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Linux is commonly preferred among network engineers—so if you’ve thought about installing it for your work, you’re not alone.

If you’re a network engineer, it’s easy to wonder which distributions will have the best features for your work. Here are the six best Linux distributions for network engineering:

1. Fedora

Of all the Linux distributions, one of the most highly regarded among network engineers is Fedora—and there’s a simple reason why.

Fedora is an open-source distribution that serves as a community equivalent to Red Hat Enterprise Linux (RHEL). RHEL itself is commonly chosen as the operating system for enterprise-level systems.

As a result, network engineers who use Fedora enjoy a greater level of familiarity with the RHEL systems they may encounter throughout their careers.

Fedora also offers users an incredible arsenal of open-source tools, built-in support for containerized applications, and consistent access to cutting-edge features and software.

Download: Fedora (free)

2. RHEL

As one of the most popular enterprise distributions, RHEL is a great option because it is robust and reinforced. Each version of RHEL has a 10-year lifecycle, meaning that you’ll be able to use your chosen version of RHEL (and enjoy little to no compatibility issues) for years.

By using RHEL, you’ll also become familiar with many of the systems you’re likely to encounter on the job.

Many of the qualities of RHEL that make it attractive as an enterprise solution are just as appealing for independent users.

RHEL comes pre-equipped with the SELinux security module, so you will find it easy to get started with managing access controls and system policies. You’ll also have access to tools like Cacti and Snort through the RPM and YUM package managers.

Download: RHEL (free for developers; $179 annually)

3. CentOS Stream

Much like Fedora, CentOS Stream is a distribution that stays in line with the development of RHEL. It serves as the upstream edition of RHEL, meaning that the content in the latest edition of CentOS Stream is likely to appear in RHEL’s next release.

While CentOS Stream may not offer the same stability as Fedora, its enticing inclusion of cutting-edge software makes it worth considering.

CentOS Stream also has a distinct advantage over downstream editions of RHEL following Red Hat’s decision to close public access to the source code of RHEL: it will continue to stay in line with the latest experimental changes considered for the next release of RHEL.

In the future, CentOS Stream is likely to become the best option for anyone seeking an RHEL-adjacent distribution.

Download: CentOS Stream (free)

4. openSUSE

Another powerful and reliable option for network engineers is openSUSE. openSUSE is impressively stable and offers frequent new releases, making it a good option if you prefer to avoid broken packages while still taking advantage of the latest software releases.

Out of the box, you won’t have any issues configuring basic network settings through YaST (Yet another Setup Tool). Many of the packages that come preinstalled with openSUSE can provide you with incredible utility.

Wicked is a powerful network configuration framework, for example, while Samba is perfect for enabling file-sharing between Linux and Windows systems. You won’t have any trouble installing the right tool for a job with openSUSE’s Zypper package manager.

Download: openSUSE (free)

5. Debian

Debian is a widely-renowned Linux distribution known for being incredibly stable and high-performance. Several branches of Debian are available, including Debian Stable (which is extremely secure and prioritizes stability) and Debian Unstable (which is more likely to break but provides access to the newest cutting-edge releases of software).

One of the biggest advantages of using Debian for network engineering is that it has an incredible package-rich repository with over 59,000 different software packages.

If you’re interested in trying out the newest niche and experimental tools in networking and cybersecurity, an installation of Debian will provide you with total access.

Download: Debian (free)

6. Kali Linux

As a distribution designed for penetration testing, Kali Linux comes with a massive variety of preinstalled tools that network engineers are certain to find useful. Wireshark offers tantalizing information about packets moving across a network, Nmap provides useful clues about network security, and SmokePing provides interesting visualizations of network latency.

Not all of the software packaged with Kali Linux is useful for network engineers, but luckily, new Kali installations are completely customizable. You should plan out what packages you intend to use in advance so that you can avoid installing useless packages and keep your Kali system minimally cluttered.

Download: Kali Linux (free)

Familiarize Yourself With Your New Networking Distro

While some Linux distributions are better suited to network engineers, almost any Linux distribution can be used with the right software and configurations.

You should test out software like Nmap and familiarize yourself with networking on your new Linux distro so that lack of familiarity doesn’t become an obstacle later on.

Data science is constantly evolving, with new papers and technologies coming out frequently. As such, data scientists may feel overwhelmed when trying to keep up with the latest innovations.

