Monitoring 101Leverage on the Power of JMX

... and beyond

Martin GutenbrunnerDynatrace InnovationLab

@MartinGoodwell

Java Forum Stuttgart, July 7 #jfs2016

@MartinGoodwell

About me

Started with Commodore 8-bit (VC-20 and C-64) Built Null-Modem connections for playing Doom and

WarCraft I Went on to IPX/SPX networks between MS-DOS 6.22

and WfW 3.11 Did DevOps before it was a thing (mainly Java

and Web) for ~ 10 years Now at Dynatrace Innovation Lab Find me on Twitter: @MartinGoodwell Austria

Passionate about life, technology, and the people behind both of them.

@MartinGoodwell

Monitoring 101Leverage on the Power of JMX... and beyond

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Agenda

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@MartinGoodwell

Warm up

Please, feel free to ask and interrupt anytime This is about you, after all

How many developers, operators and business people are here? I love Java and Spring Framework

Anyone here who hates one of them? Any previous experience with JMX or monitoring, anyone?

Who knows what APM is?

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Monitoring... your application, not your environment

@MartinGoodwell

Why monitoring, when we can debug? Debugging is for Developers only

Operations need monitoring Monitoring can be done via web apps

Debugging requires a dev-env to be setup Monitoring is about two things

Tracking problems Optimizing performance More often than not, those two things will be based on production data

Plus: when you can track errors, you can also track business

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Active vs passive approachTwo ways of thinking, two ways of integrating

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Active JMX is an active way of monitoring

You need to know, which metrics you want to monitor And actively publish/export them

Pro You can monitor all the metrics you want, even those specific to your application

Con Pollutes your code

But there‘s ways around that, like AOP

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Passive

As opposed to passive monitoring Where tools automatically pick up the most common metrics, like

Number of requests Round-trip times HTTP status codes

by eg. AOP or Java agent interface I.e. without actively integrating monitoring code into your business logic

Pro: No code pollution

Con Only collects technology-related metrics (nr of requests, ...), no business metrics (like nr of orders)

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JMXA short introduction

@MartinGoodwell

JMX Trivia Java Management Extensions Counters, gauges and strings JMX is ooold:

Integral part of Java since Java 5 MBeans can consist of

Readable/writable attributes (right, not only for reading values) Invokable operations (I am not really in favor of those) A description (rules of proper documentation apply)

@MartinGoodwell

Standard, Dynamic, Model, Open, MX MBean

Static Dynamic

ModelMBean (configurable) OpenMBean (specific data-types)

MXBean (came with Java 6) XMBean is not an MXBean with a typo

XMBean is a JBoss-specific MBean

Bottomline: use MXBean

@MartinGoodwell

Why JMX?

For Ops: Because most Java services / apps provide JMX metrics. You get it „for

free“ For Devs:

It‘s not too hard to implement, even really easy with eg. Spring Framework For DevOps (ie both):

Lots of visualization tools available, both free and commercial It‘s a unified way of monitoring (no matter whether it‘s a queue, a

database or a cache) For Business:

It allows your devs to provide and your ops to report the metrics you need.

@MartinGoodwell

Which metrics should I monitor?

Common process metrics CPU Memory

Service specific metrics Webservers: Nr of requests and response times Databases: Connection pools utilization, etc. Caches: hits and misses Queues: size, fill-rate

Business Intelligence Visitors Orders

@MartinGoodwell

Who provides JMX metrics out-of-the-box?

JVM Threading, Memory usage, Garbage Collection, CPU usage (system, process, …)

Web Servers Tomcat Jetty

Netflix OSS Eureka Discovery Server Hystrix Circuit Breaker

Connection Pools RDBMS (Tomcat DBCP, c3p0, BoneCP, HikariCP, …) MongoDB

Messaging Queues (ie JMS) HornetQ Active MQ

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... Wait, there‘s still more!

Hibernate Spring

Adds JMX to most libraries it wraps Quartz (the scheduler) EhCache (the cache)

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Some examples

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Java JMX

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Tomcat JMX

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MongoDB JMX

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HornetQ

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Business metrics

Feature usage Number of placed orders Where do my customers come from? Track a customer‘s path:

Catalog Shopping Cart Checkout Payment Dropouts

@MartinGoodwell

Correlating metrics

On a technical basis Nr of requests vs response time

Increasing response time alongside increasing number of requests probably pinpoints a scalability problem

The real fun starts when you correlate BI with technical metrics Eg. Feature usage vs error rate or response times Increasing errors in service X

And decreasing usage of feature A at the same time There seems to be a relation

Order rate vs response time?

