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Are you struggling to understand how to build an API from scratch? This guide will equip you with everything you need to know about API development. APIs are the backbone of modern software, enabling applications to communicate, share data, and integrate seamlessly. From social media platforms to e-commerce websites, APIs are everywhere.Are you struggling to understand how to build an API from scratch? This guide will equip you with everything you need to know about API development. APIs are the backbone of modern software, enabling applications to communicate, share data, and integrate seamlessly. From social media platforms to e-commerce websites, APIs are everywhere. By @goodcore.co.uk.

The main content could be divided into:

• Introduction to API
• Types of APIs
• Benefits of using APIs
• Challenges in API development
• Best practices in API development

The article starts by explaining what an API is—a bridge that allows different applications to communicate and share data. It uses examples like social media platforms and e-commerce websites to illustrate the importance of APIs in modern software development.

The guide then discusses the various types of APIs, such as RESTful APIs for simple data exchanges, SOAP for enterprise-level integrations, GraphQL for flexible queries, and WebSocket for real-time communication. Each type is suited to different scenarios based on factors like simplicity, security requirements, and the need for real-time data.

Throughout the article, there’s a emphasis on best practices in API development, including planning, design, secure implementation, thorough testing, and ongoing maintenance. The authors suggest that building a robust API is crucial for expanding offerings, integrating systems, or streamlining operations within a company. They recommend considering custom solutions tailored to specific business needs. Interesting read!

GQL addresses the need for sophisticated queries that reflect the increasingly complex and connected nature of data in the real world. The benefits of graph databases not only exist in providing more intuitive and powerful ways to visualize and interrogate data relationships but also in storing and processing data more efficiently. By Jocelyn Hoppa.

Since the last major enhancement of Structured Query Language (SQL) decades ago, the database industry has introduced a new ISO/IEC standard language called Graph Query Language (opens in new tabGQL), marking a significant milestone.

In the article you will find:

• A brief history of SQL, from the beginning up to:
  • SQL:2016 – Year: 2016 – Standardization: ISO/IEC 9075:2016 – Details: Added JSON support and advanced sharding capabilities.
  • SQL:2019 – Year: 2019 – Standardization: ISO/IEC 9075:2019 – Details: Extended functionality with enhancements in JSON, property graph queries, and temporal data.
  • SQL:2023 – Year: 2023 – Standardization: ISO/IEC 9075:2023 – Details: New features for property graph queries over tables tables and improved JSON support.
• What is GQL?

GQL is a new standard marking the rise of graph queries alongside SQL’s evolution. Graph databases offer powerful ways to visualize and interrogate connected data, promising efficient storage and processing. Good read!

This article reflects on the state of JavaScript frameworks in 2024, concluding that the pursuit of simplicity hasn’t necessarily resulted in easier development. By Ryan Carniato.

Main Points:

• Server-First Momentum: The trend towards server-first architectures continues, with new frameworks like SvelteKit, Astro, Remix, and others offering solutions for improved performance and scalability.
• Complexity Remains: Despite advancements, the overall complexity of JavaScript development persists due to intricate tooling, compilation processes, and the nature of client-server interactions.
• The Rise of Compilers: Compilers are becoming increasingly vital in optimizing code and addressing language limitations. React Compiler and Svelte 5 Runes demonstrate this trend, pushing frameworks towards more sophisticated optimization strategies.
• AI’s Growing Impact: AI tools are starting to make inroads in developer workflows, offering assistance with tasks like performance analysis and code generation.

The author predicts a return to balanced approaches, incorporating elements of both client-side and server-side paradigms. Mature frameworks like Vue and Angular may gain traction due to their emphasis on stability and maintainability. Signals, while prevalent in many frameworks, are still evolving and will likely see refinements that address their inherent tradeoffs. Nice one!

Data floods in by the second, fueling every facet of business operations. Yet, raw data offers little value on its own — this is where big data analytics tools step in, transforming numbers into actionable insights. By Irina Prevalova.

In this guide, we will introduce you to big data analytics and will tell you about some of the most essential big data analytics tools for 2025, breaking down their key features, benefits, and what makes them stand out in a crowded market.

The article covers:

• What is big data analytics and how does it work?
• The importance of big data analytics for marketers and businesses
• Key factors to consider when selecting big data analytics tools
• 7 Best big data analytics tools to consider in 2025

In terms of leveraging data for the success of your business, big data analytics tools are a great help. From improving decision-making processes to optimizing marketing strategies, these tools provide the insights needed to stay competitive in today’s data-driven landscape. Nice one!

DevOps and CI/CD are two significant methodologies that have changed software development in modern times. DevOps unites development and operations teams, and software delivery can become rapid and efficient with them. CI/CD, or Continuous Integration and Continuous Delivery, tests and releases software via automation to deliver software updates in a reliable and efficient manner to its users. By apiculus.com.

Further in this article:

• What are containers?
• Overview of DevOps and CI/CD
• The role of containers in DevOps
• Containers in the CI/CD pipeline
• Best practices for using containers in DevOps and CI/CD

Containers are important in supporting DevOps and CI/CD pipelines by providing uniformity, scalability, and efficiency in development and delivery. They eliminate environment discrepancies, simplify dependencies, and allow for rapid and reliable software delivery. As container technology continues to evolve, its influence will increasingly dominate software development in the future, and most particularly in microservices and cloud-native architectures. Good read!

