PHP & Web Development Blogs

In today's dynamic and fast-paced world of web development, ensuring the reliability, performance, and scalability of applications is paramount. Monitoring and observability tools play a crucial role in achieving these goals by providing insights into application metrics, performance trends, and system health. Prometheus, a popular open-source monitoring and alerting toolkit, offers robust capabilities for monitoring infrastructure and application metrics. In this article, we'll explore how to leverage Prometheus with PHP to monitor, analyze, and troubleshoot PHP-based applications effectively.

Understanding Prometheus:

Prometheus is an open-source monitoring and alerting system originally developed by SoundCloud. It is designed for reliability, scalability, and extensibility, making it suitable for monitoring complex, distributed systems. Key features of Prometheus include:

Time Series Data: Prometheus collects time-series data, allowing developers to track metrics such as CPU usage, memory consumption, request latency, and HTTP response codes over time.

PromQL: Prometheus Query Language (PromQL) enables users to query and aggregate metrics, create custom dashboards, and set up alerting rules based on specific conditions.

Scalability and Reliability: Prometheus is designed to be highly scalable and reliable, supporting a distributed architecture with multiple replicas and federated setups for global monitoring.

Integrating Prometheus with PHP:

To integrate Prometheus with PHP applications, developers can utilize client libraries and instrumentation libraries that facilitate metric collection and exposition. The following steps outline the process of integrating Prometheus with PHP:

Choose a Prometheus Client Library: Select a Prometheus client library for PHP that suits your needs. Popular options include prometheus/client_php and php-prometheus/client.

Instrument Your PHP Code: Instrument your PHP application code to collect relevant metrics. This involves adding instrumentation code to track metrics such as request duration, memory usage, database queries, and custom business metrics.

Exposing Metrics: Expose the collected metrics in a format compatible with Prometheus. This typically involves exposing an HTTP endpoint (e.g., /metrics) where Prometheus can scrape the metrics using the Prometheus exposition format.

Configure Prometheus Server: Configure the Prometheus server to scrape metrics from the PHP application's endpoint. Update the Prometheus configuration file (prometheus.yml) to include the target endpoint and define any additional scraping parameters.

Example Integration:

Let's illustrate how to integrate Prometheus with a PHP application using the prometheus/client_php library:

require 'vendor/autoload.php';

use Prometheus\CollectorRegistry;
use Prometheus\Storage\APC;
use Prometheus\RenderTextFormat;

$registry = new CollectorRegistry(new APC());

$requestDuration = $registry->registerCounter('php_requests_total', 'Total number of PHP requests');

$requestDuration->inc();

$renderer = new RenderTextFormat();
echo $renderer->render($registry->getMetricFamilySamples());

In this example, we register a custom metric (php_requests_total) to track the total number of PHP requests. We then increment this metric for each request and expose the metrics endpoint using the Prometheus exposition format.

Benefits of Using Prometheus with PHP:

Real-time Monitoring: Prometheus provides real-time monitoring capabilities, allowing developers to monitor application metrics and diagnose issues promptly.

Scalability: Prometheus scales horizontally, making it suitable for monitoring large-scale deployments and distributed systems.

Alerting: Prometheus supports alerting based on predefined rules, enabling proactive monitoring and alerting for potential issues or anomalies.

Integration: Prometheus integrates seamlessly with various programming languages, platforms, and frameworks, including PHP, enabling comprehensive monitoring across the entire technology stack.

Conclusion:

Prometheus offers powerful capabilities for monitoring and observability, making it a valuable tool for developers and DevOps teams tasked with ensuring the reliability and performance of PHP applications. By integrating Prometheus with PHP using client libraries and instrumentation, developers can gain valuable insights into application metrics, troubleshoot issues effectively, and proactively respond to performance anomalies. Embracing Prometheus as part of your monitoring strategy empowers organizations to build resilient, scalable, and high-performing PHP applications in today's dynamic digital landscape.

Linux is an incredibly powerful operating system favored by developers, system administrators, and tech enthusiasts alike. Whether you're just starting your journey with Linux or looking to refresh your knowledge, understanding basic Linux commands is essential for navigating the command line interface (CLI) efficiently. In this beginner's guide, we'll introduce you to some fundamental Linux commands that will help you get started and feel more comfortable in the terminal.

Accessing the Terminal:

Before we dive into the commands, let's briefly discuss how to access the terminal on different Linux distributions:

-GNOME (Ubuntu, Fedora, Debian): Press Ctrl + Alt + T to open the terminal.

