insights into enterprise application management : how do we make them faster?

APM Insights into Enterprise Application Management : How do we make them faster?

Hugh P. Brien

AppDynamics Proprietary & Confidential – All Rights Reserved

Copyright © 2010 AppDynamics. All rights reserved.

Who We Are

The leading provider of application management for

modern application architectures in both the

cloud and the data center

Our Heritage Company Facts

• Founded in 2008 by Jyoti Bansal• Based in San Francisco• 40,000 users of AppDynamics Lite

Delivering Measurable Results

Cloud AppMgmt

Needed to Maintain QoS with 40%

growth

Managing > 3000 Amazon EC2

nodes

<1% Overhead in Production with 100% visibility

New Distributed Architecture

$1B in eCommerce

revenue

End-to-end visibility into transactions

Ease-of-Use a key factor for broad

adoption

MTTR Reduction

Reduced MTTR from 6 hours to

10 minutes

Production Monitoring with Low Overhead

Deep Visibility, “Painless”

Deployment

Agile Dev & Operations

Agile – 10 Releases per

Month

Needed Visibility into Custom App

Reduced MTTR for slow

response & memory leaks

•Byte Code injection instrumentation

•Business transaction data collection

•Machine statistics data collection

•Distributed automation extension

AppDynamics Architecture

Machine Agent

Application Server Agent

(JVM/CLR)

One way HTTPS connections

•Central Management Server•SaaS or On-Premise deployment options

AppDynamics Controller


Continuously Discover and Auto-Instrument all tiers of your Application for 10x Visibility

AppDynamics Pro – How it Works

Self-Learn and Baseline the “Normal” Response Time of Business Transactions

Monitor Application Health in Production 24/7

Troubleshoot & Diagnose root-cause 90% faster

Respond via Policy-Driven automation


Monitor Application in Production 24/7

AppDynamics Pro – How it Works

Scalability – Very Very Very Large

Policy Engine And Automation

Big Data Visibility

Policy Driven Automation

Application Management Challenges

1. Production downtime and/or recurring performance problems

2. Poor end-user experiences may result in lost revenue or brand damage

• Inability to determine root cause and resolve problems in timely manner

Three Key Customer Challenges

Application Health


Tuning Your Enterprise Applications

What’s Normal


If You Can Measure It You Can’t .....

How Do You Know?


Knowledge Is Power

What Are “Your” KPIs?


Knowledge Is Power

Major Garbage Collections


Knowledge Is Power

Who Didn’t Read the Directions? - Server

Configuration


Knowledge Is Power

Request Overload


Knowledge Is Power

Hibernate Abuse


Knowledge Is Power

Web Services


Knowledge Is Power

SynchronousTransactions


Knowledge Is Power

And By the Way It’s Not the Database It’s Probably Your

Code or Indices


Primary Application Bottlenecks

- Major Garbage Collections- Who Didn’t Read the Directions? - Server Configuration- Request Overload- Hibernate Abuse- Web Services- Synchronous Transactions- And By the Way It’s Not the Database It’s Probably Your Code or Indices


How is our Approach Disruptive?

OLD WAY NEW WAY SO WHAT?

Monitor Component (server, JVM/CLR,

method) Health

Manage Application health by Business

Transaction

Right Context for Distributed Apps

Aligned with Business

Manually select what code to instrument

Self-learned Instrumentation

Easy, Easy, EasyEnables Agile

Operations

Detection based on manually set static

thresholdsDetection based on self-

learned baselinesAdaptive

No False Alarms

•Byte Code injection instrumentation

•Business transaction data collection

•Machine statistics data collection

•Distributed automation extension

AppDynamics Architecture

Machine Agent

Application Server Agent

(JVM/CLR)

One way HTTPS connections

•Central Management Server•SaaS or On-Premise deployment options

AppDynamics Controller

Product Demonstration


APM Requirements for Modern Apps

• Fit for Production Environment = Low Overhead• Ease of Use

• Can I deploy it myself in less than an hour?• Is the instrumentation self-learned or is it manual/arduous?• Are “normal” performance baselines self-learned or are thresholds manually set?

• Application Visibility• Does the tool discover, visualize and monitor distributed business transactions?• Does the tool adapt automatically in agile environment?• Does the tool adapt automatically in a hybrid cloud/virtual environment?

• MTTR Reduction – Rapid Troubleshooting & Root Cause Analysis• When a problem occurs, is diagnostic data automatically captured or is it manual?• Can the tool identify problems between the tiers/services in a SOA environment?• Are there code-level diagnostic captured for every bad session?• Does the tool find root cause of memory leaks or just identify them?

• Preferred Unit of Management is the Business Transaction• Versus Server health vs Method-only vs Log files

• Ability to Automate Action• Can the tool take action based upon what it detects?

• NetFlix, Orbitz, Exact Target, Family Search, IG Index

• Todd Radar • Orbitz• Exact Target• IG Index• StubHub• Family Search

• Real Time Live• Automation• Big Data


Common Application Performance Issues

Problem Type Frequency Difficulty to Diagnose

Slow SQLVery High Medium

Slow Response / Errors due to malformed code

Very High High

SOA Remoting IssuesHigh High

Thread & Synchronization Issues

Medium Very High

Memory Leaks & ThrashMedium Very High


What’s the New Idea?

New World: Distributed applications running constantly Changing code on Dynamic infrastructure

Key Question:

How can you assure application availability when the code and the topology are constantly changing?

New idea: Monitor the “Business Transaction”• The Business Transaction = the collection of all processing

across a distributed infrastructure that fulfills a user request• The Business Transaction is a constant in a world of change

insights into enterprise application management : how do we make them faster?

Documents

needed visibilityend

san francisco

mttrdeep visibility

jyoti bansal

hours toqos