coll going reactive 2016 report

7/23/2019 COLL Going Reactive 2016 Report

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GOING REACTIVE 2016HOW MICROSERVICES AND FAST DATA ARE DRIVING

MAINSTREAM ADOPTION OF REACTIVE SYSTEMS


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INTRODUCTION ........................................................................................................................ 3

CHAPTER 1: The Survey and Respondents........................................................................... 4

CHAPTER 2:Reactive Adoption Trends .............................................................................. 10

CHAPTER 3: Microservices and Reactive Systems ............................................................ 20

CHAPTER 4:Fast Data and Reactive Systems.................................................................... 29

CHAPTER 5: Conclusions and TL;DR.................................................................................... 36

BONUS:Tools & Technologies among all respondents.....................................................41

ADDITIONAL RESOURCES..................................................................................................... 47

Table of Contents


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INTRODUCTION

By now, you have likely heard the famous quote from Marc Andreessen,

Soware is eating the world. Well, if you believe that is true, then the

next logical question becomes, How will your business react?

Business leaders in nearly in every industry recognize the need fortheir business to react with the speed and agility of a soware startup

in order to survive. Blockbuster was bankrupted by Netix. The entire

hotel industry was disrupted by Airbnb. The phrase, Youve been

Ubered, will likely become part of our lexicon to describe industries

that have been blindsided by the future.

To execute a competitive strategy that keeps businesses agile

and adaptable to continuously evolving market conditions and

competitors, developers and architects are helping their organizations

by Going Reactive.

The Reactive Manifestowas penned in 2013

leaders and technologists with a cohesive app

vocabulary to accelerate the evolution toward

These systems are more exible, loosely-coup

makes them easier to develop and amenable

signicantly more tolerant of failure and when

meet it with elegance rather than disaster.

In this survey, we set out to understand the jo

Reactive and uncovered some interesting ado

microservices and Fast Data along the way. We

report together and hope you enjoy seeing ho

the Reactive landscape.
http://www.reactivemanifesto.org/http://www.reactivemanifesto.org/


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CHAPTER 1:THE SURVEY AND RESPONDENTS

Meet the Developers, Architects and

Managers from 28 industries


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BEFORE JUMPING INTO THE FINDINGS,

LETS ADDRESS METHODOLOGY

In August 2015, we launched Reactive Revealed, an anonymous

survey designed to understand experiences, opinions and

technologies related to Going Reactive. To inspire respondents toshare, we made a nancial donation to support to Devoxx4Kids, an

organization dedicated to getting the next generation of young geeks

excited about programming. More than 3,000 people responded.

We ran the survey through an invitation to our contact list and a

blind open call to OReilly Media newsletter recipients, readers of

TheServerSide.com and Voxxed.com, so there is a certain amount of

bias present in the report. Naturally, our customers and developersfamiliar with Typesafe and Reactive trends are more likely to reply to

the call than anyone else. Also, its likely that people who nd and

take such surveys are less conservative in their technology choice

than those who dont.

That being said, the sample size, while not sci

is double whats considered statistically relev

population of Java developers worldwide. Wi

million developers working on the JVM, we caerror using this handy tool.
http://www.devoxx4kids.org/https://www.surveymonkey.com/mp/margin-of-error-calculator/https://www.surveymonkey.com/mp/margin-of-error-calculator/http://www.devoxx4kids.org/


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Our sample size of 3060 respondents has a 2% margin of error with a

95% condence level and a 3% margin of error with a 99% condence

level. This means that these results can go plus or minus 2-3% in

either direction, so we generally stayed away from drawing any

conclusions using numbers that fell within that condence interval.

Consider this an interesting look at data culled from a very large JVM

community, rather than a formal research study.

28 industries re

62 tools & technol

3060 total responden

2O question

2%margiconfidenc


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Looking at the respondents, the majority are developers (59%).

Just over one-third are architects (24%)or in management

roles (10%), so we can appreciate a broader perspective in the

responses. A small sliver of DevOps (3%)and Other (4%)have

shared their experiences.

