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Difference Between #BigData and Internet of Things | @ThingsExpo #IoT #M2M
What does it mean, as a vendor, to say that you support the Internet of Things (IoT) from an analytics perspective?

A recent argument with folks whose intelligence I hold in high regard (like Tom, Brandon, Wei, Anil, etc.) got me thinking about the following question:

What does it mean, as a vendor, to say that you support the Internet of Things (IoT) from an analytics perspective?

I think the heart of that question really boils down to this:

What are the differences between big data (which is analyzing large amounts of mostly human-generated data to support longer-duration use cases such as predictive maintenance, capacity planning, customer 360 and revenue protection) and IoT (which is aggregating and compressing massive amounts of low latency / low duration / high volume machine-generated data coming from a wide variety of sensors to support real-time use cases such as operational optimization, real-time ad bidding, fraud detection, and security breach detection)?

I don’t believe that loading sensor data into a data lake and performing data science to create predictive analytic models qualifies as doing IoT analytics.  To me, that’s just big data (and potentially REALLY BIG DATA with all that sensor data).  In order for one to claim that they can deliver IoT analytic solutions requires big data (with data science and a data lake), but IoT analytics must also include:

  1. Streaming data management with the ability to ingest, aggregate (e.g., mean, median, mode) and compress real-time data coming off a wide variety of sensor devices “at the edge” of the network, and
  2. Edge analytics that automatically analyzes real-time sensor data and renders real-time decisions (actions) at the edge of the network that optimizes operational performance (blade angle or yaw) or flags unusual performance or behaviors for immediate investigation (security breaches, fraud detection).

If you cannot manage real-time streaming data and make real-time analytics and real-time decisions at the edge, then you are not doing IOT or IOT analytics, in my humble opinion.  So what is required to support these IoT data management and analytic requirements?

The IoT “Analytics” Challenge
The Internet of Things (or Industrial Internet) operates at machine-scale, by dealing with machine-to-machine generated data.  This machine-generated data creates discrete observations (e.g., temperature, vibration, pressure, humidity) at very high signal rates (1,000s of messages/sec).  Add to this the complexity that the sensor data values rarely change (e.g., temperature operates within an acceptably small range).  However, when the values do change the ramifications, the changes will likely be important.

Consequently to support real-time edge analytics, we need to provide detailed data that can flag observations of concern, but then doesn’t overwhelm the ability to get meaningful data back to the core (data lake) for more broad-based, strategic analysis.

One way that we see organizations addressing the IoT analytics needs is via a 3-tier Analytics Architecture (see Figure 1).

Figure 1: IoT Analytics 3-Tier Architecture

We will use a wind turbine farm to help illustrate the 3-tier analytics architecture capabilities.

Tier 1 performs individual wind turbine real-time performance analysis and optimization.  Tier 1 must manage (ingest and compress) real-time data streams coming off of multiple, heterogeneous sensors. Tier 1 analyzes the data, and processes the incoming data against static or dynamically updated analytic models (e.g., rules-based, decision trees) for immediate or near-immediate actions.

Purpose-built T1 edge gateways leverage real-time data compression techniques (e.g., see the article “timeseries storage and data compression” for more information on timeseries databases) to only send a subset of the critical data (e.g., data that has changed) back to T2 and T3 (core).

Let’s say that you are monitoring the temperatures of a compressor inside of a large industrial engine.  Let’s say the average temperature of that compressor is 99 degrees, and only varies between 98 to 100 degrees within a 99% confidence level.  Let’s also say the compressor is emitting the following temperature readings 10 times a second:

99, 99, 99, 98, 98, 99, 99, 98, 99, 99, 100, 99, 99, 99, 100, 99, 98, 99, 99…

You have 10,000 of readings that don’t vary from that range.  So why send all of the readings (which from a transmission bandwidth perspective could be significant)?  Instead, use a timeseries database to only send mean, medium, mode, variances, standard deviation and other statistical variables of the 10,000 readings instead of the individual 10,000 readings.

However, let’s say that all of a sudden we start getting readings outside the normal 99% confidence level:

99, 99, 99, 100, 100, 101, 101, 102, 102, 103, 104, 104, 105, …

Then we’d apply basic Change Data Capture (CDC) techniques to capture and transmit the subset of critical data to T2 and T3 (core).

Consequently, edge gateways leverage timeseries compression techniques to drive faster automated decisions while only sending a subset of critical data to the core for further analysis and action.

The Tier 1 analytics are likely being done via an on-premise analytics server or gateway (see Figure 2).

