Squadcast On-Call vs Automated Incident Investigation

Written by: Nimesh Chakravarthi, Co-founder & CTO, Struct | Last updated: August 19, 2026

Key takeaways for Squadcast and Struct

• Squadcast excels at human coordination through schedules and escalation policies, while automated incident investigation delivers root cause analysis within minutes.

• Teams should add automated investigation when manual triage exceeds 30 minutes or SLA windows are under 60 minutes.

• Combining Squadcast with automated investigation creates a closed-loop workflow that removes the diagnosis gap between paging and resolution.

• Real-world results show teams cutting investigation time from 30 minutes to 2 minutes and reclaiming over 50 engineer-hours monthly.

• Use Struct to automate your on-call runbook and add AI-powered investigation on top of your existing observability stack.

Squadcast on-call features vs automated investigation

Squadcast routes alerts to the correct engineer via schedules and escalation policies, while automated investigation correlates telemetry across your stack to surface root cause within minutes. You keep Squadcast for human ownership and add automated investigation when 30-minute manual triage exceeds your SLA window. The table below maps the two approaches across four dimensions.

Dimension	Squadcast On-Call Management	Automated Incident Investigation (Struct)
Core strength	Scheduling, escalation, human ownership	Root-cause analysis, timeline correlation, incident resolution verification
Time to first insight	Minutes to page, 30–45 minutes to diagnose manually	Automated investigation time for Arcana is 2 minutes with Struct.
Human dependency	High, engineer must hunt logs after the page	Low to moderate, investigation runs before engineer engages
Setup time	Varies by team size and rotation complexity	10 minutes across Datadog, Sentry, GitHub, and PagerDuty

When Squadcast alone is enough and when to add Struct

Squadcast alone is sufficient for low-volume, well-understood services where your team already holds full tribal knowledge and incidents are infrequent. Add automated investigation when alert volume or severity demands faster diagnosis, specifically when manual triage consumes 30–45 minutes per incident, junior engineers are on call without deep systemic context, or SLA windows run under 60 minutes.

A 2024 survey found that 65% of engineers experienced burnout in the past year, driven largely by alert fatigue. This fatigue compounds when a senior engineer spends an entire week reacting to recurring alerts rather than shipping product. That scenario illustrates why the tipping point for adding automated investigation falls into two categories: volume, where alert fatigue reduces product velocity to zero, and severity, where SLA windows leave no room for manual diagnosis.

Struct automatically root-causes engineering alerts by pulling and analyzing metrics, logs, traces, monitors, and code, sitting on top of your existing observability stack, such as Datadog, Grafana, and Sentry, as a dedicated investigation layer. It does not replace those tools.

See how Struct layers on top of your existing stack

Five-step workflow with Squadcast and Struct together

Running Squadcast and Struct together creates a closed-loop workflow that removes the diagnosis gap between the page and the fix.

1. Alert fires in Datadog or Sentry and enters your designated Slack channel.

2. Squadcast pages the on-call engineer based on your schedule and escalation policy.

3. Struct simultaneously queries logs, metrics, traces, and GitHub deploy history, with no human prompt required.

4. Struct posts root cause, blast radius, and incident resolution verification to Slack within minutes.

5. The engineer reviews the dynamically generated dashboard and confirms the diagnosis or escalates with full context already assembled.

This workflow removes the 12-minute coordination overhead that incident.io’s analysis of SRE workflows identifies as pure logistics time before any troubleshooting begins. It also removes the sequential log-hunting phase that automated RCA research identifies as the primary bottleneck in distributed systems diagnosis.

Real metrics from teams using Squadcast and Struct

Arcana, a Series B fintech with 40 engineers, achieved the 2-minute investigation time mentioned above and reclaimed 56 engineer-hours per month after adopting Struct. Arcana runs 2,100+ automated investigations monthly, and Struct reports an 85–90%+ helpful investigation rate overall. Senior engineer hours spent on investigation dropped from approximately 60 to 4 per month, which matches the 56-hour monthly reclamation figure.

Arcana achieved this by layering Struct on top of their existing observability stack rather than replacing it, the same pattern available to any team running Datadog, Sentry, or cloud logs today. Arcana completed the setup process in the timeframe shown above.

This investigation quality translates to the 80% triage time reduction reported by Arcana and other customers, at a scale of thousands of automated investigations per month.

Incident resolution verification with Struct

Incident resolution verification automatically confirms that an incident is resolved by checking live observability data, which closes the loop that Squadcast alone cannot provide. Squadcast tells you who owns the incident, but it does not tell you whether the system has actually recovered.

