Microservices have been on the rise along with an increasing number of containers that are being used in the industry. Because of this, IT professionals must change their approach to microservices health checks. In the world of monolithic architecture, the primary goal is to monitor at the system level. This is still needed for microservices, but you need to go one step further and monitor the service itself.
If you are dealing with microservices, serverless architecture, on any other type of distributed architecture, you have probably heard the term “Distributed Tracing.” You may have been wondering what it’s all about, and where should you start, in this post, I’ll tell you about the journey we passed at Duda, from the day we heard about distributed tracing and started to explore whether it will be useful to use it in our company, to the exploration on what is distributed tracing a
The network is foundational to distributed application environments. A distributed application has multiple microservices, each running in a set of pods often located on different nodes. Problem areas in a distributed application can be in network layer connectivity (think network flow logs), or application resources unavailability (think metrics), or component unavailability (think tracing).
Microservices architecture is getting adopted extensively in the world of distributed applications. There are various options and frameworks available to implement the Micro Services, e.g., Azure Service Fabric, Azure Kubernetes Services, Azure Functions, etc. The hottest trend these days seems to be serverless. The promise of consumption-based pricing, where you only pay for what you use and nothing more, is enticing.
Building a microservices-based application requires a wide range of tools and technologies. Since these tools/technologies work together like a multi-faceted puzzle, it’s difficult for a beginner to understand what they are and why they’re necessary. The goal of this guide is to provide an accessible introduction to each of these essential concepts – all in one place.
Companies today are breaking down their big monolithic applications into multiple microservices and one of the challenges of having to deal with multiple microservices is that it’s difficult to isolate issues such as: With microservices, there is also no dynamic way to reroute network traffic when failures occur or new containers need to be deployed.
Your team has decided to migrate your monolithic application to a microservices architecture. You’ve modularized your business logic, containerized your codebase, allowed your developers to do polyglot programming, replaced function calls with API calls, built a Kubernetes environment, and fine-tuned your deployment strategy. But soon after hitting deploy, you start noticing problems.