To effectively monitor the usage of Google Embedding 2, which is part of Google's Generative AI offerings on Vertex AI and the Gemini API, you need to leverage Google Cloud's robust monitoring and billing tools. This primarily involves using Google Cloud Monitoring for operational metrics and Google Cloud Billing for cost analysis. These tools provide comprehensive insights into API calls, resource consumption, error rates, and associated expenses, helping you manage your deployments efficiently.
For operational monitoring, Google Cloud Monitoring (formerly Stackdriver) is the primary service. It allows you to track key metrics related to your Google Embedding 2 API calls, such as traffic (requests per second), error rates, and latency. You can access these metrics through the Google Cloud console, specifically within the APIs & Services section or the Vertex AI Endpoints page for models deployed there. Cloud Monitoring provides granular data, enabling you to create custom dashboards, set up alerts for unusual activity or performance degradation, and use the Metrics Explorer for deeper analysis by filtering and aggregating data. For instance, you can combine request count metrics with HTTP Response Code class filters to monitor error rates over time or analyze the 95th percentile latency of requests.
Cost monitoring for Google Embedding 2 is handled through Google Cloud Billing. This service allows you to track and analyze the financial aspects of your embedding usage. You can view detailed billing reports that break down costs by project, service (e.g., Vertex AI), and even specific SKUs related to token usage. To gain more granular insights into AI/ML costs, it's highly recommended to enable "Detailed usage cost data" export to BigQuery. This allows you to perform advanced cost management, create custom reports using BigQuery SQL, and even build dashboards for anomaly detection. While billing reports provide cost data, they typically have a delay of a few hours, so for real-time cost warnings, you should complement them with Cloud Monitoring alerts. Gemini Cloud Assist in Cloud Billing Reports also provides AI assistance for creating and summarizing cost reports. Additionally, when working with vector databases like Milvus or Zilliz Cloud to store the embeddings generated by Google Embedding 2, monitoring their respective usage and costs within their own platforms or through integrated cloud monitoring solutions will be crucial for a holistic view of your AI application's resource consumption.