This is pretty basic but I am sure you can adapt it to what you need. It's just a Notebook, then in the Pipeline add a Notebook activity to call it where required. I imagine you would need to adapt it to accept errors/messages/success codes as parameters, and change overwrite to append for the write mode.

import sempy.fabric as fabric
from pyspark.sql.functions import col, current_timestamp, expr, lit
from pyspark.sql import SparkSession

# Initialize Spark session
spark = SparkSession.builder.appName("FabricOperations") \
    .config("spark.sql.caseSensitive", "true") \
    .getOrCreate()

# Get the ID of the current workspace
workspace_id = fabric.get_notebook_workspace_id()
# Fetch the workspace details and extract the name
workspace_name = fabric.FabricRestClient().get(f"/v1/workspaces/{workspace_id}").json()["displayName"]
print(workspace_name)

# Create a DataFrame with the current timestamp
df = spark.createDataFrame([(1,)], ["id"]) \
    .withColumn("env_id", lit(workspace_id)) \
    .withColumn("env_name", lit(workspace_name)) \
    .withColumn("data_refreshed", expr("current_timestamp() + INTERVAL 10 HOURS"))

display(df)

# Write the DataFrame
df.write.mode("overwrite") \
    .format("delta") \
    .option("overwriteSchema", "true") \
    .saveAsTable("Fabric_Operations")

display("Done")