With the growth of the JAMstack and its community, Static Site Generators are becoming more and more popular. In this article, let’s take a look at the top Static Site Generators of 2020!
First off, let’s quickly talk about the benefits of Static Site Generators.
Static Site Generators generate your site pages at build-time instead of real-time. This means that when a user requests a page from your site, there is no delay. No calls to a database. No generating of HTML. It simply responds with the file itself.
Because of this, the hosting of your files is incredibly easy. By hosting your website in a Content Delivery Network (CDN), your files can be replicated across the world for maximum speed.
Before Static Site Generators, developers would use popular Content Management Systems (CMS). Because of their popularity, they were often targeted by hackers. With Static Site Generators, you don’t need a CMS anymore. This means you don’t have to worry about your website/data being targeted.
With Static Site Generators, you don’t need to create or manage your own backend server. You also don’t have to run your own database. This makes it incredibly easy to run your site locally, automate builds, switch to a different host, etc.
There are many more benefits, but let’s get on to the list!
In the JAMstack, we will have data for our content that we grab via an API and we will have our markup that we send to our users. The flow looks like this:
Gatsby is my favorite on this list and the one that I use almost daily for personal sites and demo projects. Gatsby has really made a name for itself over the past couple of years, having successfully secured multiple rounds of funding.
I can find a Gatsby plugin for almost everything I need!
The thing that makes me most excited about Gatsby is the plugin ecosystem. For almost every problem I come across, I can usually find a plugin to help.
Gatsby also recently released Gatsby Cloud which is advertised as “the best way to create and deploy Gatsby websites”. It’s worth a look if you are building Gatsby sites.
Next.js is another amazing option that is built on top of React. It is also extremely popular in the community and basically the other de facto Static Site Generator that uses React.
Although we are listing it as a Static Site Generator, it is important to note that that is not all it is. Next.js first and foremost supports server rendering. You also can define serverless functions as API endpoints. This gives you lots of control over how you build and deploy your Next.js applications.
So far, we’ve talked about two Static Site Generators based on React. Now, let’s transition over to a few built on top of Vue, starting with Gridsome.
That said, Gridsome is most comparable to Gatsby. Similar to Gatsby, it is powered by GraphQL, which is a fan favorite in the developer community right now. It also has support for PWAs and code splitting out of the box. I hear lots of good things about Gridsome, so if you’ve got some Vue experience, this is a great place to start.
While Gridsome compares nicely with Gatsby, our next item, Nuxt.js, compares favorably with Next.js. In fact, Next.js was the inspiration for Nuxt.js.
For example, they both support server rendering as well as statically generated content. Nuxt.js states to have the “best of both worlds” with it’s ability powerfully combine the two.
Here’s one extra tid bit that Nuxt.js mentions. Developers don’t need to take advantage of either server rendering or statically generated content to find a reason to use Nuxt.js. As with with the frameworks mentioned above, Nuxt.js adds some niceties on top of Vue (think automatic route configurations) that might be worth considering regardless.
11ty brands itself as a “simpler static site generator”. This makes it easy to pick up and easy to customize. One of the favorite features I hear others talk about is the fact that you choose your own templating language. If you are already familiar with something like Handlebars, go ahead and use it.
One of the cool features of Hugo is its built-in templates. These are helpful for getting up and running with Hugo quickly. It takes advantage of shortcuts that can be used in Markdown to add more flexibility and reusability.
Jekyll is another extremely popular option, and it is built with Ruby. Ruby was an incredibly popular programming language most notably with the Ruby on Rails framework. So, if you’re coming from a Ruby/Ruby on Rails background, you’ll want to check in with Jekyll. It is one of the Static Site Generators that has been around the longest.
Jekyll combines Markdown files with the very popular Liquid templating engine. It’s also interesting to note that Github Pages are powered by Jekyll. This means that you can easily deploy your Jekyll site to GitHub for free!
