Written by: Nimesh Chakravarthi, Co-founder & CTO, Struct
Key Takeaways for Modern On-Call Teams
- Root cause analysis for software on-call relies on correlating distributed traces, logs, and metrics across multiple tools instead of physical evidence.
- Struct automates the first four steps of the classic five-step RCA framework and delivers impact summaries, data collection, causal factor identification, and root cause detection within minutes of an alert.
- Manual RCA creates predictable problems such as context switching, alert fatigue, tribal knowledge bottlenecks, and inconsistent runbook execution that stretch triage to 30–45 minutes.
- Struct ingests alerts from Slack or PagerDuty, correlates data across observability platforms and GitHub, generates dynamic dashboards, and supports conversational follow-up without leaving Slack.
- Struct reduces triage time by 80% for engineering teams and enables safe on-call shifts for junior engineers; see how automated investigations remove manual delays.
Five Practical Steps of Root Cause Analysis in Software
The classic five-step RCA framework maps cleanly onto software incident response, and Struct automates the first four steps.
Step 1 — Define the problem. In software, this means defining the blast radius. Teams need to know which users are affected, which services are degraded, and how severe the impact is. Struct delivers an instant impact summary directly in the Slack alert thread before the engineer opens a laptop.
Step 2 — Collect data. Manual triage requires switching between Datadog, CloudWatch, Sentry, and GitHub to gather logs, metrics, and traces, which fragments context and slows investigation. Struct eliminates this fragmentation by querying all connected sources simultaneously and consolidating the evidence into a single dynamically generated dashboard.
Step 3 — Identify causal factors. Struct correlates anomalies across the full stack, including Azure traces, Datadog metrics, and Sentry exceptions. It constructs a unified timeline that shows exactly when each signal appeared and in what sequence.
Step 4 — Identify the root cause. As Deepan Mehta and Nimesh Chakravarthi, co-founders of Struct, put it: “Struct gets you from alert → root cause before you even open your laptop.” The AI pinpoints the most probable root cause and surfaces suggested fixes within 5–10 minutes of the alert firing.
Step 5 — Implement and verify the fix. This step requires human judgment. Struct supports it by handing off confirmed root cause context to a local CLI, an AI coding agent, or a direct pull request. That handoff closes the loop from detection to resolution.
Common Root Cause Analysis Mistakes in On-Call
Engineering teams that rely on manual RCA in 2026 run into the same patterns of failure.
- Manual context switching. Engineers jump between Datadog, Sentry, CloudWatch, and GitHub at 3 AM while half-asleep. The process is slow and error-prone, and critical correlations get missed. Triage often takes 30–45 minutes before anyone attempts a fix.
- Alert fatigue. High-volume alert channels train engineers to deprioritize notifications. Severe, customer-facing outages get buried in noise, and teams miss the signal until customers report it.
- Tribal knowledge bottlenecks. Senior engineers hold the systemic context required to debug complex failures. New hires cannot safely take on-call shifts without escalating every alert, which drags senior engineers away from product work around the clock.
- Reactive AI usage. Engineers paste logs into ChatGPT or Claude after waking up, yet still need to gather the data, manage context window limits, and prompt-engineer during an active outage. That workflow rarely feels fast or reliable.
- No standardized runbook enforcement. Without automated runbook execution, every engineer investigates differently. Outcomes stay inconsistent, and post-incident reviews become harder to act on.
Struct customers working at large scale with many services report an 80% reduction in triage time. That reduction removes the manual context-switching window and turns a 45-minute investigation into a 5-minute review.
Cut your triage time from 45 minutes to 5 with automated runbook execution.
Struct’s End-to-End Automated RCA Workflow
Struct delivers a fully automated workflow from alert intake to root cause delivery, which directly addresses the manual failure modes described above.
Alert intake. Struct listens to designated Slack channels or PagerDuty integrations. When an alert fires, it begins the investigation immediately, with no human trigger required.
Multi-tool correlation. Struct queries Datadog, Sentry, AWS CloudWatch, GCP Logs, Azure Traces, Grafana, Prometheus/Loki, Sumo Logic, Better Stack, and GitHub at the same time. It correlates trace IDs, error rates, deployment events, and log anomalies across all sources in a single pass.
Dynamic dashboard creation. Struct generates an issue-specific dashboard that contains relevant charts pulled directly from observability tools, a unified cross-stack timeline, and the supporting evidence used to reach its conclusion. Engineers get a single pane of glass for the exact incident.
Conversational follow-up in Slack. Engineers can tag Struct in the alert thread to pull logs from a specific time window, test an alternative hypothesis, or verify impact on a specific user. All of this happens without leaving Slack.
Struct deploys in five to ten minutes, integrates with leading observability platforms, Slack, GitHub, Linear, and is fully SOC 2 and HIPAA compliant. The platform achieves an 85–90%+ helpful investigation rate across automated first-pass analyses.
