PREREQUISITE
HISTORY CONTINUED
Kubernetes and Docker are two significant technologies in the world of containerization and container orchestration. Here's a brief history of both Kubernetes and Docker:
Docker:
Docker's Inception (2013): Docker, Inc. (formerly known as dotCloud) introduced Docker in 2013. Docker was a groundbreaking technology that allowed developers to package applications and their dependencies into containers, ensuring consistency across different environments.
Rapid Adoption (2013-2014): Docker gained rapid adoption among developers and the IT industry. Its ease of use and portability made it a game-changer for software development and deployment.
Docker Engine and Ecosystem (2014-2015): Docker expanded its ecosystem by releasing the Docker Engine, the runtime for running containers. It also introduced Docker Hub, a cloud-based repository for sharing Docker images.
Standardization (2015-2016): Docker worked on creating container standards, including the Open Container Initiative (OCI), to ensure compatibility and interoperability among container runtimes.
Challenges and Security Concerns (2017-2018): Docker faced some challenges related to security and orchestration at scale. This led to the development of Docker Swarm for container orchestration, although it faced stiff competition from Kubernetes.
Shift to Kubernetes (Late 2017-2018): While Docker Swarm was a container orchestrator, Kubernetes emerged as the dominant platform for container orchestration. Docker Inc. shifted its focus away from Docker Swarm and began collaborating with the Kubernetes community.
Docker and Kubernetes Integration (2018 and Beyond): Docker and Kubernetes integration was improved to make it easier for developers to use both technologies in tandem. Tools like "Docker for Desktop" provided a seamless Kubernetes experience for Docker users.
Kubernetes:
Origin and Introduction (2014): Kubernetes was originally developed by Google, and it was introduced in 2014. It was open-sourced and quickly gained popularity as a container orchestration platform.
Growth and Adoption (2015-2016): Kubernetes gained significant traction within the industry, with major companies like Microsoft, Amazon, and IBM adopting it as a part of their container offerings.
CNCF and Wider Community (2017): The Cloud Native Computing Foundation (CNCF) took over the governance of Kubernetes in 2017, leading to broader collaboration, innovation, and support within the container ecosystem.
Kubernetes Ecosystem (2018 and Beyond): A rich ecosystem of tools and extensions developed around Kubernetes, including Helm, Istio, and Prometheus, further enhancing its capabilities.
Ongoing Development (2020 and Beyond): Kubernetes continues to evolve with regular releases, addressing security, scalability, and integration with various cloud services.
In summary, Docker revolutionized containerization by making it accessible and popular among developers, while Kubernetes became the dominant platform for orchestrating and managing containerized applications. Over time, Docker and Kubernetes worked together to provide a seamless experience for developers, especially those running containers in production environments.
WHAT IS ORCHESTRATOR
An orchestrator, in the context of container technology and microservices, is a tool or platform designed to automate and manage the deployment, scaling, and operation of containerized applications and services. The primary role of an orchestrator is to ensure that whenever containers are deployed and maintained in a way that aligns with your desired state and business requirements. Key functions of orchestrators include:
Container Deployment: Orchestrators automatically manage the deployment of containers across a cluster of servers or nodes. They determine where to place containers and ensure that they are started and stopped as needed.
Scaling: Orchestrators can automatically scale the number of containers up or down based on resource demand. When traffic increases, they create more instances; when traffic decreases, they remove unnecessary containers.
Load Balancing: Orchestrators often provide built-in load balancing to distribute incoming traffic among containers. This ensures even resource utilization and high availability.
Self-Healing: In the event of a container failure, orchestrators detect the problem and replace the failed container with a new one. This ensures that applications remain resilient and available.
Rolling Updates and Rollbacks: Orchestrators can facilitate rolling updates, allowing you to update containers one at a time with zero or minimal downtime. If an update causes issues, orchestrators enable rollbacks to the previous version.
Service Discovery: They help manage service discovery by automatically registering and resolving services, making it easier for containers to find and communicate with one another.
