Someone once described dashboards to me as “expensive TV for software engineers.” At first, I stood there quietly shocked—dashboards had informed many root cause analyses (RCAs) in my life as a developer.

Logs are key to monitoring the performance of your applications. Kubernetes offers a command line tool for interacting with the control plane of a Kubernetes cluster called Kubectl. This tool allows debugging, monitoring, and, most importantly, logging capabilities. There are many great tools for SREs. However, Kubernetes supports Site Reliability Engineering principles through its capacity to standardize the definition, architecture, and orchestration of containerized applications.

A pivotal inhibitor to mitigate these challenges is the Data Value Gap. Data automation and Data Fabric are emerging as key technologies to overcome these challenges. Learn from industry experts about these key technologies and how they create a lasting impact in enterprise IT.

A full Observability stack has the goal of providing full centralized visibility to Development, Operations and Security teams into all of the Metrics, Logs and Traces generated by the applications and services under their domain. Many companies address these observability needs by buying a complete application performance management (APM) solution from a single vendor, like DataDog.

SLOs—or Service Level Objectives—can be pretty powerful. They provide a safety net that helps teams identify and fix issues before they reach unacceptable levels and degrade the user experience. But SLOs can also be intimidating. Here’s how a lot of teams feel about them: We know we want SLOs, we’re not sure how to really use them, and we don’t know how to debug SLO-based alerts. Don’t worry, we’ve got your answer—observability!

Kubernetes is the most popular container orchestration tool for cloud-based web development. According to Statista, more than 50% of organizations used Kubernetes in 2021. This may not surprise you, as the orchestration tool provides some fantastic features to attract developers. DaemonSet is one of the highlighted features of Kubernetes, and it helps developers to improve cluster performance and reliability.

Roaming in the world of cloud technology not only helps you take a glance at the realm of cutting-edge technology but also helps you get familiar with concepts such as monitoring and observability. This article will cover an introduction to monitoring and the need for monitoring applications. From here, we will look at how you can utilize the data received when monitoring an application. This will allow us to understand how the concept of observability fits in with monitoring.

In this post, we’ll look at how you can use OpenTelemetry to monitor your unit tests and send that data to Honeycomb to visualize. It’s important to note that you don’t need to adopt Honeycomb, or even OpenTelemetry, in your production application to get the benefit of tracing. This example uses OpenTelemetry purely in the test project and provides great insights into our customer’s code. We’re going to use xUnit as the runner and framework for our tests.

There have been amazing articles on the subjects of migrating from a monolith to a microservice architecture e.g. this is probably one of the better examples. The benefits and drawbacks of the architectures should be pretty clear. I want to talk about something else though: the strategy. We build monoliths since they are easier to get started with. Microservices usually rise out of necessity when our system is already in production.