How are distributed systems on Kubernetes evolving?
Kubernetes was looking for its big break when the other industry giants such as Amazon ECS, Cloud Foundry Diego, Docker Swarm, etc., were dominating the container-orchestrator market. After the landscape evolved, the game changed. Most of the providers were already supporting & integrating Kubernetes, including major players like Google’s Kubernetes Engine, Microsoft’s Azure Container Service, IBM’s Cloud Container Service, as well as Red Hat’s OpenShift.
While designing or developing apps on Kubernetes, you have the freedom to shift to multiple cloud providers and Kubernetes distributors. With time, this distribution system has evolved and the latest evolution is the serverless computing model.
Let’s see how the distribution on Kubernetes has evolved with time –
Modern Distributed Applications
Distribution systems are composed of 100s of components and 1000s of instances, which can be stateful, stateless, or serverless. These components are polyglot, independent, and automatable. They can be built to run in hybrid environments, have open-source technologies, interoperability, and open standards. You can use the Kubernetes platform to create the ecosystem.
To create a distributed application or service, you would need the following things –
At first, you require lifestyle capabilities. If you are building an app in other languages, you need the ability to securely package & distribute the app and roll it back or run a health check on it. You can also deploy applications on multiple nodes to isolate resources, scale, and manage configurations.
This requires you to have the capabilities such as service discovery, load balancing, and traffic routing. You also need abilities to communicate with systems via retry, timeout, circuit breaking, while also getting features like adequate monitoring, tracing, observability in place.
Next, you need to have the ability of resources binding. This includes features like connectors for APIs, protocol conversion, message transformation, filtering, message routing, point-to-point or pub/sub-interactions.
Lastly, you need to be familiar with developer abstractions. You need the ability of workflow management, distributed caching, Idempotency, temporal scheduling, and transactionality.
This framework of distributed systems is used to evaluate the changes in Kubernetes.
Monolithic Architectures (Traditional Middleware Capabilities)
Monolith involves ESS. ESBs enable users to orchestrate long-run processes, for distributed transactions, idempotents, and rollbacks. ESB also provides users with an excellent set of resource-binding capabilities, hundreds of connectors, transformation & orchestration support, and networking capabilities. In addition, the ESB also performs service search and load balancing.
Traditional middleware capabilities –
- Stateful primitives
- Resource binding
Traditional middleware limitations (lifestyle management) –
- Single, shared language runtime
- Manual deployment or rollback
- Manual placement
- Manual scaling
- No resource or failure isolation
Cloud-native Architectures (Microservices and Kubernetes)
With microservices, you can break down your monolithic applications based on their business domains. Containers and Kubernetes have proven to be great platforms to manage microservices.
Enables you to deploy the container in a pod. Kubernetes then checks the health, readiness, and liveness of the application or service.
Kubernetes starts or shuts down your application, as well as moves it around on different nodes.
Kubernetes checks the logs and upgrades instances for you. It also stops old instances & starts new ones.
Demands & Placements
Kubernetes provides insights based on your containerization. It provides predictable resource demand & automated placements.
Kubernetes uses ConfigMaps in Pods as environment variables and volumes. And there’s a feature called secrets that include minimal node speed, storage in tempfs memory, backend store encryption, and restricted access with RBAC.
Other than these, there are foundational Kubernetes capabilities that involve multiple structural patterns like hybrid workloads and lifestyle capabilities.
How to extend Kubernetes?
The two ways commonly used for extending Kubernetes –
Out-of-process Extension Mechanism
This involves 2 sets where the first concept includes deploying containers on notes using abstraction. In this, the node ends up having all containers in a pod. Therefore, deployment is assured. The second set assures that a pod works around the lifecycle.
Using Sidecar, you can run multiple containers that jointly or collaboratively provide value. This is one of the main mechanisms that is seen today, used for extending Kubernetes with additional features.
You cannot load a configuration file while the app is running in a pod. However, you can utilize a custom controller for config map change detection. Restart the pod & app so the configuration changes can be picked up.
Even though Kubernetes has a great collection of resources, they are still not enough to fulfill all the different kinds of requirements. For this, you can use the custom resource, define the requirements, write the controller, design ConfigWatch, etc. That’s how the operator pattern i.e., a controller works.
- Service Mesh
It’s a configurable infrastructure layer for microservices applications that improves communication between service instances. Further, it provides service discovery, encryption, load balancing, authentication & authorization, along with the support for the circuit-breaker pattern, and other capabilities.
It’s a layer on Kubernetes that provides serverless capabilities involving request-reply interactions and event-driven interactions.
It’s a toolkit just like sidecar and provides a set of capabilities that include networking. It includes connectors to cloud APIs, multiple systems, and capabilities to publish/subscribe messaging.
Exciting developments will continue to happen in Kubernetes and it will continue to shape futures of business architectures. This is the reason for the huge demand for Docker and Kubernetes around the world as organizations worldwide are integrating these two major platforms for containers & microservices.
Learn Kubernetes online for a secure career
Get certified in Kubernetes and improve your future career prospects better.
Enroll in Cognixia’s Docker and Kubernetes certification course & upskill yourself. Make your way towards success & a better future, experience hands-on, live, interactive, instructor-led online sessions with this Kubernetes training. In this highly competitive world, Cognixia is here to provide you with an immersive online learning experience to help you enhance your skillset and knowledge with engaging online training enabling you to add immense value to your organization.
This Kubernetes online training will cover basic-to-advanced level concepts of Docker and Kubernetes. This certification course offers you an opportunity to take advantage of connecting with industry’s expert trainers, develop your competencies to meet industry & organizational standards, as well as learn about real-world best practices.
This Docker & Kubernetes Certification covers the following –
- Essentials of Docker
- Overview of Kubernetes
- Kubernetes Cluster
- Overview Kubernetes Pod
- Kubernetes Client
- Creating and modifying ConfigMaps and Secrets
- Replication Controller and Replica Set
- Exploring the Kubernetes API and Key Metadata
- Managing Specialized Workloads
- Volumes and configuration Data
- Monitoring and logging
- Maintenance and troubleshooting
- The ecosystem
Prerequisites for Docker & Kubernetes Certification
- Basic command knowledge of Linux
- Basic understanding of DevOps
- Basic knowledge of YAML programming language (beneficial, not mandatory)