- A/B Testing
- Agile
- Automation
- Blue/Green Deployment
- Build
- Canary Release
- Chaos Engineering
- CI/CD
- Cloud-Native
- Code Review
- Configuration Management
- Container
- Continuous Testing
- DevOps Culture
- Docker
- Environment
- Feedback Loop
- Idempotence
- Immutable Infrastructure
- Infrastructure as Code (IaC)
- Infrastructure Monitoring
- Jenkins
- Kubernetes
- Microservices
- Monitoring
- Pipeline
- Post-Mortem Analysis
- Provisioning
- Release
- Repository (Repo)
- Rollback
- Scalability
- Shift Left
- Smoke Testing
- Source Code Management (SCM)
- Vagrant
- Version Control
- Virtual Machine
Kubernetes is an open-source platform designed for deploying, scaling, and managing containerized applications. It orchestrates the deployment and management of containers, allowing for automation in scaling, failure recovery, and rolling updates. With Kubernetes, applications can be broken down into microservices, managed through declarative configuration, and run consistently across various environments. Kubernetes features include automatic bin-packing, self-healing, horizontal scaling, and service discovery. It integrates with popular container tools like Docker and supports cloud-native development, making it a foundational technology for modern software architectures and DevOps practices.
Use Cases
Microservices Architecture:
- Objective: Manage and orchestrate a complex system divided into loosely coupled microservices.
- Workflow: Kubernetes handles service discovery, load balancing, and scaling of microservices. It also manages inter-service communication.
- Tools: Istio, Linkerd, Envoy
Batch Processing and Scheduled Jobs:
- Objective: Automate and manage batch jobs and scheduled tasks.
- Workflow: Kubernetes CronJobs and Jobs API facilitate the running, scheduling, and retrying of batch processing tasks.
- Tools: Kubernetes native CronJobs, Airflow
Horizontal Scaling:
- Objective: Dynamically scale applications based on resource utilization or custom metrics.
- Workflow: Kubernetes uses Horizontal Pod Autoscalers (HPA) to automatically adjust the number of pod replicas based on predefined metrics.
- Tools: Kubernetes native HPA, Metrics Server
High Availability and Disaster Recovery:
- Objective: Ensure system resilience and data durability.
- Workflow: Kubernetes provides fault tolerance by distributing application instances across different nodes and even across clusters. StatefulSets and persistent volumes help in data persistence.
- Tools: Kubernetes native StatefulSets, Velero
Multi-Cloud and Hybrid Cloud Deployment:
- Objective: Enable deployment and management of applications across multiple cloud providers or a combination of public and private clouds.
- Workflow: Kubernetes’ API-driven architecture allows for consistent deployment and management of applications, regardless of the underlying cloud infrastructure.
- Tools: Anthos (Google Cloud), Azure Arc, AWS Outposts