-KDE (Kubuntu): Press Alt + F2, type konsole, and press Enter.

-Command Line Interface (CLI) Only (Arch Linux, CentOS): You're already in the terminal!

Basic Navigation:

cd (Change Directory): Use cd followed by the name of the directory to navigate to that directory. For example:

cd Documents 

ls (List Files): Use ls to list the files and directories in the current directory.

ls 

pwd (Print Working Directory): Use pwd to display the full path of the current directory.

pwd 

File Management:

mkdir (Make Directory): Use mkdir followed by the name of the directory to create a new directory.

mkdir my_directory 

touch: Use touch followed by the name of the file to create a new empty file.

touch my_file.txt 

cp (Copy): Use cp followed by the source file and destination to copy files.

cp source_file.txt destination_directory/ 

mv (Move/Rename): Use mv followed by the source and destination to move or rename files.

mv old_name.txt new_name.txt 

rm (Remove): Use rm followed by the file name to delete files. Be careful as this action is irreversible.

rm unwanted_file.txt 

Working with Text:

cat (Concatenate): Use cat followed by the file name to display the contents of a file.

cat my_file.txt 

nano or vim (Text Editors): Use nano or vim followed by the file name to edit a file in the terminal.

nano my_file.txt 

grep (Global Regular Expression Print): Use grep followed by a search term and file name to search for a specific pattern in a file.

grep "pattern" my_file.txt 

System Information:

uname (Unix Name): Use uname to display system information.

uname -a 

df (Disk Free): Use df to display disk space usage.

df -h 

top or htop (Process Monitoring): Use top or htop to display real-time system resource usage.

top 

Conclusion:

Mastering basic Linux commands is the first step toward becoming proficient in using the Linux command line interface. In this guide, we've covered some essential commands for navigation, file management, working with text, and obtaining system information. As you continue to explore Linux, you'll discover a vast array of commands and utilities that can help you streamline your workflow and accomplish a wide range of tasks from the terminal. Happy command line exploring!

Today’s digital transformation has significantly empowered every company to produce accurate information at all touch points. Whether it’s a large-scale enterprise or a small private venture, every organization irrespective of all sizes needs proper web app development services to build a sophisticated database for storing and managing its data. Examples of web applications include customer relationship management (CRM) systems, project management tools, and e-commerce platforms. These custom software developers play a crucial role in tailoring web applications to meet specific business needs, ensuring seamless integration and optimal functionality.

A database is a set of a vast range of structured & unstructured data stored in a system and adequately managed through DBMS or Database Management System. The data stored in the database is highly sensitive, hence companies need to be careful while accessing any data or information.

When considering the development of web applications, partnering with a reputable web development firm is essential to ensure the seamless integration and efficient management of databases. A skilled web development firm possesses the expertise to optimize database systems, enhancing data organization, security, and retrieval processes for an enhanced user experience. In this article, we will delve into the top database solutions for web applications in 2024 and explore the advantages they bring to the forefront of modern software development.

Types of Databases For Web Applications

Depending on your business model, industry domain, and other factors, your business application system will have certain requirements. Different databases types are used for different enterprise requirements. However, the database is technically divided into two types: SQL & NoSQL.

SQL or Structured Query Language is a relational database that comes with a relational structure. This is used for managing structured data only. On the other hand, the NoSQL database doesn’t have any relational structure & they are used to store unstructured data types. For your convenience, we have shared a complete comparison of both databases below.

SQL Databases
NoSQL Databases
Mix of proprietary & open-source
Open source database
Comes with rational structure
No rational structure
Ideal for managing structured data
Best for storing unstructured & semi-structured data
Vertically scalable
Horizontally scalable
Examples: MySQL, PostgreSQL, Oracle, etc
Examples: MongoDB, Cassandra, Firebase, etc

Enterprises have deeply relied on SQL to manage all their databases in web apps, but as cloud, microservices & distributed applications become popular, there are NoSQL options also available. Before you choose the right database, you must consider a number of factors such as size, structure & scalability requirements. Apart from that, you need to consider some of the following questions also:
* What type of data structure do you need?
* What is the amount of data you want to store?
* What is your total budget?
* Does it allow for support contracts & software licenses?
* What is the requirement for your data security?
* What third-party tools do you want to add to your database?