In the dynamic world of web development, Angular stands out as a powerful and efficient framework for building interactive web applications. Developed and maintained by Google, Angular is an open-source framework that has gained immense popularity among developers worldwide. By crsinfosolutions.com.

The article will guide you through:

• What is Angular?
• Key features of Angular
• Components
• Dependency injection
• Typescript
• Data binding
• Benefits
• Services

Angular offers numerous benefits such as efficient two-way data binding, a modular component-based architecture, effective dependency injection, and a rich ecosystem of tools. It supports strong community backing, regular updates, and extensive documentation, making it suitable for enterprise-level applications. Although Angular presents a steep learning curve due to its advanced concepts, the framework remains highly valuable in modern web development for building interactive and dynamic user interfaces. For beginners, understanding HTML, CSS, JavaScript, and TypeScript is crucial before delving into Angular’s complexities. Good read!

Ansible is an open-source automation tool that simplifies software provisioning, configuration management, and deployment across Unix-like and Windows systems by using infrastructure as code principles. Its standout features include ease of installation, agentless architecture (utilizing SSH for connections without requiring additional client-side installations), and comprehensive documentation which facilitates its use even among those with minimal system administration skills. Ansible’s modularity supports large-scale orchestration efforts, making it ideal for managing complex environments. By David Carter.

Benefits of Using Ansible:

• Free to use for everyone
• No special skills required; comprehensive documentation available
• Modular design with plugins, modules, inventories, and playbooks
• Lightweight, OS-independent, and secure due to agentless architecture

These features highlight Ansible’s effectiveness in simplifying and automating IT tasks, providing a scalable solution for managing infrastructure. Article also provides few example of ad hoc commands run via ansible and case study on simple usa case for ansible playbook with roles. Good read!

The MVP (Model View Presenter) architecture pattern is widely adopted in Android development for structuring application code into separate layers that enhance maintainability, readability, and scalability. This approach involves three distinct components: Model, View, and Presenter. By GeeksforGeeks.

The Model component focuses on data storage and handles domain logic while managing communication with databases or networks. The View layer is responsible for displaying data and tracking user actions to notify the Presenter. The Presenter fetches data from the Model, applies UI logic, manages the state of the View, and responds to user input notifications. This separation of concerns promotes better code organization, maintainability, and testing capabilities.

To show the implementation of the MVP architecture pattern on projects, you will find an example of a single activity android application in the artivlr. The application will display some strings on the View(Activity) by doing a random selection from the Model. The role of the Presenter class is to keep the business logic of the application away from the activity. Below is the complete step-by-step implementation of this android application. Note that we are going to implement the project using both Java and Kotlin language.

The MVP architecture’s key points include communication via an interface between the View-Presenter, Presenter-Model components, ensuring each component has a one-to-one relationship without knowledge of the others’ existence. This structure facilitates independent development and maintenance of each layer while promoting modularity, testability, and clean codebase. Good read!

The evolution from traditional data warehouses to modern data lakehouses marks a significant shift in how businesses approach data management. Data warehouses once served as the centralized repository for structured data and facilitated rapid query performance with robust governance mechanisms. However, companies faced challenges such as high storage costs, rigid schema enforcement, and limited support for AI and machine learning workloads. By Fawaz Ghali, PhD.

The article covers:

• The emergence of Data Lakehouses
• Apache Iceberg: A leading table format for Data Lakehouses
• The evolution from Hive to Iceberg
• Benefits of Apache Iceberg in data management
• Challenges addressed by Apache Iceberg in Data Lakehouse models

Data lakes emerged as solutions to these problems by offering a scalable and cost-effective approach to storing unstructured, semi-structured, and even structured data in cheap storage like Amazon S3, Azure Data Lake Storage, Google Cloud Storage, and Hadoop Distributed File System. While this offered several benefits such as reduced storage costs and the use of novel data formats, it also presented challenges like inconsistent data sets, inefficient query performance due to full table scans, and lack of ACID transactions.

Enter Apache Iceberg, a modern table format that solves these issues by providing ACID transactions for reliable data updates and consistency, schema evolution without breaking existing queries, and efficient management of metadata to reduce unnecessary file scans and enhance query execution speed. This transformation allows companies transitioning into a data lakehouse approach to manage their information cost-effectively and at scale while maintaining high performance.

As part of this transition, the final two blog posts in this series will delve deeper into Apache Iceberg’s architecture and explore query mechanisms within Iceberg tables, emphasizing its role in modern data architectures.

Test-driven development (TDD) is a software development process that involves writing tests for your code before you write the code. This approach has transformed the development methodology around testing. While the traditional waterfall model of software development was linear, with testing occurring near the end of one long timeline, TDD makes testing an ongoing, iterative process. By Jacob Schmitt.

Author provides following information on:

• Introduction: Test-driven development (TDD) explained
• The TDD Process Explained: A sample online scheduling system example
• Benefits of Test-Driven Development: Software delivery teams collaborate and requirements align
• Best Practices for TDD: Writing clear, targeted tests; continuous code improvement; structured organization
• Implementing TDD with CI/CD: Ensures assured code quality, rapid releases, consistent feedback loop

The test-first methodology of TDD brings code reliability, efficient bug detection, and reduced long-term maintenance costs. Structured testing with a comprehensive range of expressive test cases optimizes the software development process and improves code quality. Good read!