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Netdata is a fully-featured StatsD server, meaning it collects formatted metrics from any application that you instrumented with your library of choice. Netdata is also its own backend implementation, as it offers instant visualization and long-term storage using the embedded time-series database (TSDB). When you install Netdata, you immediately get a fully functional StatsD implementation running on port 8125.

Since StatsD uses UDP or TCP to send instrumented metrics, either across localhost or between separate nodes, you鈥檙e free to deploy your application in whatever way works best for you, and it can still connect to Netdata鈥檚 server implementation. As soon as your application exposes metrics and starts sending packets on port 8125, Netdata turns the incoming metrics into charts and visualizes them in a meaningful fashion.

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Netdata - Introduction to StatsD (netdata.cloud)
3 upvotes4K views
Avatar of kexinlin
University of Toronto

I replaced Bootstrap with Material-UI during the front-end UI development, because Material-UI adopts a component-based importing style, making it suit well in a "React programming style". This makes me comfortable when programming because I can treat importing UI components as other React components I define.

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3 upvotes624 views
Avatar of quinte22
Machine learning/ software engineer

We've chosen Sentry for our exception logging. Both our web app and mobile app are connected to sentry, which allows us to access all of our logging in one place. Our developers are able to see error reports, crashes, user browsers, and more, all in one place. Sentry also seamlessly integrates with Slack and GitHub.

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3 upvotes260 views
Avatar of renanlecaro
Founder at Ciboulette.net

Meteor lets you do a lot, very fast. The result is not as lightweight as a pure backend app sprinkled with JS, but it makes sense for the heaviest uis of your app. I use meteor for the backend of the app, where farmers list their products, clients, etc .. The data is allways up to date (real time data sync) and the UI is derived from that data, which makes state management very easy.

Express and other backend only frameworks are great for making lightweight, accessible and fast pages. I use it for the public facing forms, which are seen by ~100 times more people. They are basic, fast, light, and work without JS and on shaky connection. The client side interactions are coded in vanilla js, transpiled by babel.

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2 upvotes224 views
Avatar of quinte22
Machine learning/ software engineer

Sumo Logic is our choice for general logging. Since our web application is being run on Heroku, one of the included add ons was sumo logic, automatically collecting all of our logging from our app. It allows us to monitor and troubleshoot in real time and act on threats instantly. The ease of integration into our tech stack was the main driver behind our choice

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2 upvotes266 views
Avatar of usmanmasoodsadiq
Student at University of Toronto
Migrated
from
DjangoDjango
to
FlaskFlask
at
()

We decided to migrate our web framework from Django to Flask for a number of reasons. Firstly, Flask is a light-weight framework which makes it easier to use for simpler cases and to build a quick prototype. It gives developers full freedom for what they want their application to look like. With a coherent and neat API, Flask allows easy and flexible configurations along with integrated unit testing support which makes it a great tool. By using Flask, a simple application can be later changed to add more functionality and make it complex. It provides flexibility to expand the application quickly which is harder to do with Django where requirements change dynamically. Moreover, Flask is a minimal yet powerful platform with easy database integration which gives us the opportunity to easily develop and maintain applications. On the other hand, Django has a high learning curve and is a higher entry point for simple solutions. In addition to that, Django requires roughly more than 2 times more lines of code than Flask for the same functionality. Django is suited for bigger projects that need a lot of functionality. For simpler projects like our application, the features might be an overkill. Putting all these factors into consideration, we decided it was best to switch to Flask from Django

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2 upvotes578 views
Avatar of ehenoma
Software Developer at Indie Lemon Gmbh

Java is a well known programming language that allows developers to focus on their application rather than lower level programming problems.

It has an advanced library for concurrency and generally performs well when using NIO.

The tooling is matured and it has some of the best IDEs. In comparison to newer languages on the JVM it may be rather conservative, but that can be an advantage as it promotes good coding patterns rather than awkward syntactic sugar.

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4 upvotes2K views

We choose React for our client-side implementation because of React's virtual DOM implementation and component rendering optimization. It can help our app to be more stable and easier to debug. Also, react has strong support from the dev community. There is an enormous amount of reacting libraries we could use, which will speed up our development process.

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14 upvotes1 comment4.9K views
Abdelhadi Sabani
Abdelhadi Sabani
February 27th 2021 at 8:47PM

The same with Vue!

Reply

We choose Next.js for our React framework because it's very minimal and has a very organized file structure. Also, it offers key features like zero setups, automatic server rendering and code splitting, typescript support. Our app requires some loading time to process the video, server-side rendering will allow our website to display faster than client-side rending.

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8 upvotes1 comment6.6K views
Mayur Borse
Mayur Borse
March 2nd 2021 at 3:17PM

I'm trying Aleph.js (https://alephjs.org/), a Deno alternative to Next.js. Very good experience overall.

Reply

Python has become the most popular language for machine learning right now since almost all machine learning tools provide service for this language, and it is really to use since it has many build-in objects like Hashtable. In C, you need to implement everything by yourself.