However, with the right tips, you can stay current and remain relevant in this competitive field. Thus, here are eight ways to stay on top of the latest trends in data science.

1. Follow Data Science Blogs and Newsletters

Data science blogs are a great way to brush up on the basics while learning about new ideas and technologies. Several tech conglomerates produce high-quality blog content where you can learn about their latest experiments, research, and projects. Great examples are Google, Facebook, and Netflix blogs, so waste no time checking them out.

Alternatively, you can look into online publications and individual newsletters. Depending on your experience level and advancement in the field, these blogs may address topics you’d find more relatable. For example, Version Control for Jupyter Notebook is easier for a beginner to digest than Google’s Preference learning for cache eviction.

You can find newsletters by doing a simple search, but we’d recommend Data Elixir, Data Science Weekly, and KDnuggets News, as these are some of the best.

2. Listen to Data Science Podcasts and Watch YouTube Videos

Podcasts are easily accessible and a great option when you’re pressed for time and want to get knowledge on the go. Listening to podcasts exposes you to new data science concepts while letting you carry out other activities simultaneously. Also, using interviews with experts in the field, some podcasts offer a window into the industry and let you learn from professionals’ experiences.

On the other hand, YouTube is a better alternative for audio-visual learners and has several videos at your disposal. Channels like Data School and StatQuest with Josh Starmer cover a wide range of topics for both aspiring and experienced data scientists. They also touch on new trends and methods, so following these channels is a good idea to keep current.

It’s easy to get lost in a sea of podcasts and videos, so carefully select detailed videos and the best podcasts for data science. This way, you can acquire accurate knowledge from the best creators and channels.

3. Learn Data Science Skills and Concepts From Courses and Books

Online courses allow learning from data science academics and experts, who condense their years of experience into digestible content. Recent courses cover several data science necessities, from hard-core machine learning to starting a career in data science without a degree. They may not be cheap, but they are well worth their cost in the value they give.

Additionally, books play an important role as well. Reading current data science books can help you learn new techniques, understand real-world data science applications, and develop critical thinking and problem-solving skills. These books explain in-depth data science concepts you may not find elsewhere.

Such books include The Data Science Handbook, Data Science on the Google Cloud Platform, and Think Bayes. You should also check out a few data science courses on sites like Coursera and Udemy.

4. Meet Industry Experts and Enthusiasts From Events and Communities

Attending conferences ushers you into an environment of like-minded individuals you can connect with. Although talking to strangers may feel uncomfortable, you will learn so much from the people at these events. By staying home, you will likely miss out on networking, job opportunities, and modern techniques like deep learning methods.

Furthermore, presentations allow you to observe other projects and familiarize yourself with the latest trends. Seeing what big tech companies are up to is encouraging and educative, and you can always take away something from them to apply in your work.

Data science events can be physical or virtual. Some good data science events to consider are the Open Data Science Conference (ODSC), Data Science Salon, and the Big Data and Analytics Summit.

5. Participate in Data Science Competitions and Hackathons

Data science hackathons unite data scientists to develop models that solve real-world problems within a specified time frame. They can be hosted by various platforms, such as Kaggle, DataHack, or UN Big Data Hackathon.

Participating in hackathons enhances your mastery and accuracy and exposes you to the latest data science tools and popular techniques for building models. Regardless of your results, competing with other data scientists in hackathons offers valuable insights into the latest advancements in data science.

Consider participating in the NERSC Open Hackathon, BNL Open Hackathon, and other virtual hackathons. Also, don’t forget to register for physical hackathons that may be happening near your location.

6. Contribute to Data Science Open Source or Social Good Projects

Contributing to open-source data science projects lets you work with other data scientists in development. From them, you’ll learn new tools and frameworks used by the data science community, and you can study project codes to implement in your work.

Furthermore, you can collaborate with other data scientists with different perspectives in an environment where exchanging ideas, feedback, and insights is encouraged. You can discover the latest techniques data science professionals use, industry standards, best practices, and how they keep up with data science trends.

First, search for repositories tagged with the data science topic on GitHub or Kaggle. Once you discover a project, consider how to contribute, regardless of your skill level, and start collaborating with other data scientists.

Following data science thought leaders and influencers on social media keep you informed about the latest data science trends. This way, you can learn about their views on existing subject matters and up-to-date news on data science trends. Additionally, it allows you to inquire about complicated subjects and get their reply.

You can take it a step further and follow Google, Facebook, Apple, and other big tech companies on Twitter. This gives you the privilege of knowing tech trends to expect, not only limited to data science.