@MartinGoodwell

Correlating Business and Tech

Any error count makes a great candidate for correlation with most metrics

@MartinGoodwell

Build 17 testNewsAlert OKtestSearch OK

Build # Use Case Stat # API Calls # SQL Payload CPU

1 5 2kb 70ms1 3 5kb 120ms

Tests Metrics

Build 26 testNewsAlert OKtestSearch OK

Build 25 testNewsAlert OKtestSearch OK

1 4 1kb 60ms34 171 104kb 550ms

Ops#ServInst Usage RT

1 0.5% 7.2s

1 63% 5.2s

1 4 1kb 60ms2 3 10kb 150ms

1 0.2% 5.2s

5 75% 2.5s

Build 35 testNewsAlert -testSearch OK

- - - -2 3 10kb 150ms

- - -8 80% 2.0

s

Metrics from and for Dev(to)Ops

Re-architecture -> Performance Fixes

@MartinGoodwell

How to export your own metricsFor Ops: How to tell your Devs how to export their own metrics

@MartinGoodwellBy Donsez - self-made, CC BY-SA 3.0, https://en.wikipedia.org/w/index.php?curid=6721989

@MartinGoodwell

Vanilla JMX

https://docs.oracle.com/javase/tutorial/jmx/mbeans/standard.html

@MartinGoodwellhttps://docs.oracle.com/javase/tutorial/jmx/mbeans/standard.html

@MartinGoodwellhttps://docs.oracle.com/javase/tutorial/jmx/mbeans/standard.html

@MartinGoodwell

JMX with Spring Boot

Spring simplifies JMX by creating an MBean server automatically (as does eg Tomcat) less boilerplate code for registering your own MBeans

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JMX Tools

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JConsole, JVisualVM

Pro Comes with JVM

Con Once you quit, all data is lost

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Nagios Core Pro

Allows you to combine all different types of metrics

Host Application

Con Very tedious to setup

Dedicated plugins for each technology

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Dynatrace Allows you to combine all different types of

metrics Host Application

Zero-conf, auto-detection

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Bridges (eg JMX to HTTP)

https://jolokia.org/reference/html/protocol.html

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Downsides of JMX

For Java code only Finding the right spots for monitoring might require some iterations

Potential source of „Hell Breaks Loose“ Triggering methods out of context Changing configuration values in-memory only

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Alternatives?

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statsd real quick

http://www.slideshare.net/DatadogSlides/dev-opsdays-tokyo2013effectivestatsdmonitoring@MartinGoodwell

@MartinGoodwell

Java code calling statsd client

http://rick-hightower.blogspot.co.uk/2015/05/working-with-statsd-and-java.html

@MartinGoodwell

Why JMX over other alternatives?

You might be using it already for JVM-metrics (or Tomcat, etc) GC, CPU-usage, requests, etc

While still „polluting“ your code, interfaces allow for good structures Allows to interact with the application (although I wouldn‘t

recommend this) Notifications on a code-level (

https://docs.oracle.com/javase/tutorial/jmx/notifs/index.html) Comes with JVM – saves you from bloating small solutions with

dependencies

@MartinGoodwell

Shout outRight after lunch break at 14.30In Room Silcher-Saal

@MartinGoodwell

“Go then, there are other worlds than these.”— Jake Chambers, The Dark Tower

martin.gutenbrunner@dynatrace.com@MartinGoodwellDynatrace Innovation Labhttp://blog.ruxit.comhttp://www.dynatrace.com

@MartinGoodwell

References

JMX-Technology homepage http://www.oracle.com/technetwork/java/javase/tech/javamanagement-140525.

html Monitoring and Managing the Java Platform using JMX technology

https://docs.oracle.com/javase/8/docs/technotes/guides/management/agent.html

Call-tracing and performance management in microservice environments http://www.slideshare.net/MartinGoodwell/performance-monitoring-and-call-trac

ing-in-microservice-environments Jolokia https://jolokia.org/ Nagios https://www.nagios.org/ statsd https://github.com/etsy/statsd/wiki Sleepless Dev http://rick-hightower.blogspot.co.uk