C++ is one of the most popular programming languages in graphics. It has many fancy libraries like eigen to help us process matrix. I have many previous projects about graphics based on C++ and this time, we also need to deal with graphics since we need to analyze movements of the human body. C++ has much more advantages than Java. C++ uses only compiler, whereas Java uses compiler and interpreter in both. C++ supports both operator overloading and method overloading whereas Java only supports method overloading. C++ supports manual object management with the help of new and delete keywords whereas Java has built-in automatic garbage collection.

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6 upvotes2 comments9.9K views
Rishi Vempati
Rishi Vempati
February 26th 2021 at 4:03PM

Python is becoming popular, but if you are looking to be a software engineer, go for Java; it can be used for a lot more things and incase you want to change your mind, you can use it to make a lot more things, such as game development

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Sachin Raja
Sachin Raja
March 2nd 2021 at 1:44AM

You might as well say use Python for game development because of pygame. Python has a flourishing ecosystem, allowing you to do pretty much anything. Just use whatever you like the best. Unity and Unreal (two of the biggest game engines) use C# and C++, so that would actually be a better route to go for game development.

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OpenCV is a library of programming functions mainly aimed at real-time computer vision. It is really famous in the industry realm nowadays. Many high-tech companies have chosen it as the primary developing tool, so do I.

I have learnt related courses in computer vision and graphics and OpenCV is the key to the success of these courses. It can provide us with highly efficient noise filters, convolution matrix and classical models. In my current project, I need to analysis the movement of the human body, which will include noise filtering, object recognition, and skeleton construction. OpenCV can provide us with HOG and other build-in models to make my life easier.

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2 upvotes2.5K views

Google Cloud Platform has comprehensive features. It can provide us with static IP, Computer Engine, and GPU for this project. It also gives us 300 $ for free to use.

I personally have previous developing experience with the Google Cloud Platform. I found it is really convenient and all features have clear documentations. I used the computer engine feature to build a virtual machine for my project. The virtual machine is really stable and secure. During this time search, I also find GCP has powerful data analytics ability, and even more, it has a well-constructed ecosystem.

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3 upvotes2.7K views

Pytorch is a famous tool in the realm of machine learning and it has already set up its own ecosystem. Tutorial documentation is really detailed on the official website. It can help us to create our deep learning model and allowed us to use GPU as the hardware support.

I have plenty of projects based on Pytorch and I am familiar with building deep learning models with this tool. I have used TensorFlow too but it is not dynamic. Tensorflow works on a static graph concept that means the user first has to define the computation graph of the model and then run the ML model, whereas PyTorch believes in a dynamic graph that allows defining/manipulating the graph on the go. PyTorch offers an advantage with its dynamic nature of creating graphs.

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1 upvote3.4K views
Avatar of ducklingsoftware
GO/C developer

Not to discourage people, but if you want to build SSR(server-side rendering) without Nuxt(well actually even with it), I recommend checking if you can go with react over vue. The main thing is, for some reason, SSR components is pretty common on Vue too, but a lot of them are not working with SSR right even if stated otherwise, so you end up building almost everything from scratch. It can be an issue with react too, but community is a bit larger so the components are more frequently updated, and there is generally more expertise in terms of SSR.

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3 upvotes3.3K views

Since now Jira is offering pretty wide free plans, it can compete with asana at small teams. And they have a significant advantage especially if you're working in agile methodology. Confluence is also a big advantage, and also comes with a free plan, so it's a pretty big thing. But we had also talked about asana and used to work with it before a lot, but we chose to go with Jira, and it's pretty good for now.

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4 upvotes4.7K views
Avatar of rhondablogs
Owner at Rhonda World

I chose Shopify over other options - the leading contender of which was WooCommerce - based mainly on the availability of integrations with other tools and platforms I use, as well as the ease of adding and updating inventory. Additionally, should I ever open a physical location, my existing inventory can easily be sold via a POS system as well. Eyes to the future!

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4 upvotes3.7K views
Needs advice
on
Angular Material Angular Material
and
Angular 2Angular 2

I need to implement a web application with a sidenav "drawer".

It's a very common UI nowadays. For example, Google Maps has a collapsable sidenav on the left that shows a "drawer": inside the drawer, things can be pretty complex and interact with the main screen. Also, Google Slide has one if you choose format options.

I'm not sure which frontend framework to use. AngularJS alone will be enough? Or is there something else on top? Any useful boilerplate? I need to concentrate on the features, not much on technical details.

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4 upvotes3.9K views
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Avatar of usmanmasoodsadiq
Student at University of Toronto

We will be using git for version control. In particular, we chose GitHub as it is the largest platform for version control. It integrates really well with several applications such as Heroku through Heroku鈥檚 command-line interface which will make it efficient and less time-consuming.

We will use Visual Studio Code as our text editor due to its great support for web development. It is a very fast editor which aids the developer in using proper syntax hence cutting down time spent on programming.

