docs: sync fern with observability doc changes (#5795)

Signed-off-by: Anant Sharma <anants@nvidia.com>

fern/pages/observability/metrics-developer-guide.md

@@ -128,141 +128,9 @@ let counter = endpoint.metrics().create_counter(
 
 ---
 
-## Metrics API in Python
-
-Python components can create and manage Prometheus metrics using the same metrics API through Python bindings.
-
-### Available Methods
-
-- `endpoint.metrics.create_counter()` / `create_intcounter()`: Create a counter metric
-- `endpoint.metrics.create_gauge()` / `create_intgauge()`: Create a gauge metric
-- `endpoint.metrics.create_histogram()`: Create a histogram metric
-- `endpoint.metrics.create_countervec()` / `create_intcountervec()`: Create a counter with labels
-- `endpoint.metrics.create_gaugevec()` / `create_intgaugevec()`: Create a gauge with labels
-- `endpoint.metrics.create_histogramvec()`: Create a histogram with labels
-
-All metrics are imported from `dynamo.prometheus_metrics`.
-
-### Creating Metrics
-
-```python
-from dynamo.runtime import DistributedRuntime
-
-drt = DistributedRuntime()
-endpoint = drt.namespace("my_namespace").component("my_component").endpoint("my_endpoint")
-
-# Simple metrics
-requests_total = endpoint.metrics.create_intcounter(
-    "requests_total",
-    "Total requests"
-)
-
-active_connections = endpoint.metrics.create_intgauge(
-    "active_connections",
-    "Active connections"
-)
-
-latency = endpoint.metrics.create_histogram(
-    "latency_seconds",
-    "Request latency",
-    buckets=[0.001, 0.01, 0.1, 1.0, 10.0]
-)
-```
-
-### Using Metrics
-
-```python
-# Counters
-requests_total.inc()
-requests_total.inc_by(5)
-
-# Gauges
-active_connections.set(42)
-active_connections.inc()
-active_connections.dec()
-
-# Histograms
-latency.observe(0.023)  # 23ms
-```
-
-### Vector Metrics with Labels
-
-```python
-# Create vector metrics with label names
-requests_by_model = endpoint.metrics.create_intcountervec(
-    "requests_by_model",
-    "Requests by model",
-    ["model_type", "model_size"]
-)
-
-memory_by_gpu = endpoint.metrics.create_intgaugevec(
-    "gpu_memory_bytes",
-    "GPU memory by device",
-    ["gpu_id", "memory_type"]
-)
-
-# Use with specific label values
-requests_by_model.inc({"model_type": "llama", "model_size": "7b"})
-memory_by_gpu.set(8192, {"gpu_id": "0", "memory_type": "allocated"})
-```
-
-### Advanced Features
-
-**Constant labels:**
-```python
-counter = endpoint.metrics.create_intcounter(
-    "requests_total",
-    "Total requests",
-    [("region", "us-west"), ("env", "prod")]
-)
-```
-
-**Metric introspection:**
-```python
-print(counter.name())            # "my_namespace_my_component_my_endpoint_requests_total"
-print(counter.const_labels())    # {"dynamo_namespace": "my_namespace", ...}
-print(gauge_vec.variable_labels())  # ["model_type", "model_size"]
-```
-
-**Update patterns:**
-
-Background thread updates:
-```python
-import threading
-import time
-
-def update_loop():
-    while True:
-        active_connections.set(compute_current_connections())
-        time.sleep(2)
-
-threading.Thread(target=update_loop, daemon=True).start()
-```
-
-Callback-based updates (called before each `/metrics` scrape):
-```python
-def update_metrics():
-    active_connections.set(compute_current_connections())
-
-endpoint.metrics.register_callback(update_metrics)
-```
-
-### Examples
-
-Example scripts: [lib/bindings/python/examples/metrics/](https://github.com/ai-dynamo/dynamo/tree/main/lib/bindings/python/examples/metrics/)
-
-```bash
-cd ~/dynamo/lib/bindings/python/examples/metrics
-DYN_SYSTEM_PORT=8081 ./server_with_loop.py
-DYN_SYSTEM_PORT=8081 ./server_with_callback.py
-```
-
----
-
 ## Related Documentation
 
 - [Metrics Overview](metrics.md)
 - [Prometheus and Grafana Setup](prometheus-grafana.md)
 - [Distributed Runtime Architecture](../design-docs/distributed-runtime.md)
-- [Python Metrics Examples](https://github.com/ai-dynamo/dynamo/tree/main/lib/bindings/python/examples/metrics/)