K8s Market Trends: Use Cases, Benefits, & Solving Operational Challenges With A Cloud Native Platform Engineering / IDP.
Kubernetes is turning 10 years old in 2024. Happy birthday, K8s!
According to CNCF, Kubernetes is the most widely used container orchestration platform in existence.
Initially created by Google engineers in 2014, it became the Cloud Native Computing Foundation’s first hosted project in March 2016.
It is the second largest open source project in the world after Linux and is the primary container orchestration tool for 71% of Fortune 100 companies.
Looking ahead, says the CNCF, Kubernetes adoption shows no signs of slowing down – according to Gartner’s “The CTO’s Guide to Containers and Kubernetes” by 2027, more than 90% of global organizations will be running containerized applications in production.
Has Kubernetes become boring?
According to the SiliconANGLE & theCUBE speakers, yes,"Kubernetes is becoming boring!”
Soon, they say, we will not be talking about it anymore, just like we don't talk about Linux.
The term “boring” has a positive connotation and reflects Kubernetes’ stability and maturity as a platform for container orchestration and cloud native development.
Enterprises are adopting Kubernetes to build and run scalable applications in modern and dynamic environments.
The recent Veeam report, says that Kubernetes drives innovation, from hybrid/multi-cloud, to new cloud native apps and modernizing existing apps.
(See Kubernetes use cases below):
Kubernetes Requires a Steep Learning Curve to Reach Its Full Potential.
Kubernetes flexibility and challenges
Kubernetes has over 5.6 million developers around the globe. With these numbers, you may be tempted to think that Kubernetes is a simple technology. But it isn't.
Results from the Spectro Cloud sponsored research, The New Frontiers of Kubernetes 2023 State of Production Kubernetes, emphasize that:
Kubernetes challenges are often a direct result of the flexibility that users appreciate.
Quote from Spectro Cloud sponsored research
This report also shows that:
Kubernetes complexity has consequences
98% face challenges using Kubernetes in production
98% have identified opportunities to improve operational efficiency
Kubernetes adopters are tackling legacy VM workloads
85% have existing VM-based applications that are migrating to Kubernetes
86% want to unify containerized and VM workloads to a single infrastructure platform
Kubernetes gains traction for edge computing
93% are planning to use Kubernetes on edge computing infrastructures
Kubernetes pain points
Many of the 5.6 million developers using Kubernetes, are facing growing complexity and cognitive overload, which translates into project failures, delayed releases, difficulty in keeping up with updates and upgrades, etc.
(See the key Kubernetes pain points from the Veeam report)
Kubernetes Pain Points (Veeam report)
Like the impossible 'chicken and egg' situation, there is something else making matters worse for many enterprises.
It is the need to constantly keep up with Kubernetes upgrades and app dependencies, which requires them to comply with cloud-mandated Kubernetes version support policy – or face the costly risks associated with non-compliance.
Enterprise organizations tolerate all this complexity (and the delays and costs that come with it) since they see no alternative. But what if there was an easier way? In fact, there is.
The Missing Piece for Kubernetes Total Success: Platform Engineering/Internal Developer Platform (IDP)
Platform engineering/IDP
What is platform engineering/IDP?
As best stated by Luca Galante, head of product at Humanitec, and the Platform Engineering Community:
Platform engineering is the discipline of designing and building toolchains and workflows that enable self-service capabilities for software engineering organizations in the cloud-native era. Platform engineers provide an integrated product most often referred to as an “Internal Developer Platform” covering the operational necessities of the entire lifecycle of an application.
Platform Engineering Framework/IDP for Kubernetes Operations
Platform engineering has emerged as an approach to build, manage, and maintain an IDP to enhance developer/DevOps experience, and allow them to focus on their core expertise.
It's meant to hide the complexity of navigating and operating the needed set of cloud native tools and processes, such as Kubernetes, GitOps, multi-cluster networking, IaC, CI/CD pipelines for containers, etc.
It's all about consistency, standardization (tools, processes), and documented best-practices.
In fact, platform engineering framework/IDP is the missing piece for Kubernetes success.
