oraclecloud-observability

name	oraclecloud-observability
description	Set up programmatic monitoring, logging, and alarms for OCI resources. Use when configuring OCI Monitoring metrics, creating alarm rules, publishing custom metrics, or searching logs via the Logging service. Trigger with "oraclecloud observability", "oci monitoring", "oci alarms", "oci logging", "oracle cloud observability".
allowed-tools	Read, Write, Edit, Bash(pip:*), Grep
version	1.7.0
license	MIT
author	Jeremy Longshore <[e-mail]>
tags	["saas","oraclecloud","oci"]
compatibility	Designed for Claude Code

Oracle Cloud Observability

Overview

Set up programmatic monitoring for OCI infrastructure using the Monitoring, Logging, and Notifications services. The OCI Console buries these features behind nested menus, and the status page has historically failed to acknowledge outages (e.g., London region, January 2026). This skill builds monitoring you control through code — metric queries, alarm rules, custom metric publishing, and log searches — so you are never surprised by an outage you should have caught.

Purpose: Create a code-driven observability stack that queries metrics, fires alarms, publishes custom metrics, and searches logs without depending on the OCI Console.

Prerequisites

• OCI tenancy with an API signing key in ~/.oci/config
• Python 3.8+ with pip install oci
• Compartment OCID containing the resources to monitor
• IAM policies granting manage alarms and read metrics in the target compartment
• Notification topic created for alarm destinations (or create one in Step 4)

Instructions

Step 1: Query Metrics with MonitoringClient

OCI publishes built-in metrics for compute, networking, block storage, and more. Query them programmatically:

import oci
from datetime import datetime, timedelta

config = oci.config.from_file("~/.oci/config")
monitoring = oci.monitoring.MonitoringClient(config)

# Query CPU utilization for all instances in a compartment
response = monitoring.summarize_metrics_data(
    compartment_id="ocid1.compartment.oc1..example",
    summarize_metrics_data_details=oci.monitoring.models.SummarizeMetricsDataDetails(
        namespace="oci_computeagent",
        query='CpuUtilization[5m]{availabilityDomain = "Uocm:US-ASHBURN-AD-1"}.mean()',
        start_time=(datetime.utcnow() - timedelta(hours=1)).isoformat() + "Z",
        end_time=datetime.utcnow().isoformat() + "Z"
    )
)

for metric in response.data:
    for dp in metric.aggregated_datapoints:
        ()