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  Think Big – Now Think Even Bigger
  Join Us at Internet of Things at Cloud Expo, November 11-13,
at the Javits Center!


The Internet of Things (IoT) is the most profound change in personal and enterprise IT since the creation of the Worldwide Web more than 20 years ago.

All major researchers estimate there will be tens of billions devices - computers, smartphones, tablets, and sensors - connected to the Internet by 2020. This number will continue to grow at a rapid pace for the next several decades.

With major technology companies and startups seriously embracing IoT strategies, now is the perfect time to attend Internet of Things at Cloud Expo in New York City. Learn what is going on, contribute to the discussions, and ensure that your enterprise is as "IoT-Ready" as it can be!

Delegates to Internet of Things at Cloud Expo will be able to attend eight separate, information-packed tracks:

  • Enterprise Cloud
  • Digital Transformation
  • The API Enterprise | Mobility & Security
  • DevOps | Containers & Microservices
  • Cognitive Computing | AI, ML, DL
  • Big Data | Analytics
  • IoT | IIoT | Smart Cities
  • Hot Topics | FinTech | WebRTC

There are 120 breakout sessions in all, with Keynotes, General Sessions, and Power Panels adding to three days of incredibly rich presentations and content.


We'll see you in New York!



Day 3 Keynote at @ThingsExpo | Chris Matthieu, CTO of Octoblu
In his keynote at @ThingsExpo, Chris Matthieu, Director of IoT Engineering at Citrix and co-founder and CTO of Octoblu, focused on building an IoT platform and company. He provided a behind-the-scenes look at Octoblu's platform, business, and pivots along the way (including the Citrix acquisition of Octoblu).
  Themes & Topics to Be Discussed

Consumer IoT
• Wearables
• Smart Appliances
• Smart Cars
• Smartphones 2.0
• Automation
• Smart Travel
• Personal Fitness
• Health Care
• Personalized Marketing
• Customized Shopping
• Personal Finance
• The Digital Divide
• Mobile Cash & Markets
• Games & The IoT
• The Future of Education
• Virtual Reality

Enterprise IoT
• The Business Case for
x IoT
• Smart Grids
• Smart Cities
• Smart Transportation
• The Smart Home
• M2M
• Authentication/Security
• Wiring the IoT
• The Internet of
x Everything
• Digital Transformation
x of Enterprise IT
• Agriculture
• Transportation
• Manufacturing
• Local & State
x Government
• Federal Government

IoT Developers | WebRTC Summit
• Eclipse Foundation
• Cloud Foundry
• Linux Containers
• Node-Red
• Open Source Hardware
• Ajax and the IoT
• Leveraging SOA
• Multi-Cloud IoT
• Evolving Standards
• WebSockets
• Security & Privacy
x Protocols
• GPS & Proximity
x Services
• Bluetooth/RFID/etc
• XMPP
• Nest Labs



The Top Keynotes, the Best Sessions, a Rock Star Faculty and the Most Qualified Delegates of ANY Internet of Things Event!


The future of computing lies in these things. As computing takes a much more active role in our lives it will at the same time become much more invisible. Internet of Things Expo will address the challenges in getting from where we are today to this future.
 
The high-energy event is a must-attend for senior technologists from CEOs on down – including CIOs, CTOs, directors of infrastructure, VPs of technology, IT directors and managers, network and storage managers, network engineers, enterprise architects, and communications and networking specialists.




