These days, many IT executives believe that it is easier to deploy applications in the cloud than on-prem. They are also often under the misconception that once an application is hosted in the cloud, it is the responsibility of the cloud service provider to maintain the availability and performance of the application.

Grafana and Splunk are both used as monitoring tools. But while Grafana is majorly used as a data visualization tool, Splunk is an enterprise security and observability platform. Monitoring tools are essential for any business that wants to have visibility into its IT infrastructure. They provide real-time data that can be used to identify and troubleshoot problems. Grafana and Splunk are two of the most popular monitoring tools on the market. So, which one is better for your business?

Having user-friendly programs is paramount for any software company’s success. To gain a better understanding of your users’ experience and enjoyment, it’s vital that you learn how customers interact with your app or website. Real user monitoring (RUM) solutions enable your company to visualize how users interact with your software, helping you learn what works best for your customers so you can thrive against the competition.

In the last few years, fintech enterprises have disrupted the financial services and banking industry by taking everything computing technology offers – from machine learning to blockchain – and turning it up a notch. Traditional financial institutions must now compete with challenger banks offering electronic payment alternatives, peer-to-peer lending, and investment apps.

In the previous article, we learned what distributed tracing is, why it is necessary, how to do tracing, encountered challenges with existing tracing tools, and finally discovered that there is a more mature option available for the industry to adopt in terms of telemetry and observability. In this article, we will be trying to understand OpenTelemetry in more depth. To begin, we will examine how OpenTelemetry addresses some of the issues confronting the observability ecosystem.

Many organizations rely on distributed tracing in Datadog APM to gain end-to-end visibility into the performance of their Kubernetes applications. But as teams grow, it can become impractical for them to manually configure each new application with the libraries and environment variables needed for tracing.

Have you heard about traces? Most likely, yes! Do you confuse it with auditing? Hope not. Today, we're going to talk about tracing, specifically “Distributed Tracing,” and do a deep dive into it. Once we’re familiar with distributed tracing, we will show you how to implement it with OpenTelemetry - a new-age observability framework.