Application error/trace monitoring for agent backends
Need exception tracking, performance spans, and alerts for the services hosting agents — separate from LLM request tracing.
At a glance — Oct 2026
Updated 2026-10-27 · forward this page: /jtbds/agent-error-observability#briefScores as of 2026-09-14 (43 days old; Depot marks scores stale after 30 days). The pick is still Depot's current editorial pick; it has not been re-reviewed since. Prices below carry their own dates.
- Depot Pick
- Sentry · 8.56/10 for this job (curated estimate, high confidence)
DX + maturity for app errors. Sentry wins; keep LLM tracers separate.
- Runner-up
- Honeycomb · 8.13/10
Scores higher than the pick on: Latency / reliability.
- When not to use the pick
- LLM-only tracing/evals — Langfuse/Braintrust/Helicone. Full enterprise APM already Datadog — stay.
- Lock-in / migration
- The pick has lower stored lock-in risk than runner-up Honeycomb (4.2 vs 4.5). Self-host fallback listed for this job: SigNoz.
- Sourced price (no comparable unit)
Pick: no sourced price in this job's unit (no_matching_sourced_price).
No cheapest SKU (no_candidate_has_sourced_price_in_job_unit:error_observability). No price was invented.
- Free option
- SigNoz (oss) — source, as of 2026-10-25
- Failure modes to watch
- Observability gap: Alert on a drop in trace ingestion and on certificate expiry for the trace host. Do not treat a missing trace as a successful quiet run.
- Non-determinism: Run the task more than once and compare the end state, not a single transcript. Record the trial count next to any success rate you cite.
- Partial tool success: Require a per-item status and a failure count. Success for the task requires the failed count to be zero or explicitly handed to a retry queue.
- Runaway spend: Set a budget and a tool-call cap per task. Alert when spend jumps. Stop the run at the cap instead of summarizing a partial trace as success.
- Tool loop: Hash the last several tool names and arguments. Stop when the same call repeats and the observation did not change. Cap tool calls per task.
Cite: Agent Provider Depot, Depot Pick for agent-error-observability: sentry, scores as of 2026-09-14. Agents: GET /api/decide?jtbd=agent-error-observability
Free Application error/trace monitoring for agent backends options · for scheduled-ops agents
Sentry
DX + maturity for app errors. Sentry wins; keep LLM tracers separate.
Pricing (directional): As of 2026-09-14 (sentry.io/pricing): Developer **Free** (1 user, 5k errors class quotas + MCP access). Team from **$26/mo**; Business **$80/mo** (annual prepaid defaults). PAYG overages for errors/spans/replays/profiling. Seer AI debugging…
Lock-in risk: higher = more lock-in (worse). Overall already inverts this dimension.
Depot pick for agent-error-observability (exceptions/traces in the app hosting the agent). Keep Langfuse/Helicone for LLM request tracing; Datadog when enterprise APM is already standardized.
Quote for Application error/trace monitoring for agent backends
Depot Pick stays Sentry. Prices below are sourced SKU rows only (as of 2026-10-27). Input and output are not blended. GET /api/quote?jtbd=agent-error-observability
Nothing was compared. per-error prices were not ranked against monthly plans. Candidates do not share one unit. cheapest stays null. pickIsPriceWinner is null.
- Business usd_per_month $80 source as of 2026-10-03
- Continuous Profiling usd_per_hour $0.0315 source as of 2026-10-03
- Cron monitor additional usd_per_monitor $0.78 source as of 2026-10-03
- Developer usd_per_month $0 source as of 2026-10-03
- Team usd_per_month $26 source as of 2026-10-03
- Team errors 100K-500K usd_per_error $0.0002188 source as of 2026-10-03
- Team errors 10M-20M usd_per_error $0.0001625 source as of 2026-10-03
- Team errors 20M+ usd_per_error $0.00015 source as of 2026-10-03
- Team errors 500K-10M usd_per_error $0.0001875 source as of 2026-10-03
- Team errors 50K-100K usd_per_error $0.0003625 source as of 2026-10-03
- UI Profiling usd_per_hour $0.25 source as of 2026-10-03
- Uptime alert additional usd_per_uptime_alert $1 source as of 2026-10-03
2 of 3 candidates have no sourced price row. 3 are excluded from the Error observability price comparison (error_observability). per-error prices were not ranked against monthly plans. Candidates do not share one unit. cheapest stays null.
Runners-up
When NOT to use the top pick
LLM-only tracing/evals — Langfuse/Braintrust/Helicone. Full enterprise APM already Datadog — stay.
Full ranking (score table)
Ranked with this JTBD's weights. Scores are curated estimates unless marked otherwise. Agents: prefer /api/decide then this table for tie-breaks.
Score methodology for this job
DX + maturity for app errors. Sentry wins; keep LLM tracers separate.
capabilityFit: 25%pricePerformance: 18%latencyReliability: 15%developerDx: 15%privacyPosture: 10%lockInRisk: 7%maturity: 10%