Best Databases For Web Applications In 2024

Finding out the right database option for a web app development may impact the scalability and success of any project. With too many options available, it’s quite challenging to select which one is the best for you. 2024’s widely-popular databases include:

1. MySQL:

MySQL is one of the best open-source relational databases developed by Oracle Corporation in 1995. According to the Stack Overflow developer survey, this database was used by 46.8% as of 2022. The robustness, maturity, and stability of this database make it perfect for web applications. Moreover, MySQL database uses a structured language & written in C & C++.
Latest version: MySQL 8.0.33

Key features of MySQL database include:
* Easy to deploy & manage
* It supports Consistency, Atomicity, Isolation & Durability
* It’s an RDBMS or Relational Database Management System
* Provides fast-loading utilities with several memory caches to maintain servers
* Offers top-notch results without compromising any functionality
* Contains solid Data Security layers to offer complete security solutions

2. PostgreSQL:

Launched in 1996, PostgreSQL is also a very popular database used as a data warehouse or primary data store for web, analytics, geospatial and mobile applications. This is also an open-source SQL-based RDBMS (relational database management system) that supports C, C++, C#, Ruby, Java, Python, and other programming languages. This agile database is compatible with different OSs such as Windows, Linux, Unix, MacOSX, etc.
Latest version: PostgreSQL 15.3

Key features of the PostgreSQL database include
* Houses different constraints such as primary keys, foreign keys, exclusion constraints, explicit locks, advisory locks, etc
* Supports different SQL features like SQL Sub-selects, Multi-Version Concurrency Control,
* Streaming Replication, complex queries, etc.
* Compatible with different data types like Structured, Customizations, Primitives, Geometry & Documents.
* Supports MVCC or multi-version concurrency control

3. Microsoft SQL Server:

Launched in 1989, Microsoft SQL Server is a powerful RDBMS used for transaction processing, analytics applications, and business intelligence in IT environments. It comes with built-in intelligence & enables businesses to boost their performance, security, and availability seamlessly. MS SQL Server comes in different editions with authentication & security features.
Latest version: Microsoft SQL Server 2022

Key features of the Microsoft SQL Server database include:
* Available on both Linux & Windows platforms
* Supports semi-structured, structured, and spatial data
* It has a custom-built graphical integration
* Helps users build different designs and tables without syntax
* Comes with several features for protection, monitoring, and data classification
* Gives alerts on security gaps, misconfigurations & suspicious activities

4. MongoDB:

MongoDB is a document-oriented open-source NoSQL database used for high-volume data storage. Written in JavaScript, C++, and Python, this is a very flexible and scalable database platform that removes relational DB approaches. MongoDB offers a high level of flexibility through load balancing and horizontal scaling capacities. This is a perfect option for web apps that need high performance.
Latest version: MongoDB 6.0.5

Key features of the MongoDB database include:
* Effectively supports ad hoc queries
* Highly scalable & flexible database
* Offers schema-less database
* Appropriate indexing for query executions
* Replication for data availability & stability

5. Oracle:

Oracle is a very popular RDBMS that is known for its high-performance and cost-optimization solutions. This is a commercial relational database written in C, C++ & Java. Oracle comes with a relational database architecture that offers an easy, scalable, performant solution for accessing, defining, and managing data.
Latest version: Oracle 21c

Key features of the Oracle database include:
* Executes fast backup & recovery
* Provides multiple database support
* Offers superior scalability
* Offers better user controls and identity management
* Utilizes a single database for every data type

6. Redis:

Redis stands for Remote Dictionary Server and is a widely-used open-source database used for web applications and cache management. Redis can also be used with different streaming solutions like Amazon Kinesis & Apache Kafka to analyze & process real-time data.

This database also supports different data structures like lists, streams, bitmaps, strings, maps, and so on. Because of its high performance, Redis is vastly used in many sectors such as IoT, Gaming, Financial Services, etc.
Latest version: Redis 7.0.11

Key features of the Redis database include:
* Provides premium speed with improved caching & in-memory capabilities.
* Supports a variety of data structures (strings, hashes, lists, bitmaps, HyperLogLogs, etc)
* Compatible with different languages (Java, PHP, Python, C, C#, C++, etc)
* Offers quick access to data for training, deploying, and developing applications

7. Cassandra:

Released in 2008, Cassandra is a distributed open-source NoSQL database that effectively manages vast amounts of data. It provides excellent scalability that supports multi-datacenter replication and automatic data replication. Cassandra database is ideal for applications that need prompt data access with high performance.
Latest version: Cassandra 4.1.0

Key features of the Cassandra database include:
* Easy to scale
* Highly scalable & comes with strong architecture
* Offers flexibility for data distribution
* Faster linear-scale performance
* Very flexible data storage
* Supports properties like Consistency, Atomicity, Isolation, and Durability

How Much Does The Web Application Database Cost?

