
Tokenmaxxing Is Ending. The Era of AI Tokenomics Has Begun
Token consumption was never the right metric. Here's why enterprise AI budgets are exploding and what to measure instead.
Sedai now optimizes AI agents!
Read the newsA technology company achieved a 25% cost saving across 1,400 Kubernetes services with Sedai's autonomous optimization technology by rightsizing Dev/Test environments. AI-powered autonomous optimization optimized Kubernetes requests and limits in Kubernetes workloads and optimize instance count and type. An AI driven approach was more effective than manual optimization, especially given the small spend on each individual service. Optimization is a key capability of Sedai's autonomous cloud management platform.
Step-by-step rightsizing for Amazon EKS: Profile resource usage, tune pod requests/limits, use HPA/VPA/Cluster Autoscaler and apply recommendations.
This blog explores cloud storage challenges and how Sedai's autonomous platform optimizes AWS services like S3 by monitoring data access patterns, reducing costs by 30%, and automating storage management for improved efficiency. Learn how Sedai simplifies cloud storage with real-time recommendations and optimizations.
Learn how to optimise AKS costs in 2026. Understand pricing models, rightsizing, autoscaling and cost-tools to reduce spend on Azure Kubernetes Service.
Discover the best Kubernetes management tools for 2026–27 to manage clusters, improve visibility, and scale operations with confidence. Read now!
In the ever-evolving landscape of application deployment, we have come a long way. Once upon a time, our applications found their home on physical servers. Then, as technology advanced, we embraced the realm of virtual machines. But now, in the present day, we have entered a new era where containers have taken the center stage for application deployment. Why did we make this shift? Well, it all boils down to addressing the challenges we encountered in the traditional and virtualized modes of deployment. Containers emerged as a powerful solution, offering us a way to overcome those hurdles and unlock new possibilities for efficient and flexible application deployment.
Learn how Kubernetes autoscaling works, including HPA and VPA, key use cases, and best practices to scale workloads efficiently.
Optimizing OpenAI costs will be crucial for businesses seeking to leverage the power of AI while maintaining financial efficiency. Implementing cost optimization strategies not only helps manage expenses but also ensures that resources are allocated effectively, maximizing the value derived from OpenAI's services.
Google Persistent Disk (PD) is a durable and high-performance block storage solution designed to support a wide range of workloads on Google Cloud Platform (GCP). As organizations increasingly rely on cloud infrastructure to power their applications and services, optimizing persistent disk performance becomes crucial for ensuring optimal efficiency and cost-effectiveness.In the rapidly evolving cloud landscape, staying informed about the latest optimization strategies is essential for businesses looking to maximize the value of their GCP investments. By understanding the nuances of persistent disk types, performance metrics, and best practices, organizations can unlock the full potential of their cloud storage infrastructure.This article explores the key aspects of Google Persistent Disk optimization in 2026, providing actionable insights and recommendations to help businesses achieve their performance and cost objectives. From choosing the right disk type to leveraging advanced features and monitoring techniques, we will delve into the best practices that can drive significant improvements in your GCP storage environment.