Kirk Borne, Ronald van Loon, and Ian Goodfellow are some of the biggest names in the data science community. Start following them and big tech companies on Twitter and other social media sites to stay updated.

8. Share Your Data Science Work and Insights

Sharing your work lets you get feedback and suggestions from other data scientists with different experience levels and exposure. Their comments, questions, and critiques can help you stay up-to-date with the latest trends in data science.

You can discover trendy ideas, methods, tools, or resources you may not have known before by listening to their suggestions. For example, a person may unknowingly use an outdated version of Python until he posts his work online and someone points it out.

Sites like Kaggle and Discord have several data science groups through which you can share your work and learn. After signing up and joining a group, start asking questions and interacting with other data scientists. Prioritize knowledge, remember to be humble, and try to build mutually beneficial friendships with other data scientists.

Be a Lifelong Learner in Data Science

Continuous learning is necessary to remain valuable as a data scientist, but it can be difficult to keep up all by yourself. Consequently, you’ll need to find a suitable community to help you, and Discord is one of the best platforms to find one. Find a server with people in the same field, and continue your learning with your new team.

README

This laravel package helps you dynamically set more database configurations through the .env file or database.

REQUIREMENTS

STEPS TO INSTALL

composer require ikechukwukalu/dynamicdatabaseconfig

Introduction

The need for this package came up when I once handled an already existing project that, due to certain constraints, had 9 databases implemented for each country their application was being utilised. This application also had a central database that was used by every country as well.

The config/database file wasn’t pretty. I’d prefer to have all configurations within the .env file only. The Big question was, what if the databases required grew to 19? These were the problems, both pending and existing that needed a clean hack/solution.

Middlewares

• env.database.config
• dynamic.database.config

Env.database.config Middleware

This middleware fetches database configurations from the .env file using postfixes like ONE. This dynamically declares an additional database connection for your laravel application.

DB_HOST_ONE=127.0.0.1
DB_PORT_ONE=3306
DB_DATABASE_ONE=second_db
DB_USERNAME_ONE=root
DB_PASSWORD_ONE=

• Sample middleware implementation

use Illuminate\Http\Request;
use Illuminate\Support\Facades\Route;

/**
 * mysql is the type of relational database connection being replicated - $database
 * mysql_1 is the new connection name - $name
 * ONE is the postfix - $postfix
 */

Route::middleware(['env.database.config:mysql,mysql_1,ONE'])->group(function () {
    Route::post('/user', function (Request $request) {
        /**
         * $request->_db_connection === 'mysql_1'
         */
        return \App\Models\User::on('mysql_1')->find(1);
    });
});

Route::post('/user', function (Request $request) {
        /**
         * $request->_db_connection === 'mysql_1'
         */
        return \App\Models\User::on('mysql_1')->find(1);
})->middleware('env.database.config:mysql,mysql_1,ONE');

You would not need to add a postfix, ONE, parameter to the middleware for the $postFix variable if you simply set the following session value session(config('dynamicdatabaseconfig.session_postfix')), but when a postfix parameter has been set, it will be used instead of the session value.

Dynamic.database.config Middleware

This middleware fetches database configurations from the database_configurations table within the primary migration database. It utilises a unique $ref variable. It’s recommended that the unique $ref variable should be human readable, that way it becomes easier to run the package’s console commands for running migrations. This will also dynamically declare an additional database connection for your laravel application.

use Ikechukwukalu\Dynamicdatabaseconfig\Models\DatabaseConfiguration;

protected $hidden = [
        'ref',
        'name',
        'database',

        /**
         * Accepts only arrays
         */
        'configuration'
];

• Sample eloquent database insert

$countries = ['nigeria', 'ghana', 'togo', 'kenya'];
$config = \Config::get('database.connections.mysql');

foreach ($countries as $country) {
    $config['database'] = $country . '_db';
    DatabaseConfiguration::firstOrCreate(
    ['ref' => $country],
    [
        'ref' => $country,
        'name' => 'mysql_' . $country,
        'database' => 'mysql',
        'configuration' => $config
    ]);
}

• Sample middleware implementation

use Illuminate\Http\Request;
use Illuminate\Support\Facades\Route;

/**
 * nigeria is $ref value
 */

Route::middleware(['dynamic.database.config:nigeria'])->group(function () {
    Route::post('/user', function (Request $request) {
        /**
         * $request->_db_connection === 'mysql_nigeria'
         */
        return \App\Models\User::on('mysql_nigeria')->find(1);
    });
});

Route::post('/user', function (Request $request) {
        /**
         * $request->_db_connection === 'mysql_nigeria'
         */
        return \App\Models\User::on('mysql_nigeria')->find(1);
})->middleware('dynamic.database.config:nigeria');

You would not need to add a ref, nigeria, parameter to the middleware for the $ref variable if you simply set the following session value session(config('dynamicdatabaseconfig.session_ref')), but when a ref parameter has been set, it will be used instead of the session value.