Figure 2:  IoT Tier 1 Analytics

Tier 2 optimizes performance and predicts maintenance needs across the wind turbines in the same wind farm.  Tier 2 requires a distributed dynamic content processing rule generation and execution analytics engine that integrates and analyzes data aggregated across the potentially heterogeneous wind turbines. Cohort analysis is typical in order to identify, validate and codify performance problems and opportunities across the cohort wind turbines.  For example, in the wind farm, the Tier 2 analytics are responsible for real-time learning that can generate the optimal torque and position controls for the individual wind turbines. Tier 2 identifies and shares best practices across the wind turbines in the wind farm without having to be dependent upon the Tier 3 core analytics platform (see Figure 3).

Figure 3: Tier 2 Analytics: Optimizing Cohort Performance

Tier 3 is the data lake enabled core analytics platform. The tier 3 core analytics platform includes analytics engines, data sets and data management services (e.g., governance, metadata management, security, authentication) that enable access to the data (sensor data plus other internal and external data sources) and existing analytic models that supports data science analytic/predictive model development and refinement.  Tier 3 aggregates the critical data across all wind farms and individual turbines, and combines the sensor data with external data sources which could include weather (humidity, temperatures, precipitation, air particles, etc.), electricity prices, wind turbine maintenance history, quality scores for the wind turbine manufacturers, and performance profiles of the wind turbine mechanics and technicians (see Figure 4).

Figure 4:  Core Analytics for Analytic Model Development and Refinement

With the rapid increase in storage and processing power at the edges of the Internet of Things (for example, the Dell Edge Gateway 3000 Series), we will see more and more analytic capabilities being pushed to the edge.

How Do You Start Your IoT Journey
While the rapidly evolving expertise on the IoT edge technologies can be very exciting (graphical processing units in gateway servers with embedded machine learning capabilities with 100’s of gigabytes of storage), the starting point for the IoT journey must first address this basic question:

How effective is your organization at leveraging data and analytics to power your business (or operational) models?

We have tweaked the Big Data Business Model Maturity Index to help organizations not only understand where they sit on the maturity index with respect to the above question, but also to provide a roadmap for how organizations can advance up the maturity index to become more effective at leveraging the wealth of IOT data with advanced analytics to power their business and operational models (see Figure 5).

Figure 5:  Big Data / IoT Business Model Maturity IndexMaturity Index

To drive meaningful business impact, you will need to begin with the business and not the technology:

  • Engage the business stakeholders on day one,
  • Align the business and IT teams
  • Understand the organization’s key business and operational initiatives, and
  • Identify and prioritize the use cases (decisions/goals) that support those business initiatives.

If you want to monetize your IOT initiatives, follow those simple guidelines and you will dramatically increase the probability of your business and monetization success.

For more details on the Internet of Things revolution, check out these blogs:

The post Difference between Big Data and Internet of Things appeared first on InFocus Blog | Dell EMC Services.

About William Schmarzo
Bill Schmarzo, author of “Big Data: Understanding How Data Powers Big Business”, is responsible for setting the strategy and defining the Big Data service line offerings and capabilities for the EMC Global Services organization. As part of Bill’s CTO charter, he is responsible for working with organizations to help them identify where and how to start their big data journeys. He’s written several white papers, avid blogger and is a frequent speaker on the use of Big Data and advanced analytics to power organization’s key business initiatives. He also teaches the “Big Data MBA” at the University of San Francisco School of Management.

Bill has nearly three decades of experience in data warehousing, BI and analytics. Bill authored EMC’s Vision Workshop methodology that links an organization’s strategic business initiatives with their supporting data and analytic requirements, and co-authored with Ralph Kimball a series of articles on analytic applications. Bill has served on The Data Warehouse Institute’s faculty as the head of the analytic applications curriculum.

Previously, Bill was the Vice President of Advertiser Analytics at Yahoo and the Vice President of Analytic Applications at Business Objects.

