Operations | Monitoring | ITSM | DevOps | Cloud

As microservices architectures dominate modern application development, the ability to test, secure, and automate their deployment has become a vital skill. In this guide, you’ll learn how to: Let’s first set the stage by briefly exploring the foundational concepts of CI/CD and DevOps, which underpin the automation and agility required in development workflows.

Argo CD is a declarative continuous delivery (CD) tool for Kubernetes. Argo CD pulls Kubernetes configurations (such as manifests, Helm charts, and Kustomize overlays) from a Git repository and applies them to a Kubernetes cluster. With Argo CD, developers can automatically deploy changes to their Kubernetes environments by updating their Git repository. Argo CD continuously monitors Kubernetes deployments and ensures their state matches the configuration declared in Git.

Machine learning (ML) and artificial intelligence (AI) are often used interchangeably in tech discussions, yet they represent distinct concepts with important differences. While AI refers to the broader field of creating machines capable of intelligent behavior that mimics human capabilities, machine learning is a specific subset of AI focused on developing algorithms that allow computers to learn from and make predictions based on data.

As AI becomes increasingly central to modern software development, the ability to craft effective system prompts has emerged as a crucial skill. Whether you’re building a code generation tool, creating a chatbot, or developing AI-powered features, your success largely depends on how well you can communicate with AI models through prompts. At CircleCI, we’ve spent countless hours working with developers who are integrating AI into their applications.

Serverless computing simplifies app development by abstracting away server management. Azure Functions provides a robust platform for event-driven, on-demand code execution. In this tutorial, we’ll create and deploy a Python-based Azure Function—one that parses incoming JSON—using CircleCI. For a more granular and enable programmatic access to Azure resources, we’ll use service principal for secure authentication and the Azure CLI orb to streamline our CI/CD pipeline.

Cascading Style Sheets (CSS) is the language used by developers to apply styles to documents written in a markup language. In front-end development, enforcing consistent CSS code quality is crucial: poorly written CSS can lead to issues ranging from poor maintainability, unexpected bugs, and inconsistent designs. One effective way to ensure CSS code quality is using a linter such as Stylelint.

Agentic AI represents the next evolution in artificial intelligence systems, characterized by autonomous software entities that can independently pursue goals, make decisions, and take actions with minimal human supervision. Unlike traditional AI models that respond only to specific prompts, AI agents actively observe their environment, learn from feedback, and execute complex sequences of tasks to achieve defined objectives.

The advancement of AI has empowered businesses to incorporate intelligent automation into their applications. A serverless Generative AI (GenAI) API enables developers to harness cutting-edge AI models without the burden of infrastructure management. This guide walks you through building a scalable and cost-effective GenAI API using FastAPI, a high-performance Python framework with built-in async support and seamless AWS integration.

Visual Studio App Center is officially retiring at the end of March 2025. Now is the ideal time to upgrade your mobile app builds to CircleCI, the leading CI/CD platform trusted by thousands of mobile developers worldwide. Start building for free.

Enterprise application development is the process of designing, building, and maintaining large-scale software systems that support critical business functions. These applications are essential for managing operations, improving efficiency, and enabling digital transformation across industries. Unlike consumer applications, enterprise software must be highly scalable, secure, and capable of integrating with multiple systems to meet the complex needs of organizations.

Mobile applications are increasingly becoming complex as they provide a wide range of functionalities, catering to diverse use cases across finance, health, entertainment, and other industries. Application developers need to ensure compatibility across a wide range of devices, operating systems, and screen sizes. It is challenging to ensure a bug-free user experience, as manually testing all the features across devices would require a lot of time and effort.

CI/CD is an approach to software development that combines continuous integration (CI) and continuous delivery (CD). CI/CD makes developing apps faster, safer, and more efficient. In front-end development, CI/CD becomes even more valuable as developers frequently test, build, and deploy applications. Automating this process reduces the need for developers to manually carry out these tasks, boosting efficiency and reliability.

Change sparks innovation. Changes = updates = value delivered. Change is risky. Change is exciting. The wrong change can bring down your application… or possibly your career.

Losing a customer to a competitor can be costly; customer retention is vital for business success and growth. Businesses must anticipate when and why a customer might leave, so they can implement measures to retain them. One solution might be to build a system that predicts churn. But can it be done? Using machine learning (ML) techniques to analyze customer service interactions can provide valuable insight into customer sentiment.

API security testing is software testing performed on APIs. It is meant to identify vulnerabilities in API endpoint communication and access. In modern software development, API security is a crucial aspect that cannot be ignored. API security testing can now be automated in CI/CD, enabling early detection of vulnerabilities, maintaining security standards without slowing down development, and reducing human errors.

Chatbots are becoming essential to software applications, enhancing user engagement through automated conversations. Deploying a chatbot to a cloud platform requires integrating multiple technologies, ensuring smooth communication between services, and automating updates efficiently. In this tutorial, you will learn how to deploy a Python-based conversational chatbot to an Azure Functions app.