Written by: Nimesh Chakravarthi, Co-founder & CTO, Struct
Key Takeaways
- Datadog excels at metrics visualization but lacks built-in capabilities for automated on-call investigation and root-cause identification.
- Teams are shifting toward AI-assisted incident response tools that deliver root-cause answers within minutes of an alert.
- Top alternatives like PagerDuty, incident.io, Rootly, and Better Stack each address specific workflow gaps but still require manual triage steps.
- Struct stands out with fast setup, significant triage-time reduction, and automated root-cause analysis before human review.
- See automated investigation in action, then decide whether Struct fits your on-call workflow.
What Modern On-Call Monitoring Really Involves
On-call monitoring focuses on what happens after an alert fires, not just on collecting data. General observability covers metrics collection, log aggregation, and dashboard visualization. On-call work adds alert routing, escalation policies, runbook execution, and fast root-cause identification under pressure. An engineer woken at 3 AM does not need more charts. They need to know what broke, what it affects, and how to fix it.
Two 2026 developments have accelerated the shift away from Datadog-centric on-call stacks. First, Atlassian announced the end-of-life for Opsgenie, which forces thousands of teams to re-evaluate their alerting layer. Second, the category of AI-assisted incident response has matured from experimental to production-ready. Platforms now complete a first-pass investigation before a human acknowledges the page. These shifts have created a new landscape of on-call tools, each addressing different parts of the workflow.
Comparison of Top Datadog Alternatives for On-Call
The table below compares six tools across pricing tier, typical setup time, and triage-time impact. These three factors most directly affect on-call team efficiency. All pricing reflects publicly available 2026 information.
| Tool | Starting Price | Setup Time | Triage-Time Impact |
|---|---|---|---|
| PagerDuty | $21/user/mo (Professional) | Hours to days | Faster routing, investigation still manual |
| incident.io | incident.io offers a free Basic plan and a Team plan starting at $19/user/month (monthly) or $15/user/month (annual) | 1–2 days | Structured workflows reduce coordination time |
| Rootly | Rootly’s starting price is $20/month for the Essentials plan | 1–2 days | Runbook automation reduces manual steps |
| Better Stack | Free tier available, paid from $24/mo | Under 1 hour | Fast alerting, investigation still manual |
| Grafana OnCall | Grafana OnCall OSS was free and open source (now archived), Cloud Pro starts at $20/user/month plus $19/mo base fee | Hours (OSS requires self-hosting) | Routing improvement, no automated investigation |
| Struct | Free Startup tier, Growth and Enterprise paid | ~10 minutes | 80% reduction in triage time, automated root-cause before human review |
PagerDuty remains the enterprise standard for alert routing and escalation policies. Its Datadog, Slack, and GitHub integrations are deep and well-documented. PagerDuty routes the alert to the right person but does not investigate it. Triage remains entirely manual.
incident.io excels at structured incident coordination, including status pages, stakeholder updates, and post-mortems. It integrates with Slack and PagerDuty cleanly. It fits incident management after a root cause is known more than the initial investigation phase.
Rootly offers strong runbook automation and Slack-native workflows. It reduces the number of manual steps during an incident. An engineer still needs to perform the diagnostic work before runbooks can execute meaningfully.
Better Stack combines uptime monitoring, log management, and on-call scheduling in a single, affordable package. Setup is fast and the free tier is generous. Investigation depth is limited compared to full observability stacks.
Grafana OnCall is the open-source option with the most mature routing feature set. The cloud-hosted version integrates with Grafana’s broader observability suite. Self-hosted deployments require ongoing maintenance overhead that small teams often underestimate.
Best Datadog Alternative by Team Size
| Team Size | Best Fit | Runner-Up | Rationale |
|---|---|---|---|
| Under 20 engineers | Struct | Better Stack | 10-minute setup, free Startup tier, no dedicated SRE required to configure |
| 20–50 engineers | Struct | Rootly or incident.io | Automated investigation scales with alert volume, Growth tier adds unlimited users |
| 50+ engineers | PagerDuty + Struct | incident.io + Struct | PagerDuty or incident.io handles routing and coordination, Struct handles automated first-pass investigation |
Teams under 20 engineers rarely have a dedicated SRE. Every on-call shift pulls a product engineer away from feature work. The priority is fast setup and automated investigation, not enterprise routing complexity. For teams at 50+ engineers, routing and coordination tooling justifies its cost. Automated investigation still delivers the highest-leverage improvement in the stack.
Book a Struct demo to see how automated root-cause analysis works with your existing stack.
Manual Investigation vs. Automated Root-Cause Solutions
The standard manual on-call workflow follows a predictable pattern. An alert fires, an engineer acknowledges the page, then opens Datadog to assess metrics. They pivot to CloudWatch or GCP Logs to find relevant log lines, check Sentry for exceptions, cross-reference GitHub for recent deploys, and eventually form a hypothesis. This process takes 30–45 minutes on average for a moderately complex service. It often takes longer when the engineer is new to the system.
Struct automates this entire sequence. When an alert fires in a configured Slack channel or PagerDuty integration, Struct immediately queries logs, metrics, traces, and code context in parallel. Within five minutes, it outputs a dynamically generated dashboard containing a root-cause assessment, blast-radius summary, unified timeline, and suggested fixes. This automated approach delivers the triage-time reduction shown in the comparison above.
The practical difference is simple. Manual tools make engineers faster at investigation. Automated tools remove the investigation from the engineer’s critical path entirely.
Best Free Datadog Alternative for On-Call
Grafana OnCall (OSS) is the most feature-complete free option for alert routing and escalation. The trade-off is self-hosting burden. Teams must provision, maintain, and upgrade the stack themselves, which consumes engineering time that often exceeds the cost of a paid alternative.
