3 Most Popular Transactional Email Services for Products

One of the most basic product tasks is sending emails. No matter the interface or device; it can be a web product, a mobile product, TV product, wearable, API, etc.

So your product will send an email to register new users, to restore passwords, shipping notifications, or any message that you need to send to users triggered by internal or external events. It’s very very common for a product send emails. In the market exists some alternatives to send emails that maybe your development team want to know.

In the following 2-3 minutes I will mention the 3 main transactional email services to keep in mind. All of them are handled by their API and several software libraries to integrate with specific software languages.

Ok, here we go:

#1: Mailgun

Mailgun is my favorite transactional email service because of their simplicity to setup and integrate.

In Mailgun you can create sub-accounts, so  you can use each sub-account for each domain with separate lists of email. There’s batch sending features to personalize emails, detailed analytics, and logs, and a powerful parsing engine to turn incoming emails into JSON and route it where you want.

Mailgun is very easy to use,

 

#2: Amazon AWS SES

Amazon Simple Email Service (Amazon SES) is a cloud-based email sending service designed to help digital marketers and application developers send marketing, notification, and transactional emails. You can use the SMTP interface or one of the AWS SDKs to integrate Amazon SES directly into your existing applications.

With Amazon’s email offering, you’ll handle everything on your own. And it’s priced accordingly. There’s no plans to pick from, no tiered feature levels: just a flat fee of $0.10 per thousand emails you send, plus another $0.12 per GB of email attachments sent (up to a max of 10Mb per email message).

If you send from an application hosted in Amazon EC2, the first 62,000 emails you send every month are free.

Read more about this service in their website and learn how to integrate it with your product, examples codes and so.

 

#3: Sendgrid

Sendgrid is one of the most popular email service that recently has been acquired by Twilio.

Similar to Mailgun and AWS SES, you can use Sendgrid to send transactional email via SMTP or via API. Their API documentation is very complete.

Sendgrid includes an user interface to let user compose, send and track marketing emails (and all in between). It includes to add contacts, create segments, create and send campaigns, and view your stats.

 

Want to learn more? Check it out here.

 

Ok. Hope you can find pure value on this post and you can keep in mind these email transactional services to use into your product… it’s useful to send shipping notifications, password recovery, and almost every stage you want to communicate to your users.

Migrate from Google Cloud Messaging to Firebase Cloud Messaging, Step by Step.

Hi 4Geeks Nation!! If you are behind a product development, specifically a mobile app, you want to know this new tool built by Google to send messages (notifications) to your users on your product.

Google launched Firebase Cloud Messaging (FCM) as a new and more powerful tool to manage messaging to mobile devices.

Using FCM, you can notify a client app that new email or other data is available to sync. You can send notification messages to drive user re-engagement and retention. For use cases such as instant messaging, a message can transfer a payload of up to 4KB to a client app.

Look at the FCM schema… it’s beautiful and useful.

So, if you are using the old Google Cloud Messaging and planing to migrate to the new Firebase Cloud Messaging, this video can help you to put all factors on the table.

 

If you need help with this, our software engineers can help you. So, contact us!

Here’s a Demo to Implement Google Cloud Video Intelligence API

Some months ago Google showed to the world how to use their most recent video intelligence product, Google Cloud Video Intelligence API.

Ok, to get context, Cloud Video Intelligence is basically an API that makes videos searchable, and discoverable, by extracting metadata with an easy to use REST API.

You can now search every moment of every video file in your catalog. It quickly annotates videos stored in Google Cloud Storage, and helps you identify key entities (nouns) within your video; and when they occur within the video. Separate signals from noise, by retrieving relevant information within the entire video, shot-by-shot, -or per frame.

Take a look at the following video to understand the power of this tool.

If you working with videos, take your time to learn more about this API. If you are not working directly with videos, feel free to share this post with your boss… maybe it can be useful for next business strategies.

A Neural Network Playground In The Browser

Well, maybe Neural Network can be a fancy or very new term. The thing is that Neural Network is the “base of” Machine Learning, and other applications like Artificial Intelligence.

A Neural Network it’s a technique for building a computer program that learns from data. It is based very loosely on how we think the human brain works.

First, a collection of software “neurons” are created and connected together, allowing them to send messages to each other.

Next, the network is asked to solve a problem, which it attempts to do over and over, each time strengthening the connections that lead to success and diminishing those that lead to failure.

Web TensorFlow Playground

So, this web tool is an interactive visualization of neural networks, written in TypeScript using d3.js. Go to http://playground.tensorflow.org to start playing just in the browser. I tested it on Google Chrome.

BTW, you can find the source here in TensorFlow’s GitHub.