Resource Management: Orchestrators allocate and manage resources like CPU and memory for containers, ensuring that each container gets the required resources.
Health Checks: They perform regular health checks on containers to ensure they are running properly. If a container fails a health check, the orchestrator takes action to replace it.
Popular container orchestrators include Kubernetes, Docker Swarm, and Apache Mesos. Kubernetes, for instance, is known for its extensive feature set and is widely used in the industry.
Orchestrators are critical for managing large, dynamic, and complex container environments, enabling businesses to achieve efficient container orchestration, scalability, high availability, and reliability for their applications and services.
WHAT IS CLOUD NATIVE COMPUTING
Cloud-native computing is an approach to building and running applications that leverage the advantages of cloud computing and modern software development practices.
Cloud-native applications are designed to be highly scalable, resilient, and easily maintainable in cloud environments.
Here are some key principles of cloud-native application:
Microservices: Cloud-native applications are typically composed of small, loosely coupled services called microservices. These services can be developed, deployed, and scaled independently, which promotes agility and allows for efficient resource utilization.
Containerization: Containers, like Docker, are used to package applications and their dependencies in a consistent and isolated environment. Containers are portable, making it easier to move applications between different cloud platforms or on-premises environments.
Orchestration: Tools like Kubernetes are commonly used for orchestrating containers. Orchestration helps manage the deployment, scaling, and maintenance of containers, making it easier to operate complex, distributed applications.
Continuous Integration and Continuous Deployment (CI/CD): Cloud-native development often embraces CI/CD practices. This involves automating the building, testing, and deployment of applications, ensuring faster and more reliable software delivery.
Scalability: Cloud-native applications can scale horizontally, meaning that they can handle increased traffic and workloads by adding more instances of microservices as needed. This scalability is often automated and dynamic.
Resilience: Cloud-native applications are designed to be resilient to failures. Redundancy, failover mechanisms, and self-healing are common design considerations to ensure high availability.
DevOps Culture: Cloud-native development often goes hand-in-hand with a DevOps culture. Developers and operations teams collaborate closely to ensure smooth application deployment and operation.
Observability: Cloud-native applications are built with observability in mind. This means that they provide detailed insights into their performance and health through logs, metrics, and monitoring tools.
Serverless Computing: Serverless platforms, such as AWS Lambda or Azure Functions, are often used for event-driven and batch-processing workloads. With serverless computing, developers don't need to manage servers directly, and they pay only for the compute resources used during execution.
Polyglot Architecture: Cloud-native applications are often built using multiple programming languages, data stores, and technologies that best suit the specific needs of each microservice.
Agile Development: Cloud-native practices align with agile development methodologies, allowing for rapid feature development and iteration.
Cost Efficiency: Cloud-native applications can often optimize resource usage, leading to cost savings. You can scale resources up or down based on demand, reducing the need for overprovisioning.
In summary, cloud-native computing leverages cloud infrastructure and modern development practices to create applications that are highly agile, scalable, resilient, and cost-effective. It enables organizations to respond quickly to changing business needs and deliver software faster and more reliably.
Kubernetes Other than Orchestration
Kubernetes, often referred to as K8s, is more than just an orchestrator. It is a comprehensive container management platform that provides a wide range of features and capabilities beyond simple orchestration. In addition to the essential orchestration functions you mentioned, Kubernetes provides several other critical features and capabilities that make it a comprehensive container management platform:
Configuration Management: Kubernetes allows you to manage and version your application configurations as code, making it easier to maintain and update configurations consistently.
Custom Resource Definitions (CRDs): Kubernetes enables you to create custom resources and controllers tailored to your specific application requirements, extending its capabilities to match your use case.
Stateful Applications: Kubernetes supports stateful applications, making it possible to run databases and other stateful services within containers.
Extensibility: Kubernetes is highly extensible and offers a wide range of APIs and mechanisms to integrate with third-party tools, custom plugins, operators, and controllers.
