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Four Pitfalls To Avoid To Reap The Benefits Of Kubernetes And AI 

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The COVID-19 global pandemic accelerated the pace of digital transformation and altered the way companies do business via the Internet and cloud. Many companies accelerated the digitization of their operations by three to four years. This rapid pace of digital transformation is still being seen today, as 60% of senior executives say they believe that digital transformation will be critical for business growth this year.

As companies continue to prioritize the importance of digital transformation, the race to gain a competitive edge through infrastructure modernization and advanced technologies has heightened. Organizations are implementing cloud-native and Kubernetes infrastructures to achieve greater agility, speed to market, and innovative customer experiences. Artificial intelligence (AI), machine learning (ML), fast data pipelines, and edge computing are among the technologies that are unleashing further innovation and performance gains.

As these technologies continue to mature, implementing next-generation technology like AI and ML will no longer be seen as a nicety, but as a necessity to stay competitive. In recognition of this fact, analysts predict that by 2025 the global AI market will reach almost $60 billion. As Forrester Research principal analyst Lee Sustar points out, the cloud, Kubernetes, and AI are mutually supportive technologies whose maturation and adoption are intertwined.

Kubernetes and AI a Perfect Match

Kubernetes provides an ideal foundation for managing the many components of an AI/ML pipeline across disparate infrastructures. Organizations that can learn how to adopt cloud-native and AI technologies will be able to build their next-generation products much faster and sustain innovation over time.

We often talk only about Kubernetes, but the reality is you need dozens of other open-source pieces around Kubernetes to have a production-ready, enterprise-grade solution. Although Kubernetes is a complex technology that offers many challenges, the right mix of automation can simplify the deployment and management of Kubernetes and AI at enterprise scale.

To avoid some of the more severe problems, let’s look at key areas in which organizations should devote particular attention when deploying a Kubernetes environment.

Backup and Recovery

One of the strengths of Kubernetes is its ability to abstract away infrastructure, and provide portability across disparate environments. With the right Kubernetes configuration, organizations can fail over quickly and automatically, including from one cloud service to another, in the event of a cloud service outage, cyber attack, internal problem, or other disaster.

Running smoothly and scaling effortlessly in Day 2 production environments is the ultimate goal for modern cloud-native applications. It is this phase of the development lifecycle in which the demand for application stability, security, and resilience becomes critical.

Having a Kubernetes disaster recovery plan and proper failover configuration in place not only helps expedite the shift to Day 2 operations but also gives organizations the confidence that their data and mission-critical applications will remain fully operational in the event of a disruption. The self-healing capability of Kubernetes is one of its greatest features, and the time spent configuring your system to ensure efficient disaster recovery will pay dividends in minimizing risk and maintaining business continuity.

New Security Modes to Master

Securing Kubernetes can be a major challenge, especially when dealing with the differences involved in managing a containerized cloud-native architecture versus a legacy environment. Although the distributed nature of Kubernetes presents novel challenges that must be addressed, the emergence of security practices and technologies like zero trust, air-gapped deployments, and service mesh solutions are enabling organizations to meet the challenges.

Likewise, new technologies, techniques, and best practices are being developed, shared, and built into new solutions. The NSA/CISA Kubernetes Hardening Guide, for example, provides a valuable blueprint for securing a Kubernetes environment.

As the NSA/CISA guide points out, while Kubernetes presents a number of unique security challenges, a Kubernetes virtualized infrastructure “can provide several flexibility and security benefits compared to traditional, monolithic software platforms.”

Likewise, the “four C’s” of cloud-native Kubernetes security describe the four main levels of security on which organizations should focus when securing a Kubernetes environment:

  • Code: Security measures that protect the code, such as vulnerability scanners and secure coding practices.
  • Containers: Security measures at the container level, such as restricting access to network ports and encrypting data in transit.
  • Clusters: Security measures at the cluster level, such as defining network security policies and hardening all master nodes.
  • Cloud, or enterprise data centers: Security measures that protect infrastructure. This is usually implemented by a cloud provider or on-premise.

Kubernetes is continually receiving new features and security updates, which is why it is good practice to keep your Kubernetes version up to date to optimize security and performance.

CI/CD Stumbling Blocks

The key to business agility is DevOps agility. Among the benefits Kubernetes offers organizations is the ability to harness the advantages of continuous integration and continuous delivery (CI/CD) for easier and faster app development and revisions, which translates into agility and speed to market. Kubernetes management capability is being elevated through new technologies like Cluster API (CAPI) and FluxCD, which give DevOps teams greater power and control in the form of GitOps.

CI/CD helps to automate the software delivery process by running continuous tests and more efficiently deploying the best version of an application. Although enabling the development productivity of CI/CD is one of the biggest benefits of Kubernetes, one of the biggest challenges is deploying applications without degrading service quality and performance. Many teams run into deployment issues because of inadequate testing and configurations and environments that are not well-defined or maintained.

Declarative APIs and GitOps reduce and eliminate these problems, which is why “declarative APIs + GitOps = Kubernetes done right.” Deploying a Kubernetes platform architected around CAPI with built-in GitOps workflow will help organizations gain all the advantages of CI/CD while avoiding the pitfalls.

Plan for Current and Future Demands

Organizations are adopting Kubernetes en masse because it can simplify workload deployment, portability, and ways of working for time-pressed developers. It’s the pathway to modernizing traditional applications and enabling rapid hybrid- and multi-cloud development of new cloud-native applications.

Kubernetes, the cloud, and AI are the technologies that ultimately will power the majority of digital products and services we use. That is why it is important for organizations to keep pace with cloud-native innovation and acquire the ability to leverage Kubernetes and AI successfully. The organizations that do so will be able to build highly differentiated and smarter next-gen products that will give them a competitive edge. Organizations that fail to keep pace risk falling dangerously behind.

To enjoy the full benefits of the cloud and Kubernetes while avoiding the pitfalls described above, it is important to plan and deploy carefully. To be on the winning side of the smart cloud-native revolution, companies should establish a solid Kubernetes foundation with the ability to accommodate not only AI and ML, but every new round of disruptive technologies that are sure to emerge.


Tobi Knaup, CEO and co-founder of D2iQ

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