In general, the average web app development cost ranges from $5,000 to $100,000. However, this cost depends on too many parameters like web app database complexity, features & functionalities, backend infrastructure, etc.

If you want to get a proper estimation of your web database application cost, you can take advantage of a web app cost calculator. For your convenience, we have listed the average web application development costs based on their categories.
Factors
Basic Web Apps
Medium Apps
Complex Apps
Highly Complex Apps
Estimated cost
$3,000 to $15,000
$15,000 to $60,000
$60,000 to $2,50,000
More than $250,000
Timeline
    . to 5 weeks
    . to 20 weeks
    . to 25 weeks
More than 9 months
Features
Simple landing page
Static content
Landing page
Database integration
Admin panel
User accounts
Online payment options
Third-party integrations
Landing page
Huge database integration
Admin panel
Multipleuser accounts
Online Payment options
Third-party integrations
Personalized features
Landing page
Top-notch database integration
Admin panel
Customized features
Examples
Online brochures
Portfolio
websites
MVP
Web portals
E-commerce websites
Online gaming sites with animation
Web applications for businesses
Automated billing systems
Human resources management system (HRMS)
Complex ecommerce websites
Custom web apps
On-demand web apps
App for complex businesses
High-end features with AI/ML integration
Custom web apps

Final Words

In the past, the process of selecting a database web application was straightforward. However, in this modern era of software development, this process has become very intrinsic as too many options are available today and the business requirements have also transformed.

For a business that works with small apps, NoSQL databases like MongoDB can be the best choice & for managing large & complex applications, databases like MySQL, MS SQL Server, and PostgreSQL can be the right choice. Would you like to know more about web applications with databases? Talk to our experts today.

People that visit your website face an invisible threat each time they log on. Small businesses are especially vulnerable to digital data breaches, and that can change the way your customers feel about you. But, although you cannot stop hackers from trying, there are things you can do as a business owner to make your website a safer experience for everyone. Keep reading for tips.

Mature digitally.

You may be ahead of the times when it comes to products and services, but, chances are, your website hasn't fully kept up. It's time to learn all you can about the internet and digital security. If you are already somewhat tech savvy, a PHP Security Course from Nomad PHP can help you better understand everything from cryptography to website error messages.

Adapting to today's digital environment means transforming your website to quickly and easily identify threats via machine learning and network monitoring. And, as Upwork explains, digital maturity not only keeps your website safe, but adopting this mindset can also increase your efficiency and accuracy by reducing human errors.

Understand the threats.

It is not enough to simply keep up with your website, you also have to understand the types of threats that are out there. You're likely familiar with ransomware and phishing, but, it's also a good idea to know how a website can get hacked. Your site's content management system and vulnerabilities within your operating system are all weak points that hackers can easily identify.

Insist on security measures.

When customers log into your website, they input their credentials. Each time they do so, you can best protect their information by keeping your systems up to date. You'll also want to ensure that your site is hosted on a secure service and that you have an SSL certificate installed.

If you are not already, have your IT department or managed IT services perform regular website security checks. PhoenixNAP, an IT services provider, notes that those websites working via WordPress should also be safely outfitted with the most recent security plug-ins.

Eliminate spam.

If your website allows for comments that are not manually approved, anyone on the internet can post. This leaves it open for hackers and other unscrupulous individuals to comment with spam and malicious links that your customers may inadvertently click on. While many of these simply exist as a way for the commenter to drive traffic to another website, others are designed to draw your readers' attention, gain their trust, and access their personal information.

Prioritize passwords.

Your customers' passwords are the keys by which they open the door to your website. Unfortunately, many people do not treat them with as much care as they do the keys they use in the non-digital world.

It's true, passwords can be a pain, but you are not doing yourself or your customers any favors by allowing simple one-word passcodes to access your site. Instead, design your site to require a strong password. How-To Geek asserts that this will have a minimum of 12 characters and include a combination of upper and lower case letters, symbols, and numbers.

While you will likely rely on your IT experts to secure your website, the truth is that it is ultimately up to you to ensure this is done. So even if you are not a digital mastermind, knowing all you can about web security can help you be a better business owner. Your customers will be safer, and a secure website is just one way to strengthen your business's online presence and keep up with today's -- and tomorrow's -- technology.

