<Insert Picture Here> Application Grid: Oracle s Vision for Next-Generation Application Servers and Foundation Infrastructure

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2 <Insert Picture Here> Application Grid: Oracle s Vision for Next-Generation Application Servers and Foundation Infrastructure Paolo Ramasso Principal Sales Consultant Oracle Italy

3 Business Imperatives and Challenges Efficiency: expand despite constraints Flexibility: change course quickly Quality of service: rise above the competition 2/26/ Oracle Corporation 3

4 Traditional World: Dedicated Stacks A challenge to efficiency and responsiveness Custom App Packaged App SOA Svc C/C++/ COBOL Legacy Application Server Application Server Application Server TPM TPM JVM JVM JVM OS OS OS OS OS Underutilization Difficult Scale-Out Constrained Performance 2/26/ Oracle Corporation 4

5 Application Scaling the Old Way Custom App Packaged App SOA Svc C/C++/ COBOL Legacy App Svr JVM OS App Svr JVM OS App Svr JVM OS TPM OS TPM OS Poor energy, space and staff inefficiency Unpredictable, inefficient scale-out Adding hardware does t always help

6 Introduction to Application Grid

7 A New Approach: Application Grid Grid computing at the middleware layer Custom App Packaged App SOA Svc C/C++/ COBOL Legacy Application Grid Efficiency Flexible Scaling High Quality of Service 2/26/ Oracle Corporation 7

8 What is Application Grid? Main Characteristics Pooled application resources Container CPU Memory Threads Clustering Dynamic adjustment Automation Main Technologies Application server Java virtual machine (JVM) In-memory data grid Transaction processing monitor (TPM) 2/26/ Oracle Corporation 8

9 So you Get: Efficiency Grow despite constraints Each app no longer provisioned for individual worst case total shared resources < sum of peak loads Run more apps on given set of hardware resources Standardize configuration of hardware resources Reduce administrative costs 2/26/ Oracle Corporation 9

10 So you Get: Flexible Scaling Adjust course with agility Provisioning of new apps doesn t necessarily require new hardware Adjustment of application resources happens in seconds or minutes, not days or weeks Business can be more experimental, trying new applications without huge provisioning overhead IT easily handles spikes in load as business changes 2/26/ Oracle Corporation 10

11 So you Get: Higher Quality of Service Compete based on responsiveness and reliability Replication in application grid increases reliability Higher performance is possible because more computing resources can be applied to application without limits of bottlenecks 2/26/ Oracle Corporation 11

12 Building Application Grid

13 Application Grid Fundamentals Four basic elements for a grid foundation 1. Share Resources App App App SOA Svc SOA Svc 2. Control Allocation 3. View Behavior 4. Automate Management 2/26/ Oracle Corporation 13

14 Beyond the Fundamentals Areas to focus on for an effective application grid Management Nodes must be rock-solid Management must be comprehensive and simple Clustering must be dynamic and automatable 2/26/ Oracle Corporation 14

15 Getting Started with Application Grid

16 Do I Have to Start Over? Evolution to application grid Localized Automation/ Optimization Enterprisewide WebLogic Server, JRockit, Tuxedo Basic Management, Scripting Basic Cluster Scale-Out Grid Control: Enterprise Manager/ WLOC Automated service startup and failover Data Grid Scale-Out: Coherence Enterprise-Wide Dynamic Optimization Somewhat Dynamic Highly Dynamic Dynamic Scaling 2/26/ Oracle Corporation 16

17 1: Leverage Application Server Build foundation for efficiency and flexibility App Svr App Svr App WLS Svr App WLS Svr App WLS Svr AppWLS Svr App WLS Svr App WLS Svr App WLS Svr App WLS Svr Possible actions: Use application server clustering for scale-out Consolidate to WebLogic Server (or Tuxedo for C/C++/COBOL) Use scripting to automate scaling You now have a foundation for application grid! 2/26/ Oracle Corporation 17

18 2: Enhance Scalability and Performance Make your grid more dynamic and resilient App Svr App Svr App Svr App Svr App Svr App Svr App Svr App Svr Coherence Coherence JRockit JRockit Coherence Coherence Possible actions: Add Coherence in-memory data grid to existing machines Add Coherence nodes on non-app-server machines Add JRockit Real Time JVM 2/26/ Oracle Corporation 18

19 3: Add Grid Management Attain higher automation and optimization App Svr App Svr App Svr App Svr App Svr App Svr App Svr App Svr Enterprise Manager/ WebLogic Operations Control Possible actions: Add Enterprise Manager/WebLogic Operations Control Set up grid-wide SLAs, policies, etc. Automate scaling of application server and data grid clusters 2/26/ Oracle Corporation 19