By default, the values stored within the configuration field will be hashed, but you can adjust this from the .env file by setting DB_CONFIGURATIONS_HASH=false.

Migration

It’s compulsory to first migrate laravel’s initial database.

Other Migrations

• Default migrations
• Isolated migrations

Default Migrations

This will only migrate files within laravel’s default migration path database/migrations

php artisan env:migrate mysql mysql_1 ONE

php artisan dynamic:migrate nigeria

Isolated Migrations

This will only migrate files within the specified migration path database/migrations/folder

php artisan env:migrate mysql mysql_1 ONE --path=database/migrations/folder

php artisan dynamic:migrate nigeria --path=database/migrations/folder

Both Migrations

Running the migrations as displayed below will result in the respective database having the migrated data from migrations within database/migrations and database/migrations/folder.

php artisan env:migrate mysql mysql_1 ONE
php artisan env:migrate mysql mysql_1 ONE --path=database/migrations/folder

php artisan dynamic:migrate nigeria
php artisan dynamic:migrate nigeria --path=database/migrations/folder

Database Seeding

php artisan env:migrate mysql mysql_1 ONE --seed
php artisan env:migrate mysql mysql_1 ONE --seeder=DatabaseSeederOne
php artisan env:migrate mysql mysql_1 ONE --seeder=DatabaseSeederOne  --path=database/migrations/folder

php artisan dynamic:migrate nigeria --seed
php artisan dynamic:migrate nigeria --seeder=DatabaseSeederNigeria
php artisan dynamic:migrate nigeria --seeder=DatabaseSeederNigeria  --path=database/migrations/folder

Re-runing Migrations Afresh

php artisan env:migrate mysql mysql_1 ONE --fresh
php artisan env:migrate mysql mysql_1 ONE --fresh --seed
php artisan env:migrate mysql mysql_1 ONE --fresh --seeder=DatabaseSeederOne
php artisan env:migrate mysql mysql_1 ONE --path=database/migrations/folder --fresh
php artisan env:migrate mysql mysql_1 ONE --path=database/migrations/folder --fresh --seeder=DatabaseSeederOne

php artisan dynamic:migrate nigeria --fresh
php artisan dynamic:migrate nigeria --fresh --seed
php artisan dynamic:migrate nigeria --fresh --seeder=DatabaseSeederNigeria
php artisan dynamic:migrate nigeria --path=database/migrations/folder --fresh
php artisan dynamic:migrate nigeria --path=database/migrations/folder --fresh --seeder=DatabaseSeederNigeria

Refreshing Migrations

php artisan env:migrate mysql mysql_1 ONE --refresh
php artisan env:migrate mysql mysql_1 ONE --refresh --seed
php artisan env:migrate mysql mysql_1 ONE --refresh --seeder=DatabaseSeederOne
php artisan env:migrate mysql mysql_1 ONE --path=database/migrations/folder --refresh
php artisan env:migrate mysql mysql_1 ONE --path=database/migrations/folder --refresh --seeder=DatabaseSeederOne

php artisan dynamic:migrate nigeria --refresh
php artisan dynamic:migrate nigeria --refresh --seed
php artisan dynamic:migrate nigeria --refresh --seeder=DatabaseSeederNigeria
php artisan dynamic:migrate nigeria --path=database/migrations/folder --refresh
php artisan dynamic:migrate nigeria --path=database/migrations/folder --refresh --seeder=DatabaseSeederNigeria

Rolling Back Migrations

php artisan env:migrate mysql mysql_1 ONE --rollback
php artisan env:migrate mysql mysql_1 ONE --path=database/migrations/folder --rollback

php artisan dynamic:migrate nigeria --rollback
php artisan dynamic:migrate nigeria --path=database/migrations/folder --rollback

NOTE

• A primary database is needed before any other database can be migrated.
• A database will be created if it does not exist.
• Each database will retain it’s own independent migration table.
• It’s recommended that you do not publish the package’s migration file, unless you want the database_configurations table to be migrated into every extra database created when running Default migrations.