CURRENT JOB ROLE

MEET THE RESPONDENTS

24%Archit

10%Mana

4%Other

3%Dev Op

59%Devel


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Respondents come from a broad selection of 28 in

eight shown here. The Technology (21%) and Fin

sectors take the rst two places by a healthy margi

(8%)and Consulting (7%), Telecommunication

Services (6%)are all fairly close.

INDUSTRY OF OPERATION

4%Media

6%Telecommunications

5%Government/Military

6%Business Services

7%Consulting

8%Online Services

13%Financial Services

21%Technology


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A slight majority (51%) of respondents work in teams of ve people or less and

just over one-third (36%) work in teams of six to 25 people. A combined 13% of

respondents work with teams larger than 25 developers.

NUMBER OF DEVELOPERS ON PROJECT

51%

36%

7%

3%

3%

0-5

6-25

26-50

51-100

101 +


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CHAPTER 2:REACTIVE ADOPTION TRENDS

Experiences and predictions

about Going Reactive


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REACTIVE ADOPTION TRENDS

Reactive systems embody four tenets: Message-driven, Resilient, Elastic, Responsive. We were curious to

understand how quickly these systems were being adopted, the variables driving (or inhibiting) adoption,

and whether or not a prescriptive approach to implementation had emerged.

JameCo-fou

RedMo

The more I tho

the clearer it b

not just infras

in this way. Bu

Reactive beca

the future and

technical arch

change, which

computing. Ag

the future of b

By means of an asynchronous, non-blocking message-drivenapproach, highly resilientand elastic

systems can be formed, resulting in a consistently responsiveuser experience.

THE FOUR TENETS OF REACTIVE SYSTEMS


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HOW CRITICAL IS GOING REACTIVE?

A signicant majority of respondents (83%) feel that Reactive is a topic

that requires attention, with nearly half of that group indicating

Reactive is something we needed yesterday.

PERCEPTIONS OF THE GOING REACTIVE TREND

43%

Gaining momentshould start look

into it soon

12%

Enjoying a lot of buzz,but thats probably it

40%

Totally important,something we needed

yesterday

5%

ZOMG,not Reactive again!


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HOW QUICKLY ARE REACTIVE SY

BEING ADOPTED?

We asked respondents to perform a comparative p

organization compared to most successful enterpris

adoption of Reactive systems. By 2018, respondent

their organizations and 80% of most successful ent

adopted Reactive systems.

Comparatively, the spread between their organizat

enterprises is fairly close in the Already adopted a

As time progresses, the comparative spread becom

While clearly identifying Reactive as a characteristic

enterprises, respondents perceive their own organi

behind. Lets see what drivers and potential blocke

PREDICTIONS FOR REACTIVE SYSTEMS ADOPTION

13%

14%

Their organizationMost successful enterprises

Already adopted By 2016 By 2018 Later than 2018

26%

24%

41%

31%

20%

31%


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PRIMARY DRIVERS OF GOING REACTIVE

31%

Scalability

22%

Resilience

17%

Modernization

16%

Velocity

15%

Efficiency

WHAT IS DRIVING REACTIVE ADOPTION?

Regarding the p

Reactive, no sin

a majority. Scal

#1, with Resilie

place. The last t

(17%), Develop

and System Ef

relatively close

news is that Go

accomplishes a


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WHAT IS BLOCKING YOU FROM GOING REACTIVE?

Respondents were asked to identify all the potential blockers in Going

Reactive. A happy one-h of respondents reported no barriers, and

are actively going for it! (21%). Over half of respondents indicated

that challenges on a human level are the main barriers: whether it is

the need to retrain people in new technologies (35%)or the lack

of interest by the team (23%).

POTENTIAL BLOCKERS OF GOING REACTIVE

About the same number of respondents repor

disruption of the change (27%)or lack of s

at the top of the organization (26%)are pe

Respondents are less concerned about ndin

that Going Reactive will simply take too long

It will taketoo long to do

Finding newemployees to work

with these systems

No barriers.Were going for it!