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MEEHAN
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WITECK
Citrix

LEUFFEN
Wrecker

ROGERS
Anexia

NEW
HOUSE

Agilitiv

DE MENO
Commvault

VAN TUIN
Red Hat

LIANG
Rancher Labs

BUTLER
Tego

MURTHY
Cloud Raxak

REMIL-
LARD

Microsoft

MANN
Splunk

ROWE
IBM Cloud

SKILLERN
Intel

ALLEN
Progress

BENEDICT
Cognizant

SMITH
Numerex
Cloud Expo New York All-Star Speakers Include

DE MENO
Commvault

ERWAY
Appneta

KEYS
ConsenSys

HINCH-
CLIFFE

7Summits

DOYLE
eCube

CHAVES
Pythian

BLOOMBERG
Intellyx

BUGAYENKO
Teamed.io

LAWSON
NewSci

HAFF
RedHat

HOLT
IBM

Jewell
Codenvy

MORGENTHAL
CSC

ARMSTRONG
AppNeta

DWYER
Iron.io

MATSUMURA
Gradle

WARFIELD
Coho

CLELAND
HGST

VASILIOU
Catchpoint

WALLGREN
Electric Cloud

DE SOUZA
Cisco

RANDALL
Gartner

ARMSTRONG
AppNeta

SMALLTREE
Cazena

MCCARTHY
Bsquare

DELOACH
Infobright

QUINT
Ontegrity

MCLAUCHLAN
Buddy Platform

MCCALLUM
Falconstor

GRECO
Kaazing

PRESLEY
Pythian

LOVELL-TROY
Pythian

PALIOTTA
Vector

ATCHISON
New Relic

BHUSVANE-
SHWARI

Microsoft

MITRA
Cognizant

KOCHER
Grey Heron

GUCCIONE
Keeper

PAPDO
POULOS

Cloud9

FLOREA
Tintri

HARLAN
Two Bulls

GOLO
SHUBIN

Bit6

KERBY
BMC

PROIETTI
Location
Smart

MARTIN
nfrastructure

RAO
Asurion

BRENTON
CollabNet

MOULINE
Everbridge

MARSH
Blue Pillar

SRINIVASAN
Symantec

GALBRAITH
HPE

NEWTON
Alfresco

PARKS
SecureRF

PEROTTI
Plantronics

ROGERS
Anexia

HOFFMAN
EastBanc

MORRISH
Interoute

TIFFANY
SoftLayer

OSTROVER-
KHYI

Mobidev

LEWIS
Formation
Data

KENDRICK
Isomorphic

WATSON
Trendalyze

BENSONOFF
Unigma

REEVES
Datical

WALLER-
STORFER

Dynatrace

CIOT
Progress

SHAN
CTS

MATTELA
Redpine

MOR
Cloudyn

GILLEN
Spark
Coginition

SOLT
Netvibes

BERNARDO
GE Digital

ROMANSKY
TrustPoint

LEFORT
BMC

ANDERSON
BMC

BRODY
Webair

NIELSEN
Redis Labs

BEAMER
GoTransverse

LESTER
LogMeIn

PONO
-MAREVA

Google

SINGH
Sencha

CALKINS
Amadeus

SEHGAL
Tintri

KLEIN
Rachio

MANN
Splunk

HOASIN
Aeris

SARKARIA
PHEMI

SPROULE
Metavine

YOO
Fuze

SNELL
Intel

COTY
Alert Logic

LANDA
Kintone

CHOQUETTE
RackN

MARTIN
Security

LEVINE
CytexOne

ALLEN
Freewave

HURWITZ
Hurwitz & Assc.

HYEDT
Seamless

SWANN
Adobe

NGUYEN
Adobe

OXENHORN
FalconStor

RAJAGO-
PALAN

ACCELERITE

DESH-
PANDE

ACCELERITE

MURTHY
Cloud Raxak

HARRIS
Cloud Raxak

COLE
Peak 10

HUYNH
VAN

Glue Networks

SOBHANI
Constellation

BERMING
HAM

SIOS

STEELE
Hanu

AKELA
Appdynamics

DOWNEY
BMC

ERRAM
OUSPE

Spanning

SAADI
Govplace

JACOBS
Singlehop

KEE
GlobalSign

Cloud Expo Silicon Valley All-Star Speakers Include

KOWALL
AppDynamics

VAN TUIN
Red Hat

DEMMER
Jut

COHEN
Netflix

MUCHANDI
Red Hat Inc

BORELLO
Sysdig

GILPIN
Conjur

KANADE
Harbinger
Systems

GORBACHEV
Systems
Services Inc.