Struct vs Fabrico for Incident Investigations
| Mechanism | Fabrico | Struct | Outcome |
|---|---|---|---|
| Evidence source | Camera images, PLC data, OEE metrics | Logs, traces, metrics, GitHub diffs | Struct ingests software telemetry; Fabrico cannot |
| Investigation trigger | Manual work order creation | Automatic on alert fire (zero clicks) | Struct removes human-initiated triage delay |
| Time to root cause | Manual, document-driven process | 5–10 minutes automated | Struct delivers root cause before the engineer opens a laptop |
| Fix handoff | Corrective action logged in work order | PR creation or coding agent handoff | Struct closes the loop from alert to code resolution |
Fabrico’s workflow is purpose-built for physical production quality. It has no integration surface for Datadog anomalies, Sentry exceptions, or distributed trace correlation. For software on-call, it belongs to a different tool category.
Why Struct Matters to On-Call ICs and Engineering Leaders
For on-call ICs. Struct removes the 3 AM log-hunting expedition. By the time an engineer acknowledges an alert, the blast radius, root cause, and suggested fix already sit in Slack. Junior engineers receive a reliable, heavily contextualized starting point for every alert, which makes it safe to take on-call shifts without deep systemic knowledge.
For engineering leadership. This triage compression directly protects SLA compliance windows. When a 60-minute SLA is at risk, the difference between a 45-minute investigation and a 5-minute review determines whether you breach or deliver with time to spare. Senior engineers stop acting as the permanent escalation path for every incident, which restores product development velocity. Onboarding new engineers onto on-call rotations accelerates because Struct behaves like an automated senior engineer for the first pass.
A Series A fintech company with over 40 engineers integrated Struct in under 10 minutes. Their mandatory 30–45 minute context-gathering phase dropped to under 5 minutes per incident, which protected SLAs and enabled newer engineers to manage on-call shifts independently.
Give your team safe, fast on-call shifts with automated investigations.
Struct Integrations and 10-Minute Setup Checklist
Struct connects to the tools engineering teams already use across three categories.
- Triggers: Slack, PagerDuty, Sentry, Linear, Jira, Asana
- Observability: Datadog, AWS CloudWatch, GCP Logs, Azure Logs/Traces, Grafana, Prometheus/Loki, Sumo Logic, Better Stack
- Code context: GitHub
Teams can get Struct running in under 10 minutes.
- Authenticate your alert source, such as a Slack channel or PagerDuty.
- Connect your code repository in GitHub.
- Authenticate your observability platform, such as Datadog or CloudWatch.
- Designate which Slack channels Struct should monitor.
- Paste in your existing on-call runbook or custom correlation ID formats.
- Enable auto-investigations.
- Trigger a test alert and review the automated dashboard output.
No lengthy enterprise deployment. Unlike traditional enterprise tools that require weeks of engineering time, Struct deploys in five minutes and is SOC 2 Type II and HIPAA compliant out of the box, which removes both integration burden and compliance gaps.
Start your first automated investigation before your next standup.
Frequently Asked Questions
Is Struct secure enough for companies with strict compliance requirements?
Struct is fully SOC 2 Type II and HIPAA compliant. Logs and telemetry data are accessed and processed ephemerally, and they are not stored beyond the scope of the active investigation. For Seed-to-Series C companies, this compliance posture covers the vast majority of enterprise and regulated-industry requirements.
Can Struct follow our team’s specific on-call runbooks?
Yes. Struct supports custom instructions, proprietary correlation ID formats, and direct runbook input. Engineers paste their existing on-call runbook into Struct’s configuration, and the AI follows those exact operational procedures every time a matching alert fires. Composable widgets allow teams to guarantee specific visual data is always surfaced for defined alert types.
What happens if our logging and telemetry quality is poor?
Struct’s output quality is directly tied to the quality of the data it can access. Teams already using Sentry for exceptions, Datadog or cloud logs for metrics, and Slack for alerting will see the strongest results. If a system lacks basic trace IDs, structured logging, or alerting triggers, Struct cannot infer system state from code analysis alone. Improving logging hygiene before or alongside Struct deployment produces the best outcomes.
Will Struct work if our logs cannot leave our VPC?
Struct currently requires access to logs and telemetry via its standard integrations with AWS, GCP, Datadog, and similar providers. Organizations with strict on-premise-only policies that prohibit any log egress are not a fit for the current product. The Enterprise tier includes sidecar and on-prem support options for teams with partial VPC constraints, which is best discussed directly during a demo.
How does Struct affect MTTR, and can we measure the improvement?
Struct directly compresses the investigation and triage phase of incident response, which is the portion of MTTR that occurs between alert fire and root cause identification. Teams track this by comparing pre- and post-Struct investigation timestamps in their incident management tooling. The reduction translates directly into lower MTTR and reduced SLA breach risk.
Conclusion: Struct for Software, Fabrico for Manufacturing
Fabrico is a well-designed tool for manufacturing quality management. Its camera, PLC, and OEE-based RCA workflow solves real problems on factory floors. It does not apply to software on-call incident response, where the evidence is distributed telemetry, the timeline is measured in milliseconds, and a 45-minute manual investigation can mean a breached SLA and a burned-out engineer.
Struct is built for that environment. It automates the first four steps of RCA the moment an alert fires, delivers root cause and impact summaries in Slack within 5–10 minutes, and cuts triage time by 80%. A 3 AM crisis becomes a 5-minute review. Setup takes about 10 minutes, and the first automated investigation can run the same day.
Let Struct handle root cause analysis before you even open your laptop.
