Developing microservices destined to run in Kubernetes presents a unique set of challenges. In this blog post, we’ll explore a new approach leveraging Codezero in order to enhance both productivity and security.

Confluent has published official Docker containers for many years. They are the basis for deploying a cluster in Kubernetes using Confluent for Kubernetes (CFK), and one of the underpinning technologies behind Confluent Cloud. For testing, containers are convenient for quickly spinning up a local cluster with all the components required, such as Confluent Schema Registry or Confluent Control Center.

As software projects become more complex and the need for speed increases, catching critical bugs and vulnerabilities early in the process is crucial. This is where Codezero steps in, reshaping the DevOps cycle by focusing on “Shift Left” and early bug detection.

In this guide, we document the process of building mock APIs in Kubernetes from traffic using Speedscale.

Enhance kubernetes resilience with AWS Fault Injection Simulator, LitmusChaos, Gremlin, Chaos Monkey, ChaosBlade, Azure Chaos Studio, and Speedscale.

Kubernetes is an open-source container orchestration system for automating deployment, scaling, and management of containerized applications. It groups containers into logical units for easy management and discovery. API gateways sit between clients and microservices. They act as a reverse proxy to accept all API calls, then route and transform requests to appropriate microservice.

Dev Teams rely on their Dev Leaders and DevOps to fill a crucial role, bridging the gap between development and operations to ensure smooth workflows in the fast-paced world of software development. This role requires not only technical expertise but also the ability to navigate team dynamics and project management challenges. Enter Codezero Teamspaces, a tool essential for modern Dev Teams fostering collaborative development.