Tech Predictions for 2022 and Beyond
Top 10 must-know Kubernetes design patterns
Here are the must-know top 10 design patterns for beginners synthesized from the Kubernetes Patterns book. Getting familiar with these patterns will help you understand foundational Kubernetes concepts, which in turn will help you in discussions and when designing Kubernetes-based applications.
There are many important concepts in Kubernetes, but these are the most important ones to start with:
Source: Kubernetes Patterns
To help you understand, the patterns are organized into a few categories below, inspired by the Gang of Four’s design patterns.
These patterns represent the principles and best practices that containerized applications must comply with in order to become good cloud-native citizens. Regardless of the application’s nature, you should aim to follow these guidelines. Adhering to these principles will help ensure that your applications are suitable for automation on Kubernetes.
Health Probe dictates that every container should implement specific APIs to help the platform observe and manage the application in the healthiest way possible. To be fully automatable, a cloud-native application must be highly observable by allowing its state to be inferred so that Kubernetes can detect whether the application is up and ready to serve requests. These observations influence the life-cycle management of Pods and the way traffic is routed to the application.
Predictable Demands explains why every container should declare its resource profile and stay confined to the indicated resource requirements. The foundation of successful application deployment, management, and coexistence on a shared cloud environment is dependent on identifying and declaring the application’s resource requirements and runtime dependencies. This pattern describes how you should declare application requirements, whether they are hard runtime dependencies or resource requirements. Declaring your requirements is essential for Kubernetes to find the right place for your application within the cluster.
Automated Placement explains how to influence workload distribution in a multi-node cluster. Placement is the core function of the Kubernetes scheduler for assigning new Pods to nodes satisfying container resource requests and honoring scheduling policies. This pattern describes the principles of Kubernetes’ scheduling algorithm and the way to influence the placement decisions from the outside.
Having good cloud-native containers is the first step, but not enough. Reusing containers and combining them into Pods to achieve the desired outcome is the next step. The patterns in this category are focused on structuring and organizing containers in a Pod to satisfy different use cases. The forces that affect containers in Pods result in these patterns.
Init Container introduces a separate life cycle for initialization-related tasks and the main application containers. Init Containers enable separation of concerns by providing a separate life cycle for initialization-related tasks distinct from the main application containers. This pattern introduces a fundamental Kubernetes concept that is used in many other patterns when initialization logic is required.
Sidecar describes how to extend and enhance the functionality of a pre-existing container without changing it. This pattern is one of the fundamental container patterns that allows single-purpose containers to cooperate closely together.
These patterns describe the life-cycle guarantees of the Pods ensured by the managing platform. Depending on the type of workload, a Pod might run until completion as a batch job or be scheduled to run periodically. It might run as a daemon service or singleton. Picking the right life-cycle management primitive will help you run a Pod with the desired guarantees.
Batch Job describes how to run an isolated, atomic unit of work until completion. This pattern is suited for managing isolated atomic units of work in a distributed environment.
Stateful Service describes how to create and manage distributed stateful applications with Kubernetes. Such applications require features such as persistent identity, networking, storage, and ordinality. The StatefulSet primitive provides these building blocks with strong guarantees ideal for the management of stateful applications.
Service Discovery explains how clients can access and discover the instances that are providing application services. For this purpose, Kubernetes provides multiple mechanisms, depending on whether the service consumers and producers are located on or off the cluster.
The patterns in this category are more complex and represent higher-level application management patterns. Some of the patterns here (such as Controller) are timeless, and Kubernetes itself is built on top of them.
Controller is a pattern that actively monitors and maintains a set of Kubernetes resources in a desired state. The heart of Kubernetes itself consists of a fleet of controllers that regularly watch and reconcile the current state of applications with the declared target state. This pattern describes how to leverage this core concept for extending the platform for our own applications.
An Operator is a Controller that uses a CustomResourceDefinitions to encapsulate operational knowledge for a specific application in an algorithmic and automated form. The Operator pattern allows us to extend the Controller pattern for more flexibility and greater expressiveness. There are an increasing number of Operators for Kubernetes, and this pattern is turning into the major form of operating complex distributed systems.
Today, Kubernetes is the most popular container orchestration platform. It is jointly developed and supported by all major software companies and offered as a service by all of the major cloud providers. Kubernetes supports both Linux and Windows systems, plus all major programming languages. This platform can also orchestrate and automate stateless and stateful applications, batch jobs, periodic tasks, and serverless workloads. The patterns described here are the most commonly used ones from a broader set of patterns that come with Kubernetes as shown below.
Kubernetes Patters organized in different categories
Kubernetes is the new application portability layer and the common denominator among everybody on the cloud. If you are a software developer or architect, the odds are that Kubernetes will become part of your life in one form or another. Learning about the Kubernetes patterns described here will change the way you think about this platform. I believe that Kubernetes and the concepts originating from it will become as fundamental as object-oriented programming concepts.
The patterns here are an attempt to create the Gang of Four design patterns, but for container orchestration. Reading this article must not be the end, but the beginning of your Kubernetes journey. Happy kubectl-ing!
Reference:
https://developers.redhat.com/blog/2020/05/11/top-10-must-know-kubernetes-design-patterns/
https://k8spatterns.io/
https://github.com/k8spatterns/examples
GE IIoT Predix links as a reference...
GE IIoT Predix
https://www.ge.com/digital/iiot-platform
Predix
https://www.predix.io/
Predix catalog and services
https://www.predix.io/catalog/services/
GE Predix docs
https://www.ge.com/digital/documentation/predix-platforms/index.html
Thread Connect Integration Platform
https://www.ge.com/digital/documentation/predix-platforms/tcip-overview.html
https://github.com/thread-connect
Apache Nifi
https://nifi.apache.org/
The Internet of Things is an emerging topic of technical, social, and economic significance. Consumer products, durable goods, cars and trucks, industrial and utility components, sensors, and other everyday objects are being combined with Internet connectivity and powerful data analytic capabilities that promise to transform the way we work, live, and play. Projections for the impact of IoT on the Internet and economy are impressive, with some anticipating as many as 100 billion connected IoT devices and a global economic impact of more than $11 trillion by 2025.
