Cloud Cost & Performance Optimization

Overcome limitations of multi-tenant Kubernetes with best practices in security, isolation, RBAC, and NetworkPolicies. Click to optimize your strategy now!

Optimize Amazon RDS scaling with vertical and horizontal strategies. Improve performance, cost, and availability for your cloud database needs.

Build a smooth multi-cloud Kubernetes setup. Learn how to scale, secure, and operate clusters across clouds without added complexity.

Improve your cloud spending with Azure cost monitoring. Get expert steps to track usage, avoid cost spikes, and optimize resources.

Learn how to enable autoscaling in GKE. Use simple steps to keep pods responsive, cut resource waste, and handle traffic changes smoothly.

Compare Amazon RDS and Aurora for performance, scalability, and cost. Learn which database service best fits your engineering needs and workload requirements.

Discover Kubernetes autoscaling techniques and best practices. Scale workloads, improve performance, and reduce costs with HPA, VPA, and more.

Learn how to optimize Kubernetes costs and resources. Discover strategies to scale efficiently, reduce waste, and improve overall cluster performance.

Explore the best FinOps tools of 2026 for engineering leaders, designed to automate cloud cost management and reduce operational overhead.

Maximize cost savings with AWS Savings Plans and Reserved Instances in Kubernetes. Learn how to scale effectively while optimizing performance and cost.

Find the 27 Kubernetes management tools engineers rely on. Get a simple breakdown of what each tool solves and how it supports large cluster setups.

Achieve Azure cost optimization with 22 proven strategies. Cut waste, optimize resources, and improve performance across your cloud environment.

Find Azure cost optimization tools that rightsize compute, storage, and databases based on real workload patterns. Reduce waste and improve performance.

Discover 17 cloud optimization strategies for 2026. Save money, scale efficiently, and improve performance with actionable, expert insights.

Discover the top cloud cost optimization tools for 2025, helping engineering leaders automate savings, optimize resources, and reduce cloud waste.

Engineering leaders face millions in wasted cloud spend. Learn how to optimize costs, maintain performance, and manage resources efficiently

Explore cloud automation in 2025 and why autonomous systems are critical for engineering leaders to manage modern cloud environments safely.

Achieve Azure cost optimization with 22 proven strategies. Cut waste, optimize resources, and improve performance across your cloud environment.

Master Amazon S3 bucket storage and functions. Discover smart cost-saving tips and how Sedai’s AI-driven automation keeps your storage efficient and secure.

Learn key cloud data warehouse features and benefits. See how Sedai’s AI automation cuts cloud costs and boosts performance for your data workloads.

Learn how to optimize Google Cloud SQL for performance and cost. Explore best tools and strategies plus Sedai’s AI-driven savings.

Compare Amazon RDS vs Azure SQL across performance, scaling, cost, architecture, and migration paths. Learn which platform fits your workload and engineering roadmap.

Compare AWS Lambda, GCP Cloud Functions, and GCP VMs for performance, cost, and scalability. Learn when serverless or VMs fit your workload best.

Discover the benefits of auto remediation in cybersecurity and IT operations. Learn how platforms like Sedai use automation to improve efficiency, reduce manual workloads, and enhance team productivity.

Discover how Amazon S3 Intelligent-Tiering automatically moves data between storage tiers to cut cloud storage costs and simplify data management.

Master Amazon Elastic Compute Cloud (EC2), choose the right instances, cut cloud costs, enhance performance, and automate reliability at scale.

Explore the top 10 AWS cost optimization tools in 2025 that help engineering teams cut costs, boost efficiency, and optimize cloud resources effectively.

Explore the top multi-cloud management platforms for 2025, with insights on reducing complexity, improving performance, and boosting ROI through automation.

Compare leading cloud storage providers like AWS S3, Azure Blob, and Google Cloud Storage in 2026 and learn how Sedai cuts cost and boosts performance.

Engineers can explore Snowflake’s elastic compute, instant cloning, and multi-cloud support. Learn how to drop infrastructure burdens and focus on analytics.

Engineers shouldn’t have to invest countless hours configuring and managing infrastructure when starting with cloud databases. With Amazon RDS, they can integrate database management seamlessly into their workflow. RDS handles automation and reduces the need for manual adjustments, so engineers can stay.

Choosing the right cloud optimization tool is key to managing costs and performance. This guide covers cost vs. architectural optimization, TCO, automation, and security. It also highlights Sedai’s AI-powered automation for minimizing cloud waste and improving efficiency across AWS, Azure, and Google Cloud.

Discover strategies to manage cloud computing costs across AWS, Azure, and Google Cloud in 2025. This article offers an in-depth comparison of pricing models, hidden fees, and key cost components such as computing, storage, and networking. Learn how to calculate total cloud expenses and make informed decisions based on your infrastructure needs and cloud provider. Additionally, uncover best practices for optimizing cloud resources through techniques like right-sizing, autoscaling, and leveraging discounts to achieve cost-efficiency across your cloud environments.

