Operations | Monitoring | ITSM | DevOps | Cloud

Microservices

What's going on with the Developer Productivity debate?

Every so often, somebody in the tech industry proposes a new way to quantify software engineers’ productivity. Most recently, a leading consulting firm published a report that has reignited a recurring debate—is it even possible to effectively measure developer productivity, and if so, how? Whereas functions like sales and support have had rigorous metrics for years, software engineering has long been the exception.

Troubleshooting Spring Boot Microservices - A Real World Case Study

Today, I’ll cover Shift Left Monitoring: A Pathway to Optimized Cloud Applications and how left-shifted troubleshooting of Spring Boot code issues using observability tooling can avoid production issues, unnecessary costs and improve product quality. Shift-left is an approach to software development and operations that emphasizes testing, monitoring, and automation earlier in the software development lifecycle.

Introducing Cortex Plugins and Customization

To be a true system of record, your IDP needs to be a source of truth for all the data in your stack. While Cortex offers 50+ out of the box integrations, and the ability to bring in custom data, we know there are occasions where you’ll also want to visualize or take action on data sourced from other places including internally developed tools or repositories. That’s why we’re excited to officially launch the Cortex plugin framework plus UI customization. Now users can.

Best Practices and Potential Loopholes for Successful Microservices Architecture

Microservices architecture is a software development approach where an application is built as a collection of small, loosely coupled, independently deployable services. Each service focuses on a specific business capability and operates as an autonomous unit, communicating with other services through well-defined APIs. This architectural style is often used in the context of DevOps to create more efficient, scalable, and manageable systems.

Scaling microservices: Challenges, best practices and tools

Scaling the deployment, in order to meet demand or extend capabilities, is a known challenge in many fields, but it’s particularly pertinent when scaling microservices. This article looks at the challenges of scaling microservices and examines best practices to overcome them while maintaining app quality, dev efficiency, and a good developer experience.

Database Migrations in the Era of Kubernetes Microservices

In our extensive guide of best ci/cd practices we included a dedicated section for database migrations and why they should be completely automated and given the same attention as application deployments. We explained the theory behind automatic database migrations, but never had the opportunity to talk about the actual tools and give some examples on how database migrations should be handled by a well disciplined software team.

Establishing a Kubernetes cost management strategy

Kubernetes (k8s) adoption has skyrocketed since its 2014 introduction, becoming one of the most popular open source container orchestration platforms for its power and flexibility. K8s reduce costs by improving efficiency, optimizing resource use, and eliminating redundancies. But cost savings in Kubernetes can be tricky to maintain. In fact, a 2021 survey of 178 organizations showed that costs associated with k8s can actually increase from insufficient monitoring, resulting in overspend.

What's missing from your incident management workflow

The first fifteen minutes of an incident set the tone for the rest of the resolution process. But what makes the difference between a rapid response and a stressful scramble—clear ownership—hasn't always been easy to ascertain. In this article, we’ll cover how Cortex, an internal developer portal, can be your team’s source of truth to accelerate the incident management process, and reduce MTTR.

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Best practices for tracing and debugging microservices

Tracing and debugging microservices is one of the biggest challenges this popular software development architecture comes with - probably the most difficult one. Due to the distributed architecture, it's not as straightforward as debugging traditional monolithic applications. Instead of using direct debugging methods, you'll need to rely on logging and monitoring tools, coding practices, specific databases, and other indirect solutions to successfully debug microservices.