As a developer, you’ll always face challenges with your applications. Some of these challenges arise from the server after deploying code. It can sometimes be difficult to know what the problem is, especially if the app is running as expected in your development environment. This is something no one can escape. These errors are bound to happen to anyone, regardless of their level of experience as a software engineer or developer.
Heroku is a popular platform-as-a-service (PaaS) cloud that allows you to run your applications in a serverless manner. This blog is about optimizing applications running in Heroku: making them run faster, giving them better security, and generally fine-tuning them.
HAProxy (high availability proxy) is a critical part of modern systems infrastructure. It’s ideally the first point of contact for users who access your application. When configured correctly, HAProxy improves your app’s performance significantly. Through load balancing, HAProxy makes sure each service your application depends on is accessible to users, especially under load conditions otherwise impacting application performance.
Logging is crucial in software development, so it’s vital to get it right. That’s easier said than done, unfortunately. Application logging—Python logging included—is riddled with traps you might fall prey to if you aren’t careful.
But you can’t beware what you don’t know, and that’s where this post comes in handy. We’re here to warn you about eight of the most common logging pitfalls in Python. You’ll learn about each problem and techniques and tools you can use to avoid it.
PHP powers millions of applications. This massive success is due to PHP’s simplicity, clear documentation, and tons of free resources. The PHP community provides an incredible ecosystem of libraries and tools, enabling anyone to develop production-grade apps rapidly. What’s even more exciting is PHP projects are cheap to host and widely supported by many platform providers such as Heroku.
Robust application logging is central to any quality strategy. Unfortunately, many quality strategies fall short, implementing logging in a less than stellar way. Java application logging is no different. And since we’re talking about one of the most popular programming languages, investments in improving the overall Java logging strategy could pay off many dividends in the future.
There are a lot of “cloudy” terms out there now. Is cloud-native better than cloud-based? Am I considered in the “cloud” when my application is cloud-enabled? Let’s take a closer look at the difference between cloud-native, cloud-based, and cloud-enabled to tease apart these different terms.
After the introduction of Docker, the life of a developer became much easier. Kubernetes solved many problems and offloaded the task of setting up the necessary runtimes, libraries, and servers. Kubernetes even simplified complex deployments and made managing multiple containers for bigger applications within the reach of most developers.
Like with any software application, maintaining the app after deployment is critical. It’s important to have methods to check its status when issues inevitably arise. One of the first things most technical professionals will do when diagnosing issues is to check the logs. This way, you can dig deeper into an issue and determine the root cause.
As an IT professional, you’ll find log messages are one way to catch errors and solve your problems. As much as log messages are helpful, they can be confusing because a lot of messages—even the log messages you don’t need to see—are generated by the server. Instead of making your life easier, log messages can make things harder for you because unnecessary error messages are being logged.