Although GoMock is a simple Golang mock tool, knowing where to start can be a challenge in and of itself, which this post helps solve.

Platform engineers can influence API development by following best practices and implementing DevOps design patterns.

Observability isn't just a buzzword; it's a vital compass guiding us through the maze of system health and performance. As we’ve adopted microservice architectures, the ability to know ‘what is currently happening in our system’ has diminished as our operational resilience has increased. We find services scattered among a maze of interconnections and interdependencies. And even the logs that used to guide are now scattered throughout this maze.

When I first had the idea for this post, I wanted to provide a collection of actionable ways to handle errors caused by API rate limits in your applications. But as it turns out, it’s not that straightforward (is it ever?). API rate limiting is a minefield, and at the time of writing, there are no published standards in terms of how to build and consume APIs that implement rate limiting.

I’m pretty sure that you’ve had a situation where you deployed a major UX change on your web app and missed the most obvious issues, like a misaligned button or distorted images. Unintended changes on your site can cause not only a sharp decline in user satisfaction but also a large fall in sales and customer retention. By identifying and resolving these discrepancies before the update went live, you could have prevented these outcomes.

Open banking offers users a way to have easier access to their own bank account information, like via third-party applications. This is achieved by allowing third-party financial service providers access to the financial data of a bank's customers through the use of APIs, which enable secure communication between the different parties involved.

I'm happy to announce that visual regression & snapshot testing for our Playwright powered browser checks is now GA. If you have used these capabilities with your Playwright tests on your local machine or in your CI/CD pipeline, you can now use them 1:1 on Checkly.

Everyone needs observability. If you have a service that users rely on, you need to know if it’s working for your users. Heartbeat monitoring (Also called Synthetic Monitoring) should be a way to truly know how well our site is performing for users.

Step Function added support for testing individual states . Which lets you execute individual states with the following: And returns the following: With the TestState API, you can thoroughly test every state and achieve close to 100% coverage of a state machine. So, does this eliminate the need for Step Functions Local ? Can we do away with end-to-end tests as well? If not, where should this new API fit into your workflow, and how should you use it?