Monitoreo y análisis de aplicaciones "Multi-Tier"

Monitoreo y Análisis de aplicaciones “Multi-Tier”

Eduardo Lopes [email protected]

#GX3009

CONFIDENTIAL – RESTRICTED ACCESS: This information may not be disclosed, copied, or transmitted in any format without OPNET’s prior written consent. © 2012 OPNET Technologies, Inc. OPNET Technologies Inc., OPNET, OPNETWORK, and all OPNET hardware and software product names are trademarks of OPNET. All other trademarks are the property of their respective owners.

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Objectives

Provide an introduction to core concepts includingCross-tier code-level Transaction TracingApplication and system-level Performance MetricsMemory Analysis


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Introduction to AppInternals Xpert - What is AppInternals Xpert?

Broad and deep coverage of all application components• Cross-tier, code-level transaction tracing of all Java

and .NET transactions• High-resolution (1 second) performance metrics

collected across all tiers including Java, .NET, database, Web Server, Operating System, VMware

Real-Time and Historical dashboards Three distinct analysis engines

• Transaction Tracing• Statistical metrics correlation• Memory analysis

Easy setup and maintenance• Automatic application discovery• Dynamically-established thresholds• Intelligent auto-tuning to ensure low overhead

Designed for Production, supports QA workflows Scalable architecture supports hundreds of servers Transaction Tracing

Metric Insights

OPNET Dashboards


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Most comprehensive performance management solution for web applications

Broad and deep coverage of all application components• Thousands of performance metrics collected across all tiers

incl. Java, .NET, database, VMware, and SOA• High resolution data collection (~1 second)

Real-time and historical dashboards Three distinct analysis engines:

• Statistical metrics correlation• Transaction tracing• Memory analysis

Easy setup and maintenance• Automatic application discovery• Dynamically-established thresholds• Intelligent auto-tuning to ensure low overhead

Designed for production, supports QA workflows Scalable architecture supports hundreds of servers

Deep Application Component Monitoring

Time/Statistical Correlation

True Statistical Correlation

Memory Leak Detection

Top Offenders

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Deep Visibility for Java and .NET

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OPNET Confidential – Not for release to third parties © 2010 OPNET Technologies, Inc. All rights reserved. OPNET and OPNET product names are trademarks of OPNET Technologies, Inc.


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Code-level Transaction Tracing• Reveals exactly what happened in

a particular transaction Where in the code is time spent? What needs to be fixed/optimized?

• Identifies dependencies on code/libraries/external systems

Metric Correlation Engine• Identifies unexpected relationships among components across

many tiers• Does not require developer/code-specific knowledge to interpret• Explicitly identifies when systems are behaving abnormally• Visibility into non-Java/.NET bottlenecks: within the OS,

Database, etc.

Memory Analysis• Identifies the actual sources of memory leaks, not just that

they exist• Addresses prevalent problem: memory leaks are notoriously

difficult to track down

Three Complementary Engines

Code-level transaction tracing

Metric correlation engine

Memory analysis

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Code-level visibility into individual user transactions• Trace user transactions through the code: from URL to SQL• Both .NET and Java

Low overhead, suitable for production environments Forensic events: Automatic archiving of problematic transactions

‘Always-On’ Transaction Tracing

Detailed call stack with code-level visibility

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Enables analysis of thousands of saved traces across multiple Java and .NET tiers Captures are triggered automatically based on user-defined policies Leverages powerful transaction analysis environment

Multi-Tier Forensic Captures

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Always Low Overhead: Auto-Tuning

Auto-tuning reduces blind spots by enabling more Java/.NET packages to be instrumented overall• AppInternals Xpert’s unique auto-tuning scans the code to instrument ‘interesting’ methods

only (e.g. larger methods, methods with loops, methods that call other classes) • Certain methods exponentially increase the total overhead while providing no valuable

information for troubleshooting – these “hotspots” are additionally identified and removed at runtime

• Performance data is recorded only for methods that represent a percentage (configurable) of overall application activity

Frequently called methods of short durationMore interesting methods

Manual Instrumentation AppInternals Xpert Auto-tuning


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Application and System-Level Performance MetricsCollects metrics across a wide range of components

Application Servers• Apache Tomcat• ATG Dynamo• Caucho Resin• JBoss• Macromedia ColdFusion• Macromedia JRun• Microsoft .NET-based Applications• Mort Bay Jetty• Oracle Application Server• Sun Java System Application Server• WebLogic • WebSphere

Databases• DB2• Oracle• SQL Server• Sybase

Web Servers• Apache• IIS

Operating systems• AIX• HP-UX• Linux (Red Hat, SUSE, zLinux)• Solaris• Windows

General purpose• SNMP• VMware Guest• WMI• Generic Scripting• SDK• VMware DataCenter• Storage Systems• Hadoop


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Use Cases

QA/Testing• Problem: A load test indicates unacceptable response time when the

load increases from 40 to 50 users, but what is causing the degradation?

