Resource Observability
The page provides an overview of Machines and Resources used to monitor and optimize Platform performance.
Machine & Resources Overview
Resource observability is key to maintaining operational efficiency in systems with dynamic and distributed components, like cloud services, containerized environments, and microservices architectures. It is vital for detecting issues, optimizing performance, and ensuring reliability in complex systems, particularly in cloud computing and distributed frameworks.
The Resource Observability page provides a detailed breakdown of the system's resources to help monitor and optimize platform performance. It opens by default on the Machine tab, offering a comprehensive snapshot of key metrics related to machine and resource utilization.
Machine Tab
The Machine tab delivers real-time metrics about the platform's infrastructure, including:
Active Machines: Displays the total number of operational machines currently running.
CPU Capacity: Displays the system’s processing power, measured in cores, providing a clear picture of total CPU resources.
Memory Capacity: Measured in bytes, this metric gives an accurate assessment of the system’s memory capacity.
Number of Pods: Displays the total number of running pods, reflecting the workload distribution across machines.
In addition to these metrics, the tab also features visual aids such as:
CPU Allocation: Provides a visual representation of how CPU resources are distributed among various processes.
Memory Allocation: Offers insights into how memory is allocated and consumed within the system, helping to identify any potential bottlenecks or imbalances.
The Observability page presents a detailed list of machines and Kubernetes instances, offering a clear status overview and resource breakdown. Key information includes:
IP Address & Instances: Lists the Kubernetes-generated unique names for each platform entity that the user wants to process.
Readiness: Displays whether Kubernetes instances are in a ready state or not.
CPU Requests and Limits: Measured in cores, these metrics highlight the minimum and maximum CPU resources requested and allowed for each instance.
Memory Requests and Limits: Measured in bytes, this shows the requested and maximum memory allocation for each instance.
Percentage of Pods: Provides a percentage of how many pods are currently being utilized in the allocated resources.
Creation Time: Mentions time and date of creation for each instance, offering insights into deployment history.
The user can click on a specific entry to see the graphical presentation of information on the latest CPU Usage, Memory Usage, and Workloads.
Resource Tab
The Resource tab offers two key views—Live and All—providing detailed resource information for components or projects as managed by Kubernetes.
Live View: Displays up-to-the-minute resource details for active components, allowing you to monitor performance in real-time.
All View: Displays comprehensive data, including past and present resource usage for a deeper analysis of system behavior over time. Each entry provides essential metrics, including:
Creation Date & Time: Marks when the resource was initiated, giving you a timestamp for tracking purposes.
Age: Indicates how long the resource was operational, offering insight into its lifecycle.
Restarts: Tracks how often a pod or instance has restarted, useful for diagnosing potential stability issues.
CPU and Memory Usage: Aggregates the total CPU and memory consumed, based on request sums, to give a clear picture of resource demand. The CPU and Memory usage is indicated through color-coded bars that change color from green to yellow and finally to red based on the rise in usage.
Search Functionality: Find specific entities by name and easily navigate to them using the Search bar.
Pod Type Filters: Narrow down the results by filtering the list based on pod types, making it easy to focus on the resources that matter most when the user selects the All tab.
These metrics are essential for understanding resource allocation and ensuring optimized performance.
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