with a default set of alert thresholds. The DBA may override the default for a
given tablespace or set a new default for the entire database through Oracle Enterprise Manager.
Transparent Space Reclamation
Oracle Database 11g provides the ability of performing an in-place reorganization of data for optimal
space utilization by shrinking segments. Shrinking of a segment will make unused space available to
other segments in the tablespace and may improve the performance of queries and DML operations.
The segment shrink functionality provides the ability to both compact the space used in a segment and
then de-allocate it from the segment. The de-allocated space is returned to the tablespace and is
available to other objects in the tablespace. Sparsely populated tables may cause a performance
problem for full table scans. By performing a shrink, data in the table is compacted and the high water
mark of the segment is pushed down. This makes full table scans read less blocks, and hence run faster.
Segment shrink is an online operation – the table being shrunk is open to queries and DML while the
segment is being shrunk. Additionally, segment shrink is performed in-place. This is a key advantage
over performing online table redefinition for compaction and reclaiming space. The DBA may
schedule segment shrink for one or all the objects in the database as nightly jobs without requiring any
additional space to be provided to the database.
In order to easily identify candidate segments for shrinking, Oracle Database 11g also includes an
automatic segment advisor. The automatic segment advisor runs every night in a predetermined
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maintenance window to proactively identify segments that need shrinking. The advisor, whether
invoked manually or automatically, performs growth trend analysis on individual objects to determine
if there will be any additional space left in the object in 7 days. It then uses the reclaim space target to
select candidate objects to shrink.
Segment Creation on Demand
Installation of a packaged application can often create thousands of database tables and indexes. The
creation of these tables and indexes can be time consuming and use a significant amount of disk space.
Many of these tables and indexes may never be used if you have not licensed all the modules of the
packaged application. In Oracle Database 11g Release 2, when creating nonpartitioned tables and
indexes, the database by default uses delayed segment creation to update only database metadata and
avoids the initial creation of user segments, saving disk space and greatly speeding up installation time.
When a user inserts the first row into a table, the database creates segments for the table, its LOB
columns, and its indexes.
Segment creation on demand saves time, space and computing resources.
Compression Advisor
In Oracle Database 11g, compression of your data saves disk space, reduces memory use in the data
buffer cache, and can significantly speed query execution. Compression does have a cost in CPU
overhead for data loading and DML. However, this cost is easily offset by greatly reduced I/O
Oracle Database 11g table compression is completely transparent to applications. It is especially useful
in decision support systems, where there are lengthy read-only operations and large amounts of data,
but it can also be used in online transaction processing systems. You can specify compression for a
tablespace, a table, or a partition.
A compression advisor has been added in Oracle Database 11g Release 2 to facilitate choosing the
correct compression level for your data. As part of the existing advisor framework in Oracle Database
11g, the compression advisor analyzes the objects in the database, discovers the possible compression
ratios that could be achieved, and recommends optimal compression settings.
Fault Diagnostics
Oracle Database 11g includes an advanced fault diagnostic infrastructure for preventing, detecting,
diagnosing, and resolving problems. The problems that are targeted in particular are critical errors that
can affect the health of the database. When a critical error occurs, it is assigned an incident number,
and diagnostic data for the error (traces, dumps, and more) are immediately captured and tagged with
this number. The data is then stored in the Automatic Diagnostic Repository (ADR)—a file-based
repository outside the database—where it can later be retrieved by incident number and analyzed. The
extensive improvement of the fault diagnostics infrastructure in Oracle Database 11g aims to provide
the following benefits:
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Respond proactively to small problems and prevent catastrophic system failure by alerting DBAs
using health checks.
Limiting damage and repair and interruptions after a problem is detected using the Data Recovery
and SQL Repair Advisor.
Reducing problem diagnostic time through ADR and Test Case Builder.
Simplifying customer interaction with Oracle Support using the Incident Packaging Service (IPS) and
Oracle Configuration Support Manager.
The following are the key components of the fault diagnostic infrastructure:
Automated Health Checks
A health checker framework has been added in Oracle Database 11g for the purposes of performing
proactive checks on system health. Upon detecting a critical error, the fault diagnostic infrastructure
can run one or more health checks to perform deeper analysis of a critical error. The results of a health
check are stored in a report that can be viewed as a text file or as formatted HTML in a browser. The
report can be added to other diagnostic data collected for the error. Separate individual health checks
look for data corruptions, undo and redo corruptions, data dictionary corruption, and more.
