Alternatives to Dialpad

Using Screenhero via Slack was getting to be pretty horrible. Video and sound quality was often times pretty bad and worst of all the service just wasn't reliable. We all had high hopes when the acquisition went through but ultimately, the product just didn't live up to expectations. We ended up trying Zoom after I had heard about it from some friends at other companies. We noticed the video/sound quality was better, and more importantly it was super reliable. The Slack integration was awesome (just type /zoom and it starts a call)

You can schedule recurring calls which is helpful. There's a G Suite (Google Calendar) integration which lets you add a Zoom call (w/dial in info + link to web/mobile) with the click of a button.

Meeting recordings (video and audio) are really nice, you get recordings stored in the cloud on the higher tier plans. One of our engineers, Jerome, actually built a cool little Slack integration using the Slack API and Zoom API so that every time a recording is processed, a link gets posted to the "event-recordings" channel. The iOS app is great too!

#WebAndVideoConferencing #videochat

Server side

We decided to use Python for our backend because it is one of the industry standard languages for data analysis and machine learning. It also has a lot of support due to its large user base.

• Web Server: We chose Flask because we want to keep our machine learning / data analysis and the web server in the same language. Flask is easy to use and we all have experience with it. Postman will be used for creating and testing APIs due to its convenience.

• Machine Learning: We decided to go with PyTorch for machine learning since it is one of the most popular libraries. It is also known to have an easier learning curve than other popular libraries such as Tensorflow. This is important because our team lacks ML experience and learning the tool as fast as possible would increase productivity.

• Data Analysis: Some common Python libraries will be used to analyze our data. These include NumPy, Pandas , and matplotlib. These tools combined will help us learn the properties and characteristics of our data. Jupyter notebook will be used to help organize the data analysis process, and improve the code readability.

Client side

• UI: We decided to use React for the UI because it helps organize the data and variables of the application into components, making it very convenient to maintain our dashboard. Since React is one of the most popular front end frameworks right now, there will be a lot of support for it as well as a lot of potential new hires that are familiar with the framework. CSS 3 and HTML5 will be used for the basic styling and structure of the web app, as they are the most widely used front end languages.

• State Management: We decided to use Redux to manage the state of the application since it works naturally to React. Our team also already has experience working with Redux which gave it a slight edge over the other state management libraries.

• Data Visualization: We decided to use the React-based library Victory to visualize the data. They have very user friendly documentation on their official website which we find easy to learn from.

Cache

• Caching: We decided between Redis and memcached because they are two of the most popular open-source cache engines. We ultimately decided to use Redis to improve our web app performance mainly due to the extra functionalities it provides such as fine-tuning cache contents and durability.

Database

• Database: We decided to use a NoSQL database over a relational database because of its flexibility from not having a predefined schema. The user behavior analytics has to be flexible since the data we plan to store may change frequently. We decided on MongoDB because it is lightweight and we can easily host the database with MongoDB Atlas . Everyone on our team also has experience working with MongoDB.

Infrastructure

• Deployment: We decided to use Heroku over AWS, Azure, Google Cloud because it is free. Although there are advantages to the other cloud services, Heroku makes the most sense to our team because our primary goal is to build an MVP.

Other Tools

• Communication Slack will be used as the primary source of communication. It provides all the features needed for basic discussions. In terms of more interactive meetings, Zoom will be used for its video calls and screen sharing capabilities.

• Source Control The project will be stored on GitHub and all code changes will be done though pull requests. This will help us keep the codebase clean and make it easy to revert changes when we need to.

Hi, We are looking to implement 2FA - so that users would be sent a Verification code over their Email and SMS to their phone.

We faced some limitations with Amazon SNS where we could either send the verification code to email OR to the phone number, while we want to send it to both.

We also are looking to make the 2FA more flexible by adding any other options later on.

What are the best alternatives to SNS for this use case and purpose? Looked at Twilio but want to explore other options before making a decision.

Would be great to know what the experience with Twilio has been, especially the limitations/issues with Twilio...

Appreciate any input from users of Twilio and others who have had similar use cases.

Searching for options for SMS that integrates with SiteLink and will allow personalization of text and tracking of both incoming/outgoing messages with reporting (Time, date, call#, etc) Have been looking at Twilio, and seems most leaning toward this. Are there any other options known that integrate into SiteLink? Also looked at Clickatell.

At StackShare we were discussing how to increase the retention of our newly signed up users. We hypothesized that if we made certain changes to the emails in our on-boarding process we could increase our retention and activation of users.

We decided to use sendwithus because it offered us the ability to A/B test our transactional emails. We also utilized the sendwithus analytics dashboard to gain real time insight into the performance of our email campaigns. Furthermore sendwithus has a Rails gem that allowed us to easily integrate the product into our application. We were also able to integrate sendwithus with our SendGrid account. #ABTestingAnalytics #TransactionalEmail

Nexmo vs Twilio ?

Back in the early days at SmartZip Analytics, that evaluation had - for whatever reason - been made by Product Management. Some developers might have been consulted, but we hadn't made the final call and some key engineering aspects of it were omitted.

When revamping the platform, I made sure to flip the decision process how it should be. Business provided an input but Engineering lead the way and has the final say on all implementation matters. My engineers and I decided on re-evaluating the criteria and vendor selection. Not only did we need SMS support, but were we not thinking about #VoiceAndSms support as the use cases evolved.

Also, on an engineering standpoint, SDK mattered. Nexmo didn't have any. Twilio did. No-one would ever want to re-build from scratch integration layers vendors should naturally come up with and provide their customers with.

Twilio won on all fronts. Including costs and implementation timelines. No-one even noticed the vendor switch.

Many years later, Twilio demonstrated its position as a leader by holding conferences in the Bay Area, announcing features like Twilio Functions. Even acquired Authy which we also used for 2FA. Twilio's growth has been amazing. Its recent acquisition of SendGrid continues to show it.