Add Feast feature store example

feast/README.md

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+# Feast Feature Store Examples
+
+These examples demonstrate how to use [Feast](https://docs.feast.dev/) on prokube
+for feature management in ML workflows.
+
+## Prerequisites
+
+- Feast must be enabled on your cluster (ask your admin)
+- You have `kubectl` access to your Kubeflow profile namespace
+
+## Quick Start
+
+### 1. Deploy a Redis instance
+
+Create a password secret and a Redis CR in your namespace:
+
+```bash
+# Generate a random password
+kubectl create secret generic redis-feast \
+  -n <your-namespace> \
+  --from-literal=password=$(openssl rand -base64 24 | tr -d '/')
+
+# Deploy the Redis CR
+kubectl apply -f redis-cr.yaml   # see file below — edit namespace first
+kubectl get redis -n <your-namespace> -w
+```
+
+`redis-cr.yaml` is a plain Kubernetes manifest for the OpsTree Redis operator.
+Create it with the contents shown in the prokube [user docs](https://docs.prokube.ai/user_docs/feast/).
+
+### 2. Create the Feast Redis secret
+
+```bash
+NAMESPACE=<your-namespace>
+PASSWORD=$(kubectl get secret redis-feast -n $NAMESPACE \
+  -o jsonpath='{.data.password}' | base64 -d)
+
+cat > /tmp/redis-config.yaml << EOF
+connection_string: "redis-feast.${NAMESPACE}.svc.cluster.local:6379,password=${PASSWORD}"
+EOF
+
+kubectl create secret generic feast-redis-config \
+  -n $NAMESPACE \
+  --from-file=redis=/tmp/redis-config.yaml
+
+rm /tmp/redis-config.yaml
+```
+
+### 3. Deploy a FeatureStore
+
+Edit `feast-cr.yaml` to set your namespace, then:
+
+```bash
+kubectl apply -f feast-cr.yaml
+kubectl get featurestore -n <your-namespace> -w   # wait until Ready
+```
+
+### 4. Run the notebook
+
+Open `feast_example.ipynb` in your Kubeflow notebook. The notebook reads the
+`feast-redis-config` secret automatically and builds `feature_store.yaml` for you.
+
+## Files
+
+| File | What it is |
+|------|------------|
+| `feast-cr.yaml` | Kubernetes manifest — deploys the FeatureStore CR |
+| `feature_store.yaml` | Feast SDK config — tells the Python client where registry and stores are |
+| `features.py` | Feature definitions — entities, data sources, feature views |
+| `feast_example.ipynb` | End-to-end notebook: generate data, apply, train, materialize, serve |
+
+### Why two YAML files?
+
+`feast-cr.yaml` is a **Kubernetes resource** (`kind: FeatureStore`) that the operator
+reads to provision PVCs and the Feast server pod. You apply it once with `kubectl`.
+
+`feature_store.yaml` is a **Feast SDK config file** (fixed filename — Feast convention)
+that the Python client and CLI read to know how to connect to the registry and stores.
+You use it in notebooks and scripts.
+
+## Architecture
+
+Feast has three stores. Here is what each one does and which backend prokube uses:
+
+| Store | Purpose | Prokube default | Alternatives |
+|-------|---------|-----------------|--------------|
+| **Registry** | Stores feature definitions (entities, feature views, sources). Written on `feast apply`, read at startup. | SQLite on PVC | SQL databases (PostgreSQL, etc.) for multi-replica or shared setups |
+| **Online store** | Holds the *latest* feature value per entity. Read on every inference request — latency critical. | Redis (your `Redis` CR) | SQLite on PVC (dev/test only; not multi-replica safe) |
+| **Offline store** | Historical feature records for point-in-time joins during training. Batch workload, not on serving path. | Parquet/file on PVC | Dask (same parquet files, distributed compute — use only if data exceeds pod memory); cloud warehouses (BigQuery, Snowflake, Redshift) |
+
+The offline store default is `type: file` (pandas). You can switch to `type: dask` in
+`feast-cr.yaml` if your datasets are too large to fit in memory, but it adds complexity
+and is rarely needed.
+
+```
+                    ┌─────────────────────────────────┐
+                    │        Your Namespace            │
+                    │                                  │
+                    │  Redis CR (redis-feast)           │
+                    │    - your private Redis instance  │
+                    │                                  │
+  feast apply ──────▶  SQLite /tmp/registry.db        │
+  (notebook)        │    - feature definitions          │
+                    │    - entity schemas               │
+                    │                                  │
+  materialize ──────▶  Redis online store              │
+                    │    - latest feature values        │
+                    │    - sub-ms latency               │
+                    │    - persistent across sessions   │
+                    │                                  │
+  historical  ──────▶  Parquet on PVC (offline store)  │
+  features          │    - time-series feature data     │
+                    │                                  │
+                    │  Feast Server pod                │
+                    │    - HTTP API for online features │
+                    │    - registry on PVC (/data/...)  │
+                    └─────────────────────────────────┘
+```
+
+- **Redis** (per-namespace): your private online store. You own and manage it.
+- **Registry** (SQLite): feature definitions. In notebook workflows, uses `/tmp/registry.db`.
+  The Feast server pod uses the registry PVC at `/data/registry/registry.db`.
+- **Offline store** (parquet/PVC): historical feature data for training.

feast/feast-cr.yaml

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+# Example FeatureStore CR for prokube.
+# Edit the namespace to match your Kubeflow profile.
+#
+# The operator will create:
+#   - A Feast deployment + service (online feature server)
+#   - PVCs for the SQLite registry and offline data store
+#   - A ConfigMap (feast-<name>-client) with client connection info
+#
+# Prerequisites:
+#   - feast-redis-config secret must exist in your namespace (see README)
+apiVersion: feast.dev/v1
+kind: FeatureStore
+metadata:
+  name: my-store
+  namespace: <your-namespace>  # <-- change this
+spec:
+  feastProject: my_features
+  services:
+    runFeastApplyOnInit: false
+    securityContext:
+      runAsUser: 0
+    registry:
+      local:
+        persistence:
+          file:
+            pvc:
+              mountPath: /data/registry
+              create:
+                storageClassName: mayastor-no-redundancy  # adjust for your cluster
+                resources:
+                  requests:
+                    storage: 1Gi
+    offlineStore:
+      persistence:
+        file:
+          type: file
+          pvc:
+            mountPath: /data/offline
+            create:
+              storageClassName: mayastor-no-redundancy  # adjust for your cluster
+              resources:
+                requests:
+                  storage: 10Gi
+    onlineStore:
+      persistence:
+        store:
+          type: redis
+          secretRef:
+            name: feast-redis-config
+          secretKeyName: redis