SQL Test Case Builder
For many application problems, obtaining a reproducible test case is an important factor in problem
resolution speed. The SQL Test Case Builder allows a user to automatically gather all the necessary
information needed to reproduce the problem such as SQL text, PL/SQL, DDL, execution
environment information, etc. The information gathered can then be transmitted to Oracle Support to
help reproduce the problem.
Automatic Diagnostic Repository
The Automatic Diagnostic Repository is a file-based repository for database diagnostic data such as
traces, dumps, the alert log, health monitor reports, and more. It has a unified directory structure
across multiple instances and components of the Oracle database and it replaces the
releases. The diagnostic data in ADR is self-managing and is purged automatically based on predefined
data retention setting. ADR also maintains meta-data for all critical errors on the database such that a
user can run queries against ADR to determine what and how many critical problems occurred on the
system over the last few days, months or even years.
Incident Packaging Service
The Incident Packaging Service automates the process of collecting all necessary diagnostic data related
to one or more problems. Users no longer have to search in different directory locations trying to
gather all the relevant trace files and dump files needed for problem diagnosis by Oracle Support. By
invoking IPS, all diagnostic data (traces, dumps, health check reports, SQL test cases, and more)
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pertaining to a critical error are automatically packaged into a zip file which can then be shipped to
Oracle Support.
Support Workbench
The Support Workbench is a facility in Oracle Enterprise Manager that enables you to interact with the
new fault diagnostic infrastructure of Oracle Database 11g. With it you can investigate, report, and
where appropriate, repair problems, all with an easy-to-use graphical interface. The Support
Workbench provides a self-service means for you to package diagnostic data using IPS, obtain a
support request number, and upload the IPS package to Oracle Support with a minimum of effort and
in a very short time, thereby reducing time-to-resolution for problems.
Automatic Diagnostic
Auto Incident Creation
First-Failure Capture
Alert DBA
Targeted Health Checks
EM Support Workbench:
Package Incident &
Configuration Information
Repair Advisors
EM Support Workbench:
Apply Patch or Workaround
Repair Advisors
Figure 7. Support Workbench Workflow
The Support Workbench workflow consists of the following steps:
Create an incident in the database automatically based on the first occurrence of a failure.
Alert the DBA of the failure and run health checks in the areas where the failure was reported.
If it is a known issue, then recommend and apply any necessary patch to solve the problem.
Otherwise, package up incidents and relevant configuration information and upload to Oracle
Support and run repair advisors to recover from failure.
There are a number of different kinds of problems that can occur in an Oracle database and the right
remedy for each problem may be different. The Support Workbench has extensive workflows that
guide the user to take action that is appropriate for the problem encountered.
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Exadata Management and Cloud Consolidation
As enterprises increasingly look to consolidate their disparate databases onto the Oracle Exadata
infrastructure, Oracle Enterprise Manager Cloud Control 12c can help administrators manage the
Exadata Database Machine using a holistic approach to and can provide comprehensive lifecycle
management from monitoring to management and ongoing maintenance for the entire engineered
Integrated System Monitoring
Oracle Enterprise Manager provides comprehensive monitoring and notifications to enable
administrators to proactively detect and respond to problems with Oracle Exadata Database Machine
and its software and hardware components. Administrators can easily adjust these monitoring settings
to suit the needs of their datacenter environment. When notified of these alerts, administrators can
easily view the history of alerts and associated performance metrics of the problem component, such as
the network performance of an Infiniband port or the disk activity of an Exadata storage cell, to
identify the root cause of the problem. With direct connectivity into the hardware components of
Exadata, Oracle Enterprise Manager can alert administrators to hardware-related faults and log service
requests automatically through integration with Oracle Automatic Service Requests (ASR) for
immediate review by Oracle Support.
Problems that would have required a combination of database, system and storage administrators to
detect in traditional systems can now be diagnosed in minutes because of integrated systems
monitoring for the entire Exadata Database Machine.
Manage Many as One
Oracle Enterprise Manager provides a unified view of Oracle Exadata hardware and software where
you can view the health and performance of all components such as compute nodes, Infiniband
switches, Exadata storage cells, Oracle databases, ASM, etc.
Figure 8: Monitoring Exadata using Oracle Enterprise Manager Cloud Control 12c
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Oracle databases run transparently on Oracle Exadata Database Machine without any changes.