Although Angular might not have the type of community that React has, it is still immensely popular. Angular’s CLI is amazing and with it, you can add Scully to an existing project with one command. Angular has done some amazing things in their upgrade paths in the last several versions and this is just another example of that. The Angular CLI also has some amazing scaffolding commands built in to generate project files for you.
PHP is another incredibly popular language that we haven’t yet talked about. If you are most comfortable with PHP (maybe back from doing Wordpress development), then you’ll want to check out Sculpin. It uses Markdown files and a templating engine called Twig.
Fun fact. Sapper stands for Svelte app maker
Sapper is most easily compared with Next.js, and it actually got its inspiration from Next.js. Similar to Next.js, Snapper has the ability to server render pages as well as define API endpoints. Snapper then offers the ability to export as a static site.
Middleman is the last Static Site Generator on our list, and it uses Ruby as its language of choice. Similar to Jekyll above, you’ll want to be familiar with Ruby and the RubyGems ecosystem before jumping into Middleman. One of the things I liked when researching this framework, is that there are videos embedded in their documentation. As a person who learns best from video, I really appreciate this.
Middleman uses ERB as its default templating language, something you might be familiar with if you have worked with Ruby on Rails in the past. Middleman also gives you access to a few other templating languages as well.
Multiple vulnerabilities in the Citrix Application Delivery Controller (ADC) and Gateway would allow code injection, information disclosure and denial of service, the networking vendor announced Tuesday. Four of the bugs are exploitable by an unauthenticated, remote attacker.
The Citrix products (formerly known as NetScaler ADC and Gateway) are used for application-aware traffic management and secure remote access, respectively, and are installed in at least 80,000 companies in 158 countries, according to a December assessment from Positive Technologies.
Other flaws announced Tuesday also affect Citrix SD-WAN WANOP appliances, models 4000-WO, 4100-WO, 5000-WO and 5100-WO.
Attacks on the management interface of the products could result in system compromise by an unauthenticated user on the management network; or system compromise through cross-site scripting (XSS). Attackers could also create a download link for the device which, if downloaded and then executed by an unauthenticated user on the management network, could result in the compromise of a local computer.
“Customers who have configured their systems in accordance with Citrix recommendations [i.e., to have this interface separated from the network and protected by a firewall] have significantly reduced their risk from attacks to the management interface,” according to the vendor.
Threat actors could also mount attacks on Virtual IPs (VIPs). VIPs, among other things, are used to provide users with a unique IP address for communicating with network resources for applications that do not allow multiple connections or users from the same IP address.
The VIP attacks include denial of service against either the Gateway or Authentication virtual servers by an unauthenticated user; or remote port scanning of the internal network by an authenticated Citrix Gateway user.
“Attackers can only discern whether a TLS connection is possible with the port and cannot communicate further with the end devices,” according to the critical Citrix advisory. “Customers who have not enabled either the Gateway or Authentication virtual servers are not at risk from attacks that are applicable to those servers. Other virtual servers e.g. load balancing and content switching virtual servers are not affected by these issues.”
A final vulnerability has been found in Citrix Gateway Plug-in for Linux that would allow a local logged-on user of a Linux system with that plug-in installed to elevate their privileges to an administrator account on that computer, the company said.
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In this Intellipaat’s top 10 technologies to learn in 2020 video, you will learn all the trending technologies in the market in 2020. The end goal of this video is to educate you about the latest technologies to learn and all the top 10 trending technologies you can watch for in order to make a fantastic career in IT technologies in 2020.
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Technology has taken a place of more productiveness and give the best to the world. In the current situation, everything is done through the technical process, you don’t have to bother about doing task, everything will be done automatically.This is an article which has some important technologies which are new in the market are explained according to the career preferences. So let’s have a look into the top trending technologies followed in 2021 and its impression in the coming future in the world.
