Overview
Real-time tuning for large-scale K8s clusters finally comes true, thanks to TMaestro's AI-powered automatic tuning. Plus, TMaestro does it all -smart JVM monitoring, analysis and anomaly diagnosis.
Highlights
- TMaestro collects both K8s cluster-level and JVM-level data. It examines memory usage, CPU configs, Pod&Node info, and other key indicators to generate reports. Whenever risks are detected, it's able to alert you through in your preferred way-email, SMS, Wechat, among others.
- TMaestro's automatic tuning has been tested on OVER A THOUSAND applications. Once deployed, it analyzes an application's historic data and recommends optimal parameter values. From then on, its algorithm continuously optimizes your JVM performance and makes adjustments based on user-defined goals and constraints.
- When auto tuning is on, TMaestro will ask the machines in your application to execute new parameters group by group, instead of all at once. Once risks are detected, it can quickly roll back to the previous setting, avoiding negative impact on system stability.
Details
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Pricing
Dimension | Cost/unit |
---|---|
Starts at $0.5/day (The number of the pods <= 20) | $0.50 |
Starts at $0.001/pod/hour (The number of the pods > 20) | $0.001 |
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Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
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Any question about our product tmaestro@antgroup.com
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