September 27, 2021
Unless you’ve been developing software in a cave, you’ve probably heard people sing the praises of microservices. They’re agile, simple, and an overall improvement on the monolith and service-oriented architecture days. But of course, with all the benefits of microservices comes a new set of challenges.
July 26, 2021
A common architectural design pattern these days is to break up an application monolith into smaller microservices. Each microservice is then responsible for a specific aspect or feature of your app. For example, one microservice might be responsible for serving external API requests, while another might handle data fetching for your frontend.
October 30, 2020
As long as I can remember, I’ve included log messages in my code to provide run-time insight into what the code is really doing. From developers running locally all the way to the eyes of a production support engineer, these extra lines of code are meant to help troubleshoot unexpected scenarios.
January 22, 2020
Teams switching from a monolithic application architecture to microservices often face a jarring realization: their time-tested troubleshooting techniques don’t work as effectively. A microservice consists of many independent, distributed, and ephemeral services with varying capabilities for monitoring and logging. Techniques such as stack traces are effective troubleshooting tools in monoliths, but only paint a small portion of the big picture in a microservice-based application.
August 21, 2019
From reports of potholes and broken streetlights to complaints about garbage and vandalism, cities process more non-emergency requests from residents than ever before. Baltimore, the first U.S. city to deploy a 311 system, has processed over 13 million requests since its inception. The result is a repository of data detailing the interactions between a city and its residents. Analyzing this data can help cities learn more about their residents’ needs, prioritize tasks and projects, track performance, and improve collaboration across departments.
June 6, 2019
Sometimes developers are hesitant to include logging due to performance concerns, but is this justified? And how much does library choice affect performance? The team at SolarWinds® Loggly® and myself decided to find out. We ran a series of performance tests on some of the most popular Node.js libraries. These tests are designed to show how quickly each library processed logging and the impact on the overall application. Let’s see how they did!
June 6, 2019
Serverless architectures such as AWS Lambda have created new challenges in debugging code. Without a solid logging framework in place, you could waste hours, or even days, tracking down simple defects in your functions. A strategic logging framework can be a powerful way to track down and resolve bugs. Let’s walk through how to get the most out of logging Lambda functions. We’ll set up and troubleshoot code to find the root cause of a defect, look at some best practices for logging Lambda functions, and explore setting up alerts.
May 7, 2019
Logging is one of the first tools in a developer’s kit for fixing timing and deadlock issues. When you debug concurrent code, the debugger may appear to jump around as different parts of the code are executed. This is true for both multithreaded and asynchronous code. A log file allows you to quickly see the behavior of your application without slowly stepping through tasks in different parts of the code base.
May 7, 2019
Logging is one of the first tools in a developer’s kit for fixing timing and deadlock issues. When you debug concurrent code, the debugger may appear to jump around as different parts of the code are executed. This is true for both multithreaded and asynchronous code. A log file allows you to quickly see the behavior of your application without slowly stepping through tasks in different parts of the code base.
April 24, 2019
The core ability to search through logs quickly and intuitively is the most important feature a log management system brings to the table. Being able to quickly and efficiently search through logs generated by an infrastructure stack allows DevOps professionals to rapidly find and address problems, as well as confirm deployments and configuration changes. Because raw speed has such a direct impact on the usefulness of these products, we will compare to see which performs the best.