PUBLISH MIGRATIONS

• php artisan vendor:publish --tag=ddc-migrations

PUBLISH CONFIG

• php artisan vendor:publish --tag=ddc-config

LICENSE

The DDC package is an open-sourced software licensed under the MIT license.

Storing JSON data in a Laravel database provides a flexible solution for managing dynamic attributes or unstructured data. In this tutorial, we will walk through the process of storing JSON data in a Laravel database, using a practical example of storing product attributes. By the end of this tutorial, you will have a clear understanding of how to store and retrieve JSON data efficiently using Laravel.

Step 1: Setting up a Laravel Project

Create a new Laravel project using the following command:

laravel new json-data-storage

Step 2: Creating the Products Table Migration

Generate a migration file to create the products table using the command:

php artisan make:migration create_products_table --create=products

Inside the generated migration file (database/migrations/YYYY_MM_DD_create_products_table.php), define the table schema with a JSON column for the attributes:

<?php

use Illuminate\Database\Migrations\Migration;
use Illuminate\Database\Schema\Blueprint;
use Illuminate\Support\Facades\Schema;

return new class extends Migration
{
    /**
     * Run the migrations.
     */
    public function up(): void
    {
        Schema::create('products', function (Blueprint $table) {
            $table->id();
            $table->json('attributes');
            $table->timestamps();
        });
    }

    /**
     * Reverse the migrations.
     */
    public function down(): void
    {
        Schema::dropIfExists('products');
    }
};

Step 3: Running the Migration

Run the migration using the following command:

php artisan migrate

Step 4: Creating the Product Model

Generate a Product model using the command:

php artisan make:model Product

In the Product model (app/Models/Product.php), add the $casts property to specify that the attributes attribute should be treated as JSON:

<?php

namespace App\Models;

use Illuminate\Database\Eloquent\Factories\HasFactory;
use Illuminate\Database\Eloquent\Model;

class Product extends Model
{
    use HasFactory;

    protected $casts = [
        'attributes' => 'json',
    ];
}

Step 5: Storing Product Attributes as JSON

To store product attributes as JSON, we can simply use Laravel’s Eloquent model. Create a new Product instance, set the desired attributes as an array, and save it:

use App\Models\Product;

$product = new Product;
$product->attributes = [
    'color' => 'red',
    'size' => 'medium',
    'weight' => 0.5,
];
$product->save();

Step 6: Retrieving JSON Data

To retrieve the attributes of a product, you can access the attributes property on the model:

$product = Product::find(1);
$attributes = $product->attributes;

If you want to access a specific attribute within the JSON data, you can do so by using array access:

$color = $product->attributes['color'];

By accessing the attributes property, you can retrieve the JSON data associated with the product and access specific attributes as needed.

Step 7: Manipulating JSON Data (Full Array)

To update all the attributes of the product at once, you can assign a new array with all the key-value pairs and use Eloquent’s save() method to update the record directly.

$product = \App\Models\Product::find(1);
$product->attributes = [
    'color' => 'green',
    'size' => 'large',
    'weight' => 2.5,
];
$product->save();

Step 8: Manipulating JSON Data (One Value)

Updating a single value within the JSON data requires a slightly different approach in Laravel and has one important caveat. Directly modifying the attribute like $product->attributes['weight'] = 1.0 and saving the product will result in an ErrorException: “Indirect modification of overloaded property App\Models\Product::$attributes has no effect.”

To overcome this issue, you can follow the solution below:

$product = \App\Models\Product::find(1);
$attributes = $product->attributes; // create a copy of the array
$attributes['weight'] = 0.6; // modify the value in the copied array
$product->attributes = $attributes; // assign the copied array back to $product->attributes
$product->save();

Conclusion

Storing JSON data in a database using Laravel provides flexibility and convenience when working with dynamic or unstructured data. By following the steps outlined in this tutorial, you have learned how to create the necessary migrations and models, store and retrieve JSON data, and manipulate the JSON data efficiently. This knowledge equips you with the tools to handle various use cases in your Laravel applications and opens up possibilities for efficiently managing complex data structures.

Start implementing JSON data storage in your Laravel projects and unlock the full potential of your application’s data management capabilities. Happy coding!