I applied through a recruiter. The process took 3 weeks.

The interview process typically comprises three rigorous technical rounds, each designed to assess a candidate’s depth of knowledge and problem-solving abilities. While the experience is intellectually rewarding, the post-interview phase, particularly the offer release, is notably delayed. Despite receiving verbal confirmation from HR that the offer is "under process" and will be "released soon," there’s often a prolonged wait with limited transparency. Streamlining the offer rollout process would reflect positively on the organization's efficiency and candidate experience. A faster and more structured post-interview workflow could help retain top talent who are actively considering multiple offers.

Tell me about yourself and your roles and responsibilities in your current organization.

Let's say a pod is monitored by a Horizontal Pod Autoscaler (HPA) configured to scale out when memory usage reaches 80%. But before the HPA can spin up new pods, the existing pod's memory usage hits 100%. In this situation, what will happen to the pod? And how will the HPA behave or respond?

Is it advisable to use both a Horizontal Pod Autoscaler (HPA) and a Vertical Pod Autoscaler (VPA) on the same application? If yes, what are the possible consequences of doing so? And what kind of challenges or unexpected behaviours might occur when both are applied on the same pod?

In a Kubernetes cluster with multiple applications running, what will happen if one of the worker nodes fails unexpectedly? How does the cluster handle the workloads that were running on that node?

If a request is sent to a specific application and it successfully reaches the pod, but before the pod can respond, it crashes, what will happen to that request? How does Kubernetes handle such scenarios, and is the client informed?