Honeycomb SLOs and Triggers

Guidance for configuring and reasoning about reliability in Honeycomb. The get_slos and get_triggers tools document their own parameters — this skill focuses on designing effective SLOs, choosing between SLOs and triggers, and interpreting what the numbers mean.

Availability: SLOs require Pro or Enterprise plan. Triggers available on all plans.

SLO vs Trigger — When to Use Which

Question	SLO	Trigger
"Are we meeting our reliability commitments?"	Yes	No
"Is something broken right now?"	No	Yes
"How fast are we burning our error budget?"	Yes (burn alerts)	No
"Did error count exceed a threshold?"	No	Yes
"Should we slow down deploys?"	Yes (budget remaining)	No

Rule of thumb: SLOs measure reliability against commitments over time. Triggers catch immediate operational issues.

Designing Effective SLOs

Define the SLI

An SLI is a per-event boolean: was this event successful? Implemented as a calculated field returning 1 (success) or 0 (failure).

• Latency SLI: LTE(duration_ms, 500) — requests faster than 500ms
• Availability SLI: LTE(http.status_code, 499) — non-5xx responses
• Business logic SLI: EQUALS(checkout.status, "completed") — successful checkouts

Set the Target

• Start conservative (99% before 99.99%)
• Measure current baseline first with P50/P99 queries
• Set target slightly above current performance
• Ask: what reliability do users actually need?

Configure Burn Alerts

At minimum, two alerts:

• Fast burn (exhaustion time ~4h): pages on-call via PagerDuty
• Slow burn (budget rate over 24h): notifies team via Slack

Best Practices

• Measure close to the user (at the edge, not deep in the stack)
• Design around user workflows, not team boundaries
• Favor broad SLOs over many narrow ones
• Start with one SLO, reduce noise, then expand

Interpreting SLO Status

When reviewing SLOs with get_slos:

• Budget remaining > 50%: Healthy — room for risk
• Budget remaining 10-50%: Caution — slow down changes
• Budget remaining < 10%: At risk — freeze non-critical deploys
• Budget negative: Breached — investigate immediately with the production-investigation skill
• Compliance at 0%: Likely misconfigured SLI (wrong column, inverted logic, no matching events) — check the SLI definition

Configuring Triggers

Prefer Count-Based Over Percentile-Based

"50 requests slower than 2s" is more actionable than "P99 is 2100ms." Use COUNT WHERE duration_ms > threshold instead of P99 triggers.

Common Patterns

• Error spike: COUNT WHERE error = true, threshold > N in 5 min
• Slow requests: COUNT WHERE duration_ms > 2000, threshold > N in 5 min
• Traffic drop: COUNT WHERE is_root, threshold < N in 10 min (below normal)

Best Practices

• Name: What the alert is. Description: What to do (link to runbook).
• Set duration 5-10 min minimum to avoid flapping
• Start less sensitive, tighten based on false positive rate

Multi-Service SLOs

Share a single error budget across up to 10 services.

• SLI must be an environment-level calculated field
• Events from included services weighted equally
• Use cases: multiple edge services, monolith-to-microservices migration

Additional Resources

Reference Files

• ${CLAUDE_PLUGIN_ROOT}/skills/slos-and-triggers/references/slo-design-guide.md — Detailed SLO design methodology, multi-service SLOs, error budget math
• ${CLAUDE_PLUGIN_ROOT}/skills/slos-and-triggers/references/trigger-examples.md — Complete trigger example library organized by use case
• ${CLAUDE_PLUGIN_ROOT}/skills/slos-and-triggers/references/alerting-strategy.md — How to combine SLO burn alerts and triggers into a cohesive alerting strategy

Cross-References

• For constructing SLI queries and calculated fields, see the query-patterns skill
• For investigating SLO budget burn, see the production-investigation skill