Struct
UnclaimedAutomate on-call runbooks and proactively root-cause engineering alerts and bugs.
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What is Struct?
Struct (debugging): Automate on-call runbooks and proactively root-cause engineering alerts and bugs. Struct is an AI-powered platform designed to automate the investigation and resolution of engineering alerts and bugs. It achieves this by cross-referencing data from various sources including logs, metrics, traces, and your codebase. Key capabilities: Automated engineering alert investigation, Root cause analysis, Impact analysis, Suggested fixes for alerts, On-demand investigation via @mention (e.g., in Slack). Struct ships a free plan plus paid tiers that unlock as usage grows. Buyers most often compare Struct against FireHydrant, Rootly, Squadcast.
TL;DR - Struct
- Automates on-call incident investigation and root cause analysis.
- Integrates with observability, logging, and collaboration tools for comprehensive context.
- Provides suggested fixes and learns from past incidents to improve over time.
Pricing: Free plan available
Best for: Growing teams
Pros & Cons
Pros
- Significantly reduces manual investigation time for engineers.
- Provides a unified view by integrating with a wide range of existing tools.
- Improves over time by learning from historical incidents.
- Offers quick remediation options like one-click PRs.
- Strong security and compliance with SOC2 and HIPAA.
Cons
- Reliance on credits for usage, which may require monitoring and topping up.
- The free tier is limited to one user, which might not be sufficient for team evaluation.
Preview
Key Features
Automated engineering alert investigationRoot cause analysisImpact analysisSuggested fixes for alertsOn-demand investigation via @mention (e.g., in Slack)Integration with observability platforms (e.g., Sentry, Datadog)Integration with cloud log providersIntegration with work tools (e.g., Slack, Linear, Asana, GitHub)
Pricing
Freemium
Struct offers a generous free tier with optional paid upgrades for advanced features.
About Struct
By Toolradar Team·
Struct is an AI-powered platform designed to automate the investigation and resolution of engineering alerts and bugs. It achieves this by cross-referencing data from various sources including logs, metrics, traces, and your codebase. The tool aims to significantly reduce the time engineers spend on investigations, providing root causes, impact analyses, and suggested fixes automatically.
Struct is built for fast-moving engineering teams and on-call engineers who need to quickly diagnose and resolve incidents. It integrates with leading observability platforms, cloud log providers, and collaboration tools to provide a unified view of the entire stack. By automating the initial investigation and offering tools for deeper analysis, Struct helps teams improve incident response times and maintain system reliability.
The platform also learns from past issues and investigations to build on-call intelligence over time, further enhancing its automation capabilities. It emphasizes security with logical data isolation and no data training, while being SOC2 and HIPAA compliant.
How we evaluate tools →Source: struct.ai
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Struct FAQ
What types of data does Struct cross-reference to identify root causes?
Struct cross-references logs, metrics, traces, and your codebase to proactively identify the root cause of engineering alerts and bugs.
How does Struct provide suggested fixes for identified issues?
Struct automatically investigates engineering alerts and, as part of its response, provides a root cause, impact analysis, and a suggested fix. It also allows for one-click creation of pull requests or handoff to a coding agent with full context.
Which third-party platforms and tools can Struct integrate with?
Struct integrates with leading observability and alerting platforms like Sentry and Datadog, various cloud log providers, and work tools such as Slack, Linear, Asana, and GitHub.
How does Struct ensure the security and privacy of user data?
Struct ensures security by logically isolating user data and explicitly stating that user data is never trained on. The platform is also fully SOC2 and HIPAA compliant.
What is 'on-call intelligence' and how does Struct build it?
On-call intelligence refers to Struct's ability to learn and improve its investigation capabilities over time. It builds this intelligence by leveraging context from past issues, alerts, and investigations conducted within the platform.
Can Struct be used for on-demand investigations, or only for automated alerts?
While Struct automatically investigates engineering alerts as they occur, users can also @mention Struct to initiate an investigation on-demand for any issue.
Source: struct.ai