Herald
The AI SRE that catches issues before you know they exist.
What is Herald?
Herald is an AI SRE (Site Reliability Engineering) tool designed to proactively detect and resolve potential issues within software systems before they impact users or trigger alerts. It achieves this by building a comprehensive context graph encompassing observability data, codebase, CI/CD pipelines, and documentation. This allows Herald to understand normal system behavior and identify anomalies with high accuracy, even for novel incidents that traditional threshold-based monitoring would miss. Once an anomaly is detected, Herald automatically investigates across code, infrastructure, and telemetry to pinpoint the root cause. This investigation process is iterative and data-driven, evaluating multiple hypotheses simultaneously and correlating signals from various sources. The system then presents the determined root cause, often with actionable remediation advice, significantly reducing the Mean Time To Resolution (MTTR) and preventing downtime. Developed by a team with expertise in AI, LLMs, and data systems from UC Berkeley's RISELab, Herald is trusted by leading tech companies. It offers a next-generation approach to incident management, moving beyond reactive alert handling to true proactive incident prevention and contextualized problem-solving, aiming to deliver results in days rather than months.
SpecificationsAI-estimated
Key Features of Herald
Use Cases for Herald
Proactive Incident Prevention
Identify and resolve issues before they escalate and impact end-users or trigger traditional alerts.
Automated Root Cause Analysis
Quickly determine the underlying cause of incidents by analyzing code, infrastructure, and telemetry.
Reducing Alert Fatigue
Filter out noise by focusing on validated issues rather than just threshold breaches.
Eliminating Runbook Maintenance
Investigate novel failures without needing pre-documented procedures.
Improving System Reliability
Enhance the stability of complex software systems through continuous AI-driven monitoring and analysis.
Accelerating Incident Response
Significantly reduce Mean Time To Resolution (MTTR) by automating detection and investigation.
How to use Herald?
Learn Your Stack
Herald builds a comprehensive context graph of your observability, codebase, CI/CD, and dependencies to understand normal operations.
Detect Anomalies
Herald automatically builds custom anomaly detection models for each data stream, surfacing validated issues without manual threshold setting.
Investigate Issues
The AI evaluates multiple hypotheses against relevant data sources to determine the root cause of detected anomalies.
Receive Root Cause Analysis
Herald presents the determined root cause, often with suggested remediation steps, enabling quick resolution.
Pros & Cons of Herald
Pros
- Proactive incident detection with 70%+ accuracy on novel incidents.
- Automated root cause analysis across code, infrastructure, and telemetry.
- Eliminates the need for manual threshold tuning and runbook creation.
- Learns from every investigation to improve accuracy and prevent recurring mistakes.
- Fast onboarding and RCA delivery within days.
Cons
- Relatively new technology, reliance on advanced AI and LLMs may require a learning curve for some teams.
- Effectiveness may depend on the quality and completeness of the ingested observability data and codebase.
- Specific pricing details and integration complexity are not fully elaborated in the provided text.
Frequently Asked Questions
How does Herald detect issues before an alert fires?
Herald builds a context graph of your entire system (observability, code, infrastructure, etc.) to understand normal behavior. It then uses custom anomaly detection models to identify deviations that indicate potential issues, often before they reach critical levels.
What makes Herald different from traditional monitoring tools?
Traditional tools rely on pre-set alert thresholds and documented runbooks for known failure modes. Herald detects novel incidents without thresholds and automatically investigates them, eliminating the need for extensive manual documentation and configuration.
How accurate is Herald on new or unknown issues?
Herald demonstrates over 70% accuracy on novel incidents, making it effective for catching unexpected failures that traditional systems might miss.
How quickly can Herald provide a root cause analysis (RCA)?
Herald can determine and provide an RCA within minutes of detecting an issue. The initial setup and learning phase to see the first RCA typically takes days.
Does Herald require manual configuration of thresholds?
No, Herald builds custom anomaly detection models for each data stream, eliminating the need to instrument, tune, and maintain static thresholds.
What kind of issues can Herald investigate?
Herald investigates issues across code, infrastructure, and telemetry, correlating signals from various sources to identify the root cause, even for complex or intermittent problems.
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