Hoosh Afsar

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Hoosh Afsar Financial Engineer Fannie Mae Venkat
Tummalapalli Senior Product Manager Oracle
Corporation
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Extending the reach of Enterprise Manager 10g to
monitor custom applications across the grid
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Stove-pipe architecture is rigid and does not
scale well
Corporate Network
Public DMZ
LDAP over SSL
Internal LDAP Servers
Internal Logging Server
Intranet Firewall
External Firewall
Extranet Firewall
Secure Extranet Listeners
Internet
Intranet Oracle9iAS
Extranet Oracle9iAS
Logging Server (centralized)
Net8 over ASO
Others Interfaces
9iAS Intra
9iAS Extra
Extranet Standby Database
Intranet Listeners
Intranet Clients
Intranet Standby Database
Tuxedo Server
Authentication Server
Internal Applications
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Our Computing Grid is flexible
Business Processes
Trade Valuation
Risk Management
Financial Modeling
Portfolio Management
Adjust supply of, access to resources
Analyze demand for resources
Simulation Engine Servers
Farm of 100 machines
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Our Grid needs an extensibile system mgmt tool
Real time alerting
Root-cause Impact Analysis
Provisioning
Trending
Oracle Eco-System
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Fannie Maes use of EM Assuring availability of
a 1 billion/day trade valuation system
Reduce
SE Applications
Automate
Simplify
Sun Fire 280R 8G RAM
Scale
Repository
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Oracle Enterprise Manager 10g Extensible
solution for the Enterprise
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What Makes EM extensible ?
Zero barrier to entry
Console API
Repository API
XML
Standard API
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What makes EM Extensible?
Rapid Instrumentation

• - Declarative definition of new targets XML
• You do not need to write oraTcl scripts or C
  data gatherer catridges. Coding time is reduced
  by orders of magnitude from Months to Minutes
• - Public interface to management data Well
  documented Repository schema
• You will be able to use your favorite tools to
  slice and dice the management data or to do
  ad-hoc reporting
• - Support for Open Management Standards WBEM, JMX

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What are the integration Points ?
EM Black Box
Active Management Repository
Agent
Agent
Agent
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Integration Investment Value Curve
Management Value for Customer
Integration Investment (Time and Resources)
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Integration Points Agent

• Function
• Monitor the functioning of hardware or software
  targets.
• Public access via
• XML
• Declarative discovery of target (targets.xml)
• Declarative definition of metrics (metadata for
  target)
• Fetchlets
• data access mechanism
• SQL, Log file, OS, SNMP, URL Timing,
• Instant value to your integration Automatically
  shows up in the EM UI without having to do any
  UI changes!

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Integration Points Agent
Collection Definitions
Collector
Task Executor
Transfer
Metric Engine
Target Metadata
Fetchlet 2
Fetchlet 1
Fetchlet 3
Java API
XMI
V 1.2
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Managed Target
EM Agent
Presentation API
V 1.1
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Managed Target Examples ..
Backend
Middle Tier
JS
Apache 1
App 1
BIG IP
JS
JS
Apache 2
Cisco Router
JS
Apache 3
JS
JS
V 1.1
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Integration Points Repository

• Functions
• Uploads data into the database from loader files
• Rollups of raw data
• Notifications for event occurrences
• Global Inventory for tracking software patch
  levels
• Public access via
• Views (ad-hoc reporting)
• pl/sql api (procedural access, example add an
  admin)

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Management Repository
V 1.1
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Integration Points User Interface

• Create homepages for your custom targets
• Plug in administration components that are based
  off data collected in the repository.
• The administration components can directly
  connect to targets or go thru the Agent to make
  changes on managed node.

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Putting it all together
Managed Targets
EM Daemon
Real-time Monitoring
Reporting
Notification
Target Definition Files
Metric Definitions Metric Data Alerts Client
Response Times Web Server Response Times
Information Rollup
V 1.3
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Example Simulation Engine Queues
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How do I instrument my app ?
Prerequisite

• Separate the application into multiple targets,
  and define them separately
• Determine what makes up the application
• Components
• Availability
• Performance

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How do I instrument my app ?
Workflow
Define target type

• Define targets
• pick your metric
• compute metric
• Define collections
• collection schedule
• Instantiate your targets using the EM UI.

Define collections
Set thresholds
Declare the targets
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How do I instrument my app ?
Agent

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Example What makes up my app ?
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Are my applications available?
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Example App specific metrics
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Example App specific metrics
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-
ltTargetMetadata META_VER"1.0"
TYPE"fanniemae_vn_queue"gt
-
ltDisplaygt

•   ltLabel NLSID"fanniemae_vn_queue_name"gtFANNIEMAE
  VN Queuelt/Labelgt

•   lt/Displaygt

-
ltMetric NAME"Response" TYPE"TABLE"gt
-
ltDisplaygt

•   ltLabel NLSID"vn_qparse"gtResponselt/Labelgt

•   lt/Displaygt

-
ltTableDescriptorgt
-
ltColumnDescriptor NAME"response_time"
TYPE"NUMBER" IS_KEY"FALSE" TRANSIENT"TRUE"gt
-
ltDisplaygt

•   ltLabel NLSID"vn_qparse"gtVN Queue Response Time
  (ms)lt/Labelgt

•   lt/Displaygt

•   lt/ColumnDescriptorgt

-

•   lt/Displaygt

•   lt/ColumnDescriptorgt

-
ltColumnDescriptor NAME"Status_Message"
TYPE"STRING" IS_KEY"FALSE"gt
-
ltDisplaygt

•   ltLabel NLSID"vn_qparse"gtUpDown Status
  Messagelt/Labelgt

Step 1 How do I define a target?
 
 
 
 
 

• gt

-
lt
-

• gt

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Step 2 How do I define collections ?
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Step 3 How do I set thresholds ?
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Step4 Declaring target instances
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Step 5 Quality Assurance

• Test metrics using the EM Metrics Browser
• Setup collections into the repository
• - Edit emd.properties and specify Repository
  upload URL, Upload Interval
• The custom application is now ready to be
  monitored by EM !

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What did it buy for us ?

• The data that we collect will now be uploaded/
  rolled up periodically - Raw data -gt hourly -gt
  daily -gt ..
• Time Series charts with various statistical data
  for trending- Average, High/Low Watermark, Std
  Dev.
• Event detection and real time notifications
• Correlation across various layers of the FM stack
• Service level reporting

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When will it be available ?

• 1st planned release End of CY 2003

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A
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