AWS Spot Instances can help businesses cut EC2 costs by up to 90%, but their unpredictability makes them challenging to manage. With Sedai’s AI-powered automation, you can seamlessly optimize Spot Instance usage, prevent service disruptions, and maximize cloud savings—without manual effort. Sedai dynamically shifts workloads between Spot, On-Demand, and Reserved Instances, ensuring high availability and cost efficiency.

This blog explores how to use Spot Instances in Azure Kubernetes Service (AKS) to scale workloads while maximizing cost savings. It covers adding Spot Node Pools, best practices for managing evictions, and optimizing Kubernetes costs using Spot VMs. You’ll learn how tools like Cluster Autoscaler and Sedai’s autonomous optimization can help maintain high availability even with potential interruptions. By blending Spot and On-Demand instances, you can strike the perfect balance between resilience and efficiency, achieving a scalable, cost-effective AKS environment with minimal manual intervention.

Optimize your Kubernetes clusters with Sedai! Discover how our autonomous platform detects orphaned resources, improves performance, and reduces costs. Sedai fine-tunes workload configurations, manages resources efficiently, and ensures scalability.

This blog dives into effective strategies for optimizing Azure Kubernetes Service (AKS) costs, focusing on resource right-sizing, autoscaling, and leveraging cost-saving pricing models like Spot VMs and Reserved Instances. It highlights best practices such as regular resource audits, tagging for cost tracking, and training teams on cost-efficient Kubernetes practices. The blog also introduces Sedai’s autonomous optimization platform, which automates resource adjustments and scaling to minimize costs while maintaining performance. Practical insights and actionable tips empower teams to manage AKS clusters efficiently, balance cost with reliability, and thrive in a cloud-driven environment.

This blog explores the strategy of running Kubernetes clusters on spot instances, a cost-saving approach that taps into unused cloud capacity. It covers key benefits of using spot instances in Kubernetes, best practices for autoscaling, and methods for managing instance interruptions to maintain workload stability. Additionally, it introduces Sedai's autonomous optimization platform, which enhances spot instance management through real-time adjustments and predictive analytics, minimizing manual intervention. Practical steps for node group configuration, pod scheduling, and balancing reliability with cost-efficiency are also included to help teams optimize Kubernetes clusters for cost-effective, resilient operations.

Optimizing costs in Google Kubernetes Engine (GKE) is crucial for businesses seeking to balance cloud spending with operational efficiency. This post explores essential strategies for achieving cost savings without compromising performance. Key practices include adjusting pod resource requests and limits, leveraging autoscaling for dynamic resource management, and utilizing Spot VMs for non-critical workloads to take advantage of significant cost reductions. Understanding GKE’s pricing models, such as committed use discounts (CUDs) and sustained use discounts (SUDs), is also essential for long-term cost management.

Managing Azure Kubernetes Service (AKS) efficiently requires automation to prevent unnecessary cloud costs. This article explores methods to automate AKS cluster shutdowns and startups using Azure Automation, PowerShell, Logic Apps, and Sedai. Learn how to optimize costs, reduce manual interventions, and ensure clusters run only when needed. Discover best practices, scripts, and scheduling techniques for smarter AKS management.

At autocon we held a panel to generate in-depth insights on the business case of AI, tackling some big questions about autonomy and AI: How are big organizations using autonomy? To what extent is autonomy helpful? How willing are companies to adopt autonomy? How does the staff react to automation?How to go about the cost of using automations?

Best practices for cloud cost management and optimization include cost visibility, automating infrastructure rightsizing, and building cost-awareness culture within teams.

In a recent survey conducted by McKinsey with IT directors and IT organizations, one of the key takeaways was that FinOps is one of the most important and emerging practices that they have been adopting throughout their IT and technology organizations in the last couple of years.

A 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 optimized 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 one key capability of Sedai's autonomous cloud management platform.

KnowBe4's autonomous journey has led to 98% of their Amazon. ECS and Lambda services running autonomously, with a 27% cost reduction and over 1,100 autonomous actions in the past 3 months. KnowBe4 fhad aced an optimization challenge with their Amazon Elastic Container Service (ECS) services, leading them to adopt Sedai's autonomous optimization to reduce toil for engineers and improve efficiency. KnowBe4 implemented a three-part approach (Crawl, Walk, Run) to gradually adopt autonomous optimization, resulting in significant cost savings and performance gains.

In this post, we will cover how to master Amazon ECS optimization using autonomous techniques. The autonomous approach can help with both ECS cost optimization and performance optimization.

To optimize AWS ECS costs, focus on workload optimization by right-sizing resources, configuring efficient infrastructure with the appropriate instance types and mix, and making strategic purchasing decisions such as leveraging Savings Plans or Reserved Instances.