Crack your next Microservices Docker & Kubernetes Interview

Explore how spring cloud config server centralizes microservice configuration by externalizing settings in a git repository, enabling automatic updates without rebuilds across services and discovery configurations.

Understand how Spring Cloud Bus works with the config server to broadcast configuration changes to microservices via a message broker, enabling automatic updates without restarts.

Register microservices with a centralized service discovery to enable dynamic inter-service communication without hard-coded URLs. Netflix Eureka (Spring Cloud) provides this registry and automatic URL resolution as services scale.

Explore the circuit breaker pattern in spring-based microservices architecture, emphasizing graceful handling of inter-service calls when a service is down, using Resilience4J or Hystrix via Spring Cloud Circuit Breaker.

Spring Cloud Sleuth enables tracing of client requests across microservices by generating and propagating a correlation ID, enabling centralized logging with the ELK stack for end-to-end visibility.

Explore how Spring Cloud Stream enables asynchronous, event-driven communication between microservices using a message broker, illustrated by a product back-in-stock notification flow involving inventory and notification services.

Master the API gateway pattern to shield microservices, route all client traffic through a gateway, and enforce security, rate limiting, and monitoring via Keycloak authentication and Spring Cloud Gateway.

Compare rest template, web client, and feign client for calls in spring boot microservices; rest template is blocking, web client non-blocking, feign declarative with load balancing via eureka and ribbon.

Master centralized session management in a microservice architecture by using Redis cache as an in-memory, distributed key-value store to share user data across services and validate sessions via a token.

Explore Docker fundamentals, Kubernetes architecture, and deployment and service concepts to confidently prepare for Docker and Kubernetes interviews.

Explore how Docker, an open source platform for building, deploying, and managing containerized applications, solves the traditional development and deployment bottlenecks across local and server environments.

Explore Docker as an open source platform for building, deploying, and managing containerised applications. Containers bundle runtime, dependencies, configuration, and server settings to ensure identical execution across environments.

Discover how Docker delivers consistent, isolated environments, fast deployment, and cost savings, with the ability to run anywhere and automate tests, rollbacks, and scalable, modular stacks.

Define your application with a docker file that specifies the runtime and dependencies, build a docker image, push it to a registry, and run scalable containers that communicate with databases.

Introduce kubernetes and compare traditional hardware-based deployment with virtualization using hypervisors and virtual machines, highlighting resource underutilization and OS overhead, and foreshadow a more efficient deployment approach.

Explore how Docker containers run isolated applications from Docker images on any host, delivering lightweight, scalable deployment across on-prem and cloud, while addressing health monitoring and security challenges.

Kubernetes is a container orchestration tool that manages thousands of containers with high availability and scalability. It handles monitoring, security, auto scaling, and rolling deployments to update apps without downtime.

Discover how Kubernetes forms a cluster by linking physical or virtual machines into nodes, with a master node instructing worker nodes to run tasks across on-premises or cloud environments.

Explore how Kubernetes uses master and worker nodes and how namespaces isolate resources within a cluster and keep resource names unique inside each namespace to support multiple applications and security.

Explore how a Kubernetes cluster uses master and worker nodes to form a curated cluster with kubelet on each worker, where pods run Docker containers from images.

Learn how the API server is the entry point to the Kubernetes control plane, routing commands to the master node and worker pods via UI, REST APIs, or kubectl-like tools.

Explore the master node's controller manager and its four controllers: node, application, endpoint, and service account and token, and how they maintain node health, replicas, and endpoints.

Discover how the master node's scheduler assigns a new port by checking worker capacity, handling API server requests, and issuing commands to create the port on the chosen node.

Store the cluster state in a highly available etcd key-value store to ensure consistency and enable redundancy with two master nodes in production.

Discover the Kubernetes internal virtual network, an internal cluster network that enables communication between components, including the master and worker nodes, ensuring the cluster remains functional.

A pod is the smallest deployable unit hosting one container, and a service provides a stable DNS name and load balancing to connect pods despite dynamic IPs.

Define replica sets as an abstraction that guarantees a minimum number of parts running at all times, and work with the application controller to maintain them.

Create and manage deployments by wrapping pods, databases, and apps in a deployment yaml or json, deploy via kubectl, and control replicas, auto-scaling, upgrades, and rollbacks with helm.

Explore running a Kubernetes cluster with Minikube for local testing, on-premise deployments, and cloud options like AKS, EKS, and GCS, with pay-as-you-go pricing.