Systems | Development | Analytics | API | Testing

The more services you have running across different clouds and Kubernetes clusters, the harder it is to ensure that you have a central place to collect service mesh observability metrics. That’s one of the reasons we created Kuma, an open source control plane for service mesh. In this tutorial, I’ll show you how to set up and leverage the Traffic Metrics and Traffic Trace policies that Kuma provides out of the box. If you haven’t already, install Kuma and connect a service.

Optoro’s platform finds returned items a new home. Here’s how its data engineering team keeps mission-critical data flowing.

This article provides an introduction to API Observability and how it fits within the overall APIOps Cycles. Then, we will walk through an example of how to successfully deploy and leverage Tyk Gateway and Moesif API Observability on Amazon EC2.

API Observability is a key component to properly execute APIOps Cycles and ensure your building something of value for your API users. If you’re not familiar with APIOps Cycles, take a look at this guide which provides an agile framework to quickly build APIs that are business-oriented and serve customer needs. API Observability itself is an evolution of traditional monitoring and born out of control systems theory.

In the modern SaaS world, observability is key to running software reliability, managing risks and deriving business value out of the code that you’re shipping. To measure how your service is performing, you record Service Level Indicators (SLIs) or metrics, and alert whenever performance, correctness or availability is affected.