Neural Network Playground, TensorFlow

I would like to know if you are working on some Neural Network project. Maybe you can get the exposure needed 🙂 Use the comments section below.

Real-time diagnostics from nanopore DNA sequencers on Google Cloud (Proof of Concept)

Guys, I want to share with you a blogpost from Google Cloud Blog, about a proof of concept on real-time diagnostics from nanopore DNA sequencers.

In a healthcare setting, being able to access data quickly is vital. For example, a sepsis  patient’s survival rate decreases by 4% for every hour we fail to diagnose the species causing the infection and and intervene with an appropriate antibiotic regimen.

Typical genomic analyses are too slow. You transport DNA samples from the collection point to a centralized facility to be sequenced and analyzed in a batch process, which can take weeks or even months. Recently, nanopore DNA sequencers have become commercially available that stream raw signal-level data as they are collected and provide immediate access to them. However, processing the data in real-time remains challenging, requiring substantial compute and storage resources, as well as a dedicated bioinformatician. Not only is the process still too slow, it’s also failure-prone, expensive, and doesn’t scale.

We recently built out a proof of concept for genomics researchers and bioinformatics developers that highlights the breadth and depth of Google Cloud’s data processing tools. In this article we describe a scalable, reliable, and cost effective end-to-end pipeline for fast DNA sequence analysis built on Google Cloud and this new class of nanopore DNA sequencers.

We envision four scenarios that can use this application, specifically to detect biocontaminants:

  • Medical professionals
  • Veterinary clinics
  • Agronomists
  • Biosecurity professionals

In all cases, analytical results are made available in a dynamic dashboard for immediate insight, decision-making, and action.

Here’s a video of the University of Queensland’s application performing real-time analysis of DNA nanopore sequencer data:

You can read the full article here.

Deconstructing Chatbots

AI and Chatbots are trending topics nowadays, but some people don’t understand how terrific could be a chatbot in business.

The following video shows how chatbots works, can they understand what humans says, and how they can response by using artificial intelligence.

Is your business leveraging chatbots to support clients or maybe your business planing the next move? Take a look.

 

7 Steps of Machine Learning (Artificial Intelligence)

Hi 4Geeks Nation! I want to share with you this video (from Google AI) that explain so clear 7 steps of Machine Learning.

  • Gathering Data
  • Preparing that Data
  • Choose a model
  • Training
  • Evaluation
  • Hyperparameter Tuning
  • Prediction

 

SmarterSelect: 4 Main Product Challenges Solved

Digital businesses need a good ideation, implementation, execution and growth, but at the development side the challenges are huge as well. As much as a product grows, so do the challenges and problems to solve.

In this opportunity I want to tell you the main product development challenge our engineering team faced, and I will show you how we fixed it. Maybe your business are facing some similar issues and this post can help you to find a solution.

SmarterSelect is a web platform to create and manage forms. As they say: “Online Applications. Made Easy”. Over 1 million active users (and counting) are creating and managing online applicationsgrantsscholarships on SmarterSelect every week in the United States.

SmarterSelect enable partners like Texas Tech UniversitySan Angelo Area Foundation and Vermeer to manage online applications.

4Geeks created a engineers dedicated team, getting together Ruby on Rails engineers and Quality Assurance experts, to solve past issues and improve the product constantly.

Let’s start! Here is the 4 main problems we found and how we fixed it.

Challenge #1: QA manual

Too many projects faces issues in production, customers don’t like that for sure. Our first recommendation is to add human power to avoid mistakes on development. QA people is amazing to think on hundred of combinations for test scenarios, that what SmarterSelect needed.

We added QA experts to the team, in the same building to improve communication on issues and help the developers to create ever more code quality.

Listen to this podcast episode when we talked with Meli, the QA Leader in SmarterSelect.

Challenge #2: Dockerize the app

I remember having some bad nights working with server infrastructure, libraries. With Docker we got rid of that, same container, same for all environment, we forget about the differences on development, staging or production.

Also, some advantage we see is when some new developer joins to the team. There will be no need to spend hours or days trying to install all gems, libraries and dependencies with just a docker command, voilà! environment ready. Our client is definitely happy for that.

Challenge #3: Implemented CI tools

The team introduced CircleCI to the projects, helping us on running the small (increasing)  set of automated tests before putting any code into main branches.

For every PR (Pull Request) we run CircleCI containers and confirm the code is not breaking any configuration or code.

Have you implemented (or thinking to do) CI tools on your project? Comment below your experience.

Challenge #4: Rails upgrade

This is a huge deal. Some day we decided that It was time to move from Rails 2 to Rails 4. It sounds crazy but we didn’t want to do a little migration to Rails 3 to later move to Rails 4. It was time to do the roughest change.