Lack of interest by developersand operations staff

Not enough support at the topof the organization

Disruption to existing activitieswould be too high ne

27%26%23%21%17%13%


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WHO IS (OR SHOULD BE) RESPONSIBLE FOR

TRYING NEW SYSTEM APPROACHES?

Consistent with the market trend in which developers are the new kingmakers,

a majority of respondents feel that Development teams (52%)are

responsible for taking the rst step in testing new technologies or architectural

concepts.Architects (31%)are the second group that respondents identied

as being responsible for disrupting business as usual and tr ying out new

things. Respondents considered the CTO (11%)of the organization to be third,

whereas the entire Executive Board (2%) is considered to be less responsible

than the CTO role.

WHO SHOULD LEAD THE WAY TO GOING REACTIVE?

2nd

Architects

1st

Developers

31%

52%

2nd

Architects

1st

Developers

31%

52%


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Just starting to look

into the topic

Not applicable to me

Already learningor doing research

Building a prototype

Running a productionapplication

Developing aproduction application

4%

19%

29%14%

18%

16%

34%Powerusers

43%Active

starters

19%Entrylevel

WHERE ARE YOU TODAY IN THE GOING REACTIVE JOURNEY?

Of the 3060 overall respondents, 9

in Going Reactive at some level, w

applicable to them. For purposes o

grouped respondents into three a

Thepower usersrepresent 34%

either developing a product

or running in production (1

The active startersgroup is lar

respondents who are buildin

or already learning or doing

The entry levelgroup is less tha

with 19% just starting to loo

GOING REACTIVE PHASE OF JOURNEY


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WHICH APPROACH WOULD YOU TAKE TO GO REACTIVE TODAY?

Where implementing Reactive systems is

concerned, multiple approaches can be

considered. The most common approach

by respondents is to refactor their legacysystems one module at a time (41%).

From there, others would do a complete

rewrite (24%), or shave down their existing

stack and replace legacy bottlenecks or

APIs (23%)that way. The smallest group

would create a new front-end (12%)to

integrate with a legacy back-end. Going

module-by-module wins in popularity.

HOW TO APPROACH GOING REACTIVE

Create a greenfield front-end,use a legacy back-end

Shave the existing stackand replace legacy

bottlenecks or APIs

Completely rewrite a newproject to eventuallyreplace legacy system

41%

24%

23%

12%


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MAJOR FINDING: REACTIVE IS GOING MAINSTREAM

Based on the data, its fair to sugg

behind Reactive systems are ente

Our round-up of data and sentime

indicates that more than 4 out of

believe that Reactive systems is a

attention. When it comes to predi

respondents expect that 80% of s

have adopted Reactive systems b

Drilling down, its interesting to no

respondents are Going Reactive t

43% already researching or protot

building or deploying production

next section, its this 34% of powethe adoption of Microservices-bas

when Going Reactive.

PREDICTIONS AND ACTIONS TAKEN TOWARDS GOING REACTIVE

Say that Reactive demands attention83%

Already researching and prototyping43%

Building and deploying production systems34%

Expect enterprise adoption by 201880%


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CHAPTER 3:MICROSERVICES AND REACTIVE SYSTEMS

The embrace of Microservices and

related tools in Reactive


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MICROSERVICES AND REACTIVE SYSTEMS

Microservices has been gaining a lot of attention lately. Martin Fowler, the well-known

co-author of the Agile Manifesto, has produced a popular explanationof microservices

with James Lewis that has been getting a lot of traction with developers. Industry analyst

Gartner is emphasizing the importance of microservices within its enterprise clientele,

ranking microservice-based architecture (MSA) within its top 10 strategic technology

trends for 2015.

With all of this buzz in the market, we were wondering what role microservices adoption

was playing in the Reactive journey. For the purposes of this survey, we did not set out

to dene microservices. Rather, we simply asked respondents to self-select whether or

not they considered their systems to be microservices-based. The data reveals a notable

increase in MSA adoption as respondents progress along their Reactive journey fromlearning to deploying. Additionally, a preference for tools and technologies begins to

emerge among adopters of MSA.