20 Summary Application Grid is an approach to foundation middleware based on resource pooling with automated dynamic adjustment Fundamental Enablers: Share Control View Automate Key Benefits: Efficiency Flexibility Quality of service 2/26/ Oracle Corporation 20

21 Application Grid with Oracle Fusion Middleware

22 Elements of the Application Grid Comprehensive, hot-pluggable, pre-integrated Enterprise Manager WebLogic Server Coherence Tuxedo WebLogic Operations Control JRockit 2/26/ Oracle Corporation 22

23 JRockit JVM Full Java SE implementation Core of the entire JRockit product line Integrated component in many Oracle products

24 Performance Leadership Higher performance leads to significant cost savings SPECjbb Quad core Intel Xeon X % +91% SPECjbb2005 bops Sun JVM (base) Sun JVM (tuned) JRockit (base) JRockit (tuned) 0 32-bit JVM 64-bit JVM Note: The percentage comparison is compared to the baseline (Sun JVM base). Relative performance varies with workload.

25 JRockit Technologies JRockit #1 server-side performance Full-stack support JRockit Mission Control Visualization of zero-overhead diagnostics (operations & dev) WebLogic Real Time Real-time low-latency standard Java

26 Managing Latency 120 Traditional Java JRockit Real Time During Low Load: GC spikes and occasional timeouts visible JRRT Makes garbage collection deterministic. Allowing for the guarantee of SLAs. During High Load: GC pauses can result in unacceptable response times

27 WLRT Deterministic GC Provides QoS guarantees Usage: -Xgcprio:deterministic Xpausetarget=10ms Highly tuned mostly concurrent mark-n-sweep GC Most work done concurrently, pauses are frequent but very short Back off, split work and reschedule if nearing QoS limit (divide and conquer) One GC cycle (phases 0-2, 2-4, 4-5, 5 visible) 500 ms 20 s

28 Throughput and Latency Tradeoffs The key objective of JRRT is deterministic GC pause time Finer control of GC behavior adds workload to the VM Optimizing for low-latency with determinism Typically reduces overall throughput General JRockit optimizations benefit both latency and throughput The impact on throughput is highly dependent on the application May require lower targets for CPU utilization (e.g. 75% rather than 90%) May reveal application latencies that are not attributable to GC

29 JEE Server:Oracle WebLogic Server Converged Infrastructure for the Oracle Platform The Number #1 Java EE application server, designed for the most Mission-Critical of applications Developer-friendly productive, standards-based development Focus on quality of service performance, scalability, reliability, availability Built-in manageability configuration, monitoring, diagnostics, maintenance WebLogic Server Clusters WebLogic Application Grid Legacy Commodity Databases Virtualized Mainframes 29

30 Continued Leadership in Performance Runtime performance Across all subsystems - SPECjAppServer as representative example Console and startup performance 2x to 3x improvement over WLS 9.2 and 10.0 Asynchronous HTTP session replication Reduce latency in HTTP client response

31 Oracle WebLogic Server 10.3 Background WLS Major administrative and runtime enhancements WLS JEE5 support WLS 10.3 Maturity release of WLS 10 Developer usability Lightweight, Workshop, Spring, Web 2.0, FastSwap Runtime and Console Performance SPECjAppServer and support of lightweight improvements Updating WLS 9.2/10.0 work Web Services, JMS, Security compliance/standards Oracle compliance requirements added License key removal, certification, branding, security WLS Essex Status

32 Architectural Overview: Big Picture

33 Deployment Architecture Overview DMZ Firewall DMZ Firewall Intranet Firewall External Users Internal Users HTTP Servers Proxy Plugin Managed Servers Node Manager DB Servers Internet wireless& Mobile Network Dispatcher/LBR HTTP Servers Proxy Plugin Active/Active Cluster Managed Servers Node Manager Admin Server Active/Active Cluster Directory Server Client Tier Web Tier DMZ App Tier DMZ Data Tier / Intranet

34 Lightweight WebLogic Server Lightweight installers Core WLS install option, add-ons (JDKs, etc) optional Reduce download and install time, installation footprint FastSwap Modify classes without requiring redeployment Accelerate develop/deploy/debug cycle Optional service startup Start WebApp container without starting EJB, JMS, JCA services Provide developer flexibility Deployment process/startup performance improvements EJB compilation performance improvements

35 Production Redeployment Side by Side Deployment Multiple application versions can coexist New client requests are routed to active version; Existing client requests can finish up with existing version Automatic Retirement Policy: Graceful, Timeout Test application version before opening up for business Rollback to previous application version Two versions of the application can be active at any given point of time