However, there are times when a DBA needs to drilldown from the database to the storage system to
identify and diagnose performance bottlenecks or hardware faults. Enterprise Manager’s integrated
view of the hardware and software of Exadata allows the DBA to navigate seamlessly from the
database performance pages to the associated Exadata storage server to isolate the problem, whether
they may be caused by a hardware component or other databases running on the same storage
subsystem. The SQL monitoring capability that analyzes the performance of SQL executions in real
time is Exadata aware and can pinpoint the plan operations of the execution plan that are being
offloaded onto the Exadata storage servers, giving DBAs visibility into the efficiency of the SQL
The Exadata management capabilities in Enterprise Manager are provided in-line with the health and
performance features of the specific component being managed. For example, in addition to
monitoring the performance of the Infiniband network, administrators can also alter the port settings if
Enterprise Manager detects port degradation. On the Exadata storage cell, administrators can configure
and activate I/O resource manager plans within Enterprise Manager if they see excessive I/O resource
consumption by one particular database affecting the performance of other databases on the same set
of storage cells.
Consolidation Planning
As enterprises increasingly look to consolidate their disparate databases onto the Oracle Exadata
infrastructure, administrators can use Consolidation Planner in Oracle Enterprise Manager to
determine optimal consolidation strategies for different Exadata configurations. Using the actual
hardware configurations and the server workload history stored in Enterprise Manager, Consolidation
Planner analyzes the workloads of the source systems and computes the expected utilization for the
consolidation plan on the target Exadata systems. Equipped with a rich library of hardware
configurations, Consolidation Planner can guide administrators to define consolidation scenarios for
phantom Exadata servers, ranging from the different versions of X2-2 to X2-8. Now, businesses can
make smarter and optimal decisions about the exact configurations of Exadata that is right for their
database consolidation needs.
Database as a Service
Oracle Cloud Management for Oracle Database delivers capabilities spanning the entire database cloud
lifecycle. It lets cloud administrators identify pooled resources, configure role-based access, define the
service catalog, and the related chargeback plans. It allows cloud users to request database services, and
consume them on-demand. It also allows for users to scale-up and scale-down their platforms to adapt
to changes in application traffic. Finally, it lets both parties to understand the costs of the service
delivered, and establish accountability for consumption of resources.
Oracle Enterprise Manager ships with an out-of-box self-service portal that allows developers, testers,
DBAs, and other self service users to log on and request new single instance and RAC databases, as
well as perform lifecycle operations like start/stop, status and health monitoring, etc. on them. One
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can also deploy virtual assemblies containing databases on an Oracle VM virtualized server
infrastructure. The portal provides access to a service catalog which lists various published service
templates for standardized database configuration and versions. Users can review their past and
outstanding requests, resource quotas, and current utilization as well as chargeback information for the
databases they own.
Metering and Chargeback
A critical aspect of cloud delivery is the ability to establish usage cost for consuming cloud resources,
and metering actual usage to deliver chargeback reports. Enterprise Manager provides tools for
defining detailed chargeback plans spanning different metrics collected for each type of resource as
well as defining cost centers for grouping costs across multiple developers. Chargeback plans can use
not only usage based costs, but also configuration-based costs (e.g., version of the platform) or fixed
costs (e.g. flat-rate management fee).
Figure 9. Chargeback for Databases
What does it mean to you?
Change and consolidation are relentless in today’s rapidly evolving IT environments but it does not
have to be difficult for data center managers and administrators. Thanks to the manageability features
in Oracle Database 11g managed using Oracle Enterprise Manager Cloud Control 12c, database
administrators can keep their systems performant and available while providing higher quality of
service to their users through testing and consolidation
Modern enterprises are aggressively adopting new technology solutions to enhance their
competitiveness and profitability. As a result, management challenges continue to rise. Oracle Database
11g addresses these critical challenges by enabling database administrators to maintain database
performance at peak levels, adopt new technology rapidly and without risk, and increase DBA
productivity and system availability by automating routine administrative tasks. Oracle Database 11g
managed by Oracle Enterprise Manager Cloud Control 12c offers next-generation database
management for the next-generation DBA.
Oracle Database 11g Release 2:
Copyright © 2011, Oracle and/or its affiliates. All rights reserved. This document is provided for information purposes only and the
Database Manageability Overview
contents hereof are subject to change without notice. This document is not warranted to be error-free, nor subject to any other
September, 2011
warranties or conditions, whether expressed orally or implied in law, including implied warranties and conditions of merchantability or
Author: Kurt Engeleiter
fitness for a particular purpose. We specifically disclaim any liability with respect to this document and no contractual obligations are
Contributing Authors: Jagan Athreya, Mughees
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Minhas, Debaditya Chatterjee
means, electronic or mechanical, for any purpose, without our prior written permission.
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