@Marvin - Approx 2% of my flow is falling with crashed status. with log: Crash detected! Execution was cancelled by the runtime environment. my all workers are with unlimited currency. also prefect server logs showing database connection error. with max connection reached. how can limit database connect also is these crashes are due to DB connections?

It looks like there was an issue with retrieving the necessary information to address your concerns directly from the documentation and GitHub. But fear not, I'll guide you as best as I can. The error message "Crash detected! Execution was cancelled by the runtime environment" often points to issues with resource availability, such as CPU, memory, or database connections. Given that you mentioned database connection errors with "max connection reached," it's highly plausible these issues are related. Here's what you can do to mitigate these problems: 1. Limit Database Connections: Ensure you're not exceeding the maximum number of connections supported by your database. Check your database settings and increase the maximum connections if needed, or adjust the settings in your Prefect deployment to use fewer connections simultaneously. This can usually be adjusted in the database configuration used by the Prefect Server. 2. Review Flow Configuration: Check your flow and task configurations to ensure they are optimized and not excessively consuming database connections. You might need to throttle tasks or use concurrency limits, even if your worker has "unlimited" concurrency. 3. Deployment Environment: Inspect the infrastructure running Prefect (e.g., Kubernetes, virtual machines, etc.) and ensure it has adequate resources. While I wasn't able to fetch specific documents, you can try looking at Prefect's documentation on resource management and troubleshooting for more details and specific configuration settings. You can explore these links for possible configuration changes: - Prefect documentation: Prefect 2.x docs - Prefect 3.x docs (ControlFlow-based): ControlFlow Hopefully, troubleshooting these areas will improve your situation. I feel like Prefect's clandestine way of asking us to calm down and check everything twice... or was it thrice?

@Marvin can we control control concurrency of flow run at worker level?

Yes, you can control the concurrency of flow runs at the worker level in Prefect, specifically through the use of work pools and work queues. Here's how you can do it: ### Prefect 2.x In Prefect 2.x, concurrency can be managed at the level of work pools: - Work Pools: Each work pool can have concurrency limits to restrict the number of concurrent runs. For example, if a work pool has a concurrency limit of 5, it will only allow 5 runs to proceed concurrently. If there are more runs queued, they will wait until the number of concurrent runs falls below the limit. More details are available here. ### Prefect 3.x In Prefect 3.x, the concept of work queues is further developed: - Work Queues and Concurrency: You can set up concurrency limits at various levels including work pools, work queues, and deployments. This allows for fine-grained control over the number of flow runs being processed concurrently by workers allocated to these queues. It's useful for managing resource utilization effectively across various priorities and workloads. Learn more in the Prefect 3.x documentation here. Setting up concurrency limits ensures that your system resources are used efficiently and prevents overloading your processes. Think of it as a courteous line at a theme park—everyone gets a turn without overloading the rides!

@Marvin also i am getting this log: 145155.027 | WARNING | prefect.server.services.cancellationcleanup - CancellationCleanup took 32.499643 seconds to run, which is longer than its loop interval of 20.0 seconds. what is this?

The warning message you're encountering, "CancellationCleanup took 32.499643 seconds to run, which is longer than its loop interval of 20.0 seconds", suggests that the Cancellation Cleanup service in Prefect is taking longer to process cancellations than the time allocated for its loop. Essentially, this service is responsible for cleaning up resources associated with cancelled flow runs. ### Potential Reasons and Solutions: 1. Resource Intensity: If the system handling cancellations is overloaded or the cancellation task itself is complex, this process might take longer. You can try optimizing the task logic or increasing system resources. 2. Loop Interval Configuration: Inspect the configuration and logs to see if the loop interval or the complexity of the CancellationCleanup process can be adjusted. 3. Database and I/O Operations: If there's database or other I/O interaction involved in the cancellations, ensure these operations are optimized to avoid excess delays. While I couldn't find specific references in the Prefect documentation, these general tips should help address the warning. For more technical insights, you can try reaching out on Prefect's community support or Slack channel for targeted advice. Think of it as a slow traffic light operation—giving it more green light time in the loop could help!

@Marvin if flow crashed will it log in agent log?

When a flow crashes in Prefect, it will indeed generate logs, but the logs are typically divided between flow/task logs and worker/agent logs. - Flow and Task Logs: These logs are directly related to the execution of specific flows and tasks. They provide details and stack traces regarding errors occurring during the execution process and are viewable in the Prefect UI. - Worker and Agent Logs: These logs can be pivotal for understanding system-level issues that might prevent a flow from starting or completing successfully. They capture the activities and interactions of the Prefect worker or agent, and can log information about crashes or failures before the flow even kicks off. You might not find extensive details about the specific flow failure, but you should see entries related to the worker's interaction with the flow. If your flow logs are empty, it's advisable to check the worker logs, as they might provide insights into infrastructure issues or failures that prevented the flow from functioning as expected. Additionally, increasing the logging level to DEBUG may reveal more detailed information, but be prepared for a much larger volume of logs. You can adjust the logging level through environment variables or Prefect configuration settings. For more detailed guidance, check these Prefect documentation resources: - Prefect 2.x on Agents - Prefect 3.x on Troubleshooting Think of the Prefect logs like a diary with two separate sections: one for each flow's story, and another for the journal of worker happenings. The story might skip a beat, but the diary will have some inkling of what happened!