Google Cloud Monitoring Features
What are the features of Google Cloud Monitoring?
Monitoring
- Usage Monitoring
- Database Monitoring
- API Monitoring
- Real-Time Monitoring - Cloud Infrastructure Monitoring
Administration
- Activity Monitoring
- Multi-Cloud Management
- Automation
Analysis
- Reporting
- Dashboards and Visualizations
- Spend Forecasting and Optimization
Google Cloud Monitoring Categories on G2
Filter for Features
Monitoring
Usage Monitoring | Based on 23 Google Cloud Monitoring reviews. Tracks infrastructure resource needs and alerts administrators or automatically scales usage to minimize waste. | 88% (Based on 23 reviews) | |
Database Monitoring | Monitors performance and statistics related to memory, caches and connections. This feature was mentioned in 23 Google Cloud Monitoring reviews. | 86% (Based on 23 reviews) | |
API Monitoring | As reported in 22 Google Cloud Monitoring reviews. Detects anomalies in functionality, user accessibility, traffic flows, and tampering. | 87% (Based on 22 reviews) | |
Real-Time Monitoring - Cloud Infrastructure Monitoring | Constantly monitors system to detect anomalies in real time. 23 reviewers of Google Cloud Monitoring have provided feedback on this feature. | 90% (Based on 23 reviews) | |
Security and Compliance Monitoring | Enables monitoring of security and compliance standards across cloud infrastructure. | Not enough data | |
Performance Baselines | Not enough data | ||
Performance Analysis | Not enough data | ||
Performance Monitoring | Not enough data | ||
AI/ML Assistance | Not enough data | ||
Multi-System Monitoring | Not enough data |
Administration
Activity Monitoring | As reported in 22 Google Cloud Monitoring reviews. Actively monitor status of work stations either on-premise or remote. | 90% (Based on 22 reviews) | |
Multi-Cloud Management | Allows users to track and control cloud spend across cloud services and providers. This feature was mentioned in 23 Google Cloud Monitoring reviews. | 84% (Based on 23 reviews) | |
Automation | Efficiently scales resource usage to optimize spend whith increased or decreased resource usage requirements. This feature was mentioned in 23 Google Cloud Monitoring reviews. | 83% (Based on 23 reviews) | |
Auto-Scaling & Resource Optimization | Automatically scales resources based on demand and optimizes for performance and cost. | Not enough data |
Analysis
Reporting | Based on 22 Google Cloud Monitoring reviews. Creates reports outlining resource, underutilization, cost trends, and/or functional overlap. | 88% (Based on 22 reviews) | |
Dashboards and Visualizations | As reported in 23 Google Cloud Monitoring reviews. Presents information and analytics in a digestible, intuitive, and visually appealing way. | 90% (Based on 23 reviews) | |
Spend Forecasting and Optimization | Ability to project spend based on contracts, usage trends, and predicted growth. 21 reviewers of Google Cloud Monitoring have provided feedback on this feature. | 87% (Based on 21 reviews) |
Response
Dashboards and Visualization | Not enough data | ||
Incident Alerting | Not enough data | ||
Root Cause Analysis (RCA) | Not enough data |
Performance
Real User Monitoring (RUM) | Captures and analyzes each transaction by users of a website or application in real time. | Not enough data | |
Second by Second Metrics | Provides high-frequency metrics data. | Not enough data |
Functionality
Synthetic Monitoring | Monitors and test apps to address issues before they affect end users. | Not enough data | |
Dynamic Transaction Mapping | Provides dynamic end-to-end maps of every single transaction. | Not enough data | |
Load Balancing | Automatically adjusts resources base on application usage. | Not enough data | |
Cloud Observability | Monitors cloud microservices, containers, kubernetes, and other cloud native software. | Not enough data |
Agentic AI - Application Performance Monitoring (APM)
Autonomous Task Execution | Capability to perform complex tasks without constant human input | Not enough data | |
Cross-system Integration | Works across multiple software systems or databases | Not enough data | |
Adaptive Learning | Improves performance based on feedback and experience | Not enough data | |
Proactive Assistance | Anticipates needs and offers suggestions without prompting | Not enough data | |
Decision Making | Makes informed choices based on available data and objectives | Not enough data |
Agentic AI - Cloud Infrastructure Monitoring
Multi-step Planning | Ability to break down and plan multi-step processes | Not enough data | |
Cross-system Integration | Works across multiple software systems or databases | Not enough data | |
Adaptive Learning | Improves performance based on feedback and experience | Not enough data | |
Natural Language Interaction | Engages in human-like conversation for task delegation | Not enough data | |
Proactive Assistance | Anticipates needs and offers suggestions without prompting | Not enough data | |
Decision Making | Makes informed choices based on available data and objectives | Not enough data |
AI Automation - Cloud Infrastructure Monitoring
AI-Powered Anomaly Detection | Utilizes machine learning to automatically detect and alert on unusual patterns in infrastructure metrics. | Not enough data | |
AI-Driven Insight Recommendations | Provides AI-generated insights and actionable recommendations to optimize resource performance and cost. | Not enough data |
