As more and more aspects of human life continue to move online, the need to expand the reach of the Internet increases exponentially. This trend started many years ago (we can say during the dotcom boom) and has seen many iterations of technological progress.
Launched in 2002 as the first public cloud offering, AWS opened the door for companies to outsource their IT operations and scale resource consumption up and down as needed. Virtual machines began to strip application software away from physical hardware, and soon the need for new modes of deployment emerged.
Microservices are collections of isolated, unconnected services that can be maintained and configured independently of their surrounding environment. They can be deployed at scale when packaged into containers (commodified in 2014 by Docker), which have become the building blocks for a new, distributed generation of infrastructure.
Various technologies, such as Rancher, Docker Swarm, and Mesos, competed to take the lead in coordinating containers. But in the end, it was Kubernetes (which was opened by Google in 2014) that became the champion of containerized microservices.
While companies have clearly seen the benefits of Kubernetes, its innate complexity and steep learning curve have always been barriers to entry. Small businesses lack the experience and operational resources to successfully run the tech giants. Larger companies have struggled to integrate cloud-native tools and processes into legacy infrastructures.
grappling with the complexity of Kubernetes
Over the years, many solutions have appeared in the industry with the goal of helping organizations adopt Kubernetes and improve container orchestration. Rancher, OpenShift, and public cloud managed services such as Azure Kubernetes Service, Elastic Kubernetes Service, and Google Kubernetes Engine are some examples. These solutions have greatly simplified deployment and management of Kubernetes clusters, accelerating the transition to cloud-native applications while making them more flexible and scalable.
For this reason, Kubernetes has achieved great adoption. In 2021, Traefik . Laboratories Survey Over 1,000 IT professionals report their use of technology. More than 70% of respondents reported using Kubernetes in a business project. However, companies that have just overcome the challenges of adopting container technologies are now facing hurdles in expanding their reach.
As Kubernetes continues to be adopted, new challenges are beginning to emerge. Companies are now supporting larger and larger Kubernetes clusters to meet the needs of a growing number of containerized applications. However, more collections means more components to manage and keep up to date with updates. Problems that can be solved relatively directly within a Kubernetes deployment process are one that is significantly more difficult in large, multi-cluster environments. The complexity of Kubernetes vehicles as they scale. However, multi-group coordination is inevitably the next frontier that engineers must address.
Multi-cluster Kubernetes requirements
Developers need the right tools to manage multi-cluster challenges, from contextual alerting to new deployment strategies and beyond. Let’s break it down:
- the Union Tools provide mechanisms for expressing which groups a configuration has been managed and what that configuration should look like. A single set of APIs in a host cluster coordinate the configuration of multiple Kubernetes clusters across distributed environments. Unified cloud technologies support the interconnection of two or more geographically separated computing clouds, making complex multi-cluster use cases easier for engineering teams to handle.
- It is very complicated to maintain multiple groups and make them work together as a single unit. Connection makes it possible to do so. The right tools can help you handle inter-cluster threading, control routing to clusters, load balancing across geographically distributed pools (with Global Server Load Balancing, or GSLB), and manage application updates across multiple clusters.
- protection Challenges accumulate in complex and distributed IT environments but can be resolved when cloud-native security tools and processes are adopted. This means asking new questions. How do you deal with security in environments of mistrust? How do you manage end-to-end encryption for communications? How do you control access to your apps? How do you maintain TLS certificate management in distributed infrastructures? When security is integrated into the cluster, distributed applications become more secure.
- Note It allows you to quickly see the big picture of your distributed infrastructure, so you can diagnose problems quickly and easily. Grafana and Prometheus are examples of tools widely used to this end. As you expand the number of groups posted, the possibility of observation and contextual alert become more important because there are more ways things can go wrong. Having the right tools to enable developers to know exactly where issues are will not only keep apps running smoothly, but it cuts down on big guesswork and saves valuable time.
The future of multi-cluster Kubernetes
Ensuring groups, services, and network traffic work together seamlessly in the cloud-native world is a major challenge. Kubernetes has won the regulation war and is still widely adopted by organizations around the world, but the technology is also naturally maturing. With this maturity come new problems and new challenges for multi-cluster deployments.
The development, engineering, and operations teams (of all skill levels) that build and run applications on Kubernetes need easier ways to achieve visibility, scalability, and security for their clusters and networks. When looking for tools to manage standard microservice architectures, developers should prioritize solutions that provide capabilities such as real-time monitoring capability, ready contextual alerting, geo-aware content delivery, and built-in service interlocking.
Challenges of multi-cluster coordination are becoming increasingly prevalent, but by adapting to the cloud-native world with the right tools, development and operations teams will be able to discuss the complexity of multi-cluster Kubernetes and see the huge benefits that come with Kubernetes like never before.
Emile Fuege is the founder and CEO of Traffic coefficient.
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