First in the list of newest technologies is surprisingly Data Science. Data Science is the automation that helps to be reasonable for complicated data. The data is produces in a very large amount every day by several companies which comprise sales data, customer profile information, server data, business data, and financial structures. Almost all of the data which is in the form of big data is very indeterminate. The character of a data scientist is to convert the indeterminate datasets into determinate datasets. Then these structured data will examine to recognize trends and patterns. These trends and patterns are beneficial to understand the company’s business performance, customer retention, and how they can be enhanced.
Next one is DevOps, This technology is a mixture of two different things and they are development (Dev) and operations (Ops). This process and technology provide value to their customers in a continuous manner. This technology plays an important role in different aspects and they can be- IT operations, development, security, quality, and engineering to synchronize and cooperate to develop the best and more definitive products. By embracing a culture of DevOps with creative tools and techniques, because through that company will gain the capacity to preferable comeback to consumer requirement, expand the confidence in the request they construct, and accomplish business goals faster. This makes DevOps come into the top 10 trending technologies.
Next one is Machine learning which is constantly established in all the categories of companies or industries, generating a high command for skilled professionals. The machine learning retailing business is looking forward to enlarging to $8.81 billion by 2022. Machine learning practices is basically use for data mining, data analytics, and pattern recognition. In today’s scenario, Machine learning has its own reputed place in the industry. This makes machine learning come into the top 10 trending technologies. Get the best machine learning course and make yourself future-ready.
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The Deep Learning DevCon 2020, DLDC 2020, has exciting talks and sessions around the latest developments in the field of deep learning, that will not only be interesting for professionals of this field but also for the enthusiasts who are willing to make a career in the field of deep learning. The two-day conference scheduled for 29th and 30th October will host paper presentations, tech talks, workshops that will uncover some interesting developments as well as the latest research and advancement of this area. Further to this, with deep learning gaining massive traction, this conference will highlight some fascinating use cases across the world.
Here are ten interesting talks and sessions of DLDC 2020 that one should definitely attend:
By Dipanjan Sarkar
**About: **Adversarial Robustness in Deep Learning is a session presented by Dipanjan Sarkar, a Data Science Lead at Applied Materials, as well as a Google Developer Expert in Machine Learning. In this session, he will focus on the adversarial robustness in the field of deep learning, where he talks about its importance, different types of adversarial attacks, and will showcase some ways to train the neural networks with adversarial realisation. Considering abstract deep learning has brought us tremendous achievements in the fields of computer vision and natural language processing, this talk will be really interesting for people working in this area. With this session, the attendees will have a comprehensive understanding of adversarial perturbations in the field of deep learning and ways to deal with them with common recipes.
By Divye Singh
**About: **Imbalance Handling with Combination of Deep Variational Autoencoder and NEATER is a paper presentation by Divye Singh, who has a masters in technology degree in Mathematical Modeling and Simulation and has the interest to research in the field of artificial intelligence, learning-based systems, machine learning, etc. In this paper presentation, he will talk about the common problem of class imbalance in medical diagnosis and anomaly detection, and how the problem can be solved with a deep learning framework. The talk focuses on the paper, where he has proposed a synergistic over-sampling method generating informative synthetic minority class data by filtering the noise from the over-sampled examples. Further, he will also showcase the experimental results on several real-life imbalanced datasets to prove the effectiveness of the proposed method for binary classification problems.
By Dongsuk Hong
About: This is a paper presentation given by Dongsuk Hong, who is a PhD in Computer Science, and works in the big data centre of Korea Credit Information Services. This talk will introduce the attendees with machine learning and deep learning models for predicting self-employment default rates using credit information. He will talk about the study, where the DNN model is implemented for two purposes — a sub-model for the selection of credit information variables; and works for cascading to the final model that predicts default rates. Hong’s main research area is data analysis of credit information, where she is particularly interested in evaluating the performance of prediction models based on machine learning and deep learning. This talk will be interesting for the deep learning practitioners who are willing to make a career in this field.
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