A Persistent Volume Claim (PVC) is a request for storage by a user. It is similar to a Pod, which is a request for compute resources by a user. A PVC enables a Pod to consume a slice of the available storage in the cluster without knowing the details of the underlying storage infrastructure. A PVC is associated with a StorageClass, which defines the type and characteristics of the storage. A PVC is also bound to a Persistent Volume (PV), which is an abstraction of the physical or cloud-based storage resource. A PV is created by the cluster administrator and has a lifecycle independent of any Pod. A PVC can specify the size, access mode, and storage class of the PV it requires. Before deploying an application that needs persistent state, a user must create a PVC for the Pod that will run the application. The PVC will then be automatically bound to a suitable PV by the cluster, or dynamically provisioned if the storage class supports it. The Pod can then mount the PVC as a volumeand access the persistent storage12345. References: Persistent Volumes | Kubernetes, How Kubernetes Persistent Volume Claims Work - CBT Nuggets, Exploring Kubernetes Storage: Persistent Volumes and Persistent Volume Claims - Atatus, Configure a Pod to Use a PersistentVolume for Storage | Kubernetes, kubernetes - How to mount a persistent volume on a Deployment/Pod using PersistentVolumeClaim? - Stack Overflow.

 A one off/non parallel job is a workload type that runs a single task to completion and then terminates. This is suitable for running a database migration on SAP BTP, Kyma runtime, as it does not require scaling, persistence, or parallelism. A parallel job, on the other hand, is a workload type that runs multiple tasks in parallel and then terminates. This is useful for batch processing or data analysis, but not for database migration. A StatefulSet is a workload type that runs one or more pods that maintain a stable identity and persistent storage. This is useful for stateful applications such as databases or message brokers, but not for database migration. A DaemonSet is a workload type that runs one pod on each node in the cluster. This is useful for providing node-level services such as logging or monitoring, but not for database migration. References: Workload Concepts, Kubernetes Workloads

Observability tools are used to monitor system behaviour and performance, as well as to troubleshoot issues and identify root causes. Observability tools in SAP BTP, Kyma runtime include Grafana, Prometheus, Loki, and Jaeger, which provide dashboards, metrics, logs, and traces for the workloads running in the cluster1. Distributed tracing is a technique to track the flow of requests across microservices and visualize the latency, errors, and dependencies of each service2. Observability tools help developers and operators to ensure the reliability, availability, and security of their applications and services.