R&D managers, when first stepping into the role, tend to make the mistake of choosing one of two extreme management approaches. Each of these comes with its own set of challenges – and its own set of organizational waste. And that’s the last thing you want to create as a manager.
This blog is a follow-up to our earlier discussion of multibranch pipelines and how they can help streamline software development processes. There we explored the benefits of managing pipelines in the same repository as code and how that gives developers the ability to version their pipelines alongside their code, ensuring they remain in sync.
Making mistakes is a part of life. It’s how we learn and grow. However, many people – and teams – struggle with the aftermath of making a mistake, and it can be challenging to recover quickly.
As engineering leaders, we all struggle to find the balance between creating cool technology and useable technology. Let’s be real. We all want to create cool things. It’s in our nature. But what’s the point of doing so when no one will use it? It’s crucial to remember that the ultimate goal of our work is to create something helpful and effective. Our work has to have a purpose.
Lately, everyone has been jumping on the cloud transformation bandwagon, which isn’t surprising, because when it comes to tech, you don’t want to find yourself behind, stuck with your dusty old monoliths. Just kidding – we love ourselves some good old monolith architectures – but there’s no comparing to dynamic, cloud-native technology.
When it comes to understanding what’s happening in your code – and your service health, specifically – business and code-level metrics are key. While most developers are experts in their own code, that doesn’t mean that they’re also experts on the metrics, statistics, or distributed tracing from the code they’re working with. The code-level metrics they need are tough to set up and it’s something that no one else can do for them.
Installing Rookout on your Node.JS application is usually a breeze. Run `npm install`, add a line of code, and you are done. Yet, in some rare cases, we encounter more frustrating use cases. For example: When those tough situations arise, our customers often refer to this blog post we wrote years ago about deploying a Java Agent. So, if you are looking for an easy and portable way to deploy Node agents without changing your code, you’ll want to read this article.
In every job and every company, that day always comes where you find that you…actually need to do some work. And by that, I mean finding new innovative solutions to tasks and projects instead of going with the tried-and-true methods. Recently, my team, of full stack developers were tasked with building a webview app to support our live debugging IDE plugin. This would allow us to align the user experience with our pre-existing web app.
If you have been a long-time user of the Google Cloud Platform, you’re likely familiar with the StackDriver suite of Observability and Operations tools. The most unique part of that suite was Google’s StackDriver Debugger, which was designed to debug live code in cloud and production environments with a click of a button. Unfortunately, StackDriver has been renamed as Google’s Operations suite, and the Debugger has been deprecated.
We all know that debugging and troubleshooting cloud-native environments is no walk in the park. Sometimes we forget that debugging the frontend portion of those applications is no simpler and comes with its own set of challenges. We also all know how hard it is to get logging just right: managing verbosity, volume, and usefulness to just the right level.
