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To avoid “bill shocks,” Palo Alto Networks deploys custom AI-powered cost anomaly detection
- Palo Alto Networks has deployed a custom AI-powered cost anomaly detection solution developed with Google Cloud to help customers manage their cloud costs and avoid bill shocks.
- The problem occurs when AI systems and workloads grow and services become more complex leading to unexpected charges.
- Unexpected charges can arise from a variety of factors such as human error and mismanagement, unexpected workload changes, and lack of proactive governance and cost transparency.
- By implementing real-time cost monitoring and analysis, businesses can identify and address potential anomalies before they result in unexpected expenses. This approach enables businesses to maintain financial control and support their growth objectives.
- Google Cloud launched the Cost Anomaly Detection as part of the Cost Management toolkit to help customers manage their cloud spend, which automatically detects anomalies for your Google Cloud projects and empowers teams with details to alert and provide root-cause analysis.
- Palo Alto Networks created a customised solution to identify anomalies based on labels, such as applications or products which span across Google Cloud projects, and provide more control over anomaly variables that are detected and alerted to its teams.
- Palo Alto Networks partnered with Google Cloud Consulting to train the ARIMA+ model with billing data from its applications using BigQuery ML.
- The ARIMA+ model allowed Palo Alto Networks to generate a baseline spend with upper and lower bounds for its cost anomaly solution.
- Looker, Google Cloud’s business intelligence platform, serves as the foundation for custom data modelling and visualisation, seamlessly integrating with Palo Alto Networks’ existing billing data infrastructure.
- By leveraging the power of AI and partnering with Google Cloud, Palo Alto Networks is enabling businesses to unlock the full potential of AI while ensuring responsible and sustainable cloud spending.
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