Gartn

Top 1

Trend

Monolithic, lin

are giving way

coupled integ

Microservice a

pattern for bu

applications t

and scalable d
http://martinfowler.com/articles/microservices.htmlhttp://www.gartner.com/newsroom/id/3143521http://www.gartner.com/newsroom/id/3143521http://www.gartner.com/newsroom/id/3143521http://www.gartner.com/newsroom/id/3143521http://martinfowler.com/articles/microservices.html


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Just Learning Researching & Prototyping

16%

28%

THE RISE OF MSA ADOPTION BY JOURNEY PHASE

Out of 3060 overall users, 33% (or 1020 people) identied their systems

as microservices-based. Overlaying this data with phase of journey

reveals a sharp rise in MSA adoption. Among the respondents that are

just beginning to learn about Reactive, 16% are using microservices,

rising to 28% among those that are already doing research or building

a prototype. Where MSA adoption truly becomes signicant is among

the power user group, where 50% are working with microservices.

MICROSERVICES ADOPTION BY PHASE OF JOURNEY


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USING SCALA OR JAVA WITH MICROSERVICES?

Where MSA adopters are concerned, an increasing appetite for Scala (64%) and Java 8 (61%) is

indicated, rising from approximately half of all respondents using these languages. Not surprisingly,

usage of Java 7 or lower drops from 41% average to 30% among MSA adopters. These usage trends

are consistent with the ndings from our Java 8 survey, where nearly half of the respondents

reported plans to jump directly to Java 8 and bypass Java 7 altogether.

USE OF JAVA AND SCALA WITH MICROSERVICES

30% Jav

Jav

64% Sca

61%

41%

52%

50%

- --------- = average for all respondents
https://info.typesafe.com/COLL-2014-10-20-Java-8-II-Survey-Report-LP.html?lsd=COLL-2014-10-20-Java-8-II-Survey-Report&lst=GR2016https://info.typesafe.com/COLL-2014-10-20-Java-8-II-Survey-Report-LP.html?lsd=COLL-2014-10-20-Java-8-II-Survey-Report&lst=GR2016


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MAJOR FINDING: THE PREFERRED TOOLSET FOR MSA

Microservices-based architectures have their foundation in the core concepts of Reactive systems:

asynchronous and message-driven, highly resilient against failures, elastically scalable on demand,

and consistently responsive. In addition to Scala and Java 8, here are the tools and technologies tha

rise signicantly in use among MSA adopters:

For all look at tools and technologies selected by all respondents, please go to the BONUS Chapter.

Akka

Apache Cassandra

Apache Kafka

Apache Spark

Play Framework

Amazon EC2

Docker

Apache Mesos


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PREFERRED OPS/INFRA/DEVOPS TECHNOLOGIES WITH MICROSERVICES

29% Not Microservices-based

34% All respondents

47% Microservices-based architectures

Uses Docker


7% All respondents


Uses Mesos


40% All respondents


Uses Amazon EC2


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18% All respondents


Uses Cassandra


17% All respondents


Uses Kafka


22% All respondents


Uses Spark

PREFERRED BIG [FAST] DATA TECHNOLOGIES WITH MICROSERVICES


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All respondents


43%

Uses Akka


30% All respondents


Uses Play

PREFERRED DEVELOPER TECHNOLOGIES WITH MICROSERVICES


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26% Spring:Microservices-based Architectures

40% Play:Microservices-based Architectures

30% Play:All respondents

29% Spring: All respondents

24% Play:Not Microservices-based

32% Spring:Not Microservices-based

USE OF SPRING AND PLAY WITH MICROSERVICES

As was mentioned earlier, a

bias is likely present in this r

customers and developers f

are more likely to reply to th

before others. Although usa

when it comes to all respon

a preference takes hold: Pla

30% to 40%, whereas Sprinslightly from 29% to 26%.


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CHAPTER 4:FAST DATA AND REACTIVE SYSTEMS

The embrace of data in motion and

related tools in Reactive systems


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FAST DATA AND REACTIVE SYSTEMS

Reactive systems for Mobile, Web and Internet of Things (IoT) increasingly operate on data

in near real-time. As these systems embrace data in motion, traditional batch processing

systems are being re-imagined as pure stream-based architectures. Specications such

as Akka Streamsamong other technologies included in the Reactive Streams initiative

and stream processing technologies like Spark Streaming are emerging to provide the

standards and plumbing necessary to implement such systems eectively.