@ThingsExpo Power Panel | The World's Many IoTs: Which Are the Most Important?
The Internet of Things is clearly many things: data collection and analytics, wearables, Smart Grids and Smart Cities, the Industrial Internet, and more. Cool platforms like Arduino, Raspberry Pi, Intel's Galileo and Edison, and a diverse world of sensors are making the IoT a great toy box for developers in all these areas. In this Power Panel at @ThingsExpo, panelists discussed what things are the most important, which will have the most profound effect on the world, and what should we expect to see over the next couple of years.
Benefits of Attending the Three-Day Technical Program
  LEARNexactly why Internet of Things is relevant today from an economic, business and technology standpoint.
  HEAR first-hand from industry experts the common issues and requirements for creating a platform for the Internet of Things.
  SEE what new tools and approaches the Internet of Things requires.
  DISCOVER how to drive a distributed approach to the Internet of Things, where applications move to the data.
  FIND OUThow the vast volumes of new data produced by the Internet of Things provides a valuable new source of business insight through advanced analytical techniques.
  MASTER how the ongoing development of smart cities, cars, and houses will enhance connectivity infrastructure.
Lunch Power Panel | Microservices & IoT- Moderated by Jason Bloomberg
In this Power Panel at @DevOpsSummit, moderated by Jason Bloomberg, president of Intellyx, panelists Roberto Medrano, Executive Vice President at Akana; Lori MacVittie, Evangelist for F5 Networks; and Troy Topnik, ActiveState's Technical Product Manager; and Otis Gospodnetic, founder of Sematext; peeled away the buzz and discuss the important architectural principles behind implementing IoT solutions for the enterprise. As remote IoT devices and sensors become increasingly intelligent, they become part of our distributed cloud environment, and we must architect and code accordingly. At the very least, you'll have no problem filling in your buzzword bingo cards.


Software Quality Metrics for Your Continuous Delivery Pipeline | Part 3
It is safe to say that insightful logging and performance are two opposite goals

Let me ask you a question: would you say that you have implemented logging correctly for your application? Correct in the sense that it will provide you with all the insights you require to keep your business going once your users are struck by errors? And in a way that does not adversely impact your application performance? Honestly, I bet you have not. Today I will explain why you should turn off logging completely in production because of its limitations:

  • Relies on Developers
  • Lacks Context
  • Impacts Performance

Intrigued? Bear with me and I will show you how you can still establish and maintain a healthy and useful logging strategy for your deployment pipeline, from development to production, guided by metrics.

What Logging Can Do for You
Developers, including myself, often write log messages because they are lazy. Why should I set a breakpoint and fire up a debugger if it is so much more convenient to dump something to my console via a simple println()? This simple yet effective mechanism also works on headless machines where no IDE is installed, such as staging or production environments:

System.out.println("Been here, done that.");

Careful coders would use a logger to prevent random debug messages from appearing in production logs and additionally use guard statements to prevent unnecessary parameter construction:

if (logger.isDebugEnabled()) {
logger.debug("Entry number: " + i + " is " + String.valueOf(entry[i]));
}

Anyways, the point about logging is that that traces of log messages allow developers to better understand what their program is doing in execution. Does my program take this branch or that branch? Which statements were executed before that exception was thrown? I have done this at least a million of times, and most likely so have you:

if (condition) {
logger.debug("7: yeah!")
} else {
logger.debug("8: DAMN!!!")
}

Test Automation Engineers, usually developers by trade, equally use logging to better understand how the code under test complies with their test scenarios:

class AgentSpec extends spock.lang.Specification {

def "Agent.compute()"() {
def agent = AgentPool.getAgent()

when:
def result = agent.compute(TestFixtures.getData())

then:
logger.debug("result: "  + result);
result == expected
}
}

Logging is, undoubtedly, a helpful tool during development and I would argue that developers should use it as freely as possible if it helps them to understand and troubleshoot their code.

In production, application logging is useful for tracking certain events, such as the occurrence of a particular exception, but it usually fails to deliver what it is so often mistakenly used for: as a mechanism for analyzing application failures in production. Why?

Because approaches to achieving this goal with logging are naturally brittle: their usefulness depends heavily on developers, messages are without context, and if not designed carefully, logging may severely slow down your application.

