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CircleCI

Building a React dashboard to visualize workflow and job events

Data visualization is the process of translating large data sets and metrics into charts, graphs, and other visuals. The resulting visual representation of data makes it easier to identify and share real-time trends, outliers, and new insights about the information represented in the data. Using CircleCI webhooks, we can gather data on workflow and job events. In this tutorial, I will lead you through the steps to create a React-based dashboard to visualize this data.

Building a Laravel API for CircleCI webhooks

Software applications consist of interconnected systems - each providing a specialized service towards the common goal of meeting a business need. As with any network, an efficient data exchange mechanism is key to its functionality, effectiveness, and responsiveness. In the past, data exchange was performed using polling requests. At regular intervals, a system would make a request to get the latest information or find out if there is an update to deal with.

Season 1 Finale: The Top 3 Themes for Software Leaders in 2022

CircleCI CTO Rob Zuber reflects on season 1 of The Confident Commit, finding the common threads that emerged, including these top 3 themes for software leaders: complexity, scale, and people. Listen to Rob's take on where software is headed and hear about the upcoming season 2 of The Confident Commit.

HTTP request testing with k6

Many of the multi-faceted applications development teams deploy every day are loosely coupled and every service exists to power another service. Most teams developing fullstack applications know that testing the communication between these services essential. Part of the process is testing HTTP request endpoints, and this tutorial focuses on exactly that. I will lead you through learning how to extend the k6 framework to test our HTTP endpoints.

Integrating GitOps with DevOps: implementing the best of both

GitOps has become a buzzword. Developers love it, because it folds DevOps into Git, a frequently used and familiar tool. Using one tool to manage multiple DevOps activities sounds fantastic, and it can be helpful for many. The truth is GitOps has limits. In this article, we explore DevOps and GitOps, compare their similarities and differences, and examine how their principles can work together to support your software development goals.

Cloud misconfiguration: vulnerability hiding in plain sight

This post originally appeared on The New Stack and is re-published here with permission. In our technology-driven business climate, most companies have at least some, if not all, workloads on the cloud. And unlike on-premises networks, these cloud environments lack secure outer perimeters and specific off times. Cloud networks are always on and always available. While convenient, this also means hackers can access them at any time.

Object validation and conversion with Marshmallow in Python

Marshmallow is a Python library that converts complex data types to and from Python data types. It is a powerful tool for both validating and converting data. In this tutorial, I will be using Marshmallow to validate a simple bookmarks API where users can save their favorite URLs along with a short description of each site.

Trigger your CircleCI pipelines from a GitHub Actions workflow

If you are already a GitHub user, you may know that GitHub Actions provides you with powerful tools to increase efficiencies in your software delivery life cycle. Actions can be impactful for team collaborations and process simplification. For example, you can automate things like building a container, welcoming new users to your open source projects, managing branches, or triaging issues.

Is Arm the future of cloud computing?

The Arm architecture dates back to Acorn Computers’ BBC Micro in 1981. The BBC Micro was a conventional machine, yet it ran nearly twice as fast as its contemporaries, such as the Apple II. About the same time, research on a microprocessor design based on the Reduced Instruction Set Computer (RISC) demonstrated that simple chip designs could easily outperform the current high-end 32-bit offerings.