In early 2015, we published the resultsof over 2000 respondents about Apache Spark

adoption, and we wanted to check in to see what role, if any, Apache Spark adoption is

playing in the Reactive journey. In this section we look at data that reveals the attitudes

and appetites among Apache Spark users.

Wall S

The F

Forget the clu

of the online w

information
https://info.typesafe.com/COLL-20XX-Spark-Survey-Report_LP.html?lst=WS&lsd=COLL-20XX-Spark-Survey-Trends-Adoption-Reporthttp://www.wsj.com/articles/the-future-of-the-internet-is-flow-1443796858http://www.wsj.com/articles/the-future-of-the-internet-is-flow-1443796858https://info.typesafe.com/COLL-20XX-Spark-Survey-Report_LP.html?lst=WS&lsd=COLL-20XX-Spark-Survey-Trends-Adoption-Report


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THE RISE OF SPARK ADOPTION

IN PRODUCTION REACTIVE SYS

Out of 3060 total respondents, 22% are working wi

Overlaying this data with phase of journey reveals a

usage. A similar trend was revealed regarding Micro

architecture (MSA) adoption, increasing as the Reac

from learning to deploying. For this segment of resp

are just learning about Reactive represent 13%, incrthose researching and prototyping, and climbing to

deploying Reactive systems in production.

USAGE OF SPARK ALONG STAGE OF JOURNEY

Just Learning13%

Building & Deploying28%

Researching & Prototyping21%


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MICROSERVICES AND SPARKNext, we were curious to see whether or not there was a

correlation between Spark usage and MSA adoption. As

indicated in the previous section, 30% of MSA adopters

indicate using Spark. Inverting this data, however, paints a

dierent picture: 46% of Spark users describe their systemarchitecture as microservices-based. This correlation is

interesting, and we look forward to learning more about this

picture in the future. MSA using

Spark

30%

Spark uswith M

46%


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SCALA OR JAVA WITH SPARK?

Although the average for Java 8 and Scala across all respondents is neck-and-neck, Scala rises from

50% to 76% usage among Spark users, and Java 8 rises slightly from 52% to 58%. Use of Java 7 and

lower drops signicantly from 41% to 30%.

With the needs of scalability paramount in Fast Data systems, its not surprising to see Scala as thepreferred programming language for working with Spark. Not only was Spark written in Scala,

but response data conrms the results of a recent reportby Databricks that also show the majority of

Spark developers prefer using the Scala API.

USE OF JAVA AND SCALA WITH APACHE SPARK

34% Jav

58% Jav

76% Sca

41%

52%

50%

- --------- = average for all respondents
https://www.quora.com/Why-is-Apache-Spark-implemented-in-Scalahttp://cdn2.hubspot.net/hubfs/438089/Spark-Survey-2015-Infographic.pnghttp://cdn2.hubspot.net/hubfs/438089/Spark-Survey-2015-Infographic.pnghttps://www.quora.com/Why-is-Apache-Spark-implemented-in-Scala


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43%

64%

Average Spark users

Akka Amazon EC2 Cassandra HadoopDocker

40%

55%

18%

44%

34%

52%

16%

46%

MesosKafka

17%

49%

7%

22%

MAJOR FINDING: THE SPECIFIC TOOLSET PREFERRED FOR FAST DATA

As traditional technologies that rely on oline batch processing are being replaced with technologies that support

data in motion, respondents identify Apache Spark and related tools rising to the challenge. As the adoption of Fast

Data architectures rises as respondents progress along the Reactive journey, the data reveals large increases in specic

technologies among Spark users.

INCREASED TOOL USAGE AMONG APACHE SPARK USERS

In addition to Scala

following tools for p

using Spark:

Akka

Amazon E

Apache C

Docker

Apache H

Apache K

Apache M

For all look at tools

respondents, please


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WHERE DOES HADOOP FIT

INTO THE SPARK PICTURE?

