Problems due to inadequate resources

It emphasizes the importance of ensuring compatibility with existing infrastructure and highlights key considerations for optimal performance. Additionally, it provides guidance on preparing the environment to align with Forcepoint's standards and recommendations. This preparation ensures a smooth and efficient deployment process.

Resource requirements for Kubernetes cluster

Forcepoint DSPM leverages Kubernetes for its underlying infrastructure which requires stringent hardware requirements. Meeting the minimum resource requirements for containers is essential to avoid several potential issues later.
  • Resource Starvation: If a container requests more CPU or memory resources than are available on the cluster, it can lead to resource starvation. This means other containers may not get the necessary resources to run correctly, causing performance degradation or even crashes.
  • Throttling: Kubernetes imposes resource limits for containers, and if a container's requested resources exceed its limits, Kubernetes may throttle or terminate the container to prevent it from consuming excessive resources, resulting in performance degradation.
  • Out of Memory or ‘CrashLoopBackOff’ Errors: Oversubscribing memory resources can lead to containers running out of memory, causing them to terminate abruptly or enter a constant restart loop, commonly referred to as a ‘CrashLoopBackOff’ error.
  • Performance Degradation: When requested CPU resources are larger than allocated, it can lead to performance issues as containers compete for CPU time, potentially slowing down critical processes and making the application unresponsive.
  • Difficult Troubleshooting: Wrongly allocating resources, whether too little or too much, can be challenging to identify and correct. This can lead to extended troubleshooting efforts and downtime as administrators attempt to resolve resource-related issues.

To ensure a stable and efficient Kubernetes deployment of our product, it's essential to accurately configure resource requests and limits for containers based on their actual requirements. This prevents resource-related problems and ensures smooth operation within the Kubernetes cluster.