Breaking down larger, monolithic software, services, and applications into microservices has become a standard practice for developers. While this solves many issues, it also creates new ones. Architectures composed of microservices create their own unique challenges. In this article, we are going to break down some of the most common. More specifically, we are going to assess how observability-based solutions can overcome many of these obstacles.

If you’re reading this, you have probably been convinced that taking on Kotlin for your mobile application is the most sensible choice. Now that you’ve come to this decision, it’s imperative to know what you need to do to stay on top of your monitoring and logging. Like with any application or system, they are essential, cornerstone qualities of any successful project.

When we look at information, numbers, percentages, statistics, we tend to have an easier time understanding and interpreting them if they’re also represented by corresponding visual cues. Kibana Canvas is a tool that helps us present our Elasticsearch data with infographic-like dashboards – fully visual, dynamic, and live.

MySQL is the de facto choice for open-source relational databases, and you should learn how to use MySQL database logs to improve efficiency and security. As an open-source product, it is free to use and has a large and active developer community. It is crucial to understand how to diagnose and monitor the performance of a MySQL instance in the long run. Logs to the rescue!

As software is evolving away from monoliths and towards service-based architectures, it is becoming more apparent than ever that logging performance needs to be a first-class consideration of our architectural designs. This article will explore how to build and maintain a logging solution for a microservice-oriented containerized application, how to address some common difficulties which come with running such a solution, plus some tips for debugging and eliminating bottlenecks.

The Internet of Things (or, IoT) is an umbrella term for multiple connected devices sharing real-time data, and IoT logging is an important part of this. Troubleshooting bug fixes, connection problems, and general malfunctions rely heavily on logs, making them an invaluable asset not only in designing systems but also in system maintenance. To maximize system potential, this plethora of generated data needs to be managed efficiently.

For an organization to be compliant with PCI logging requirements, it must follow PCI Requirement 10 of the Payment Card Industry Data Security Standards (PCI DSS). Below, we’ve listed the highlights of this section and the important details that you need to know.

Metrics and Insight have been the obsession of every sector for decades now. Using data to drive growth has been a staple of boardroom meetings the world over. The promise of a data-driven approach has captured our imaginations. What’s also a subject of these meetings, however, is why investment in data analysis hasn’t yielded results. Directors give the go ahead to sink thousands of dollars into observability and analytics solutions, with no returns.

Elasticsearch was designed to allow its users to get up and running quickly, without having to understand all of its inner workings. However, more often than not, it’s only a matter of time before you run into configuration troubles. Elasticsearch is open-source software that indexes and stores information in a NoSQL database and is based on the Lucene search engine. Elasticsearch is also part of the ELK Stack.