Operations | Monitoring | ITSM | DevOps | Cloud

Microservice architectures have become extremely popular in recent years, and for good reason. When managed properly, they improve scalability, encourage faster development and deployment, and reduce data and domain coupling. Companies of all sizes, from small startups to large enterprises, have migrated their monolithic applications over to microservice and service-oriented architectures. Making the move from monolith to microservices is a big shift, though.

Have you ever tried to find a bug in a multi-layered architecture? Although this might sound like a simple enough task, it can quickly become a nightmare if the system doesn’t have proper monitoring. And the more distributed your system is, the more complex it becomes to analyze the root cause of a problem. That’s precisely why observability is key in distributed systems. Observability can be thought of as the advanced version of application monitoring.

The past ten years marked a significant change in how software teams build and deploy applications. We moved away from bulky, slow, monolithic applications toward lightweight, scalable, distributed service-based applications. Meanwhile, tools like Docker, Kubernetes, and other container platforms helped accelerate this process. Despite this sudden growth, a fundamental question remains: what exactly is a service, and how does it fit into a microservice architecture?

Microservices have grown to become one of the most optimal alternatives to monoliths. However, just building your app and releasing it to the public isn’t everything. Monitoring microservices is as important as building and releasing them. You need to maintain it to resolve issues that may occur and also introduce new features from time to time.

Is microservice quality a focus for your team this year? Perhaps you’re looking to improve your service performance. Maybe you feel like your organization needs better ways to enforce best practices or ensure that service quality doesn’t degrade over time. Let’s take a look at these three areas and share some concrete recommendations for strengthening your services and creating a long-term culture of quality.

There have been amazing articles on the subjects of migrating from a monolith to a microservice architecture e.g. this is probably one of the better examples. The benefits and drawbacks of the architectures should be pretty clear. I want to talk about something else though: the strategy. We build monoliths since they are easier to get started with. Microservices usually rise out of necessity when our system is already in production.

Moving from a monolith to microservices lets you simplify code deployments, improve the reliability of your applications, and give teams autonomy to work independently in their preferred languages and tooling. But adopting a microservices architecture can bring increased complexity that leads to gaps in your team members’ knowledge about how your services work, what dependencies they have, and which teams own them.

Moving from a monolith to microservices lets you simplify code deployments, improve the reliability of your applications, and give teams autonomy to work independently in their preferred languages and tooling. But adopting a microservices architecture can bring increased complexity that leads to gaps in your team members' knowledge about how your services work, what dependencies they have, and which teams own them.

LM Envision is a unified observability platform from LogicMonitor that unites comprehensive monitoring and observability capabilities. In this blog post, we’ll show how to integrate Istio service mesh with a LogicMonitor APM so that application traces can be used within LM Envision to better understand, optimize, and troubleshoot application performance.

Over the past decade, organizations have reinvented themselves through digital transformation. Nowadays, this journey is well in its second chapter and gaining momentum – also driven by the explosion of app and service deployment, data and intelligence, digital reach, and post-pandemic customer expectations. And the newest cutting-edge technological trends – such as hybrid infrastructure and edge computing – are making it particularly difficult for traditional tools to keep up.