A comprehensive guide to instrument Golang applications using OpenTelemetry libraries for metrics and traces.

Application security testing tools are designed to ensure that applications are put through rigorous security assessments to identify security flaws within the application and its code. Even though applications are tested thoroughly (in static and dynamic ways), attackers always seem to find new ways of compromising them.

For high throughput systems that focus on gathering continuous data or have a heavy read-only traffic, NoSQL databases came as a blessing. NoSQL databases, due to their unstructured nature of data, allow relatively faster inserts as well as reads compared to relational databases. One such database that’s quite popular today is MongoDB. In this article, our focus would be to understand how to extract metrics out of MongoDB and ship them to Signoz using the Open Telemetry collector.

Let's dive deep into the realm of Memcached, where we'll uncover the power of monitoring with OpenTelemetry and SigNoz. This isn't just about caching data; it's about watching over Memcached like a vigilant guardian, ensuring it performs at its best, and optimizing your application's speed. In this tutorial, you will install OpenTelemetry Collector to collect Memcached metrics that should be monitored for performance and then send the collected data to SigNoz for visualization and alerts.

Enabling auto-instrumentation for your Lambda functions provides detailed insights into the performance and security of your serverless applications. Developers often also use custom instrumentation to fine-tune visibility and further tailor telemetry to their business needs. However, different teams within your organization might use a variety of instrumentation libraries, and achieving more granular visibility can come at the expense of data portability and interoperability.

To monitor and troubleshoot the performance of microservice-based applications, Jaeger and Zipkin are examples of the most commonly used open-source distributed tracing systems. They both supply users with insight into the flow of requests through various components of a system, which can be utilized to find latency bottlenecks, errors, and performance problems in the system.

Database monitoring is an important aspect to look at for a high-volume or high-traffic system. The database performance drastically impacts the response times for the application. In this tutorial, you will install OpenTelemetry Collector to collect MySQL metrics and then send the collected data to SigNoz for monitoring and visualization. In this tutorial, we cover: If you want to jump straight into implementation, start with this pre-requisites section.

In the realm of modern software development, achieving true observability is paramount for understanding application behavior and performance. This demonstration focuses on a.NET application that harnesses the capabilities of OpenTelemetry to seamlessly integrate logging and tracing functionalities. OpenTelemetry, a key player in the Cloud Native Computing Foundation, provides a unified framework for comprehensive observability.

OpenTelemetry provides a component called OpenTelemetry Collector, which can be used to collect data from multiple sources. Prometheus is a popular metrics monitoring tool that has a wide adoption. If you’re using Prometheus SDKs to generate metrics, you can collect them via OpenTelemetry collector and send them to a backend of your choice.