36 Integration with Oracle RAC Oracle RAC Support Use WLS Multi-Data-Sources Fast failover upon node failure Automatic failback upon node recovery Load-balancing or Failover algorithm Periodic health check of connections

37 Best-of-Breed Messaging (JMS) Engine

38 JMS Unit-of-Order Strictly ordered messaging FIFO Processing messages out of order can be disastrous JMS spec does not cater for strict ordered delivery of messages WebLogic offers Unit of Order add-value feature Producers mark messages as part of same unit All message processed sequentially in the order they are placed on destination Each producer uses same text name for unit of order (via WebLogic ( call JMS API Alternatively, a Connection Factory can be configured to always enforce a specific UOO

39 Self-Tuning and Work Managers WebLogic's Self-Tuning Thread Pool Network Socket Handlers ( Muxers ) Request Queue Self Tuning Thread Pool Active Standby Stuck Hogging Asynchronously dispatched work from WebLogic kernel, subsystem, or application 1. Monitor rate of request processing 2. Adjust thread pool size accordingly

40 Self-Tuning and Work Managers Configurable Work Managers Every application has its own Work Manager based on the 'global' 'fair-share' work manager by default Can explicitly configure a new Work Manager apply to one or more specific applications and even individual resources (eg. ( Servlet a Each work manager can have a mix of the following configuration elements... REQUEST CLASS ELEMENT ( default ) Fair Share ( goal ) Response Time Context based (per ( user/group CONSTRAINT ELEMENT ( active ) Minimum Threads Maximum Threads Capacity (threshold for ( rejection TRIGGER ELEMENT Shut-down Trigger

41 Cluster A cluster is a group of Managed Servers running simultaneously and working together to provide increased scalability and reliability Scalability: through parallelism Reliability/Availability: through replication and redundancy Admin Svr Cluster 1 A cluster appears as a single instance to most clients. Clusters enable some advanced features, such as Whole Server Migration, Service Migration, and clustered JMS destinations. Cluster 2

42 Clustering and High Availability Transparent Load Balancing and Failover HTTP, EJB, JNDI and JMS clients HTTP requires Hardware Load Balancer or Web Server Proxy EJB/JNDI/JMS client 'stubs' are automatically cluster aware

43 Demonstration Playing with Oracle Weblogic Server

44 Oracle Coherence Data Grid Distributed in Memory Data Management Enterprise Applications Real Time Clients Data Services Web Services Oracle Coherence Data Grid Provides a reliable data tier with a single, consistent view of data Enables dynamic data capacity including fault tolerance and load balancing Ensures that data capacity scales with processing capacity Databases Mainframes Web Services

45 The Coherence Approach Traditional scale-out approaches limit Scalability, Availability, Reliability and Performance In Coherence Servers share responsibilities (health, services, data ) No SPoB No SPoF Massively scalable by design Logically servers form a mesh No Masters / Slaves etc. Members work together as a team

46 The Distributed Scheme Sophisticated approach for Clustered Caching Why: Designed for extreme scalability How: Transparently partition, distribute and backup cache entries across Members Often referred to as Partitioned Topology Configurable Expiration Policies: LFU, LRU, Hybrid (LFU+LRU), Time-based, Never, Pluggable

47 The Distributed Scheme

48 The Distributed Scheme

49 The Distributed Scheme

50 Distributed Scheme Clients & Servers Cache Client Member has storage disabled for Partitioned Topologies Cache Server Member has storage enabled for Partitioned Topologies Same Cache API Transparent to developer Storage is (re)configured outside of code

51 Distributed Scheme Clients & Servers

52 Session State Management Integration Coherence*Web is a generalized state replication framework for any application server Certified with WebLogic, OracleAS, JBoss, WebSphere,Tomcat, SunOne Plugs directly into Application Servers HTTP session only Augments existing HTTP session state replication Stateful EJB replication uses existing AS infrastructure Value with Application Servers More sophisticated state replication - policy based Transactionality for session replication Offload state replication to independent tier from application server

53 Coherence*Web: Session State Management Web Application Coherence Web Java EE or Servlet Container Application State Router Web Application Web Tier Load Balanced Coherence Web Java EE or Servlet Container Application State Clustered Oracle, WebLogic, WebSphere, JBoss, Tomcat In Memory Coherence Data Grid for Session State

54 Data Source Integration

55 Data Source Integration

56 Data Source Integration

57 WebLogic Operations Control Monitoring and Management Rich console GUI One pane of glass for multiple domains and applications Deploy, monitor, control, manage Secure, highly available App level entitlement Secure agent to controller communications HA protection for agents and controller no single point of failure Complements Enterprise Manager Focus on application management Continue to use EM for standard config. mgmt. of Oracle products

