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At Papertrail we are software engineers who are passionate about programming, debugging, logging and pretty much everything about building and running applications. We enjoy keeping our coding skills sharp and playing with new technologies. Below are some of things we have picked up along the way.
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Docker changed the way developers build software. It solved many issues, but bugs can still occur. When this happens, the first step in the debugging process is usually to read logs. However, when using Docker, this isn’t as straightforward as you may think. You can simply execute docker logs [container_id], but it’s not always possible to use this command, and it’s not an ideal solution for bigger applications. In this post, you’ll learn the pros and cons of the different logging options and what to consider when choosing a logging strategy in Docker.
Today’s applications and services support the core business activities organizations rely on. Service interruptions and downtime time are no longer just inconvenient, they’re directly tied to both lost revenue and customers. It’s more important than ever to actively monitor the health of your applications and services to detect issues before there’s an outage. Being able to quickly detect and resolve issues is key to your organization’s financial and competitive position, as well as your career success.
Logs play a crucial role in any service as they provide tons of information about the wellbeing of your service. For example, logs can contribute important data to metrics, such as the incident rate, retry rate, latency rate, or even the number of issues a user experiences. Logs are also useful for monitoring the health of your service. For example, a high error rate indicates you need to improve the quality of your service to make it more reliable for users.
Logging is vital for any modern software team, and it’s essential to get it right. A poorly-implemented logging strategy could cause you more headaches than it solves. In this article, we’ll discuss PHP logging and the main best practices you should be aware of and adopt.
Let’s imagine you’re looking for a flight ticket booking app for your Android smartphone. When you search for such an app in the Play Store, you’ll find multiple options. How do you decide which one to install? Easy! You try out a few of them. Find out which one is fastest, serves your purpose, and has a nice user interface.
Logs are often the foundation of metrics and observability infrastructure because they contain business-level statistics that help you and your team make decisions. Without them, it’s impossible to know how often users are hitting errors or how the latencies in your services are varying over time.
If you’re responsible for keeping web servers running, you already know easy access to log messages is critical when troubleshooting issues. Apache provides comprehensive support for logging, and its highly customizable configuration allows you to tailor its logging to your exact needs. You can gain visibility into your web servers by logging everything from the initial request through to the URL mapping process and connection termination. And if this wasn’t enough, third-party modules provide additional logging capabilities such as support for application runtimes including PHP, Java, and CGI programs.
The JSON format is ubiquitous and used everywhere from logging in web apps to message passing for microcontrollers. Thanks to its compact nature and it being easily readable by humans, JSON has become the de facto standard for sharing structured data.
Modern apps and services generate a constant stream of log data capturing the inner workings of the code and how users interact with it externally. Buried inside those logs are golden nuggets of information critical for troubleshooting problems in development and in production.
Managing log files on a single server is a cakewalk, and familiar tools such as grep, tail, and sed can expose the data you need. But it’s a completely different story once you’re working at scale and need to analyze logs across tens, hundreds, or even thousands of machines. In this case, the best solution is to aggregate your logs in the cloud and use a log viewer to analyze your logs holistically. Fortunately, that’s exactly what SolarWinds® Papertrail™ does.
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