So for 4 months the team was focused on create features and migrate at the same time. It was a complete successful, and now we are thinking on move to Rails 5 for sure, but our client doesn’t know (probably he will find out here).

We improve some security issues by that migration and we also did some refactors on old legacy code.

 

Bonus: Download the full Case Study in order to get know how SmarterSelect grew up more than 110% in 2018.

If you need help with your business/product and your annual revenue is $3M+, please reach out to us; our consultants will be happy to assist you on find the right path and solution.

How We Built a Real Chatbot for Google Assistant, Step by Step

I know a lot of software companies blogging about top emerging technologies, and talking about how easy can be create a product by implementing technologies like Machine Learning, Artificial Intelligence and so. There are hundred of people requesting attention out there.

Instead of talking, 4Geeks is building and creating products; and today I would like to show you how we built a real chatbot for Google Assistant… for example purposes.

 

Google Assistant is the engine running on Google Home (smart speakers – similar to Amazon Alexa), mobile phones, websites, watches and cars. Yep, cars. Take a look at this video to understand Google Assistant scope.

A chatbot basically is a program with capability to understand natural language (English, Spanish, French…) and trigger orders.

We have been sharing a lot of valued content for developers and decision makers about the unmeasurable power of Artificial Intelligence for so many industries.

Step by step

Please, look at the following 52-min video (please enable captions) where I built a real chatbot, step by step. For this demo I used some technologies like DialogFlow, to send orders and interact with Google Assistant on a natural-language way.

 

If you want to learn more about text-based and voice-based chatbots, maybe you want to listen this podcast episode where Sergio and I talked about chatbots. If you need help with your business processes automation, just let us know.

Have any questions? Please use the comments below.

4 Main Benefits of Using a Cloud Storage Service on Your Product

Hello there! Today I want to put in perspective one of the most powerful tools of Cloud Computing on modern products. Any kind of product, any industry… it may be a SaaS or PaaS.

If you already know what cloud storage is, good. But if don’t have idea what is it, let me explain you in a few words: Cloud storage is a cloud computing model in which data is stored on remote servers accessed from the internet. That’s it. And there are some excellent providers in the game like Amazon Web Services (AWS S3), Google Cloud Storage and Microsoft Azure Storage.

One of my favorite cloud storage providers is Google Cloud Storage. Why? Listen to this podcast episode when I talked, with Sergio, about this service, pros and cons.

Some popular services like Netflix, Uber, Coca-Cola, Spotify and Mall4G are storing a huge size of objects on cloud storage, keeping a good server performance and scaling as much they can.

Let me know detail you the 4 main benefits of using cloud storage on your current or next product, and why founders love it:

Benefit #1: Better product performance – auto CDN.

More and more product owners are splitting assets (images, CSS, videos, fonts…) to upload it to a cloud storage service because they already how fast and secure is the content delivery rate. So, it means two advantages: don’t overcharge main servers and leveraging on a CDN (Content Delivery Network) to delivery objects to users browser or phone app.

When the 4Geeks team integrated a storage service on Appetito24 (food delivery app), users in different regions automatically obtained an improvement in the mobile app and web administration panel: 65% faster.

Here the map of Google Cloud Platform datacenter locations around the world.

Google Cloud Platform datacenter locations

 

And here is the Amazon Web Services (AWS) and Microsoft Azure datacenter location around the world.

Amazon and Azure datacenter locations

Benefit #2: Money saving

This is one of the most important advantages of cloud storage, because the current providers have very competitive billing plans. The price may vary depending on the provider, but I can say that starts from $0.026 USD per Gigabyte per month.

Now you can figure out the price to store a movie on a cloud storage service.

Google, for example, offers a free quota of 5GB per month.

 

Benefit #3: Good for a recovery plan

I know some traditional companies, like Despacho Carvajal in Costa Rica, that are hosting its important docs, images and videos on a cloud storage service as its main backup plan. Store unlimited objects, 100% private (or public– you choose.).

Google Cloud Storage, for example, can manage different versions of a single object; so it make possible to rollback as much you need to get a preview object version. This is so powerful.

 

Benefit #4: Scalable service

Founders know the power of scalability. Please imagine for a few seconds: Netflix uploads a movie one single time, and it can appears instantly on all TVs, computers, phones and tables around the globe. By magic.

 

Security deserves a complete article, which I will publish soon for you.

As always, if you need help to migrate your product assets to a cloud storage service, please feel free to pick a date to autogenerate an online meeting with me. Or if just looking for more information, write us at any time. The engineering team can assist you to take a good decision for your company.

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