We have been interested to see where Spark ts into the Hadoop

ecosystem. In a recent article called Big Data Industry Predictions

for 2016, the general consensus is that Spark is breathing new life into

the well-established Hadoop ecosystem, with some comments even

going so far as to predict that, Spark will kill MapReduce, but save

Hadoop.

Overall Spark (22%) adoption is higher than Hadoop (16%) across

all respondents. Spark is now rmly established within the big data

ecosystem, and in use by 61% of Hadoop users. Pivoting, the data

reveals that 46% of Spark users are also employing Hadoop; however,

with over half of Spark users not using Hadoop, clearly other platform

approaches are arising as alternatives.

Spark users

that use Hadoop

46%Hatha

SPARK AND HADOOP TOGETHER
http://insidebigdata.com/2015/12/08/big-data-industry-predictions-2016/http://insidebigdata.com/2015/12/08/big-data-industry-predictions-2016/http://insidebigdata.com/2015/12/08/big-data-industry-predictions-2016/http://insidebigdata.com/2015/12/08/big-data-industry-predictions-2016/


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CHAPTER 5:CONCLUSIONS AND TL;DR

Three conclusions nicely wrapped

up for busy readers


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CONCLUSIONS (TL;DR)

For those of you too busy to internalize everything in this report at

once, we can narrow down the nal points into three main conclusions:

Reactive system adoption is going mainstream

Reactive adoption is being driven by two key

technology trends: Microservices and Fast Data

Microservices and Fast Data users are rallying around

a preferred group of tools and technologies

1

2

3


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Reactive system adoption is going mainstream

We acknowledge the responses in this report are likely biased. Nevertheless, based on

the data from more than 3000 respondents, its fair to suggest that Reactive systems are

entering the mainstream. An overwhelming majority of respondents (83%) report that

Going Reactive is critical, with nearly half of the group indicating Reactive is something we

needed yesterday. Respondents predict that 70% of their organizations and 80% of most

successful enterprises will have adopted Reactive systems by 2018, citing improvements in

scalability (31%) and resilience (22%) as the top drivers. What we found really amazing was

the current rate of adoption being reported. A total of 77% of respondents indicate theyare already Going Reactive to some degree with 43% researching and prototyping Reactive

systems and 34% building and deploying systems to production.


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Reactive adoption is being driven by two key technology

trends: microservices and Fast DataWith all of the buzz in the market around microservices and Apache Spark, we were wondering

what roles these technology trends were playing in the Reactive journey. For the purposes of

this survey, we did not set out to dene microservices. Rather, we simply asked respondents

to self-select whether or not they considered their systems to be microservices-based. The

data revealed a notable increase in microservices and Spark usage as respondents progressed

along their Reactive journey from just beginning to learn about Reactive (16% microservices,

13% Spark), rising among those that are already doing research or building a prototype (28%microservices, 21% Spark), and climbing even higher within the Reactive power users that are

building and deploying production systems (50% microservices, 28% Spark).

Microservices and Fast Data users are


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Microservices and Fast Data users are

rallying around a preferred group of

tools and technologies

Another key area we set out to understand was whether or not a

particular set of tools and technologies were being embraced overothers for building Reactive systems. We cast the lens through the data

of microservices and Spark users and found a tremendous amount of

overlap in their preferences. To these respondents, this is aprescription

for Going Reactive:

43% 59%

40% 52%

18% 28%

34% 47%

17% 27%

7% 13%

30% 40%

22% 30%

ALLRESPONDENTS

MICROSERUSER


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BONUS:TOOLS & TECHNOLOGIES AMONG ALL RESPONDENTS

Development, Operations and

Big [Fast] Data tools in use


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TOOLS & TECHNOLOGIES

Seeing which tools are being used is always interesting. We included 62

tools and technologies to choose from, and though some may think this

isnt nearly enough, we wanted to get a reasonable group of tools used in

Development, Infrastructure/DevOps, and Big [Fast] Data systems.