Struct’s Incident Tracker runs an approximately one-minute automated verification loop against your observability data after a fix is applied. If metrics, error rates, and traces return to baseline, the incident is marked resolved. If anomalies persist, the tracker surfaces that signal immediately rather than waiting for a customer complaint. This closed-loop verification step turns incident management from a human-declared state into an evidence-backed confirmation.

Struct ingests Sentry issues the moment they fire and correlates them with Datadog metrics, cloud infrastructure, GitHub deploy history, logs, and traces to produce a cited root-cause hypothesis, using the same telemetry that verifies resolution after the fix lands.

See incident verification in a live Struct demo

Neutral decision matrix for Squadcast and Struct

Use the criteria below to determine the right configuration for your team.

Stay with Squadcast alone when all of the following are true:

• Incidents are infrequent, with fewer than 10–15 actionable alerts per on-call shift.

• Your team holds complete tribal knowledge for every service in scope.

• SLA windows exceed 60 minutes and manual diagnosis fits comfortably within them.

• Your logging and observability instrumentation is minimal or inconsistent.

Add automated investigation (Struct) when any of the following apply:

• Manual triage consumes 30+ minutes per incident and threatens SLA compliance.

• Junior or new engineers are on call without the systemic context to debug independently.

• Alert volume has reached the point where senior engineers spend more time firefighting than building.

• You need sub-5-minute diagnosis across Datadog, Sentry, GitHub, and PagerDuty without changing your existing stack.

• You require incident resolution verification, with evidence-backed confirmation that the system has recovered, not just a human declaration.

Automated RCA methods for microservice systems require reliable telemetry as input; without basic logging, trace IDs, and alerting triggers, automated investigation cannot deduce system state from code analysis alone. The golden configuration is a team already using Sentry, Datadog or cloud logs, and Slack for alerts.

Frequently asked questions about Struct and Squadcast

This section covers five common questions engineering teams ask when evaluating Struct alongside Squadcast or PagerDuty.

Does Struct replace Squadcast or PagerDuty?

No. Struct is an investigation layer that sits on top of your existing alerting and on-call stack. Squadcast and PagerDuty handle scheduling, escalation, and human ownership. Struct handles the diagnosis, querying logs, metrics, traces, and code the moment an alert fires, and posts results to Slack before the on-call engineer begins manual triage. The two systems are complementary, not competitive.

What telemetry quality does Struct require to produce accurate root cause analysis?

Struct relies on the observability data your stack already produces. Teams using Datadog, Sentry, AWS CloudWatch, GCP Logs, or Grafana with consistent trace IDs and structured logging get the highest-quality investigations. If your system lacks basic logging or alerting triggers, automated investigation cannot fill that gap through code analysis alone. The setup process surfaces these gaps quickly, because Struct connects in under 10 minutes, so you know immediately what data is available.

How does incident resolution verification work in practice?

After a fix is applied, Struct’s Incident Tracker runs an automated verification loop, approximately every minute, against your live observability data. It checks whether error rates, latency, and relevant metrics have returned to baseline. If they have, the incident is confirmed resolved with evidence. If anomalies persist, the tracker flags the ongoing issue rather than relying on a human to declare resolution. This closes the loop that on-call coordination tools alone leave open.

Is Struct compliant with security and data residency requirements?

Struct is SOC 2 Type II and HIPAA compliant, documented at trust.struct.ai. Logs are accessed and processed ephemerally during investigation. For organizations with strict requirements that no logs leave an internal VPC, which require full on-premise deployment, Struct’s Enterprise tier includes sidecar and on-prem support options. Teams with standard Series A–C compliance requirements are covered by the Startup and Growth tiers.

How quickly can a team get from zero to automated investigations?

Setup takes under 10 minutes. You authenticate your alert source, such as Slack or PagerDuty, your code repository, such as GitHub, and your observability context, such as Datadog, Sentry, or cloud logs. Once connected, auto-investigations activate immediately. Arcana reached 2,100+ automated investigations per month from that starting point, with no additional engineering work required to maintain the integration.

Conclusion: pairing Squadcast with Struct for faster resolution

Squadcast solves the human coordination problem, getting the right engineer paged at the right time. Automated incident investigation solves the diagnosis problem, delivering root cause and incident resolution verification before that engineer opens a single log file. The two approaches address different bottlenecks in the same incident lifecycle, and the strongest on-call programs run both.

For Series A–C engineering teams where manual triage consumes 30–45 minutes per incident, where junior engineers need a reliable starting point on every alert, or where SLA windows leave no margin for log-hunting, Struct layers onto your existing stack in 10 minutes and cuts investigation time by 80%, as Arcana’s results demonstrate at 2,100+ investigations per month.

Start cutting investigation time by 80%