Top 10 Alternatives to Amazon Aurora Serverless V2 Recently Reviewed By G2 Community
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Compute Engine enables you to create and run large-scale workloads on virtual machines hosted on Google Cloud. Get running quickly with pre-built and ready-to-go configurations or create machines of your own with the optimal amount of vCPU and memory required for your workload.
Multiple clouds. One cluster. All the benefits combined. Cast AI allows you to combine the benefits from multiple cloud providers in any way you want. Start with one or multiple clouds and Cast AI will create one cluster spanning them all. With auto-scaling, key metrics dashboard and management in vanilla Kubernetes out of the box.
Reduce K8s costs by up to 80%. Ensure workloads SLA. Free engineers from repeated manual configurations. ScaleOps is the industry-first Kubernetes Optimization Platform that automatically adjusts Compute Resources to changes in real-time, streamlining a new Kubernetes experience for engineering teams.
Pepperdata automatically optimizes system resources while providing a detailed, correlated understanding of each application using hundreds of application and infrastructure metrics collected in real-time. It highlights applications that need attention, automatically identifies bottlenecks, and alerts on duration, failure conditions, and resource usage. In the cloud or on-premises, this automated approach gives you complete observability and insight into your big data stack
Xosphere's super power is reducing AWS EC2 expense by up to 80%. Xosphere is the world's only intelligent cloud orchestration company empowering enterprises to seamlessly move applications to the right place at the right time to reduce cloud expense and increase reliability. Xosphere's intelligent cloud software transforms unreliable Spot instances into robust resources that have the same reliability as On-Demand but at a fraction of the cost, yielding unparalleled savings. For enterprises that want to reduce cloud costs, Xosphere's optimization engine maximizes savings with the fastest speed of implementation in the industry. Xosphere Instance Orchestrator is a cloud-native, self-hosted subscription software application. It installs into your Amazon Web Services (AWS) account using either a CloudFormation stack or a Terraform module and runs using Lambda functions. Instance Orchestrator uses an opt-in design; it only executes on Auto-Scaling groups or individual instances that have explicitly been enabled via an AWS tag. Tags can be applied using any method or tool that is used within the organization to manage tags (for example, AWS Console, AWS CLI, AWS APIs, infrastructure-as-code platforms such as CloudFormation or Terraform, cloud management platforms, etc.). Once this enabling tag has been applied, Instance Orchestrator will automatically perform its management duties on an ongoing basis.
Avi Networks enables public-cloud-like simplicity and flexibility for application services such as load balancing, application analytics, and security in any data center or cloud.
UbiOps by Dutch Analytics is an all-in-one software platform that enables you to very quickly turn your algorithms into scalable, robust and secure end-to-end applications. This without requiring knowledge to set up Cloud infrastructure, micro-services, automated scaling, or DevOps practices. Save months of work as UbiOps takes care of a smooth transition from where data science ends to where IT starts. Easily deployed across public/private Cloud or On-Premise. Centrally managed and fully secured with data and code encryption.
Sedai incorporates key autonomous system characteristics in a cloud context. By leveraging a massive influx of data streams, Sedai builds a layer of intelligence via its core decision engine, which derives concepts from probability theory and applied machine learning techniques. Its self-learning and self-correcting model seamlessly manages cloud platforms with a focus on explainable decisions. Our products S.Watch Sedai connects with various monitoring tools, including Prometheus, Datadog, Cloudwatch, etc., and tracks four golden signals: Latency, Traffic, Errors, and Saturation. S-Watch distills noise to provide insights and recommendations to bring key KPIs such as MTTD, MTTF, MTBF, and MTTR to acceptable levels. S.Run Sedai distills data into an explainable and tunable knowledge base that powers its machine learning models. These models fuel Sedai’s core decision engine, which determines efficient and corrective workflows for all identified drifts to infer optimal strategies for detection and safe remediations. Its true closed-loop learning model enables self-configuration at optimal levels, ensuring the highest levels of availability. Armed with vast data, deep insights, and a rich knowledge base, platforms that are managed by Sedai are able to achieve a self-optimized state.
Meet your infrastructure Al toolkit: Thoras leverages bleeding-edge Al to predict GPU and CPU resource needs, prevent downtime, and optimize Kubernetes workloads-saving you money and keeping your systems running smoothly.
Auto Scaling is a service to automatically adjust computing resources based on your volume of user requests. When demand for computing resources increase, Auto Scaling automatically adds ECS instances to serve additional user requests, or alternatively removes instances in the case of decreased user requests.