• Solution: OPNET AppInternals Xpert’s advanced analytics compares the 40 vs. 50 user scenarios, shows potential sources of poor performance with drill downs into specific application components and transactions.

Production Monitoring • Problem: The application is slow but the network is fine and the

servers are up, so where is the problem?• Solution: OPNET AppInternals Xpert quickly shows the slowest

running transactions over a period of time as well as sifts through thousands of metrics in the application, across all servers, and helps to rapidly isolate the poorly performing components -- dramatically reducing the mean time to repair (MTTR)


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Questions that AppInternals Xpert Can AnswerExamples

What was a particular user doing during a period of time? How many times did a particular transaction occur during a period of

time? Are the load balancers doing their job? Which database instances are most transactions being executed on? Which transactions are causing exceptions? Are there any servers from one environment making calls to other

environments? Is there a relationship between CPU spikes and execution of particular

EJBs, Servlets or .NET Managed Components? Which components of my application perform poorly with unusually heavy

workloads? As load on an application increases, at what point does throughput

plateau? How is memory being allocated and released on my JVM/CLR and how is

this effecting performance?


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Performance MetricsWhat AppInternals Xpert Collects

Within Java and .NET applications• Code-level including load, throughput, response times, exceptions• Down to method level for component types (ADO, JDBC, Servlet/JSP,

ASP..)• Memory (objects allocated, free heap, consumed, garbage collections..)

Infrastructure • Operating systems - Windows, Linux (Red Hat, SUSE), AIX, HP-UX,

Solaris• VMware, Storage Systems, WMI and SNMP

Application Tiers Components running on front-end, back-end, and middleware Databases, Web Servers, App Servers

Extendable through Scripting, SDK and share.opnet.com• REST API, scripting API, C/C++ API


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Performance MetricsDynamic Baselines, Deviation and Correlation Analysis

Dynamic Baselines• Automatically determines “normal” range for every metric• Production vs. QA/Test Mode

What is considered “normal” can be very different Calibrate the analysis engine with a reference load

“Normal”

“Abnormal”

Deviations • Show abnormalities in observed metric values

relative to dynamic baselines• Deviation score is calculated across large numbers

(thousands) of metrics to determine what is the “most abnormal”

Correlations• Take a metric of interest and see other metrics

across entire application stack whose behavior is correlated to that metric

• Finds relationships among components, unknown cause effect, root cause “Correlation”


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Managed Memory Concepts

Symptoms of a Memory Leak

• Out of memory exceptions.• CPU utilization goes up because GCs are taking longer.• Garbage collection runs more frequently, as the application attempts to

free up space in an ever decreasing pool of usable memory. Thus causing the application to slow down.


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Memory AnalysisObject Sampling Metrics

AppInternals Xpert has the ability to provide live object counts and the allocation rates of different objects

Requires the “memanalysis” setting in Java and .NET instrumentation adapters and Java version 1.5 or later

Classes with the highest live object count and allocation rates


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Memory AnalysisHeap Snapshots

Records detailed information about memory usage in Java and .NET applications at a particular time

Use to identify the cause of complex heap problems, when the heap analysis metrics are not enough

Can identify specific method and source code line number responsible for memory leaks or excessive heap throughput

Depending on the size of the application’s heap, this can be resource intensive and suspend the application for some time Run in Dev/QA/Pre-production

Use with load balancer – remove node from cluster, when all users session have ended then run snapshot


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Conferencias que brindaremos

Incorporación de procesos de Ingenieria de Performance dentro de su organización• Hoy 17:15

Presentación de las soluciones de OPNET para la Gestión de Performance de Aplicaciones (APM)• Mañana 9:30

AppResponse Xpert SaaS Edition• Mañana 11:45

GRACIAS!!

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Monitoreo y análisis de aplicaciones "Multi-Tier"