Whether you're transitioning away from a monolith or building a green-field app, opting for a microservice architecture brings many benefits as well as certain challenges. These challenges include namely managing the network and maintaining observability in the microservice architecture. Enter the service mesh, a valuable component of modern cloud-native applications that handles inter-service communication and offers a solution to network management and microservice architecture visibility.
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.