ITS NOW JAVA 8 AND SCALA NOT OR


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USAGE OF JAVA AND SCALA

IT S NOW JAVA 8 AND SCALA, NOT OR...

The combined forces of J

than either language sep

proportion of either lang

see that Java and Scala u

languages have their use

With Java 8s features bo

functional programming

and Streams, building Re

more straightforward in t

With JDK 9 coming...soon

mainstream introduction

the JVM, an industr y init

back-pressure mechanis

led by engineers from NeTypesafe and others. Rat

alone, we hope to see the

incrementally over time,

the job regardless of sem

by the most out spoken fa

29%

50%

Uses Java 8 and Java 7 or lower together

Uses Scala

52% Uses Java 8

56% Uses Java 8 and Scala together

61% IntelliJ IDEA DEVELOPMENT TECHNO
http://www.reactive-streams.org/http://www.reactive-streams.org/


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29% Spring Framework

24% Hibernate

1 8% Gradl e

12% Scala IDE

24% O ther

52% Java 8

50% Scala

43% Akka

42% Maven

41% Java 7 or lower

39% sbt

3 4% E cl ipse

30% Play Framework

8%

7%

Ant + Ivy

RxJava

5%

3%

2%

NetBeans IDE

None of the above

Vert.x

DEVELOPMENT TECHNO

DEVELOPMENT TECHNOLOGIES IN USE

IntelliJ IDEA (61%)emerges as the most comm

among respondents, even overtaking programm

Eclipse IDE (34%)takes a distant second, with

NetBeans IDE (5%)rounding out the section.

Java 8 (52%)has slightly larger adoption than S

lower (41%)takes third place among programm

over 50% of both Java 8 and Scala users also em

well. Use of Java 7 or lower among Java 8 and Sc

average to less than 32% for either one.

Among build tools, Maven(42% overall, but 61%

sbt(39% overall, but 73% of Scala users) are pot

time in overall adoption, with Gradle (18%)in a

Ant+Ivy (8%)maintaining a sliver of market sha

Akka (43%)is the 4th most-used tool among re

where Akka rises most, its across a pretty distrib

Akka usage increases considerably to 73% for Sc

Spark users and 59% among Microservices-base

Between frameworks (whose choices were limite

brevity), Play Framework (30%)and Spring F

neck and neck.


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INFRA/OPS/DEVLOPS TECHNOLOGIES IN USE

Among infrastructure and operations

technologies, we can see Jenkins CI (49%)

andAmazon EC2 (40%) maintaining

strong footholds.

Docker (34%)has taken a strong third placein overall use, andVagrant (19%)is in use

by nearly one-h of respondents.

New Relic (13%)shows its dominance

in the monitoring space compared to other

players like Dynatrace (1%)and

Takipi (1%).

Among provisioning & conguration tools,

we see a close race between Puppet (14%),

Ansible (13%)and Chef (11%). Heroku

(8%),Apache Mesos (7%)and OpenStack

(6%)have relatively small shares.

JenkinsCI

49%

Amazon

WebService

s

(i.e.

EC2)

40%

Docker

34%

Vagrant

19%

Pupp

et

14%

NewRelic

13%

Ansible

13%Ch

ef

11% Heroku

8%

None

oftheAb

7%

Ap

7%

32% MySQL

28% PostgreSQL


46/47

28% MongoDB

22% OracleDB

22% Apache Spark

19% Redis

18% Apache Cassandra

17% Apache Kafka

16% Apache Hadoop

12% MS SQL Server

10% Slick

7% Other

7% Hazelcast

5% YARN

26% Other

4%

4%

4%

Apache Storm

Cloudera CDH

IBM DB2

4%

4%

2%

None of the above

Heroku

Membase

2%

1%

1%

HortonWorks HDP

Apache Samza

Riak

DATA FOCUSED

TECHNOLOGIES IN

BIG [FAST] DATA TECHNOLOGIES IN USE

When it come to Big [Fast] Data antechnologies, we see a line up of t

DB world: MySQL (32%), Postgre

(28%)and Oracle DB (22%)com

With a prevalence of Java 8 and Sc

these results, its not surprising to

at a smaller uptake.Apache Spar

used data technology, followed by

Cassandra (18%),Apache Kafka

Hadoop (16%).

