Best Auto Scaling Software in Asia

Compute Engine (IaaS), a platform from Google that allows organizations to create and manage cloud-based virtual machines, is an infrastructure as a services (IaaS). Computing infrastructure in predefined sizes or custom machine shapes to accelerate cloud transformation. General purpose machines (E2, N1,N2,N2D) offer a good compromise between price and performance. Compute optimized machines (C2) offer high-end performance vCPUs for compute-intensive workloads. Memory optimized (M2) systems offer the highest amount of memory and are ideal for in-memory database applications. Accelerator optimized machines (A2) are based on A100 GPUs, and are designed for high-demanding applications. Integrate Compute services with other Google Cloud Services, such as AI/ML or data analytics. Reservations can help you ensure that your applications will have the capacity needed as they scale. You can save money by running Compute using the sustained-use discount, and you can even save more when you use the committed-use discount.

Avi Vantage offers multi-cloud application services, including a Software Load Balancer (iWAF), Intelligent Web Application Firewall(iWAF), and Elastic Service Mesh. The Avi Vantage Platform ensures a secure, fast, and scalable application experience. Avi Vantage provides multi-cloud application services, including load balancing for containerized apps with microservices architecture, application traffic management, web application security, and dynamic service discovery. Container Ingress offers scalable and enterprise-class North/South (Kubernetes Ingress) traffic management. This includes local and global server load balancing, web application firewall (WAF), and performance monitoring across multi-cluster, multiregion and multi-cloud environments. Avi seamlessly integrates with Kubernetes to enable container and microservice orchestration and security.

AWS Auto Scaling monitors and adjusts your applications to ensure predictable, consistent performance at the lowest cost. AWS Auto Scaling makes it easy to set up application scaling for multiple resources and multiple services in minutes. It offers a simple and powerful user interface that allows you to create scaling plans for resources such as Amazon EC2 instances, Spot Fleets and Amazon ECS tasks, Amazon DynamoDB indexes and tables, and Amazon Aurora Replicas. AWS Auto Scaling simplifies scaling with recommendations that optimize performance, cost, or balance between them. You can combine Amazon EC2 Auto Scaling with AWS Auto Scaling if you already use it to dynamically scale Amazon EC2 instances. AWS Auto Scaling ensures that your applications have the right resources at all times.

Kubernetes AI-driven cloud optimization Reduce your cloud bill instantly, prevent downtime and get 10X the power from DevOps. CAST AI reduces container costs and keeps them low. While AI automates infrastructure provisioning, engineers can continue to work as before. Same performance, half-the cost, and zero hassle. Get in touch with our team to set up the deal and get started. Get the most out of every dollar you spend. Our AI engine will automatically select the best instance type and bin pack nodes for each pod. The pods will automatically be given the correct CPU and memory limits. Your instances will automatically scale up or down according to the load. Scale to zero when there is no work to do. Spot instance support of production grade for Kubernetes workloads. Reserved instances allow you to save up to 90% without locking yourself into a contract.

Xosphere Instance Orchestrator performs automatic spot optimization using AWS Spot instances. This optimizes the cost of your infrastructure, while maintaining the same reliability as on-demand instance. Spot instances have been diversified by family, size and availability zone in order to minimize the impact of reclaiming Spot instances. Spot instances will not replace instances that use reservations. Respond automatically to Spot termination notifications. EBS volumes can configured to be attached new replacement instances, enabling stateful apps to work seamlessly.

Automated Optimization of Big Data Workloads. Control costs on any cloud. Pepperdata offers a 3X price performance improvement. We optimize your system resources and provide a correlated and detailed understanding of your infrastructure and applications, unlike traditional infrastructure monitoring vendors and APM vendors. Machine learning powers us to deliver the application SLAs required for business and provide complete visibility into your big data stack. Automated reduction of dynamic instances and packing more workloads into existing instances. Use application-specific recommendations to identify areas for manual tuning. Be alert for abnormal behavior in your application. Optimize the performance of your existing big data infrastructure without sacrificing observability. Our customers can run more applications and manage their costs with real-time optimization.

Amazon EC2 Auto Scaling allows you to maintain application availability by adding or removing EC2 instances automatically using scaling policies you define. Dynamic or predictive policies allow you to add or remove EC2 instances capacity in response to real-time or established demand patterns. The fleet management features in Amazon EC2 Auto Scaling maintain the health and availability your fleet. Automating DevOps is essential, and getting your fleets to automatically launch, provision software and self-heal is a major challenge. Amazon EC2 Auto Scaling offers essential features to automate each of these steps in the instance lifecycle. Use machine learning to predict the number of EC2 instance to be used to anticipate traffic changes.

Auto Scaling allows you to automatically adjust computing resources according to your user requests. Auto Scaling automatically adds new ECS instances when there is a greater demand or removes existing instances when there are fewer user requests.

UbiOps provides an AI infrastructure platform to help teams run AI & ML workloads quickly as reliable and secure Microservices without disrupting their existing workflows. UbiOps can be integrated seamlessly into your data-science workbench in minutes. This will save you time and money by avoiding the hassle of setting up expensive cloud infrastructure. You can use UbiOps as a data science team in a large company or a start-up to launch an AI product. UbiOps is a reliable backbone to any AI or ML services. Scale AI workloads dynamically based on usage, without paying for idle times. Instantly access powerful GPUs for model training and inference, enhanced by serverless, multicloud workload distribution.