How has Web development changed in the last decade? Take a look at Ivan Zarea’s summary of the decade of Web development. The following is an excerpt from the author’s blog.
https://medium.freecodecamp.org/web-development-explained-to-a-time-traveler-from-ten-years-ago-600fad81170d
Dear friends, I hope you enjoy our new world. It has changed dramatically since 2007. It’s good to see that people still like computers. We now have far more computers than we did a decade ago, and that has created new challenges. Wearables, pocket devices, furniture smart devices, self-driving cars, they’re all computers. We also taught programs to play various games and beat humans. Of course, drinking may be the only thing that computers can’t compete with humans.
Apple has become the largest and richest technology company largely because of the iPhone and its operating system, iOS. Google has a rival operating system, Android, and Microsoft has tried unsuccessfully to get a piece of the action with Windows Phone.
The iPhone 3GS was released in 2008 and the iPhone X in 2017
We started calling programs apps, and some websites called themselves Web apps. In 2008, Google released its Chrome browser. Nine years later, Chrome is one of the most popular browsers.
The Chrome team put a lot of effort into JavaScript, and Web apps use a lot of JavaScript code.
Many other companies have also invested heavily in JavaScript, which now supports classes and modules. Some languages can be compiled into JavaScript, such as TypeScript (from Microsoft) or Flow.
Nowadays, we use JavaScript a lot more because so few people use Flash anymore. We even use JavaScript instead of Perl on the server side, something called Node.
Responsive design
Remember Swing, SWT, and WXWidgets? We reinvented them in browsers, and new UI programming models emerged that focused on componentization.
We have to figure out how to design, build and test responsive apps while keeping them from getting too bloated, because everyone has a phone, but they don’t have a lot of data.
Component frameworks emerged: Google’s Angular, Facebook’s React, and Vue from the open source community.
In 2007, Facebook made its debut in the United States and is now a giant company. In addition to its large number of users, Facebook also has one of the most code in the world.
Facebook’s development team developed a lot of code and made it open source. They also have their own developer conference, F8. Most big companies have their own developer conferences.
New apps require more and more complex UI layouts, so CSS needs to change as well. We no longer use the table element to lay out images, and the frame element has pretty much disappeared. We built new standards, such as CSS Floats, Flexbox, and CSS Grid.
People have been iterating on these standards, developing frameworks like Bootstrap, Foundation, etc. We’ve also invented languages that can compile to CSS. They complement some of CSS’s weaknesses, such as variables and modularity, but are not perfect.
If you’re confused, you’re right, and in fact, we all are. There are more developers and tech companies are becoming more successful. We used to use the term “startup” to describe companies that were growing fast and a little out of place, but even that term is a bit out of date these days.
There are more programmers, more programs, more devices, and more data. We have to keep increasing the processing power of computers to process them, and we’ve developed techniques to extract useful value from data.
First, there is data science, which seeks to extract information from data.
For example, there’s a startup called Waze that lets users install an App on their phones that tracks their movements as they drive. Because so many people have installed the App, Waze has accumulated a lot of data on the movement of cars. Based on that data, they developed an app that can tell users about traffic congestion. Users can now open Waze’s App on their phones and see in real time where traffic jams are occurring and choose alternative routes.
Then Waze was acquired by Google, which is what happens to most startups.
A user is using Waze, and the screen displays other users’ pictures at the same time
Data science faces three major challenges — data storage, data learning and data application.
We now need to save a lot of information and find out what is useful. We need new databases. Databases like MySQL and PostgreSQL can no longer store terabytes of data.
Big Internet companies often face such challenges, so they have pioneered such technologies. Most of the technology is developed within these companies and then open source.
Then came NoSQL, which transformed some parts of the traditional relational database into a new database.
Hadoop stores data on many discrete computer nodes and defines MapReduce data processing.
Then Cassandra came along, which stores data on different nodes by keys and columns rather than tables, and also ensures that data is not lost when some nodes are offline.
Then there’s MongoDB, a handy database for prototyping. In 2017, we treat technology in the same way we treated stars a decade ago — with both adoration and extol. MongoDB is the Nickelback of 10 years ago.
