Operations | Monitoring | ITSM | DevOps | Cloud

A mock server can prove useful in many circumstances. Imagine you’re an engineer working on optimizing a feature inside of an existing API that relies on multiple other microservices to function properly. To fully test the optimizations, you’ll have to set up test versions of all the dependencies, which quickly proves to be quite a task in and of itself. This is where a mocks—a server that simulates the behavior of a real server—can be very beneficial.

Nowadays, when most people think about the term “machine learning,” they think of advanced, refined applications such as Chat-GPT, the chatbot-based deep learning text generator, or AlphaGo, the computer program that’s currently the “world's best player” of the board game Go.

Monitoring is not a goal, but a path. Depending on the maturity of your project, it can be labeled in one of these six steps of the cloud monitoring journey. You will find best practices for all of them and examine what companies get from each one. From classic virtual machines to large Kubernetes clusters or even serverless architectures, companies have adopted the cloud as a mainstream way to provide their online services.

Kubernetes is a quintessential operating system for the cloud, providing a platform for the deployment, scaling, and management of containerized microservice applications. At the heart of Kubernetes is the Kubernetes API, which serves as the primary entry point for interacting with the system. The official client for the Kubernetes API is kubectl, a Kubernetes CLI tool that allows users to manage a Kubernetes cluster and perform a wide range of tasks.

Managing your clusters has become a complex and confusing task. With scattered tools and the requirement to learn specific tools from cloud providers, many companies have trouble making the most of the cloud. That's where OpenCP comes in. Join us as we explore the benefits of simplifying management across cloud platforms with OpenCP. We’ll dive into the benefits of using OpenCP, how it works, and how it is built on the best practices of kubectl and kubeapi.

DevOps engineers wishing to troubleshoot Kubernetes applications can turn to log messages to pinpoint the cause of errors and their impact on the rest of the cluster. When troubleshooting a running application, engineers need real-time access to logs generated across multiple components. Collecting live streaming log data lets engineers: The challenge that engineers face is accessing comprehensive, live streams of Kubernetes log data.

In this third and final part, you’ll get to see a few examples that aren’t strictly related to configuration changes or new tools, but rather ways that traffic replay can help streamline the development process for those deploying in Kubernetes.

Managing infrastructure while developing, building, and running an application is difficult for developers. In fact, many businesses often struggle with infrastructure management besides managing their applications. To tackle this problem, Platform-as-a-Service or PaaS came into existence. PaaS provides a platform with a cloud-based environment for developers to develop and manage their applications with pre-configured tools and frameworks.