I always like The Setup. Discover what kind of technologies, hardware and softwares other skilled people are using is extremely useful and really fun for me. This time I’d like to share some tips from the complete reboot I did to my personal ecosystem after switch to my new Macbook.

macbook_pro_13_retina

From the hardware side is a simple high-end 2015 Macbook Pro 13″ Retina with Intel Core i7 Haswell dual-core at 3,4GHz, 16GB of RAM and 1TB of SSD PCI Express 3.0. Is fast, solid, lightweight and flexible. The only required accessory is the Be.eZ LArobe Second Skin.

From the software side I decided to avoid Time Machine restore in order to setup a completely new environment. I started on a OS X 10.10 Yosemite fresh installation.

As polyglot developer I usually deal with a lot of different applications, programming languages and tools. In order to decide what top install, a list of what I had on the previous machine and what I need more was really useful.

Here is a list of useful software and some tips about the installation process.

Applications

paid_apps

Paid softwares worth having: Evernote (with Premium subscription and Skitch) and Todoist (with Premium subscription) both available on the Mac App Store. 1Password, Fantastical 2, OmniGraffle, Carbon Copy Cloner, Backblaze and Expandrive available on their own websites.

Free software worth having: Google Chrome and Mozilla Firefox as browser, Apache OpenOffice, Skype and Slack as chat, VLC for multimedia and Transmission for torrents.

app_from_suites

Suites or part of: Adobe Photoshop CC, Adobe Illustrator CC and Adobe Acrobat Pro DC are part of the Adobe Creative Cloud. Microsoft Word 2016, and Microsoft Excel 2016 are part of Microsoft Office 2016 for Mac (now in free preview). Apple Pages, and Apple Keynote are preinstalled as Apple iWork suite as well as Apple Calendar and Apple Contacts.

Development tools

Utilities for Power Users: Caffeine, Growl and HardwareGrowler, iStat Menu Pro, Disk Inventory X, Tor Browser and TrueCrypt 7.1a (you need to fix a little installation bug on OS X 10.10), Kinematic and Boot2Docker for Docker, Sublime Text 3 (with some additions like: Spacegray Theme, Soda Theme, a new icon, Source Code Pro font), Tower, Visual Studio Code, Android SDK (for Android emulator) and XCode (for iOS emulator), VirtualBox (with some useful Linux virtual images), iTerm 2.

CLI: OhMyZSH, Homebrew, GPG (installed using brew), XCode Command Line Tools (from Apple Developers website), Git (with git-flow installed using brew), AWS CLI (install via pip), PhantomJS, s3cmd and faster s4cmd, Heroku toolbelt and Openshift Client Tools (install via gem).

daemons

Servers: MariaDB 10.0 (brew), MongoDB 3.0 (brew), Redis 3.0 (brew), Elasticsearch 1.6 (brew), Nginx 1.8.0 (brew), PostgreSQL 9.4.2 (via Postgres.app), Hadoop 2.7.0 (brew), Spark 1.4 (download from official website), Neo4j 2.2 (brew), Accumulo 1.7.0 (download from official website), Crate 0.49 (download from official website), Mesos 0.22 (download from official website), Riak 2.1.1 (brew), Storm 0.9.5 (download from official website), Zookeeper 3.4.6 (brew), Sphinx 2.2 (brew), Cassandra 2.1.5 (brew).

languages

Programming languages: RVM, Ruby (MRI 2.2, 2.1, 2.0, 1.9.3, 1.8.7, REE 2012.02, JRuby 1.7.19 installed using RVM), PHP 5.6 with PHP-FPM (installed using brew), HHVM 3.7.2 (installed using brew with adding additional repo, has some issues on 10.10), Python 2.7 (brew python) and Python 3.4 (brew python3), Pip 7.1 (shipped with Python), NVM, Node.js 0.12 and IO.js 2.3 (both installed using NVM), Go 1.4.2 (from Golang website), Java 8 JVM (from Oracle website), Java 8 SE JDK (from Oracle website), Scala 2.11 (from Scala website), Clojure 1.6 (from Clojure website), Erlang 17.0 (brew), Haskell GHC 7.10 (brew), Haskell Cabal 1.22 (brew), OCaml 4.02.1 (brew), R 3.2.1 (from R for Mac OS X website), .NET Core and ASP.NET (brew using DNVM), GPU Ocelot (compiled with a lot of libraries).