Use machine learning techniques to turn an ordinary puppy image into an artistic work
In the data learning camp, the focus is on machine learning. Data scientists have a variety of tools in their technology toolbox, from classification to deep learning. They generally use Python and work with developers to apply machine learning to various areas.
With the help of data scientists, Web apps can use A/B testing techniques. The technique uses two different versions of the server to serve similar users to see which version achieves the desired goal faster.
Big companies like Airbnb, Uber, and Netflix run thousands of A/B tests at the same time to ensure the best possible experience for their users.
Companies like Netflix have a lot of users and they need to make sure their service is running all the time. Servers must be managed, and hundreds of new servers must be added if necessary.
That’s hard to do in a traditional data center, where Netflix’s engineers use virtual machines. Amazon launched AWS in 2006 to offer elastic cloud computing, or EC2, so people could use virtual machines in Amazon’s data centers.
Amazon has launched more than 80 services that help other companies grow quickly. We call it the cloud, but the name is hard to define.
Cloud services provided by Amazon
Google and Microsoft have launched their own cloud services to steal the market. These smart people compete with each other, and all sorts of crazy innovations start to happen.
First, we started thinking about how to make the infrastructure look more like code. Before, we had to buy a new server, plug in a keyboard, and install dependencies.
Today, we use administrative configuration tools such as Puppet, Chef, and Ansible to automate server configuration. We write code in programming languages, such as Ruby, and assign servers based on configuration. If you need to make a change, you just need to modify the configuration and update the server, using SSH at most.
Then the container appears. EC2 provides us with machine allocation services, so our development environment should be as consistent as possible with our production environment.
First, we started the virtual machine with Vagrant, then came the Linux container, and finally Docker. We found a way to run Linux on a MacBook without having to install a full virtual machine.
By using Docker, we can create a development environment that is similar to the production environment. Developers use Docker images to deploy applications into containers.
There were a lot of macBooks at the Windows 10 launch
Cloud vendors are also following suit, running containers directly on their clouds and offering orcheation frameworks like Marathon and Kubernetes. With these frameworks, developers don’t have to worry about application scaling, fault tolerance, monitoring, and discovery. Servers can be recalled, but this time we won’t give them fancy names.
Developers can create small applications, called microservices, that run independently. And because microservices are less dependent on the outside world, we started experimenting with more new programming languages to implement microservices, such as Go and Java.
We can also use JVM-based Scala and Clojure, as well as the associated class libraries. Airbnb uses hundreds of microservices in many different languages and databases.
Because of microservices, we have to rethink our programming model. Because now we need to coordinate more and smaller applications.
Apache Kafka, Google PubSub, and RabbitMQ came along to help servers interact better. Kafka was originally developed by LinkedIn and later open-source.
There are more and more developers, software, and ideas coming out, and I hope that people are still interested in computers. In fact, we have every reason to do so.
The first macOS bug to hit Twitter? Is not
Like a magic carpet, how about Motan, the open RPC framework for Weibo?
Recently, I found an expert on JVM. When I think of the students we talk about architecture, in fact, many of them are Java department, so I recommend them. If you are interested, you can have a look at them.
The official account name is “you fake stupid” (LovestBlog), which is a rare JVM official account in China. The author is Han Quanzi, former JVM expert of Ali JVM team, who has many fans in Ali. The public number is mainly the author for the work encountered or the classic JVM case proposed by users from the perspective of THE JVM source in-depth analysis, the article is quite classic.
I recommend ArchSummit, the global Architect Summit, which kicks off this Friday.
There were a lot of big things happening in architecture in 2017. Kubernetes ended the container orcheography debate, Kafka released 1.0, Serverless gained momentum, edge computing replaced cloud computing, and Service Mesh was poised to take off. In addition, artificial intelligence enables business and brings new challenges to architecture.
We hope to summarize the past practice with 4 in-depth training sessions and 100+ sharing, and also look into the future of architecture for the readers who talk about architecture. We also have Dr. Jian Wang here to share his thoughts on technology.
Conference full speech catalog, you can identify the following TWO-DIMENSIONAL code or click to read the original to understand, looking forward to progress with you!
