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API mock testing with Nock

For the latest full-stack applications to work, a backend service is required. That is especially true when the frontend service depends on the backend service to render data. In many cases, it can be difficult to replicate the setup of the backend services so that you can test the application. This tutorial will show you how to mock HTTP requests from an API so that you can test endpoints without actually calling them in your tests.

Scheduling load tests and persisting output with k6

In this k6 series I have covered HTTP request testing with k6 and performance testing with k6. I designed these tutorials to introduce you to k6 and to show you how to use k6 for performance testing of microservices. As the third tutorial in the k6 series, this will cover how you can store your k6 test results locally and also how to schedule your load tests using CircleCI’s scheduled pipelines feature.

How Lightspeed optimized iOS test runs with parallelism and caching

At Lightspeed, we maintain multiple large iOS projects as well as their modularized dependencies. The last year of acquisitions brought together many different approaches to CI/CD at our company. I recently led the initiative to bring these projects and practices into alignment. In this post, I will explain the goals we had for our continuous integration pipeline and the implementations we used to achieve them.

Config best practices: concurrency and parallelism

When is the last time you updated your CI/CD workflow? A year ago? Never? You are not alone, my friends. Reconfiguring workflows can be one of the most daunting tasks for DevOps practitioners. But with new opportunities to benefit from CircleCI plans, there’s one simple and effective place to start: understanding concurrency and parallelism. Using concurrency and parallelism can cut your build times significantly. But you need to know what they are and how to find them in your config file.

Top 5 CI/CD best practices

For engineering teams, CI/CD is the key to improving their development cycles. CircleCI is committed to helping our customers optimize their pipelines to streamline delivery to production. If your team values speeding your time to market, commit to trying these 5 best practices. These are CircleCI’s recommendations for cutting your development cycle times and improving your CI/CD processes in general.

Benefits of scheduling continuous integration pipelines

Scheduling is an integral part of software development practices. Tools for scheduling jobs help development teams save time by scheduling recurring tasks — like modifying a database or sending out periodic emails — for execution at specified times. There are many to choose from, including cron for Linux, scheduled tasks for Windows, launchd for macOS, Jobber, and anacron.

Build an automated invoice generator application

As a software engineer and technical content creator, I work with a lot of companies on many different contracts. To get paid for my work, most companies require that I send an invoice. Sometimes they want one daily, at the end of the week, or even when the project has been completed. Sending an invoice to my clients is crucial because it determines when and if I will get paid on time. If this sounds like a repetitive task that can eat deep into my productive hours, you are right.

Schedule database backups for MongoDB in a Node.js application

Database backup protects your data by creating a copy of your database locally, or remotely on a backup server. This operation is often performed manually by database administrators. Like every other human-dependent activity, it is susceptible to errors and requires lots of time. Regularly scheduled backups go a long way to safeguarding your customers’ details in the case of operating system failure or security breach.

Observability versus monitoring in software development

To supervise the behavior of distributed applications and track the origin of service failures and downtime, developers often use traditional monitoring technologies and tools. However, this approach can fall short in its ability to measure the overall health of modern cloud-native architectures, which can span multiple hosting environments and encompass hundreds of microservices.