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Infrastructure Monitoring
Get complete visibility into your cloud infrastructure performance at any scale, easily access all your metrics in one place and optimize infrastructure efficiency.
The groundcover platform offers infrastructure monitoring capabilities that were built for cloud-native environments. It enables you to track the
health and efficiency of your infrastructure instantly, with an effortless deployment process.
Troubleshoot efficiently - acting as a centralized hub for all your infrastructure, application and customer metrics allows you to query, correlate and troubleshoot your cloud environments using real time data and insight on your entire stack.
Store it all, without a sweat - store any metrics volume without worrying about cardinality or retention limits. Your subscription costs remain unaffected by the granularity of metrics you store or query.
groundcover's proprietary eBPF sensor leverages all its innovative powers to collect comprehensive data across your cloud environments without the burden of performance overhead. This data is sourced from various Kubernetes components, including kube-system workloads, cluster information via the Kubernetes API, and the applications' interactions with the Kubernetes infrastructure. This level of detailed collection at the kernel level enables the ability to provide actionable insights into the health of your Kubernetes clusters, which are indispensable for troubleshooting existing issues and taking proactive steps to future-proof your cloud environments.
You also have the option to define the retention period for your metrics in the VictoriaMetrics database. By default, logs are retained for 7 days, but you can adjust this period to your preferences.
Beyond collecting data, groundcover's methodology involves a strategic layer of data enrichment that seeks to correlate Kubernetes metrics with application performance indicators. This correlation is crucial for creating a transparent image of the Kubernetes ecosystem. It enables a deep understanding of how Kubernetes interacts with applications, identifying potential points of failure across the interconnected environment. By monitoring Kubernetes not as an isolated platform but as an integral part of the application infrastructure, groundcover ensures that the monitoring strategy aligns with your dynamic and complex cloud operations.
Monitoring a cluster involves tracking resources that are critical to the performance and stability of the entire system. Monitoring these essential metrics is crucial for maintaining a healthy Kubernetes cluster:
- CPU consumption: It's essential to track the CPU resources being utilized against the total capacity to prevent workloads from failing due to insufficient CPU availability.
- Memory utilization: Keeping an eye on the remaining memory resources ensures that your cluster doesn't encounter disruptions due to memory shortages.
- Disk space allocation: For Kubernetes clusters running stateful applications or requiring persistent storage for data, such as etcd databases, tracking the available disk space is crucial to avert potential storage deficiencies.
Available LabelstypeclusterId region namespace node_name workload_namepod_name container_name container_imageAvailable MetricsName | Description | Type |
|---|---|---|
groundcover_container_m_cpu_usage_seconds_total | cumulative cpu time consumed (mCPU * seconds) | Gauge |
groundcover_container_cpu_request_m_cpu | K8s container CPU request (mCPU) | Gauge |
groundcover_container_cpu_limit_m_cpu | K8s container CPU limit (mCPU) | Gauge |
groundcover_container_mem_working_set_bytes | current memory working set (B) | Gauge |
groundcover_container_memory_request_bytes | K8s container memory request (B) | Gauge |
groundcover_container_memory_limit_bytes | K8s container memory limit (B) | Gauge |
groundcover_container_cpu_delay_seconds | K8s container CPU delay accounting in seconds | Gauge |
groundcover_container_disk_delay_seconds | K8s container disk delay accounting in seconds | Gauge |
groundcover_container_cpu_throttled_seconds_total | K8s container total CPU throttling in seconds | Gauge |
Available Labelstype clusterId region node_name Available MetricsName | Description | Type |
|---|---|---|
groundcover_node_allocatable_cpum_cpu | amount of allocatable CPU in the current node (mCPU) | Gauge |
groundcover_node_allocatable_mem_bytes | amount of allocatable memory in the current node (B) | Gauge |
groundcover_node_mem_used_percent | percent of used memory in current node (0-100) | Gauge |
groundcover_node_used_disk_space | current used disk space in current node (B) | Gauge |
groundcover_node_free_disk_space | amount of free disk space in current node (B) | Gauge |
groundcover_node_total_disk_space | amount of total disk space in current node (B) | Gauge |
groundcover_node_used_percent_disk_space | percent of used disk space in current node (0-100) | Gauge |
Available Labelstype clusterId region name namespaceAvailable MetricsName | Description | Type |
|---|---|---|
groundcover_pvc_usage_bytes | PVC used bytes (B) | Gauge |
groundcover_pvc_capacity_bytes | PVC capacity bytes (B) | Gauge |
groundcover_pvc_usage_percent | percent of used pvc storage (0-100) | Gauge |