Technology is constantly changing the way we interact, research, and react. One such way artificial intelligence is impacting our daily lives, and we may not even realize it is in weather forecasting.

The forecast we usually have been receiving in our phones and in older times primarily in newspapers, was based on data collected via satellites, radar system and weather balloons. In recent times there has been the addition of IoT based sensors as well. However, with the advent of Artificial Intelligence (AI) finding its way in numerous areas, AI has taken a role in improving the accuracy of weather as well.

The Dataset expansion

A significantly enormous set of data is available - from the weather satellites in space, to the private and government owned weather stations which are gaining real-time data. IBM for instance has more the 0.25 million weather stations that help IBM collect real-time data. Additionally, as we are in the age of Internet of Things (IOT), each small device to big device- cellphones, solar panels and vehicles everything has become or is yet to become yet another data source. Companies like GE have installed IOT street lights, which help in monitoring air quality and humidity. These are some of the few sources which help us in collecting the vast amount of data necessary for building on the AI technology, in future these sources and the amount of available data would grow exponentially.

Google and Weather forecast

Using the AI technology Google is able to develop a weather forecast tool, it has been trained to predict rainfalls accurately as much as six hours before. The underlying technology on which this prediction is build upon is U-Net convolutional neural network which is originally used in biomedical research. It works by taking satellite images as input and uses AI technology to transform these images into high resolution images. The only off-set is this is not real-time prediction and the delay due to complex calculations results in using six-hour old data and hence can only predict six-hours before.

IBM and its efforts in weather prediction

The quest for IBM to venture into weather forecasting began with IBM acquiring The Weather Company. IBM plans on using the large amount of weather data available coupled with IBM Watson and the cloud platform to enhance weather forecasting. In 2019 IBM developed Global High-Resolution Atmospheric Forecasting System (GRAF) in order to forecast weather conditions 12 hours prior to a greater degree of accuracy. The radius encompassed by the GRAF is also more narrowed down up to 3 kilometers as opposed to generally being 10-15 kilometers. Another of its marvel is that it gives accurate predictions down to each hour and not just daily.

Artificial Intelligence and Panasonic

Panasonic is the company behind TAMDAR, the weather sensor installed on commercial airplanes. With this advantage of extensive amount of data from in-flight sensors as well as publicly available data Panasonic developed Global 4D Weather. Proving to their claim of being the most advanced global forecasting platform globally they were able to timely predict Hurricane Irma in its early days.

Uses of Weather Forecasting

Sales

Everyday life decisions are affected by weather, it makes us choose in the way we travel, things we eat and things we buy to wear. The rise in temperature may increase sales of chilled drinks, if the company is fully aware of the forecast it would be able to manage productions as per demand. AI can help brands in maximizing sales based on weather forecasts and in minimizing waste.

Natural Disasters

The Panasonic Global 4D weather predicting Hurricane Irma is just another example where timely prediction can save millions of lives in face of situations like floods and Hurricanes. Companies like IBM combine weather forecasting data with utilities distribution network, which enables them to narrow down areas with likely outages. This enables utilities to place their workforce timely so the repair process catering to damage repairs post disasters is shortened. This in turn brings huge benefits to the overall economy.

Agriculture

The weather and agriculture have the most obvious correlation, each process in farming from sowing to reaping all depends on the weather. As farmers cultivate on huge farming lands, accurate information about each part of the land can help farmers in improving their crops and yield by manifolds. Weather conditions can lead to almost 90 percent of crop losses, 25 percent of these losses can be avoided using accurate AI prediction models to forecast weather and in turn improve the yield.

Transportation

Sea travel has always been eventful, timely prediction of storms by using machine learning techniques and hyper-local data allows companies to plan shipments accordingly and avoid severe weather conditions that usually result in delays. Tools like IBM’s Operations Dashboard for Ground Transportation equips in enhancing productivity based on weather predictions.

Another of the implementation of AI in transportation industry corelating to weather is fuel consumption. For instance, using weather prediction models to reduce airplane fuel consumption during its ascent.

To conclude Artificial Intelligence has a key role to play in weather forecasting, weather direct or indirectly impacts each sector in the economy. As the amount of information available to improve predictions increases exponentially it gives a chance to AI to improve accuracy even further. As we continue narrowing down weather conditions precise to time and location the benefits of such advancements across all industries are innumerable.