For communication, we chose Slack as it will let us collaborate effectively and coordinate our work from anywhere. With features such as impromptu video and voice chats as well as quick polls, Slack is great for quick questions and decisions and keeping everyone feel connected and in sync over time.

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9 upvotes6.5K views
Avatar of usmanmasoodsadiq
Student at University of Toronto

We will be using JavaScript and ReactJS on the frontend. React consumes much less development time in creating the user interface as it allows us to write modular and clean code which can then be reused later on. This modular code also allows us to easily maintain and update the application. React also creates declarative user interfaces which can result in more engaging and interactive user interfaces hence improving user experience. Furthermore, with features such as virtual DOM and server-side rendering, we can create applications that are really fast. Compared to Angular, React鈥檚 data synchronization process between Model and View is unidirectional which means bindings are not assigned watchers. This results in no additional workload created. React is also one of the most popular JavaScript frameworks worldwide and has a strong community supporting it. The flexibility offered in which structure to choose for the application also sets React apart

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9 upvotes6.1K views
Avatar of usmanmasoodsadiq
Student at University of Toronto

We chose Python as the primary language on the back end as it is easily readable, user-friendly, versatile, and has strong cross-platform compatibility. Due to it having a large and active developer community, it also has many libraries available which would cut down on time spent manually building everything from scratch. Most modern human pose estimation technologies are implemented in Python, so since much of our project revolves around pose estimation, using the same language for other components of our application will make it easier to integrate everything. In addition to that, Python is easily extensible as it has a number of web application frameworks. Python鈥檚 maturity is also attractive from the perspective of long-term support. Moreover, our team has a strong background in Python which means we would not have to spend time learning it from scratch.

The web framework we chose is Django due to its speed, safety, and stability. Django is very stable and robust and was created for fast development of complex web applications. Furthermore, Django has been around for a long time which means it has a number of extensions, plugins, and third-party applications.

We will be using Gunicorn as our WSGI application server. Gunicorn would handle everything that happens between the web server and the web application. This means that it will take care of reacting to a lot of web requests and distributing the load accordingly, communicating with the web-server, and keeping multiple processes running for the application. Therefore, the deployment will be more stable as well as be fast and handle more requests at once. Gunicorn is also the recommended HTTP server for use with Django on Heroku. It can run multiple Python concurrent processes within a single dyno which makes it the superior choice.

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7 upvotes5.5K views
Avatar of usmanmasoodsadiq
Student at University of Toronto

We chose PostgreSQL as our database due to it being relational. Given that our data is structured and limited, it would be easier to build schemas, divide the data into categories and define relationships between data points. These relationships will have constraints which will promote a high level of data integrity. Moreover, it is very easy to navigate around the database and join the tables to get whatever we desire. Our data would also comfortably fit in rows and columns and the data transactions would be very secure which makes a relational database a better choice. We picked PostgreSQL as the relational database because it is fast, it supports a wide array of extensions, and has high scalability. Being an object-relational database, PostgreSQL includes features like table-inheritance and function-overloading which will be beneficial. In addition to that, all of the team members have prior experience in using it. It is also very easy to connect the database to Python on the back-end with pyodbc which makes it extremely easy to work with.

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6 upvotes4.4K views
Avatar of usmanmasoodsadiq
Student at University of Toronto
Chose
OpenCVOpenCV

We plan to use OpenCV due to its clear leadership among computer vision libraries, and due to most modern human pose estimation technologies being built on top of it. It is one of the largest computer vision libraries available which can be incorporated with a number of open-source languages. Moreover, OpenPose has the additional advantage of simple integration with several mature numerical analysis libraries like numpy, which will support the continuous addition and improvement of pose-estimation-based analysis features in our application.

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4 upvotes3.6K views
Avatar of usmanmasoodsadiq
Student at University of Toronto

For our cloud platform, we will be using Heroku. Heroku allows us to focus on the code and innovation rather than the infrastructure and operations, and have a unified dashboard for the team, hence improving the team鈥檚 productivity. It also has broad support for many modern technologies, making it easy to integrate whatever building blocks might be required for our application. Moreover, a strong command-line interface makes it easy and quick to use.

In order to store our videos, we will be using Amazon S3, a very durable and accessible storage service which integrates cleanly with Heroku. It is a secure object storage platform with a simple web service interface that can store and retrieve any amount of data at any time. This will make it extremely easy to store a large number of files on Amazon S3 and use them with Heroku when needed. Furthermore, it lets us preserve, retrieve and restore every version of every object in the bucket which would be beneficial for getting older versions of our data if needed. There are also many options for cloud data migration which makes it simple to transfer large amounts of data to Amazon S3 or out of Amazon S3

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3 upvotes4K views

As a backend dev, it was quite easy to go with vue over react. Important note that Im now talking about Vue2 maybe the are crucial changes in third version, but the second one is super easy to get into without spending too much time learning concepts. And vue-cli is just a breeze to start a project with.

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6 upvotes8.1K views