58 WLOC Abstracts Application Deployments from Underlying Hardware Multiple Independent Applications Application Application Application Application WebLogic Operations Control Demand JVM Pool Supply Shared Hardware Resources Quality of Service metrics Resource requirements Virtualized containers Physical servers

59 WLOC Based on Controller-Agent Architecture WLOC Controller Data & config aggregation Centralized decision making WLOC OS Agent App A JRockit JVM Operating System Server Hardware App B JRockit JVM Endpoint monitoring Action execution WLOC OVM Agent Operating System Server Hardware Oracle VM Manager App 1 App 2 App 3 JRockit OS JVM WLS OS JRockit VE Oracle VM

60 WebLogic Operations Control Centralized Governance and Control Define services and operational policies, rules, & SLAs Manually or auto-adjust resource allocations across apps Deploy & manage apps & services in resource pools Actively monitor all deployments against policy

61 Defining Services and Process Types Service Set of related processes managed by WLOC Services are comprised of process types E.g. CreditCheckService application deployed across multiple WLS instances Process Type This represents a kind of process E.g. AdminServer and ManagedServers process type defined within a service Process Instance This represents a particular instance of a process A Process Type has one or more process instances within it CreditCheckService AdminServer Admin Server ManagedServers Managed Server 1 Managed Server 2

62 Policies Policies are Service Level Agreements (SLA) that govern Services Comprised of constraint and action to take when constraint is violated Policies can be classified as: Resource policies Deployment Policies - Define the min and max number of servers Software Policies - These policies define the required software to start processes IP Address Policies Define the IP Addresses required CPU Policies Define the amount of CPU cycles required Memory Policies - Define the amount of memory required Monitoring policies These policies define constraints on data that is monitored from the processes that are running. Monitoring information is retrieved for the processes via JMX or Virtual Center APIs Calendar policies These policies are defined to be executed at a certain time

63 Actions and Pipelines A pipeline is a collection of actions that are executed sequentially WLOC supports the following actions: Service Start, Stop Process Start, Stop, Suspend*, Resume* (* JRockit VE instances only) Notifications JMX JMS SNMP Console Can be configured to require user Adjudication before proceeding

64 Demonstration Oracle Weblogic Operation Control: Dynamically Provisioning an Oracle Coherence Cluster

65 Application Diagnostic Challenges Limited Production visibility Not enough depth to diagnose production issues Diagnostic tools not suited for production Inability to reproduce problems on other environments Hard to isolate culprit tier and component Impacts Time to Resolution Java is a black box

66 Enterprise Manager Application Diagnostics for Java (AD4J) Strengthening APM solution AD4J Configuration Management Service Level Management Application Performance Mgmt Lifecycle Management Dashboards Applications Middleware Database Diagnose problems in production View all java activity: instrumentation not needed Trace transactions across tiers, into the Oracle DB Operating Systems

67 AD4J Architecture Agent Console AD4J Agent Java Class Monitored JVM JVM Information to browsers AD4J Agent Native library SNMP Traps AD4J Agent Java Class Monitored JVM Console JVM AD4J Agent Native library JVM Activity Monitoring DB Activity Monitoring Memory Leak Analysis Root Cause Analysis Monitored DB AD4J Console Java Classes AD4J Console JSPs AD4J Repository AD4J Console Native library AD4J DB Agent

68 Platform Support Standalone Java i-11g

69 Competitive Advantage in-depth Application view Diagnose & Root Cause Monitor The Platform 24X7 AD4J Console Memory Analysis DB Activity Monitoring JVM Activity Monitoring Diagnose & Root Cause Memory Leak Analysis AD4J Console Java Classes AD4J Console JSPs AD4J Repository NOC App Support & QA DEV

70 Competitive Advantage Low overhead & easy to use 1. Complicated to install, deploy, use Code instrumentation and server restarts Experts needed to instrument and diagnose 2. High overhead (>20%) Can t run in production 3. Silo oriented No visibility from App Server through to DB 1. Very easy to install, deploy, and use No modification of code or server restarts Immediate visibility with no Application expertise required 2. Minimal Overhead (<1%) Runs in production Servers 3. Transaction Visibility Follow transactions from AS to Oracle database

71 JRockit Technologies JRockit #1 server-side performance Full-stack support JRockit Mission Control Visualization of zero-overhead diagnostics (operations & dev) WebLogic Real Time Real-time low-latency standard Java

72 JRockit Mission Control Use Cases Developer Debug Application Optimize Application Find, Diagnose and Fix Issues Support / Admin Monitor Application

73 Oracle JRockit Mission Control

74 Oracle JRockit Mission Control

75 Oracle JRockit Mission Control

76 Demonstration Playing With Application Diagnostic 4 Java

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