Your background jobs.
Under control.
Track multi-project executions, leverage AI-powered incident intelligence, and assign background-job incidents to your team in real-time.
Active Jobs
14
● 100% ActiveExecutions / 24h
12,840
99.8% SuccessP95 Latency
240ms
↓ -14msActive Incidents
1
INC-14 DEGRADEDsync_user_stripe_events (Current: 15.5% vs Threshold: 10%)Architecture Workflow
How Background Job Tracker Works
From execution telemetry to automated incident resolution, BJT gives you end-to-end visibility.
Job Discovery
SDK automatically registers background task signatures from your Celery, Django, or FastAPI code.
Telemetry Stream
Lightweight async sender batches execution start, finish, retry, and duration events.
Health Monitoring
Aggregates P50/P95 latency percentiles, failure rates, and execution counts per project.
Failure Analysis
Extracts tracebacks, categorizes error types, and deduplicates repeated error signatures with AI.
Alert Evaluation
Evaluates thresholds for high failure rates, retries, or execution volume anomalies for Webhooks.
Incident Resolution
Generates actionable incidents with automated runbooks and team assignment workflows.
Deep Incident Intelligence & Execution Tracking
Inspect real-time execution tracebacks, analyze AI-assisted root causes, and manage team incident assignments in one clean workspace.
High Failure Rate on sync_user_stripe_events
Triggered 12 minutes ago across 450 total task executions.
"Repeated Stripe API rate limit (HTTP 429 Too Many Requests) causing worker retry cascades. Recommended action: Implement exponential backoff in Celery task retry config."
Recent Task Executions
Real-time execution telemetry stream for this task signature
stripe.error.RateLimitError: Request rate limit exceeded.
File "tasks/stripe_sync.py", line 42, in sync_user_stripe_eventsPlatform Capabilities
Everything You Need To Monitor Background Jobs
Built for engineering teams running Celery, Django, FastAPI, and standalone Python task queues.
AI Incident Intelligence & Tracebacks
Automatically extract tracebacks, categorize error types, and generate AI-assisted root cause summaries for Celery execution failures.
"Detected 429 Rate Limit cascade across worker pool. Suggested fix: Apply exponential backoff parameters in Celery task retry settings."
Multi-Project Isolation & Incident Assignment
Isolate job telemetry into distinct projects, switch project scopes globally, and assign reliability incidents to teammates for resolution.
Toolbar scope synced across all metrics, execution logs, and incident feeds.
Real-Time Telemetry
Track execution start, finish, retry, and duration events live across your worker fleet.
P95 Latency Metrics
Monitor P50/P95 latency percentiles, failure rates, and task execution counts.
Runbooks & Postmortems
Guide team incident response with structured step-by-step runbooks and summaries.
PyPI SDK & REST API
Official `background-job-tracker` Python SDK with async batch sender and REST API.
Developer Integration
From Your Code To BJT In 3 Lines
Zero-config Celery & RQ signal hooks, automatic task discovery, and lightweight async sender. Supports Django, FastAPI, Flask & custom Python workers.
Supported Technology Stack
Works Seamlessly With Your Stack
BJT supports Celery and Python background tasks across Django, FastAPI, Flask, and standalone Python scripts, as well as any REST client.