Operations | Monitoring | ITSM | DevOps | Cloud

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.

When evaluating CI/CD platforms, it can be easy to view them as commodities — interchangeable tools that accomplish the same basic tasks. But as development teams scale, small differences in platform performance can be compounded, significantly impacting development velocity and resource utilization. To better understand these differences, we conducted a head-to-head comparison between CircleCI and GitHub Actions, focusing specifically on performance at enterprise scale.

CI/CD for generative AI applications presents unique challenges in model deployment, testing, and monitoring. Unlike traditional software applications, generative AI systems involve large model artifacts, complex dependencies, and specialized hardware requirements, making a sophisticated CI/CD pipeline essential for reliable delivery. As organizations embrace generative AI technologies, the need for specialized CI/CD solutions becomes critical.

For platform teams, success means empowering developers with efficient, reliable tools and workflows that accelerate software delivery. As organizations scale, platform engineering teams must balance developer autonomy with standardization while providing infrastructure that supports rapid, reliable software delivery. In today’s complex development environments, platform teams are crucial for maintaining productivity at scale.

So much of our modern software runs on containers. Containerized applications offer great flexibility for developers, but they also come with security risks. Container security is a holistic approach to managing risk in containerized environments. Securing containers requires a broad approach incorporating different tools and policies that enforce security in the software supply chain, infrastructure, container runtime environments, and other potential container attack surfaces.

Behavior-Driven Development (BDD) is a software development methodology in which applications are built to match the behaviors a user would expect from the software. An evolution of Test-Driven Development (TDD), BDD gathers user stories about how users expect applications to behave, then creates software tests to validate that their applications match this behavior. The BDD methodology utilizes specific language and naming conventions.

Unit testing is a software testing methodology that tests the behavior of individual functional units of code. Through unit testing, developers can verify that their code performs as intended. Providing an opportunity to catch bugs, validate the implementation of logic, and assess the quality of the code, unit testing enhances the quality of applications and preemptively identifies problems before they become major issues.