Secretly, what you are really hoping to get from your application logs, in the one or the other form, is something like this:

A logging strategy that delivers out-of-the-box using dynaTrace: user context, all relevant data in place, zero config

The Limits of Logging
Logging Relies on Developers
Let's face it: logging is, inherently, a developer-centric mechanism. The usefulness of your application logs stands and falls with your developers. A best practice for logging in production says: "don't log too much" (see Optimal Logging @ Google testing blog). This sounds sensible, but what does this actually mean? If we recall the basic motivation behind logging in production, we could equally rephrase this as "log just enough information you need to know about a failure that enables you to take adequate actions". So, what would it take your developers to provide such actionable insights? Developers would need to correctly anticipate where in the code errors would occur in production. They would also need to collect any relevant bits of information along an execution path that bear these insights and, last but not least, present them in a meaningful way so that others can understand, too. Developers are, no doubt, a critical factor to the practicality of your application logs.

Logging Lacks Context
Logging during development is so helpful because developers and testers usually examine smaller, co-located units of code that are executed in a single thread. It is fairly easy to maintain an overview under such simulated conditions, such as a test scenario:

13:49:59 INFO com.company.product.users.UserManager - Registered user ‘foo'.
13:49:59 INFO com.company.product.users.UserManager - User ‘foo' has logged in.
13:49:59 INFO com.company.product.users.UserManager - User ‘foo' has logged out.

But how can you reliably identify an entire failing user transaction in a real-life scenario, that is, in a heavily multi-threaded environment with multiple tiers that serve piles of distributed log files? I say, hardly at all. Sure, you can go mine for certain isolated events, but you cannot easily extract causal relationships from an incoherent, distributed set of log messages:

13:49:59 INFO com.company.product.users.UserManager - User ‘foo' has logged in.
13:49:59 INFO com.company.product.users.UserManager - User ‘bar' has logged in.
...
13:49:60 SEVERE org.hibernate.exception.JDBCConnectionException: could not execute query
at org.hibernate.exception.SQLStateConverter.convert(SQLStateConverter.java:99)
...

After all, the ability to identify such contexts is key to deciding why a particular user action failed.

Logging Impacts Performance
What is a thorough logging strategy worth if your users cannot use your application because it is terribly slow? In case you did not know, logging, especially during peak load times, may severely slow down your application. Let's have a quick look at some of the reasons:

Writing log messages from the application's memory to persistent storage, usually to the file system, demands substantial I/O (see Top Performance Mistakes when moving from Test to Production: Excessive Logging). Traditional logger implementations wrote files by issuing synchronous I/O requests, which put the calling thread into a wait state until the log message was fully written to disk.

In some cases, the logger itself may cause a decent bottle-neck: in the Log4j library (up to version 1.2), every single log activity results in a call to an internal template method Appender.doAppend() that is synchronized for thread-safety (see Multithreading issues - doAppend is synchronised?). The practical implication of this is that threads, which log to the same Appender, for example a FileAppender, must queue up with any other threads writing logs. Consequently, the application spends valuable time waiting in synchronization instead of doing whatever the app was actually designed to do. This will hurt performance, especially in heavily multi-thread environments like web application servers.

These performance effects can be vastly amplified when exception logging comes into play: exception data, such as error message, stack trace and any other piggy-backed exceptions ("initial cause exceptions") greatly increase the amount of data that needs to be logged. Additionally, once a system is in a faulty state, the same exceptions tend to appear over and over again, further hurting application performance. We had once monitored a 30% drawdown on CPU resources due to more than 180,000 exceptions being thrown in only 5 minutes on one of our application servers (see Performance Impact of Exceptions: Why Ops, Test and Dev need to care). If we had written these exceptions to the file system, they would have trashed I/O, filled up our disk space in no time and had considerably increased our response times.

Subsequently, it is safe to say that insightful logging and performance are two opposite goals: if you want the one, then you have to make a compromise on the other.

For more logging tips click here for the full article.

About Martin Etmajer
Leveraging his outstanding technical skills as a lead software engineer, Martin Etmajer has been a key contributor to a number of large-scale systems across a range of industries. He is as passionate about great software as he is about applying Lean Startup principles to the development of products that customers love.

Martin is a life-long learner who frequently speaks at international conferences and meet-ups. When not spending time with family, he enjoys swimming and Yoga. He holds a master's degree in Computer Engineering from the Vienna University of Technology, Austria, with a focus on dependable distributed real-time systems.

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