Thoras.ai Description
Cloud waste is no longer an issue. Your critical applications will continue to run smoothly. Anticipate fluctuations in demand to ensure optimal capacity and uninterrupted performance. Early anomaly detection allows for rapid identification and resolution of problems, resulting in smooth operations. Intelligent workload rightsizing reduces under- or over-provisioning. Thoras optimizes itself, giving engineers recommendations and visualizing trends.
Thoras.ai Alternatives
Fairwinds Insights
Protect and optimize mission-critical Kubernetes apps. Fairwinds Insights, a Kubernetes configuration validation tool, monitors your Kubernetes containers and recommends improvements. The software integrates trusted open-source tools, toolchain integrations and SRE expertise, based on hundreds successful Kubernetes deployments. The need to balance the speed of engineering and the reactive pace of security can lead to messy Kubernetes configurations, as well as unnecessary risk. It can take engineering time to adjust CPU or memory settings. This can lead to over-provisioning of data centers capacity or cloud compute. While traditional monitoring tools are important, they don't offer everything necessary to identify and prevent changes that could affect Kubernetes workloads.
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Sensai
Sensai is an AI-based algorithm that detects anomalies, predicts root causes, and analyzes root causes. This allows for real-time resolution of issues. Sensai AI solution dramatically improves uptime and time to root cause. IT leaders are empowered to manage SLAs for better performance and profitability. Automates anomaly detection, prediction root cause analysis (RCA), and resolution. Integrating 3rd party tools allows for a holistic view and integrated analytics. Pre-trained models & algorithms from day one.
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cloudNito
CloudNito, an AI-powered SaaS solution, is designed to help companies of all sizes optimize AWS cloud costs. Our solution combines real time monitoring, advanced anomaly detecting, and automated cost saving actions to eliminate wasteful cloud spending and improve efficiency.
The following are the key features:
AI-driven cost anomaly identification
Automated resource scaling, optimization and scaling
Cost allocation and reporting in detail
Cost forecasting - a predictive tool
Customizable alerts, thresholds and alerts
CloudNito allows companies to save on their AWS costs, ensuring that they get the most out of their cloud investment.
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Zilliz Cloud
Searching and analyzing structured data is easy; however, over 80% of generated data is unstructured, requiring a different approach. Machine learning converts unstructured data into high-dimensional vectors of numerical values, which makes it possible to find patterns or relationships within that data type. Unfortunately, traditional databases were never meant to store vectors or embeddings and can not meet unstructured data's scalability and performance requirements.
Zilliz Cloud is a cloud-native vector database that stores, indexes, and searches for billions of embedding vectors to power enterprise-grade similarity search, recommender systems, anomaly detection, and more.
Zilliz Cloud, built on the popular open-source vector database Milvus, allows for easy integration with vectorizers from OpenAI, Cohere, HuggingFace, and other popular models. Purpose-built to solve the challenge of managing billions of embeddings, Zilliz Cloud makes it easy to build applications for scale.
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Thoras.ai
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thoras.ai
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Product Details
Platforms
SaaS
Type of Training
Live Online
Customer Support
Online
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