Easily monitor the performance of your Celery application with the Scout APM library. Scout automatically monitors the performance of your Celery jobs, records transaction traces, and instruments many Python libraries automatically.
Key Celery Monitoring Features
Scout calculates the memory increase caused by web or background jobs, surfacing the exact transactions leading to memory bloat - and even which users triggered it. Scout also tracks object allocations so you can work to minimize or eliminate unnecessary overhead within your application.
Scout hooks into the Python VM to track every single object allocation during a request. Reduce CPU and memory usage and garbage collection time by optimizing transactions with excessive object allocation.
Background jobs can process a lot of data by iterating over many objects, often database queries. This makes background jobs a common place to find extremely wasteful N+1 queries. Scout has you covered by detecting N+1 queries and even listing how much time you could save by fixing them.
Background Job Latency
Scout measures the time from when a job is placed in the queue to the time the job starts executing - this is known as job latency. When latency continues to increase, your jobs fall further and further behind. Reduce your latency by making your jobs more efficient or adding more workers. Either way, Scout’s got your back.
Scout collects detailed traces of slow requests and, along with our GitHub integration, shows you the exact line of code responsible for the slow response time.
- Performance details on every web endpoint and background job
- Detailed transaction traces with backtraces
- Enhanced database query monitoring
- Detects repeatedly expensive database queries
- Memory Bloat Detection
- Deploy Tracking
- Intelligent performance digest email
- Embed charts
- Integrates with GitHub, Sentry, Rollbar, Bugsnag, Zapier, and more.