Source URL: https://cloud.google.com/blog/products/containers-kubernetes/gke-gets-new-pricing-and-capabilities-on-10th-birthday/
Source: Cloud Blog
Title: Happy birthday, GKE! Let’s celebrate with new features and better pricing
Feedly Summary: “While containers make packaging apps easier, a powerful cluster manager and orchestration system is necessary to bring your workloads to production.”
Ten years ago, these words opened the blog post announcing Google Kubernetes Engine (GKE). The need for a managed Kubernetes platform is as important today as it was then, especially as workloads have evolved to meet increasingly complex demands.
One year before GKE’s arrival, we open-sourced large parts of our internal container management system, Borg, as Kubernetes. This marked the beginning of offering our own platforms to customers, and as we continue to use Kubernetes and GKE to power leading services like Vertex AI, we distill our learnings and best practices into GKE. Innovating and evolving GKE to meet the demands of our global platforms and services means that we deliver a best-in-class platform for our customers.
Enhanced flexibility with updated pricing
After ten years of evolution comes another shift: we are updating GKE to make sure every customer can balance efficiency, performance, and cost as effectively as possible. In September 2025, we’re moving to a single paid tier of GKE that comes with more features, and that lets you add features as needed. Now, every customer can take advantage of multi-cluster management features like Fleets, Teams, Config Management, and Policy Controller — all available with GKE Standard at no additional cost.
Flexibility and versatility are always in demand. The new GKE pricing structure provides à la carte access to additional features to meet the specific needs of all of your clusters. We want you to direct your resources toward the most impactful work at all times, and are confident that a single GKE pricing tier will help you manage your workloads — and your budgets — more effectively.
Optimized compute with Autopilot for every cluster
When we launched GKE Autopilot four years ago, we made Kubernetes accessible to every organization — no Kubernetes expertise required. More recently, we rolled out a new container-optimized compute platform, which delivers unique efficiency and performance benefits, ensuring you get the most out of your workload’s allocated resources, so you can serve more traffic with the same capacity, or existing traffic with fewer resources.
Now, we’re making Autopilot available for every cluster, including existing GKE Standard clusters, on an ad hoc, and per-workload basis. Soon, you’ll be able to turn on Autopilot (and off) in any existing Standard cluster to take advantage of fully managed Kubernetes with better performance, at the best price.
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Innovations for customer success
The technological landscape shifts quickly. A few years ago, organizations were thinking about stateless microservices; today, the focus is on running complex AI workloads. Throughout, we’re always adapting GKE to meet the needs of innovative companies for new scenarios.
We’re proud of the many incredible products and services built on GKE by customers ranging from startups, to enterprises, to AI companies. AI-powered advertising provider Moloco trains and runs its models with TPUs running on GKE. For nearly a decade, Signify has leveraged GKE as the foundation for its Philips Hue smart lighting platform worldwide. And AI unicorn Anthropic depends on GKE to deliver the scale they need to train and serve their models.
“GKE’s new support for larger clusters provides the scale we need to accelerate our pace of AI innovation." – James Bradbury, Head of Compute, Anthropic
Foundations for consistent evolution
The AI era has just begun, and we’ve been pushing GKE to meet tomorrow’s workload demands today. With customer insights and Google’s best practices baked in, GKE is the ideal platform for developing and deploying AI at scale.
Thank you to our community, customers, and partners who have been on the GKE journey with us. Celebrate a decade of GKE with us by joining the GKE Turns 10 Hackathon and reading the 10 years of GKE ebook. The future is revealing itself every day, and GKE is ready for wherever AI takes us next.
AI Summary and Description: Yes
Summary: The text discusses the evolution and current features of Google Kubernetes Engine (GKE), emphasizing its significance in managing complex workloads, especially those related to AI. With updated pricing structures and features like GKE Autopilot, the platform is positioned as a critical tool for businesses needing flexibility and optimized resources, underscoring its relevance in cloud computing and infrastructure security.
Detailed Description:
The provided text outlines key developments regarding Google Kubernetes Engine (GKE) over its ten-year history and its utility for managing containerized applications in cloud environments. Here are the major points discussed:
– **Historical Context**:
– The inception of GKE was marked ten years ago, pinpointing the necessity for robust orchestration systems to handle growing application complexities.
– GKE was built on learnings from Google’s internal container management tool, Borg, underscoring its foundational significance for developers and enterprises.
– **Recent Enhancements**:
– GKE is evolving to meet modern demands, indicating its adaptability and relevance in fast-changing tech landscapes.
– The update introduces a single paid tier model that encompasses various essential features such as multi-cluster management and policy enforcement, improving overall cost efficiency for customers.
– **Autopilot Feature Expansion**:
– GKE Autopilot, which simplifies Kubernetes management, is now available for all cluster types, enabling organizations without Kubernetes expertise to leverage the platform effectively.
– This feature enhances the performance and resource efficiency of applications, allowing organizations to maximize their resource allocations.
– **Focus on AI and Innovation**:
– The text highlights the increasing relevance of GKE in supporting complex AI workloads, citing examples from companies like Moloco and Anthropic that successfully deploy their AI initiatives using GKE.
– Google aims to make GKE the go-to platform for developing and deploying AI applications at scale, underlining the platform’s significance in the AI domain.
– **Community and Future Outlook**:
– The commitment to evolve with customer demands and the rapid changes in technology assures businesses that GKE will continue to innovate.
– The text ends on a celebratory note, inviting engagement through a hackathon and encouraging exploration of the platform’s advancements.
This analysis showcases GKE’s critical role in cloud computing security and AI workload management, making it particularly interesting for professionals focused on infrastructure security and compliance within the domain of AI and cloud services.