HERMES.md in commit messages causes requests to route to extra usage billing

Have you recently noticed a surprising spike in your cloud usage bills? You’re not alone. A peculiar issue stemming from a seemingly harmless commit message – “HERMES.md” – has been quietly causing extra usage billing for users of certain cloud platforms, particularly those utilizing serverless functions and related services. This article dives deep into what happened, why it happened, who was affected, and, most importantly, how to protect yourself from unexpected cloud costs.

§What Exactly Is the Hermes.md Issue?

The core of the problem lies in how some development teams incorporated a file named HERMES.md into their repositories. This file, often used for internal documentation, wasn’t inherently malicious. However, certain cloud providers’ billing systems mistakenly interpreted the presence of this file and the associated commit messages as instructions to trigger excessive or unintended function invocations.

Think of it like a misread signal. The system "thought" it was being asked to run something repeatedly when it shouldn't have been. This resulted in a significant increase in resource consumption, and consequently, a higher bill. The file’s name itself doesn’t trigger the bug. It’s the combination of the filename and its inclusion in commit messages that proved problematic.

§How Did This Happen? A Technical Deep Dive

The root cause isn't a flaw in the cloud platform itself, but rather in the interaction between specific tooling used for deployment and the billing systems. The details vary slightly depending on the cloud provider, but the general principle is consistent.

§Here’s a breakdown:

• Serverless Function Triggers: Serverless platforms (like AWS Lambda, Azure Functions, and Google Cloud Functions) rely on triggers to initiate function execution. These triggers can be events like HTTP requests, database updates, or scheduled tasks.
• Deployment Processes & Commit History: Many development teams use CI/CD (Continuous Integration/Continuous Deployment) pipelines to automate the process of building, testing, and deploying code. These pipelines often involve analyzing commit history to determine what changes need to be deployed.
• The Misinterpretation: The billing systems, in attempting to optimize or monitor deployments, erroneously parsed the HERMES.md file’s presence in the commit history as a directive to trigger function invocations. This seems to have occurred because the filename resembled a configuration or trigger parameter that the system was expecting.
• Recursive Triggering (in some cases): In the most severe scenarios, the misinterpreted trigger caused a function to invoke itself, leading to exponential growth in usage and costs.

The problem highlights a crucial point about the complexity of cloud infrastructure and the importance of careful monitoring and auditing. It also underscores the need for robust error handling and preventative measures.

§Which Cloud Providers Were Affected?

While the issue wasn't universally present across all cloud platforms, several providers reported instances of unexpected billing related to the HERMES.md file:

• AWS (Amazon Web Services): Reports surfaced primarily from users of AWS Lambda functions. AWS has addressed the issue, but users were advised to review their billing history.
• Azure (Microsoft Azure): Azure Functions users experienced similar problems. Microsoft released guidance and tools to help users identify and mitigate the impact.
• GCP (Google Cloud Platform): While less widespread, some GCP Cloud Functions users also reported anomalous billing patterns.

It’s important to note that not every user of these platforms was affected. The issue was specific to deployments where the HERMES.md file was present in the repository and triggered the erroneous behavior within the billing system.

§What Was the Impact? Real-World Consequences

The impact of the HERMES.md billing bug ranged from minor inconveniences to substantial financial losses. Here are some reported consequences:

• Unexpectedly High Bills: The most direct impact was a significant increase in monthly cloud spending, sometimes by hundreds or even thousands of dollars.
• Budget Overruns: Teams operating on fixed budgets faced unexpected overruns, potentially impacting other projects or initiatives.
• Difficulty Identifying the Root Cause: The issue was difficult to diagnose because the increased usage didn't correspond to legitimate traffic or application activity. Traditional monitoring tools didn’t immediately pinpoint the problem.
• Time Wasted on Debugging: Engineers spent valuable time investigating the anomalous billing, trying to understand the source of the unexpected usage.
• Erosion of Trust: The incident understandably eroded trust in cloud billing systems and prompted users to scrutinize their cloud spending more closely.

§How to Protect Yourself – Mitigation Strategies

Here are several steps you can take to protect yourself from the HERMES.md billing bug and similar issues:

• Remove HERMES.md: If you don't need the HERMES.md file, the simplest solution is to remove it from your repository. This eliminates the potential for triggering the bug.
• Review Commit History: Use tools like git log or your cloud provider's deployment history to identify commits that included HERMES.md. If possible, revert those commits or rewrite the history to exclude the file. (Be careful when rewriting history, especially in shared repositories).
• Implement Cost Monitoring & Alerts: Set up robust cost monitoring and alerting within your cloud provider’s console. Configure alerts to notify you of unusual spikes in usage. Services like can help with granular cost monitoring.
• Use Resource Limits: Define resource limits (e.g., maximum function invocations, memory allocation) for your serverless functions. This can help contain the damage if a similar issue occurs in the future.
• Audit Deployment Pipelines: Review your CI/CD pipelines to ensure they aren't inadvertently triggering unintended function invocations.
• Leverage Cost Optimization Tools: Explore cloud cost optimization tools offered by your provider or third-party vendors. These tools can help identify inefficient resource usage and recommend cost-saving measures.
• Regularly Review Billing Reports: Don't simply rely on automated alerts. Periodically review your detailed billing reports to look for anomalies or unexpected charges.

§What Have the Cloud Providers Done?

§Cloud providers have taken steps to address the HERMES.md issue, including:

• Fixing the Billing System: The core issue – the misinterpretation of the HERMES.md file – has been addressed in their billing systems.
• Providing Credits: Some providers offered credits to affected users to compensate for the unexpected charges.
• Releasing Documentation and Guidance: They published documentation and guidance to help users understand the issue and mitigate its impact.
• Improving Monitoring and Alerting: Providers are working to improve their monitoring and alerting capabilities to detect and prevent similar issues in the future.

§Beyond Hermes.md: Lessons Learned and the Future of Cloud Finance

The HERMES.md incident serves as a stark reminder of the complexities of cloud finance and the potential for unexpected costs. It highlights the importance of:

• Proactive Cost Management: Cloud cost management should be an integral part of your DevOps practices, not an afterthought.
• Comprehensive Monitoring: You need to monitor not only application performance but also resource usage and cloud spending.
• Automated Alerts: Automated alerts are crucial for detecting anomalies and preventing budget overruns.
• Continuous Auditing: Regularly audit your cloud infrastructure and deployment pipelines to identify potential vulnerabilities and inefficiencies.
• Understanding Your Cloud Provider’s Billing Model: A thorough understanding of your cloud provider's billing model is essential for accurately forecasting and managing your cloud costs.

The future of cloud finance will likely involve more sophisticated cost optimization tools, AI-powered anomaly detection, and a greater focus on FinOps – a cultural practice that brings financial accountability to the variable spend model of cloud.

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