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Ongoing observations by End Point people

Meet the End Point Windows consulting group

By Chris Hopkins
July 27, 2018

As the share of internet traffic passing through mobile devices hovers around 50%, it’s easy to forget that a lot of computing still happens on desktops and laptops—​and perhaps even easier to forget that the majority of those desktops and laptops are running Microsoft Windows.

At End Point, we take pride in being a multi-platform organization and using open source technologies in real-world business environments. Our internal chat service, wiki, and many other libraries and tools we employ across our client base are all open source. However, for various reasons many companies choose Microsoft’s solutions including long-time standards Windows Server, Active Directory, and Exchange.

With the acquisition of Series Digital in 2017 and the addition of Dan Briones to our staff, End Point has begun supporting Windows infrastructure in a new way. In 2018 we’ve recently added two new engineers to the mix, Chris Hopkins and Charles Chang, to form a full-service Windows consulting team, all local to our New York City office on Park Avenue.

Dan Briones

Dan Briones

Dan is the team lead and has over three decades of hands-on experience in IT systems management, systems integrations, migrations, virtualization, networking, security, orchestration, security, compliance, and maintenance, specializing in the Microsoft Windows ecosystem. He also develops applications using the .NET framework and SQL Server database. Dan works with many of our local New York clients, focusing on their network and infrastructure.

Charles Chang

Charles Chang

Charles has 21 years of experience in IT ranging from managing Windows infrastructure, to datacenter relocation and hardware refresh initiatives, office relocation, virtualization, disaster recovery and business continuity strategy. Charles has worked extensively with major vendors such as VMware, IBM, EMC, Cisco, and Dell in building enterprise environments in the datacenter. He also has experience in implementing data loss prevention technology, web and email filtering...

windows integration company

Recommender System via a Simple Matrix Factorization

By Kamil Ciemniewski
July 17, 2018

people sitting and laughing
Photo by Michael Cartwright, CC BY-SA 2.0, cropped

We all like how apps like Spotify or Last.fm can recommend us a song that feels so much like our taste. Being able to recommend an item to a user is very important for keeping and expanding the user base.

In this article I’ll present an overview of building a recommendation system. The approach here is quite basic. It’s grounded though in a valid and battle-tested theory. I’ll show you how to put this theory into practice by coding it in Python with the help of MXNet.

Kinds of recommenders

The general setup of the content recommendation challenge is that we have users and items. The task is to recommend items to a particular user.

There are two distinct approaches to recommending content:

  1. Content based filtering
  2. Collaborative filtering

The first one bases its outputs on the the intricate features of the item and how they relate to the user itself. The latter one uses the information about the way other, similar users rank the items. More elaborate systems base their work on both. Such systems are called hybrid recommender systems.

This article is going to focus on collaborative filtering only.

A bit of theory: matrix factorization

In the simplest terms, we can represent interactions between users and items with a matrix:

item1 item2 item3
user1 -1 - 0.6
user2 - 0.95 -0.1
user3 0.5 - 0.8

In the above case users can rate items on the scale of <-1, 1>. Notice that in reality it’s most likely that users will not rate everything. The missing ratings are represented with the dash: -.

Just by looking at the above table, we know that no amount of math is going to change the fact that user1 completely dislikes item1. The same goes for user2 liking item2 a lot. The ratings we already have make up for a fairly easy set of items to propose. The goal of a recommender is not to propose the items users know already though. We want to predict which of the “dashes” from the table are most likely to be liked the most. Putting it in...

python machine-learning

Currency exchange rates with exchangeratesapi.io

By Jon Jensen
July 14, 2018

city street with currency exchange signs

Several of our clients run ecommerce sites, built on custom software, that allow customers to pay in their choice of a few different currencies.

Some have set up separate merchant bank accounts for each currency and use separate payment gateway accounts to accept payments natively in each currency. But more commonly they use a payment gateway that allows them to accept payment in several currencies, but receive funds converted into their specified native currency in their merchant bank account.

In either case, it is common to store prices for products, shipping, etc. in one base currency (say, USD for companies based in the U.S.) and dynamically convert prices for customers. Non-native prices may need to be marked up to cover the cost of conversion into the native currency, depending on the terms of the agreement with the payment gateway or bank.

Because currency exchange rates change often, and because payment gateways generally do not offer a way to retrieve the exchange rates in advance, we need our own source for ongoing retrieval and storage of our exchange rates (also known as forex rates).

For a while we were very pleased with Fixer.io, which was a free service that collected exchange rates from the European Central Bank (ECB) and provided current or historical rates via a simple JSON API. We were sad to find that in March 2018 they deprecated that API and in June 2018 they discontinued it entirely, as described to their users. Fixer.io has transitioned to a paid service and they appear to have improved their operation to retrieve exchange rate data from at least a dozen more sources than the ECB, and to store far more frequent rate updates. Those are nice features, but not something our clients need.