Better Stack offers a free tier that covers basic uptime monitoring and on-call scheduling with no self-hosting requirement. This makes it the fastest free starting point for small teams.
Struct’s free Startup tier supports up to five users and 30 investigations per month, including automated root-cause analysis and code agent handoff. For early-stage teams with moderate alert volume, this tier delivers automated investigation at zero cost.
Datadog Alternatives for Startups
Seed-to-Series-C teams share a common constraint. Senior engineers are the primary on-call responders, and every hour spent on triage is an hour not spent on product. The evaluation criteria for startups differ from enterprise. Setup speed matters more than customization depth, per-seat pricing matters more than volume discounts, and automated investigation matters more than advanced reporting.
Better Stack and Struct both offer fast onboarding and startup-friendly pricing. Better Stack accelerates alert delivery, while Struct eliminates the investigation phase. For teams already using Datadog, Sentry, and GitHub, Struct’s integration layer connects in under 10 minutes and immediately begins automating the most time-consuming part of the on-call workflow.
Start a 30-day Struct pilot with white-glove onboarding and evaluate automated investigation on real incidents.
Open-Source Datadog Alternatives for On-Call Monitoring
Grafana OnCall and the broader Grafana OSS stack (Loki for logs, Prometheus for metrics, Tempo for traces) represent the most complete open-source observability and on-call suite available. Teams with strong platform engineering capacity can build a highly capable system at infrastructure cost only.
The realistic limitations for on-call workflows are significant. Self-hosted Grafana OnCall requires ongoing maintenance. Alert routing configuration is manual and complex. No open-source tool in this category provides automated root-cause investigation. That capability requires either significant custom engineering or a dedicated AI layer. Teams that choose the open-source path typically still need a separate solution for the investigation phase.
Cheaper Alternatives for APM Spend
Datadog’s APM pricing scales with host count and ingested spans, which becomes expensive as infrastructure grows. Common alternatives include the following options.
Grafana Cloud offers a generous free tier and pay-as-you-go pricing for traces, logs, and metrics. For teams already using Prometheus and Loki, it is the lowest-friction migration path.
Better Stack includes log management and APM-adjacent features at a lower per-seat cost than Datadog for teams with moderate data volumes.
APM cost reduction and on-call automation are separate problems. A team can reduce APM spend by migrating to Grafana Cloud while adding Struct on top of their existing alerting layer to automate investigation. The two decisions are independent and complementary.
Frequently Asked Questions
Is Struct secure enough for companies with strict compliance requirements?
Struct is SOC 2 and HIPAA compliant. Logs and telemetry data are accessed and processed ephemerally during an investigation, and they are not stored persistently by Struct. For the majority of Seed-to-Series-C companies, this compliance posture meets standard security requirements. Teams with strict on-premise or zero-egress requirements should evaluate Struct’s Enterprise tier, which includes sidecar and on-prem support options.
Can we customize how Struct investigates our specific alerts and services?
Struct supports custom runbook input, proprietary correlation ID formats, and composable widgets that guarantee specific data is always pulled for defined alert types. Teams can paste their existing internal on-call runbooks directly into Struct, and the AI will follow those procedures when a matching alert fires. This approach means the automated investigation reflects how your senior engineers would actually approach the problem.
How quickly can a team get Struct running in production?
As noted in the comparison above, setup takes approximately 10 minutes. The process involves authenticating an issue source such as Slack or PagerDuty, a code repository such as GitHub, and at least one observability context such as Datadog, AWS CloudWatch, or GCP Logs. Once connected, auto-investigations activate immediately. No professional services engagement or multi-week configuration period is required.
What happens if our logging and observability setup is incomplete?
Struct’s investigation quality depends on the data available in connected integrations. Teams already using Sentry, Datadog or cloud logs, and Slack-based alerting will see the highest investigation accuracy. If a system lacks structured logging, trace IDs, or configured alert triggers, Struct cannot infer system state from code analysis alone. Improving baseline observability before or alongside Struct deployment produces the best results.
Does Struct replace PagerDuty or just complement it?
Struct complements PagerDuty rather than replacing it. PagerDuty handles alert routing, escalation policies, and on-call scheduling. Struct handles the investigation that happens after the page fires. The two tools integrate directly. Struct can receive alerts from PagerDuty and return root-cause findings to the same incident thread, so engineers get automated context without changing their existing routing setup.
How to Evaluate On-Call Tools in 2026
Three criteria separate useful on-call tools from expensive dashboards, and each one covers a different aspect of effectiveness. First, MTTR impact measures whether the tool reduces the time from alert to resolution or only improves one phase of the workflow. Tools that automate investigation compress the longest phase of MTTR, which directly affects customer-facing downtime. Second, alert fatigue mitigation measures whether the tool helps engineers distinguish critical outages from transient noise without requiring manual review of every alert. This criterion focuses on engineer sustainability, since automated triage that confirms severity before paging prevents burnout from false alarms. Third, onboarding readiness measures whether a junior engineer can take an on-call shift confidently within their first month. Tools that encode institutional knowledge into automated outputs lower the barrier to distributing on-call responsibility across the team.
The 2026 on-call stack for most Seed-to-Series-C teams follows a consistent pattern. An existing observability layer such as Datadog, Grafana, or cloud-native logs captures telemetry. A routing layer such as PagerDuty or Slack-native alerting handles notifications and escalation. An automated investigation layer such as Struct closes the gap between alert and root cause. The first two categories are largely solved problems. The third is where triage time is lost and where the highest leverage improvement is available.
Connect Struct to your stack in about the time it takes to grab coffee and let AI complete your next investigation before you open your laptop.
