Modern software development is evolving rapidly, and while the latest innovations allow companies to grow through greater efficiency, there is a cost. Modern architectures are incredibly complex, which can make it challenging to diagnose and rectify performance issues. Once these issues affect customer experience, the consequences can be costly. So, what is the solution? Observability — which provides a visible overview of the big picture.

In this blog series, we are covering application instrumentation steps for distributed tracing with OpenTelemetry standards across multiple languages. Earlier, we covered Java Application Manual Instrumentation for Distributed Traces, Golang Application Instrumentation for Distributed Traces, and DotNet Application Instrumentation for Distributed Traces. Here we are going to cover the instrumentation for NodeJS.

A JSON web token (JWT) is a URL-safe method of transferring claims between two parties. The JWT encodes the claims in JavaScript object notation and optionally provides space for a signature or full encryption. The JWT proposed standard has started to see wider adoption with frameworks like OAuth 2.0 and standards like OpenID connect leveraging JWTs.

Sogeti, a Managed Service Provider (MSP) that provides tech and engineering resources worldwide, had a crucial IT challenge to solve. The MSP operates in more than 100 locations globally and was using six different monitoring tools to monitor its customers’ environments. It was a classic example of tool sprawl and needing to scale where multiple teams of engineers relied on too many disparate tools to manage their customers’ environments.

LogicMonitor continues to grow its visibility of critical business infrastructure and applications. We acquired Airbrake to help see more of what is happening in a customer’s environment at the code level. Simply integrating Airbrake’s dashboard metrics within LogicMonitor alongside your existing networks, services, and cloud infrastructure enables you to gain access to errors and the context you need to effectively troubleshoot issues impacting your systems and users.

In this blog series, we are covering application instrumentation steps for distributed tracing with OpenTelemetry standards across multiple languages. Earlier, we covered Golang Application Instrumentation for Distributed Traces and DotNet Application Instrumentation for Distributed Traces. Here we are going to cover the instrumentation for Java.

Historically, enterprise IT organizations have turned to application performance management (APM) systems to monitor and manage critical applications. However, throughout the world, enterprise organizations are suffering massive and systemic failures at an increasing rate. One of the main reasons these failures are increasing is that organizations aggressively seek to execute digital transformation initiatives.

Use this guide to write a DotNet (.Net) application emitting traces using the OpenTelemetry Protocol (OTLP) Specification. All you need is.NET Framework 4.6.2+ or.NET Core 2.1+ and a basic understanding of developing applications on the.Net framework.

The complexity of applications is continually increasing the need for good logs. This need is not just for debugging purposes but also for gathering insight about the performance and possible issues with an application. The Python standard library is an extensive range of facilities and modules that provide most of the basic logging features. Python programmers are given access to system functionalities they would not otherwise be able to employ.

Use this guide to write a golang application emitting traces using the OpenTelemetry Protocol (OTLP) Specification. All you need is a basic understanding of developing applications in golang.