Fixer.io still offers a free plan that allows 1000 API calls per month but in that plan the exchange rates are all based on the Euro. You need to sign up for at least the $10/month plan to retrieve exchange rates from the other currencies as base. As our...

saas ecommerce

Vue, Font Awesome, and Facebook/​Twitter Icons

By David Christensen
July 12, 2018

some Font Awesome fonts


Font Awesome and Vue are both great technologies. Here I detail overcoming some issues when trying to get the Facebook and Twitter icons working when using the vue-fontawesome bindings in the hopes of saving others future debugging time.


Recently, I was working with the vue-fontawesome tools, which have recently been updated to version 5 of Font Awesome. A quick installation recipe:

$ yarn add @fortawesome/fontawesome
$ yarn add @fortawesome/fontawesome-svg-core
$ yarn add @fortawesome/free-solid-svg-icons
$ yarn add @fortawesome/free-brands-svg-icons
$ yarn add @fortawesome/vue-fontawesome

A best practice when using Font Awesome is to import only the icons you need for your specific project instead of the thousand+, as this just contributes to project bloat. So in our main.js file, we import them like so:

// Font Awesome-related initialization
import { library } from '@fortawesome/fontawesome-svg-core'
import { faEnvelope, faUser } from '@fortawesome/free-solid-svg-icons'
import { faFacebook, faTwitter } from '@fortawesome/free-brands-svg-icons'
import { FontAwesomeIcon } from '@fortawesome/vue-fontawesome'

// Add the specific imported icons

// Enable the FontAwesomeIcon component globally
Vue.component('font-awesome-icon', FontAwesomeIcon)

This allows you to include icons in your view components like so:

  <div class="icons">
    <font-awesome-icon icon="user"/>
    <font-awesome-icon icon="envelope"/>

This worked fine for me until I tried to use the facebook and twitter icon:

  <div class="icons">
    <font-awesome-icon icon="user"/>
    <font-awesome-icon icon="envelope"/>
    <font-awesome-icon icon="twitter"/>  <!-- broken -->
    <font-awesome-icon icon="facebook"/> <!-- broken -->

Only blank spots and errors in the browser console like so:

[Error] Could not find one or...

vue javascript

Training Tesseract 4 models from real images

By Kamil Ciemniewski
July 9, 2018

table of ancient alphabets

Over the years, Tesseract has been one of the most popular open source optical character recognition (OCR) solutions. It provides ready-to-use models for recognizing text in many languages. Currently there are 124 models that are available to be downloaded and used.

Not too long ago, the project moved in the direction of using more modern machine-learning approaches and is now using artificial neural networks.

For some people, this move meant a lot of confusion when they wanted to train their own models. This blog post tries to explain the process of turning scans of images with textual ground-truth data into models that are ready to be used.

Tesseract pre-trained models

You can download the pre-created ones designed to be fast and consume less memory, as well as the ones requiring more in terms of resources but giving a better accuracy.

Pre-trained models have been created using the images with text artificially rendered using a huge corpus of text coming from the web. The text was rendered using different fonts. The project’s wiki states that:

For Latin-based languages, the existing model data provided has been trained on about 400000 textlines spanning about 4500 fonts. For other scripts, not so many fonts are available, but they have still been trained on a similar number of textlines.

Training a new model from scratch

Before diving in, there are a couple of broader aspects you need to know:

  • The latest Tesseract uses artificial neural networks based models (they differ totally from the older approach)
  • You might want to get familiar with how neural networks work and how their different types of layers can be used and what you can expect of them
  • It’s definitely a bonus to read about the “Connectionist Temporal Classification”, explained brilliantly at Sequence Modeling with CTC (it’s not mandatory though)

Compiling the training tools

This blog post talks specifically about the latest version 4 of Tesseract. Please make sure that you have that installed...

ruby machine-learning

SRV DNS records in Terraform and Cloudflare

By Jon Jensen
June 26, 2018

woman walking across train tracks
(Photo by David Goehring, CC BY 2.0, cropped)

At End Point we are using Terraform for a few clients to manage their web hosting infrastructure as code (IaC). Terraform is particularly helpful when working with multiple cloud or infrastructure providers and stitching together their services.

For example, for one web application that involves failover from the primary production infrastructure to a secondary location at a different provider, we are using Cloudflare as a CDN to provide caching, DDoS mitigation, and traffic routing in front of virtual servers at DigitalOcean and Amazon Web Services (AWS).

We decided we wanted to store all of their infrastructure configuration in Terraform, not just what is required for the web application, so we can recreate their entire infrastructure from their Git repository.