SUSSMAN
Coalfire

KHAN
Solgeniakhela

CHOKSI
Harbinger
Systems

DE MENO
CommVault

BLOOMBERG
Intellyx

BUGWADIA
Nirmata

COTY
Alert Logic

FLETCHER
Alert Logic

CAUTHRON
NIMBOXX

LYNN
AgilData

WAGNER
Cloudyn

ANAND
Appocito

WEISS
Pythian

BRODY
Webair

JACKSON
Softlayer

DAVIDSON
Juniper

HOFFMAN
Pivotal

VERVAET
HGST

Murthy
CloudRaxak

FRANCISCO
Evolute

LETCHIN
Nexenta

SIMON
JFrog

BONIFAZI
Solgenia

WEISS
ProfitBricks

HOLT
IBM

HANNON
SoftLayer

GALLO
SoftLayer

SAYEGH
Codero

BIMMU
Clouber

SRINIVAS
IBM

CHAVAN
IBM

HEDGES
Clouddata

AHUJA
Cloud

MEINER
Oracle

SWARTZ
Ericsson
Cloud Expo New York All-Star Speakers Included

DE SOUZA
Cisco

POTTER
SafeLogic

ROBINSON
CompTIA

WARUSA
-WITHANA

WSO2 Inc

MEINER
Oracle

CHOU
Microsoft

HARRISON
Tufin

BRUNOZZI
VMware

KIM
MapR

KANE
Dyn

SICULAR
Basho

TURNER
Cloudian

KUMAR
Liaison

ADAMIAK
Liaison

KHAN
Solgenia

BONIFAZI
Solgenia

SUSSMAN
Coalfire

ISAACSON
RMS

LYNN
CodeFutures

HEABERLIN
Windstream

RAMA
MURTHY

Virtusa

BOSTOCK
IndependenceIT

DE MENO
CommVault

GRILLI
Adobe

WILLIAMS
Rancher Labs

CRISWELL
Alert Logic

COTY
Alert Logic

JACOBS
SingleHop

MARAVEI
Cisco

JACKSON
Softlayer

SINGH
IBM

HAZARD
Softlayer

GALLO
Softlayer

TAMASKAR
GENBAND

SUBRA
-MANIAN

Emcien

LEVESQUE
Windstream

IVANOV
StorPool

BLOOMBERG
EnterpriseWeb

BUDHANI
Soha

HATHAWAY
IBM Watson

TOLL
ProfitBricks

LANDRY
Microsoft

BEARFIELD
Blue Box

HERITAGE
Akana

PILUSO
SIASMSP

HOLT
IBM Cloudant

SHAN
CTS

PICCININNI
EMC

BRON-
GERSMA

Modulus

PAIGE
CenturyLink

SABHIKHI
Cognitive Scale

MILLS
Green House Data

KATZEN
CenturyLink

SLOPER
CenturyLink

SRINIVAS
EMC

TALREJA
Cisco

GORBACHEV
Systems Services Inc.

COLLISON
Apcera

PRABHU
OpenCrowd

LYNN
CodeFutures

SWARTZ
Ericsson

MOSHENKO
CoreOS

BERMINGHAM
SIOS

WILLIS
Stateless Networks

MURPHY
Gridstore

KHABE
Vicom

NIKOLOV
GetClouder

DIETZE
Windstream

DALRYMPLE
EnterpriseDB

MAZZUCCO
TierPoint

RIVERA
WHOA.com

HERITAGE
Akana

SEYMOUR
6fusion

GIANNETTO
Author

CARTER
IBM

ROGERS
Virtustream
Cloud Expo Silicon Valley All-Star Speakers

TESAR
Microsoft

MICKOS
HP

BHARGAVA
Intel

RILEY
Riverbed

DEVINE
IBM

ISAACSON
CodeFutures

LYNN
HP

HINKLE
Citrix

KHAN
Solgenia

SINGH
Bigdata

BEACH
SendGrid

BOSTOCK
IndependenceIT

DE SOUZA
Cisco

PATTATHIL
Harbinger

O'BRIEN
Aria Systems

BONIFAZI
Solgenia

BIANCO
Solgenia

PROCTOR
NuoDB

DUGGAL
EnterpriseWeb

TEGETHOFF
Appcore

BRUNOZZI
VMware

HICKENS
Parasoft

KLEBANOV
Cisco

PETERS
Esri

GOLDBERG
Vormetric

CUMBER-
LAND

Dimension

ROSENDAHL
Quantum

LOOMIS
Cloudant

BRUNO
StackIQ

HANNON
SoftLayer

JACKSON
SoftLayer

HOCH
Virtustream

KAPADIA
Seagate

PAQUIN
OnLive

TSAI
Innodisk

BARRALL
Connected Data

SHIAH
AgilePoint

SEGIL
Verizon

PODURI
Citrix

COWIE
Dyn

RITTEN-
HOUSE

Cisco

FALLOWS
Kaazing

THYKATTIL
TimeWarner

LEIDUCK
SAP

LYNN
HP

WAGSTAFF
BSQUARE

POLLACK
AOL

KAMARAJU
Vormetric

BARRY
Catbird

MENDEN-
HALL

SUPERNAP

SHAN
KEANE

PLESE
Verizon

BARNUM
Voxox

TURNER
Cloudian

CALDERON
Advanced Systems

AGARWAL
SOA Software

LEE
Quantum

OBEROI
Concurrent, Inc.