The adage "a picture is worth a thousands words" is highly relevant here:
Kubernetes application operations platform (By Nethopper)
In his ebook (What Happened to Platform Engineering), Dan Donahue points out that “Platform engineering is not new. Platform engineering simply moved from software engineering to DevOps/IT. Therein lies the awakening of DevOps/IT folks to platform engineering, and the challenge it presents for them.
With that said, enterprise organizations are now looking to platform engineering as a way to simplify their Kubernetes operations and reduce the need to recruit, hire, and retain an army of Kubernetes and cloud native experts. They see platform engineering/IDP as a way to boost existing teams' efficiency through automation, reduction of cognitive load, and standards.
According to Chris Munford, well designed IDPs follow a Platform as a Product approach, where a platform team builds, maintains and continuously improves the IDP, following product management principles and best practices.
He also says that:
A well designed Internal Developer Platform (IDP) reduces cognitive load.
So, what's the best way to implement a well designed platform engineering/IDP? Do you build, buy or simply use it?
Let's ponder on this:
1. Building a custom IDP (in-house) requires recruiting, hiring and retaining a lot of hard-to-find Kubernetes and cloud native experts to build the foundational framework - and then maintain/upgrade it, going forward.
Building "it" in house requires intense expertise and experience to-do-it-right-the-first time-around. Can you afford to spend another 2 years trying-it-again?
Consider also the unintended consequences of business outcomes when you build-it-wrong or not fast enough.
Prepare for using Kubernetes in-production (day-2), and plan for making it easy to troubleshoot and remediate problems.
2. Buying a commercial platform engineering/IDP solution off-the-shelf still requires the enterprise to hire and retain experts to operate and customize it.
The solution may lack an easy way to deal with customizations. So your internal teams need to be prepared to build and support your customizations, which may (or may not) incur a steep learning curve.
Be sure to add corporate guidance/guardrails to avoid increase in both spend and unwanted and unexpected costs in cloud services.
3. Using a platform engineering framework/IDP that is cloud native and comes with a pre-integrated foundational stack of OSS/cloud native tools and best-practices, like GitOps and multi-cluster networking.
A ready-to-use solution can provide you with the jumpstart you need to help you avoid wasting 2+ years reinventing the wheel.
Your team gets the enterprise support they need to easily extend the solution. Yes, ease of extendability is a must-have.
Consider strategic initiatives, such as AI, multi-cluster/cloud. It will dictate the need for GitOps and multi-cluster/cloud networking.
Learn more about KAOPS powered by Nethopper. It fits well in this category with its friendly UI, unified dashboard, and integrated stack of open source/cloud native software, out of the box. With KAOPS, your Junior developers/engineers can, for instance, start optimizing your support for cloud-mandated Kubernetes upgrades and app dependencies. It's that simple.
Nethopper KAOPS Platform Engineering Framework (Layer-3) Helps You Control, Manage and Upgrade Any (Layer-2) Kubernetes Clusters, in Any (Layer-1) Private/Public Cloud.
Kubernetes: The Road Ahead
The sentiment among industry professionals, according to theCUBE speakers, suggests that there is still work to be done in simplifying and unifying IT environments.
The perception is that the Kubernetes stack is too complex, and there is a need for further simplification to address this challenge.
This indicates an ongoing effort to streamline the technology landscape and make it more accessible and manageable for organizations.
The goal of platform engineering framework/IDP is to streamline the application delivery/deployment process in a way that reduces or eliminates infrastructure concerns - and accelerates time to innovation/revenue.
In this brave new world of AI (which is not addressed here), enterprise platform and DevOps teams need to get their Kubernetes management and operations right, because AI innovation is knocking at the door.
Here is a glimpse of a use case by GigaOm's Chester Conforte:
"The benefits of using Kubernetes at the edge include not only improved business agility but also the ability to rapidly deploy and scale applications in response to changing demands.
GigaOm says that the AI-enabled edge is a prime example of how edge Kubernetes can be the toolchain to enable business agility from development to staging to production all the way out to remote locations.
In sum, Kubernetes may be getting "boring," but platform engineering/IDP is hot. It is the missing piece capable of helping enterprise organizations realize the full potential of Kubernetes now, and beyond.