Security and Access Control: Kubernetes provides robust security features, including role-based access control (RBAC), network policies, and secure secrets management, allowing you to control and secure access to resources and data.
Storage Orchestration: Kubernetes offers storage orchestration capabilities, allowing you to manage persistent storage volumes for containers.
Networking: Kubernetes provides advanced networking features, allowing containers to communicate within pods and across clusters using a variety of networking models.
Monitoring and Logging Integration: Kubernetes integrates with popular monitoring and logging solutions to provide insights into the health and performance of applications and infrastructure.
Service Mesh Integration: Kubernetes can be used in conjunction with service mesh technologies like Istio and Linkerd to manage and secure communication between services.
Continuous Integration/Continuous Deployment (CI/CD): Kubernetes integrates seamlessly with CI/CD pipelines, facilitating the automated building, testing, and deployment of containerized applications.
Multi-Cloud and Hybrid Cloud Support: Kubernetes is cloud-agnostic and can be used across various cloud providers and on-premises environments, allowing for multi-cloud and hybrid cloud strategies.
Kubernetes' extensive ecosystem, vibrant community, and feature-rich architecture make it more than just an orchestrator; it's a versatile platform for managing and orchestrating containerized applications and services across a wide range of use cases and scenarios.
KUBERNETES ABSTRACTION
Tell the system what you want to achieve, and it takes care of how to do it.
Here's a simple example:
What to do: "I want to run three instances of my web application, make sure it's always available, and automatically handle any failures."
How Kubernetes does it: Kubernetes will deploy and manage those three instances of your web application in a way that ensures high availability. If one instance fails, Kubernetes will replace it with a new one automatically.
In essence, Kubernetes abstracts the technical details of managing your applications and infrastructure, allowing you to focus on specifying your desired state, and it handles the rest.
SOME RECAP, AND HOW KUBERNETES IS CONTAINER AGNOSTIC WITH THE HELP OF CRI
CRI (Container Runtime Interface), OCI (Open Container Initiative), Kubernetes, and Docker are all interconnected components in the container ecosystem, and their relationships can be explained as follows:
OCI (Open Container Initiative):
OCI is a standard for container runtimes and image formats. It defines specifications for the format and runtime of containers, ensuring compatibility and portability between different container runtimes.
OCI specifications define two key components: the image specification (OCI Image Format) and the runtime specification (OCI Runtime Specification).
Docker contributed its container format and runtime to OCI, which became the basis for these standards.
CRI (Container Runtime Interface):
CRI is an interface for container runtimes in Kubernetes. It standardizes how Kubernetes interacts with container runtimes to create, run, and manage containers.
The CRI allows Kubernetes to be container runtime-agnostic, meaning it can work with different container runtimes like Docker, containerd, or CRI-O.
CRI implementations provide an API for Kubernetes to interact with the container runtime, ensuring that Kubernetes can manage containers consistently across various runtimes.
Docker:
Docker is both a company and a set of tools, which includes container runtime and container image management tools.
Docker provides a comprehensive solution for building, packaging, and distributing container images, and it includes the Docker Engine as the container runtime.
Docker's container format and runtime are based on OCI standards.
Kubernetes:
Kubernetes is an open-source container orchestration platform for automating the deployment, scaling, and management of containerized applications.
Kubernetes uses container runtimes to run and manage containers within pods. It interacts with container runtimes through the CRI.
Kubernetes can work with multiple container runtimes, such as Docker, containerd, or CRI-O, due to its CRI interface.
In summary, Docker, as both a company and a technology, was instrumental in popularizing containers and played a significant role in creating OCI standards. These standards led to more compatibility and interoperability between container runtimes. Kubernetes, on the other hand, uses the CRI to interact with container runtimes, and it's designed to be runtime-agnostic, allowing it to work with various container runtimes based on OCI standards. While Docker and Kubernetes can work together, Kubernetes is designed to be independent of the container runtime, which enables flexibility and choice in the container ecosystem.