HATEM
Verizon

GALEY
Autodesk

CAUTHRON
NIMBOXX

BARSOUM
IBM

GORDON
1Plug

LEWIS
Verizon

YEO
OrionVM

NAKAGAWA
Transparent Cloud Computing

SHIBATA
Ubiquitous Corp

NATH
GE

GOKCEN
GE

STOICA
Databricks

TANKEL
Pivotal Software

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@CloudExpo Blogs
I recently had the opportunity to give a 10-minute keynote at DataWorks Summit 2017. I know what most of you are thinking: Schmarzo can barely introduce himself in 10 minutes! What sort of keynote could he give in just 10 minutes? And to be honest, I too struggled with what to say. But after some brainstorming with my marketing experts (Jeff Abbott, Erin Banks, and Chris Hill), we came up with an idea: Pose 5 questions that every organization needs to consider as they prepare themselves for digital transformation. And while I didn’t have enough time in 10 minutes to answer those questions...
All organizations that did not originate this moment have a pre-existing culture as well as legacy technology and processes that can be more or less amenable to DevOps implementation. That organizational culture is influenced by the personalities and management styles of Executive Management, the wider culture in which the organization is situated, and the personalities of key team members at all levels of the organization. This culture and entrenched interests usually throw a wrench in the works because of misaligned incentives.
Because IoT devices are deployed in mission-critical environments more than ever before, it’s increasingly imperative they be truly smart. IoT sensors simply stockpiling data isn’t useful. IoT must be artificially and naturally intelligent in order to provide more value In his session at @ThingsExpo, John Crupi, Vice President and Engineering System Architect at Greenwave Systems, will discuss how IoT artificial intelligence (AI) can be carried out via edge analytics and machine learning technologies that enable things to process event data at the source, learn patterns of behavior over time...
FinTechs use the cloud to operate at the speed and scale of digital financial activity, but are often hindered by the complexity of managing security and compliance in the cloud. In his session at 20th Cloud Expo, Sesh Murthy, co-founder and CTO of Cloud Raxak, showed how proactive and automated cloud security enables FinTechs to leverage the cloud to achieve their business goals. Through business-driven cloud security, FinTechs can speed time-to-market, diminish risk and costs, maintain continuous compliance, and set themselves up for success.
"Suddenly a lot of companies started focusing on producing services in the cloud. I like to call it Cloud Native - everything is built for the cloud. The main concept there is to enable developers to work fast," explained Ben Bernstein, CEO & Co-Founder of Twistlock, in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
These days, change is the only constant. In order to adapt and thrive in an ever-advancing and sometimes chaotic workforce, companies must leverage intelligent tools to streamline operations. While we're only at the dawn of machine intelligence, using a workflow manager will benefit your company in both the short and long term. Think: reduced errors, improved efficiency and more empowered employees-and that's just the start. Here are five other reasons workflow automation is leading a revolution in the 9-5 world.
As today's digital disruptions bounce and smash their way through conventional technologies and conventional wisdom alike, predicting their path is a multifaceted challenge. So many areas of technology advance on Moore's Law-like exponential curves that divining the future is fraught with danger. Such is the problem with artificial intelligence (AI), and its related concepts, including cognitive computing, machine learning, and deep learning.
There are several reasons why businesses migrate their operations to the cloud. Scalability and price are among the most important factors determining this transition. Unlike legacy systems, cloud based businesses can scale on demand. The database and applications in the cloud are not rendered simply from one server located in your headquarters, but is instead distributed across several servers across the world. Such CDNs also bring about greater control in times of uncertainty. A database hack can be easily averted by shutting down the breached server and only rendering from servers that are ...
We have Continuous Integration and we have Continuous Deployment, but what’s continuous across all of what we do is people. Even when tasks are automated, someone wrote the automation. So, Jayne Groll evangelizes about Continuous Everyone. Jayne is the CEO of the DevOps Institute and the author of Agile Service Management Guide. She talked about Continuous Everyone at the 2016 All Day DevOps conference. She describes it as "about people, culture, and collaboration mapped into your value streams."
Blockchain is a shared, secure record of exchange that establishes trust, accountability and transparency across business networks. Supported by the Linux Foundation's open source, open-standards based Hyperledger Project, Blockchain has the potential to improve regulatory compliance, reduce cost as well as advance trade. Are you curious about how Blockchain is built for business? In her session at 21st Cloud Expo, René Bostic, Technical VP of the IBM Cloud Unit in North America, will discuss the basics of Blockchain, preview the Blockchain Reference Architecture, and introduce the mechanics o...
