Previously, I wrote a Beginner’s Guide to Jaeger + OpenTracing Instrumentation for Go providing guidance on manually instrumenting Go services. This is useful for cases where we want fine-grained tracing of specific functions. However, what if all we want is to trace a service’s inbound and outbound calls with little to no additional code?

When did our infrastructure get so complicated? For many of my clients, the number of resources their applications are built on seems to have snowballed overnight. It was, of course, a gradual progression, and usually a conscious one, but complexity can feel like it grows geometrically with each new resource element. And that complexity can create problems.

Many of you use HashiCorp Consul for service discovery. It makes connecting one backend application or service to another easy: Your Consul servers store a catalog of addresses to all of your services; when an application within the network wants to discover where a service is listening, it asks Consul, which gives it the address.

Istio is an open source service mesh that can be used by developers and operators to successfully control, secure, and connect services together in the world of distributed microservices. While Istio is a powerful tool for teams, it's also important for administrators to have full visibility into its health. In this blog post, we'll take a look at monitoring Istio and its microservices with Elastic Observability. As the Istio docs mention.

Istio is an open source service mesh that provides an abstraction layer for network traffic between applications, so you can run canary deployments, implement circuit breakers, and otherwise manage the architecture of your network using high-level configuration files. As service meshes become increasingly popular among containerized environments, dev and ops teams need to ensure that Istio is healthy, performant, and routing traffic as intended to keep their network infrastructure running smoothly.

Service Mesh is an emerging architecture pattern gaining traction today. Along with Kubernetes, Service Mesh can form a powerful platform which addresses the technical requirements that arise in a highly distributed environment typically found on a microservices cluster and/or service infrastructure. A Service Mesh is a dedicated infrastructure layer for facilitating service-to-service communications between microservices.

With the acceleration of digitalization, enterprises across all verticals are running more and more distributed applications deployed on multiple clouds. This poses a new set of challenges when it comes to maintaining, updating, and securing these distributed applications. Our customers are looking for solutions to connect and secure their applications for rapid delivery with minimal disruptions and code changes.