Sedai Blog

Workload Rightsizing in Amazon EKS: Steps, Tools & Savings

Step-by-step rightsizing for Amazon EKS: Profile resource usage, tune pod requests/limits, use HPA/VPA/Cluster Autoscaler and apply recommendations.

Optimizing Cloud Storage: Unlocking Cost & Performance Gains with Autonomous Optimization

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.

Azure Kubernetes Service (AKS) Cost Optimization Guide 2026

Learn how to optimise AKS costs in 2026. Understand pricing models, rightsizing, autoscaling and cost-tools to reduce spend on Azure Kubernetes Service.

27 Best Kubernetes Management Tools for 2026

Discover the best Kubernetes management tools for 2026–27 to manage clusters, improve visibility, and scale operations with confidence. Read now!

Kubernetes Cluster Scaling Challenges

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.

Kubernetes Autoscaling: How It Works and Best Practices

Learn how Kubernetes autoscaling works, including HPA and VPA, key use cases, and best practices to scale workloads efficiently.

Effective Strategies for OpenAI Cost Management in 2026

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.

Best Practices for Optimizing Google Persistent Disk Costs in 2026

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.

Top Practices for Optimizing Google Cloud Compute Costs in 2026

In 2026, cloud cost optimization remains a top priority for businesses as they navigate an increasingly complex landscape of cloud services and pricing models. Enterprises must adopt effective strategies to manage their Google Cloud expenses while ensuring optimal performance and resource utilization.As cloud computing continues to evolve, organizations face the challenge of balancing innovation with cost-efficiency. To stay competitive, businesses must leverage the latest tools and best practices to optimize their Google Cloud infrastructure and maximize their return on investment.Achieving cost optimization in Google Cloud requires a proactive approach that involves understanding pricing models, implementing automated management tools, and continuously monitoring and adjusting resources based on workload requirements. By following best practices and leveraging advanced technologies, organizations can significantly reduce their cloud expenses without compromising on performance or availability.