At the same time, however, the Internet of Things raises significant challenges that could stand in the way of realizing its potential benefits. Attention-grabbing headlines about the hacking of Internet-connected devices, surveillance concerns, and privacy fears already have captured public attention. Technical challenges remain and new policy, legal and development challenges are emerging.
This overview document is designed to help the Internet Society community navigate the dialogue surrounding the Internet of Things in light of the competing predictions about its promises and perils. The Internet of Things engages a broad set of ideas that are complex and intertwined from different perspectives. Key concepts that serve as a foundation for exploring the opportunities and challenges of IoT include:
Five key IoT issue areas are examined to explore some of the most pressing challenges and questions related to the technology. These include security; privacy; interoperability and standards; legal, regulatory, and rights; and emerging economies and development.
While security considerations are not new in the context of information technology, the attributes of many IoT implementations present new and unique security challenges. Addressing these challenges and ensuring security in IoT products and services must be a fundamental priority.Users need to trust that IoT devices and related data services are secure from vulnerabilities, especially as this technology become more pervasive and integrated into our daily lives. Poorly secured IoT devices and services can serve as potential entry points for cyber attack and expose user data to theft by leaving data streams inadequately protected.
The interconnected nature of IoT devices means that every poorly secured device that is connected online potentially affects the security and resilience of the Internet globally. This challenge is amplified by other considerations like the mass-scale deployment of homogenous IoT devices, the ability of some devices to automatically connect to other devices, and the likelihood of fielding these devices in unsecure environments.
As a matter of principle, developers and users of IoT devices and systems have a collective obligation to ensure they do not expose users and the Internet itself to potential harm. Accordingly, a collaborative approach to security will be needed to develop effective and appropriate solutions to IoT security challenges that are well suited to the scale and complexity of the issues.
The full potential of the Internet of Things depends on strategies that respect individual privacy choices across a broad spectrum of expectations. The data streams and user specificity afforded by IoT devices can unlock incredible and unique value to IoT users, but concerns about privacy and potential harms might hold back full adoption of the Internet of Things. This means that privacy rights and respect for user privacy expectations are integral to ensuring user trust and confidence in the Internet, connected devices, and related services.
Indeed, the Internet of Things is redefining the debate about privacy issues, as many implementations can dramatically change the ways personal data is collected, analyzed, used, and protected. For example, IoT amplifies concerns about the potential for increased surveillance and tracking, difficulty in being able to opt out of certain data collection, and the strength of aggregating IoT data streams to paint detailed digital portraits of users. While these are important challenges, they are not insurmountable. In order to realize the opportunities, strategies will need to be developed to respect individual privacy choices across a broad spectrum of expectations, while still fostering innovation in new technology and services.
A fragmented environment of proprietary IoT technical implementations will inhibit value for users and industry. While full interoperability across products and services is not always feasible or necessary, purchasers may be hesitant to buy IoT products and services if there is integration inflexibility, high ownership complexity, and concern over vendor lock-in.
In addition, poorly designed and configured IoT devices may have negative consequences for the networking resources they connect to and the broader Internet. Appropriate standards, reference models, and best practices also will help curb the proliferation of devices that may act in disrupted ways to the Internet. The use of generic, open, and widely available standards as technical building blocks for IoT devices and services (such as the Internet Protocol) will support greater user benefits, innovation, and economic opportunity.
The use of IoT devices raises many new regulatory and legal questions as well as amplifies existing legal issues around the Internet. The questions are wide in scope, and the rapid rate of change in IoT technology frequently outpaces the ability of the associated policy, legal, and regulatory structures to adapt.
One set of issues surrounds crossborder data flows, which occur when IoT devices collect data about people in one jurisdiction and transmit it to another jurisdiction with different data protection laws for processing. Further, data collected by IoT devices is sometimes susceptible to misuse, potentially causing discriminatory outcomes for some users. Other legal issues with IoT devices include the conflict between law enforcement surveillance and civil rights; data retention and destruction policies; and legal liability for unintended uses, security breaches or privacy lapses.
While the legal and regulatory challenges are broad and complex in scope, adopting the guiding Internet Society principles of promoting a user’s ability to connect, speak, innovate, share, choose, and trust are core considerations for evolving IoT laws and regulations that enable user rights.
The Internet of Things holds significant promise for delivering social and economic benefits to emerging and developing economies. This includes areas such as sustainable agriculture, water quality and use, healthcare, industrialization, and environmental management, among others. As such, IoT holds promise as a tool in achieving the United Nations Sustainable Development Goals.
The broad scope of IoT challenges will not be unique to industrialized countries. Developing regions also will need to respond to realize the potential benefits of IoT. In addition, the unique needs and challenges of implementation in less-developed regions will need to be addressed, including infrastructure readiness, market and investment incentives, technical skill requirements, and policy resources.
The Internet of Things is happening now. It promises to offer a revolutionary, fully connected “smart” world as the relationships between objects, their environment, and people become more tightly intertwined. Yet the issues and challenges associated with IoT need to be considered and addressed in order for the potential benefits for individuals, society, and the economy to be realized.
Ultimately, solutions for maximizing the benefits of the Internet of Things while minimizing the risks will not be found by engaging in a polarized debate that pits the promises of IoT against its possible perils. Rather, it will take informed engagement, dialogue, and collaboration across a range of stakeholders to plot the most effective ways forward.
