[docs] Update the monitoring introduction for Flink agents

Author: GreatEugenius

docs/content/docs/operations/monitoring.md

@@ -24,24 +24,115 @@ under the License.
 
 ## Metric
 
-{{< hint warning >}}
-**TODO**: How to use add custom metrics.
+### Built-in Metrics
 
-**TODO**: List of all built-in Metrics.
+We offer data monitoring for built-in metrics, which includes events and actions. Events provide general-level metrics, while actions deliver both general-level and type-specific data metrics.
 
-**TODO**: How to check the metrics with Flink executor.
-{{< /hint >}}
+| Component Type                  | Count                        | Meter                          |
+|-------------------------------|------------------------------|--------------------------------|
+| Agent (Operator Builtin)      | NumOfInput<br>NumOfOutput    | NumOfInputPerSec<br>NumOfOutputPerSec |
+| Event                         | numOfEventProcessed          | numOfEventProcessedPerSec      |
+| Action                        | numOfActionsExecuted         | numOfActionsExecutedPerSec     |
+| Pre-Action                    | numOfActionsExecuted         | numOfActionsExecutedPerSec     |
+
+#### 
+
+### How to add custom metrics
+
+In Flink Agents, users implement their logic by defining custom Actions that respond to various Events throughout the Agent lifecycle. To support user-defined metrics, we introduce two new properties: `agent_metric_group` and `action_metric_group` in the RunnerContext. These properties allow users to create or update global metrics and independent metrics for actions. For an introduction to metric types, please refer to the [Metric types documentation](https://nightlies.apache.org/flink/flink-docs-release-1.20/docs/ops/metrics/#metric-types).
+
+Here is the user case example:
+
+``````python
+class MyAgent(Agent):
+    @action(InputEvent)
+    @staticmethod
+    def first_action(event: Event, ctx: RunnerContext):  # noqa D102
+        start_time = time.time_ns()
+        input = event.input
+        content = input.get_review() + " first action."
+        ctx.send_event(MyEvent(value=content))
+
+        # Access the main agent metric group
+        metrics = ctx.agent_metric_group
+
+        # Update global metrics
+        metrics.get_counter("numInputEvent").inc()
+        metrics.get_meter("numInputEventPerSec").mark()
+
+        # Access the per-action metric group
+        action_metrics = ctx.action_metric_group
+        action_metrics.get_histogram("actionLatencyMs") \
+            .update(int(time.time_ns() - start_time) // 1000000)
+
+    @action(MyEvent)
+    @staticmethod
+    def second_action(event: Event, ctx: RunnerContext):  # noqa D102
+        input = event.value
+        content = input + " second action."
+        ctx.send_event(OutputEvent(output=content))
+
+        # Access the main agent metric group
+        metrics = ctx.agent_metric_group
+
+        # Update global metrics
+        metrics.get_counter("numMyEvent").inc()
+        metrics.get_meter("numMyEventPerSecond").mark()
+
+        # Creating and tracking metrics for MyEvent using submetric group
+        if isinstance(event, MyEvent):
+            sub_metrics = metrics.action_metric_group
+            sub_metrics.get_counter("numEvent").inc()
+            sub_metrics.get_meter("numEventPerSecond").mark()
+``````
+
+
+
+### How to check the metrics with Flink executor
+
+We can check the metric result in the WebUI of Flink Job:
+
+{{< img src="/fig/operations/metricwebui.png" alt="Metric Web UI" >}}
 
 ## Log
 
-{{< hint warning >}}
-**TODO**: How to add log in Flink Agents.
+The Flink Agents' log system uses Flink's logging framework. For more details, please refer to the [Flink log system documentation](https://nightlies.apache.org/flink/flink-docs-master/docs/deployment/advanced/logging/).
+
+### How to add log in Flink Agents
+
+For adding logs in Java code, you can refer to [Best practices for developers](https://nightlies.apache.org/flink/flink-docs-master/docs/deployment/advanced/logging/#best-practices-for-developers). In Python, you can add logs using `logging`. Here is a specific example:
+
+```python
+@action(InputEvent)
+@staticmethod
+def process_input(event: InputEvent, ctx: RunnerContext) -> None:
+    logging.info("Processing input event: %s", event)
+    # the action logic
+```
+
+### How to check the logs with Flink executor
 
-**TODO**: How to check the logs with Flink executor.
-{{< /hint >}}
+We can check the log result in the WebUI of Flink Job:
+
+{{< img src="/fig/operations/logwebui.png" alt="Log Web UI" >}}
 
 ## Event Log
 
-{{< hint warning >}}
-**TODO**: How to use and check the event logs.
-{{< /hint >}}
+Currently, the system supports **File-based Event Log** as the default implementation. Future releases will introduce support for additional types of event logs and provide configuration options to let users choose their preferred logging mechanism.
+
+### File Event Log
+
+The **File Event Log** is a file-based event logging system that stores events in structured files within a flat directory. Each event is recorded in **JSON Lines (JSONL)** format, with one JSON object per line.
+
+#### File Structure
+
+The log files follow a naming convention consistent with Flink's logging standards and are stored in a flat directory structure:
+
+```
+{baseLogDir}/
+├── events-{jobId}-{taskName}-{subtaskId}.log
+├── events-{jobId}-{taskName}-{subtaskId}.log
+└── events-{jobId}-{taskName}-{subtaskId}.log
+```
+
+By default, all File-based Event Logs are stored in the `flink-agents` subdirectory under the system temporary directory (`java.io.tmpdir`). In future versions, we plan to add a configurable parameter to allow users to customize the base log directory, providing greater control over log storage paths and lifecycle management.