Full reboot takes about 2 days. Some software are still missing but I was able to restart my work almost completely. I hope this list would be helpful for anyone 🙂

I few days ago I have been at Codemotion in Milan and I had the opportunity to discover some insights about technologies used by two of our main competitor in Italy: BlogMeter and Datalytics. It’s quite interesting because, also if technical challenges are almost the same, each company use a differente approach with a different stack.

datalytics_logo

Datalytics a is relatively new company founded 4 months ago. They had a desk at Codemotion to show theirs products and recruit new people. I chatted with Marco Caruso, the CTO (who probably didn’t know who I am, sorry Marco, I just wanted to avoid hostility 😉 ), about technologies they use and developer profile they were looking for. Requires skills was:

Their tech team is composed by 4 developers (including the CTO) and main products are: Datalytics Monitoring™ (a sort of statistical dashboard that shows buzz stats in real time) and Datalytics Engage™ (a real time analytics dashboard for live events). I have no technical insights about how they systems works but I can guess some details inferring them from the buzz words they use.

Supported sources are Twitter, Facebook (only public data), Instagram, Youtube, Vine (logos are on their website) and probably Pinterest.

They use DataSift as data source in addition to standard APIs. I suppose their processing pipeline uses Storm to manage streaming input, maybe with an importing layer before. Data is crunched using Hadoop and Java and results are stored on MongoDB (Massimo Brignoli, Italian MongoDB evangelist, advertise their company during his presentation so I suppose they largely use it).

Node.js should be used for frontend. Is fast enough for near real time application (also using websockets) and play really well both with Angular.js and MongoDB (the MEAN stack). D3.js is obviously the only choice for complex dynamic charts.

I’m not so happy when I discover a new competitor in our market segment. Competition gets harder and this is not fun. Anyway guys at Datalytics seems smart (and nice) and compete with them would be a pleasure and will push me to do my best.

Now I’m curios to know if Datalytics is monitoring buzz on the web around its company name. I’m going to tweet about this article using #Datalytics hashtag. If you find this article please tweet me “Yes, we found it bwahaha” 😛

[UPDATE 2014-12-27 21:18 CET]

@DatalyticsIT favorite my tweet on December 1st. This probably means they found my article but the didn’t read it! 😀

klout_logo

According to WikipediaKlout is “a website and mobile app that uses social media analytics to rank its users according to online social influence via the “Klout Score“, which is a numerical value between 1 and 100“.

This is not so different from what I try to do everyday. They get signals from social networks, process them in order to extract relevant data and show some diagrams and a synthetic index of user influence. It’s really interesting for me observe how their data is stored and processed.

At Hadoop Summit 2012, Dave Mariani (by Klout) and Denny Lee (by Microsoft) presented the Klout architecture and shown the following diagram:

klout_architecture

It shows many different technologies, a great example of polyglot persistence 🙂

Klout uses a lot of Hadoop. It’s used to collect signals coming from different Signal Collectors (one for each social network i suppose). Procedure to enhance data are written using Pig and Hive used also for data warehouse.

Currently MySQL is used only to collect user registrations, ingested into the data warehouse system. In the past they use it as bridge between the data warehouse and their “Cube“, a Microsoft SQL Server Analysis Services (SSAS). They use it for Business Intelligence with Excel and other custom apps. On 2011 data were migrated using Sqoop. Now they can leverage on Microsoft’s Hive ODBC driver and MySQL isn’t used anymore.

Website and mobile app are based on the Klout API. Data is collected from the data warehouse and stored into HBase (users profile and score) and MongoDB (interaction between users). ElasticSearch is used as search index.

Most of custom components are written in Scala. The only exception is the website, written in Javascript/Node.js.

In the end Klout is probably the biggest company working both using open source tools coming from the Hadoop ecosystem and Microsoft tools. The Hadoop version for Windows Azure, developed in pair with Hortonworks, is probably the first product of this collaboration.

Sources