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    1. Products
    2. kwatch
    3. Alternatives
    The best alternatives to kwatch are Monitor ML, Hall Monitor, and Sensei. If these 3 options don't work for you, we've listed a few more alternatives below.
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    Best alternatives to kwatch
    • Monitor ML tracks the performance of models throughout their lifecycle and connects them to business metrics. We support model tracking, metric logging/analysis/alerting and production event logging. You choose the framework, we monitor the model.
    • Hall Monitor is an easy way to manage your entire business in one place. We bring all your apps - Stripe, Shopify, Twitter, Instagram, and more - into unified automated reports, delivered to Slack or your inbox.
    • Sensei is a native macOS app for monitoring and optimizing your Mac performance. With a wide range of features spanning hardware and software, it can help you clean out your disk space, optimize your boot speeds, monitor your hardware health, and much more.
    • Server monitoring done right
    • Platypus is an application platform built to provide sysadmins access to realtime statistics of their servers using websockets and Python.
    • See how your servers are doing in real-time, get alerted when there is something off and analyse the performance of your infrastructure over time.
    • ezyLogs is full DevOps platform allowing you to remotely view application logs, view log metrics, monitor server vitals like RAM, CPU and get alerted when your server has issues. We feel that log and server management shouldn't be hard and costly. With only a few lines of code you can add logging and server monitoring to your application.
    • The HealthyServers solution is simple, yet powerful. It gathers information from all of your servers and stores KPl-related information in a scalable database for graphical and in-depth analysis and forecasting.
    • Konstellation is an open-source distributed tracing tool built specifically for Kubernetes. Its innovative Source Map approach to trace analysis enables unparalleled ease in resolving root cause investigations and clearly illustrates service dependencies within your clusters.