API Security is complex! Vendors like Forum Systems, IBM, CA and Axway have invested almost 2 decades of engineering effort and significant capital in building API Security stacks to lockdown APIs. The API Security stack diagram shown below is a building block for rapidly locking down APIs. The four fundamental pillars of API Security - SSL, Identity, Content Validation and deployment architecture - are discussed in detail below.
SYS-CON Events announced today that GrapeUp, the leading provider of rapid product development at the speed of business, will exhibit at SYS-CON's 21st International Cloud Expo®, which will take place October 31-November 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Grape Up is a software company, specialized in cloud native application development and professional services related to Cloud Foundry PaaS. With five expert teams that operate in various sectors of the market across the USA and Europe, we work with a variety of customers from emerging startups to Fortune 1000 c...
Having a well-rounded brand strategy helps you identify the marketing channels you must focus on, and defines every aspect of how your business is viewed by your customers. Marketing and advertising is an integral component of every business. The US Small Business Administration recommends that businesses with do under $5 million in gross sales and whose net profit margin is in the 10-12% should spend at least 7-8% of their gross revenue in marketing and advertising. In other words, if you are doing $100,000 in annual revenue, you should be spending around $8,000 a year in advertising your b...
In Michael Lewis’s 2013 best-seller Flash Boys, in which he takes a deep dive into the world of high-speed trading, he reveals how certain financial insiders had managed to game the system by reducing latency as much as possible in order to get an advantage over their competitors. Lewis showed how a fiberoptic connection that is just a millisecond or two faster than someone else’s can allow automated trading software to conduct transactions at the lowest possible prices. For the user (or machine) that had just the tiniest increase in latency, a stock price would appear on screen, but by the ti...
We define Hybrid IT as a management approach in which organizations create a workload-centric and value-driven integrated technology stack that may include legacy infrastructure, web-scale architectures, private cloud implementations along with public cloud platforms ranging from Infrastructure-as-a-Service to Software-as-a-Service.
SYS-CON Events announced today that DXWorldExpo has been named “Global Sponsor” of SYS-CON's 21st International Cloud Expo, which will take place on Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Digital Transformation is the key issue driving the global enterprise IT business. Digital Transformation is most prominent among Global 2000 enterprises and government institutions.
Increasingly, in a world of compressed times and distances, humans will be the inventors, designers and managers of digital systems and processes, rather than the operators. Operations will be measured in milliseconds, an inhumane speed where only the machines can deliver. Professor Paul Virilio, a philosopher of speed, urbanist and cultural theorist, wrote at length about the impact of speed on society. He wrote that speed compresses both time and distance. Where once it took a letter 6 months to get to the other side of the world, an email can now arrive in seconds. Today's near real-tim...
In the cloud era, you as an IT professional are being forced to adopt new roles and take on new responsibilities you may not feel equipped to handle. Businesses are becoming increasingly hybrid, leaving you to manage, secure, monitor, and remediate technology on-premises and in the cloud. Of course, this comes with risks because it means you must manage mission-critical layers of application services across networks, systems, and services you neither own nor control. In fact, in many cases, you may not even have visibility into all the environments you’re responsible to ensure the performance ...
In his session at 20th Cloud Expo, Scott Davis, CTO of Embotics, discussed how automation can provide the dynamic management required to cost-effectively deliver microservices and container solutions at scale. He also discussed how flexible automation is the key to effectively bridging and seamlessly coordinating both IT and developer needs for component orchestration across disparate clouds – an increasingly important requirement at today’s multi-cloud enterprise.
One of the core benefits of Java is the JVM, which is an out-of-the-box memory management. Essentially, we can create objects and the Java Garbage Collector will take care of allocating and freeing up memory for us. Nevertheless, memory leaks can still occur in Java applications. In this article, we're going to describe the most common memory leaks, understand their causes, and look at a few techniques to detect/avoid them. We're also going to use the Java YourKit profiler throughout the article, to analyze the state of our memory at runtime.