This all went fine until we got to their email DNS records. Our client is using Microsoft Office 365 for their email, which requires some SRV records. Terraform’s Cloudflare provider works fine with the universal MX records, but when we first wanted to do this, the Terraform provider for Cloudflare did not support SRV records at all.

Luckily for us, Terraform recently (6 April 2018) gained support for DNS SRV records as mentioned in the release notes and described in more detail in the pull request that added the feature.

Great! So now we can get on with this.

I began by naively assuming that the SRV record data should be given in space-separated form like many DNS interfaces use, including BIND and Cloudflare’s web interface itself. I tried setting it like this:

resource "cloudflare_record" "_sipfederationtls_tcp" {
  domain = "${var.domain}"
  name   = "_sip._tcp.${var.subdomain}"
  type   = "SRV"
  value  = "100 1 443 sipdir.online.lync.com."

But that resulted in an error. So when in doubt, consult the documentation, right? I did that:

Those make it clear that a data element is required...

devops terraform cloud hosting

Ecommerce Shakeups: Magento Acquisition and Etsy Rate Increases

By Steph Skardal
June 19, 2018

Magento, Etsy

If you’ve been paying any attention to much in the ecommerce world, there have been a couple shakeups and transitions that could affect how you look at your ecommerce options these days.

Adobe to Acquire Magento

A few weeks ago, it was announced Adobe would acquire Magento in a large acquisition. We’ve seen Magento clients come and go. It used to be the case that the Magento Community version was free and open source, but lacking in features, and the Magento Enterprise version was not free and came with many more features but was closed source.

But, times change, and admittedly I haven’t looked into the current Magento offerings until writing this post. The two current options for Magento are Magento Commerce Starter and Magento Commerce Pro, more details here. These plans are not for small potatoes, starting at $2k/mo. I can see how the cost of this is worth it in lieu of paying a full time developer, but this is not a good fit for small businesses just getting started.

There at not many public details on the acquisition, other than bringing Magento to Adobe’s range of “physical and digital goods across a range of industries, including consumer packaged goods, retail, wholesale, manufacturing, and the public sector”. Only time will tell.

Etsy Hikes Rates

I am personally connected to the craft industry by way of my own hobby, so I’ve heard rumblings of the changes going on within Etsy with a new CEO throughout the last year. They will be shutting down Etsy wholesale as of July 31st, 2018, closing Etsy Studio & Manufacturing later this year, and last week, they announced increasing transaction fees from 3.5% to 5% which will now also apply to shipping charges. With that money, they will be offering improved tools and marketing efforts. You can read the official announcement here and more Q&A from Etsy here.

There are so many overwhelming options when it comes to determining what the best ecommerce solution is for any size of ecommerce business, and whether...

ecommerce magento etsy saas

systemd: a primer from the trenches

By Ian Neilsen
June 18, 2018

Gears image by Guy Sie, CC BY-SA 2.0, cropped & scaled

systemctl: Let’s get back to basics

''Help me systemd, you are my only hope.''

Sometimes going back to day zero brings clarity to what seems like hopeless or frustrating situation for users from the Unix SysV init world. Caveat: I previously worked at Red Hat for many years before joining the excellent team at End Point and I have been using systemd for as long. I quite honestly have forgotten most of the SysV init days. Although at End Point we work daily on Debian, Ubuntu, CentOS, and BSD variants.

Here is a short and sweet primer to get your fingers wet, before we dive into some of the heavier subjects with systemd.

Did you know that systemd has many utilities you can run?

  • systemctl
  • timedatectl
  • journalctl
  • loginctl
  • systemd-notify
  • systemd-analyze - analyze system
  • systemd-cgls - show cgroup tree
  • systemd-cgtop
  • systemd-nspawn

And systemd consists of several daemons:

  • systemd
  • journald
  • networkd
  • logind
  • timedated
  • udevd
  • system-boot
  • tmpfiles
  • session

That’s a long way from the old SysV init days. But in all essence it’s not that different. The one thing that stands out to me is we have more information with less typing then previously. That can only be a good thing, right?

Well, let’s see! There are many many web pages out there that list systemd or systemctl switches/​flags. However in everyday use I want to speed up the work I do, I want information at my fingertips, and I find flags and switches which mean something sure do make it easier.

Pro Tip 1: Tab completion

Before you begin playing with the commands, you should install bash-completion. Some distros don’t auto-complete with systemd until you install that, and without tab auto-completion you miss out on a lot of systemctl.

As an example when you tab for completion you will see many of the systemctl options:

# systemctl
add-requires           enable                 is-system-running      preset                 show
add-wants              exit ...

hosting systemd
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