Cloud Native or Cloud Chaos?
Building Your Own Cloud with CNCF Tools
The term "cloud-native" has become a buzzword for modern infrastructure, often associated with flexibility, scalability, innovation, and simply being “cool.” The CNCF (Cloud Native Computing Foundation) offers a plethora of tools (if you don’t believe me, check out the CNCF landscape) designed to make this vision a reality, primarily built around Kubernetes as the core orchestration platform.
On the surface, this ecosystem promises a modular, best-of-breed approach to building and running cloud applications, with an opportunity to achieve more control and cost savings versus a public cloud provider. But dig deeper, and you’ll realize that
Choosing to go "cloud native" with CNCF tools often means you're embarking on a monumental task: building your own cloud infrastructure from scratch.
Before you leap into this brave new world, consider whether this level of control and customization is truly worth the effort—or if it’s a distraction from more impactful business priorities.
The Allure of the CNCF Ecosystem
The CNCF Landscape showcases an impressive and perhaps overwhelming array of tools spanning everything from logging and monitoring to networking, service meshes, and CI/CD pipelines. The flexibility to select precisely the right tool for your needs is empowering. Kubernetes itself is a powerful platform for managing containerized workloads, providing the foundational layer for a cloud-native environment.
But here’s the catch: while Kubernetes solves some problems, it introduces others. It’s not a fully managed service—it’s a framework. And the tools surrounding Kubernetes often require deep expertise, customization, and significant integration work.
Indeed, while an engineer with intermediate knowledge might be able to get a basic Kubernetes cluster up and running relatively quickly, that’s just the starting line. Turning that cluster into something you can confidently run in production involves addressing a host of challenges, including:
Security: Configuring network policies, managing secrets, and ensuring the cluster is hardened against attacks.
Observability: Setting up tools like Prometheus, Grafana, or OpenTelemetry to monitor logs, metrics, and traces effectively.
Scalability: Implementing auto-scaling for workloads and the cluster itself to handle varying loads.
Disaster Recovery: Planning for backup and restore, and ensuring high availability in case of node or region failures.
CI/CD Pipelines: Integrating continuous deployment processes that work seamlessly with Kubernetes.
Networking: Managing ingress and egress traffic, service meshes, and DNS configurations.
Cost Management: Optimizing resource usage to control costs, which can quickly spiral out of control without proper oversight.
Compliance: Ensuring the system adheres to organizational or industry-specific compliance requirements (e.g., SOC 2, GDPR).
Each of these layers requires specialized knowledge, tooling, and often a significant amount of trial and error to get right. Kubernetes is powerful, but it assumes a high level of responsibility on the user’s part to make it truly production-ready.
In other words, by choosing the CNCF route, you’re effectively creating your own cloud environment. This comes with all the challenges of building and maintaining infrastructure: scalability, reliability, security, and more. If this isn’t your core business, you need to ask yourself, is this effort really worth it?
The True Cost of Building Your Own Cloud
When adopting cloud-native principles via CNCF tools, you’ll face some other hard truths on the business, management, and leadership sides:
Engineering Overhead: Building a custom cloud-native stack demands highly skilled engineers, ideally those who have done it before. These are hard-to-find resources, and they don’t come cheap. Instead of focusing on delivering business-critical features, your engineers will spend time configuring, integrating, and maintaining the infrastructure stack.
Tool Proliferation and Fragmentation: Without strong governance, the vast CNCF Landscape becomes a double-edged sword. Allowing every team to choose its own tools for logging, monitoring, or service meshes creates chaos. A few years down the road, your organization might find itself using five different monitoring solutions, three competing CI/CD pipelines, and a service mesh no one remembers how to configure.
Hidden Costs: While the open-source nature of CNCF tools may seem cost-effective at first glance, the hidden costs of operational complexity, training, and troubleshooting can quickly outweigh any perceived savings.
Opportunity Costs: Every hour spent on platform engineering is an hour not spent on delivering features or innovations that directly impact your bottom line. If your core business isn’t infrastructure, consider whether this is the best use of your engineers’ time.
If You Go Cloud Native, Platform Engineering is Non-Negotiable
If you evaluate the trade-offs and go the CNCF cloud-native route, avoid falling into the trap of allowing every team to select their own tooling. This approach can lead to a fragmented ecosystem that undermines security, maintainability, and efficiency.
For instance, consider the critical practice of Docker image signing to ensure the authenticity and integrity of container images. One team might choose Cosign, an open-source tool that integrates seamlessly with Kubernetes and supports keyless signing. Another might prefer Notary v2, which introduces different operational requirements and integration workflows. Without a standardized approach, organizations can end up with inconsistent implementations, increased attack surfaces, and operational headaches when enforcing a unified security posture. Gaps in knowledge transfer between teams can lead to vulnerabilities, as engineers struggle to manage and audit multiple tools effectively.
A robust platform engineering team eliminates this chaos by establishing clear guidelines, curating a standardized set of tools, and ensuring best practices are followed organization-wide.
Platform engineering acts as the backbone of a successful CNCF-based cloud-native strategy. This team should:
Select Tools with a Long-Term Vision: Choose a cohesive, standardized stack of tools that integrate well and align with your organization’s needs.
Promote Best Practices: Establish clear guidelines for using the selected tools effectively and ensure they’re well-documented.
Provide a Center of Excellence: Be the go-to experts for onboarding, training, and troubleshooting, reducing the operational burden on individual teams.
Continuously Evolve: Stay updated on the CNCF Landscape to evaluate whether your stack should evolve as the ecosystem matures.
Without this centralization, you risk an "anything goes" approach that leads to fragmentation, inefficiency, and ultimately failure.
The Bottom Line
The cloud-native approach isn’t inherently bad—it offers unparalleled flexibility and control. But the level of effort required to make it successful is often underestimated. Organizations must weigh the benefits of control and customization against the costs of complexity and the potential distractions from business priorities.
Building your own cloud using CNCF tools is not for the faint of heart. It requires skilled engineers, strong governance, and a platform engineering team to keep chaos at bay. But for many organizations, the question remains:
Why spend so much effort on infrastructure when that energy could be directed toward building features that directly drive revenue and growth?
If your organization is navigating the challenges of cloud-native adoption or deciding between CNCF tools and managed cloud services, let’s talk. With years of experience in cloud strategies and platform engineering, I can provide advice to help you make informed decisions and build an infrastructure that works for your business—not the other way around. Reach out to discuss further!