ADDITIONAL RESOURCES


47/47

ADDITIONAL RESOURCES

Typesafe (Twitter: @Typesafe) is dedicated to helping developers build Reactive applicationson the JVM. Backed by Greylock

Partners, Shasta Ventures, Bain Capital Ventures and Juniper Networks, Typesafe is headquartered in San Francisco with

ofices in Atlanta, Switzerland and Sweden. To start building Reactive applications today,learn about Reactive Platform.

2015 Typesafe

Reactive Streams, Akka S

and Akka HTTP

DOWNLOAD

Microservices in

Production

DOWNLOAD

Fast Data:

Big Data Evolved

DOWNLOAD
http://www.reactivemanifesto.org/http://www.typesafe.com/products/typesafe-reactive-platformhttps://info.typesafe.com/COLL-20XX-Enterprise-Architect-Akka-Streaming-Guide_LP.html?lst=WS&lsd=COLL-20XX-Enterprise-Architect-Akka-Streaming-Guide&_ga=1.34067814.615845212.1447436070https://info.typesafe.com/COLL-20XX-Enterprise-Architect-Akka-Streaming-Guide_LP.html?lst=WS&lsd=COLL-20XX-Enterprise-Architect-Akka-Streaming-Guide&_ga=1.34067814.615845212.1447436070https://info.typesafe.com/COLL-20XX-Enterprise-Architect-Akka-Streaming-Guide_LP.html?lst=WS&lsd=COLL-20XX-Enterprise-Architect-Akka-Streaming-Guide&_ga=1.34067814.615845212.1447436070https://info.typesafe.com/COLL-20XX-Microservices-in-Production-WP_LP.html?lst=WS&lsd=COLL-20XX-Microservices-in-Production-WP&_ga=1.34067814.615845212.1447436070https://info.typesafe.com/COLL-20XX-Microservices-in-Production-WP_LP.html?lst=WS&lsd=COLL-20XX-Microservices-in-Production-WP&_ga=1.34067814.615845212.1447436070https://info.typesafe.com/COLL-20XX-Microservices-in-Production-WP_LP.html?lst=WS&lsd=COLL-20XX-Microservices-in-Production-WP&_ga=1.34067814.615845212.1447436070https://info.typesafe.com/COLL-20XX-Fast-Data-Big-Data-Evolved-WP_LP.html?lst=WS&lsd=COLL-20XX-Fast-Data-Big-Data-Evolved-WP&_ga=1.34067814.615845212.1447436070https://info.typesafe.com/COLL-20XX-Fast-Data-Big-Data-Evolved-WP_LP.html?lst=WS&lsd=COLL-20XX-Fast-Data-Big-Data-Evolved-WP&_ga=1.34067814.615845212.1447436070https://info.typesafe.com/COLL-20XX-Fast-Data-Big-Data-Evolved-WP_LP.html?lst=WS&lsd=COLL-20XX-Fast-Data-Big-Data-Evolved-WP&_ga=1.34067814.615845212.1447436070https://info.typesafe.com/COLL-20XX-Fast-Data-Big-Data-Evolved-WP_LP.html?lst=WS&lsd=COLL-20XX-Fast-Data-Big-Data-Evolved-WP&_ga=1.34067814.615845212.1447436070https://info.typesafe.com/COLL-20XX-Microservices-in-Production-WP_LP.html?lst=WS&lsd=COLL-20XX-Microservices-in-Production-WP&_ga=1.34067814.615845212.1447436070https://info.typesafe.com/COLL-20XX-Enterprise-Architect-Akka-Streaming-Guide_LP.html?lst=WS&lsd=COLL-20XX-Enterprise-Architect-Akka-Streaming-Guide&_ga=1.34067814.615845212.1447436070http://www.typesafe.com/products/typesafe-reactive-platformhttp://www.reactivemanifesto.org/

coll going reactive 2016 report

Documents