Using eBPF to Troubleshoot Process Contention in PostgreSQL: A Guide to Monitoring Locks, CPU, and I/O Performance

PostgreSQL Performance Troubleshooting Whitepaper – Using eBPF to Troubleshoot Process Contention in PostgreSQL



To use eBPF for troubleshooting process contention in PostgreSQL, we focus on understanding how processes are interacting with each other, particularly in terms of resource access such as CPU, memory, and I/O. Process contention often manifests as high lock wait times, slow query execution due to CPU scheduling delays, or I/O wait. Here’s how you can approach this using eBPF:

1. Monitoring Lock Contention

PostgreSQL uses various types of locks for managing access to data. Lock contention happens when multiple processes are waiting to acquire a lock held by another process. While PostgreSQL’s own logging and monitoring can track lock waits, eBPF can help identify underlying system-level contention that impacts these locks.

Using eBPF to Trace Lock Contention: You can write an eBPF script to monitor the fcntl system calls, which PostgreSQL uses for advisory locks. The script can record the time spent in these calls and correlate them to specific PIDs (Process IDs). Here’s a simple example using BCC:

2. Identifying CPU Contention

If PostgreSQL processes are contending for CPU, it can be observed via context switches and scheduler delays. Monitoring these events can reveal if PostgreSQL processes are frequently preempted or spend long times waiting to be scheduled.

Using eBPF to Monitor CPU Contention: You can use a bpftrace script to monitor context switches and scheduler events related to PostgreSQL processes. Here’s a basic example to get you started:

This script prints out every context switch in the system, but you can modify it to focus on PostgreSQL processes by checking if prev_pid or next_pid matches PostgreSQL PIDs.

3. I/O Wait and Performance

I/O wait is another common source of contention. Monitoring disk read/write and blocking I/O operations can provide insights into whether disk access is a bottleneck.

Using eBPF for Disk I/O Monitoring: Again, using BCC or bpftrace, you can trace block device I/O operations. This can help identify slow disk operations that may be affecting PostgreSQL performance.

This script needs to be refined to focus on the devices relevant to PostgreSQL.

Combining These Approaches

Combine these monitoring scripts to get a comprehensive view of where contention might be occurring in your PostgreSQL deployment. eBPF can provide deep insights, but it requires careful tuning and understanding of both PostgreSQL internals and system performance characteristics to interpret the data effectively. Each script provides a foundation that should be tailored to your specific environment and needs.

Install bpftrace on CentOS

Linux Performance Troubleshooting with eBPF – MinervaDB Webinar

Introduction to eBPF in Red Hat Enterprise Linux 7

How can you reduce lock contention in MySQL?

About Shiv Iyer 452 Articles
Open Source Database Systems Engineer with a deep understanding of Optimizer Internals, Performance Engineering, Scalability and Data SRE. Shiv currently is the Founder, Investor, Board Member and CEO of multiple Database Systems Infrastructure Operations companies in the Transaction Processing Computing and ColumnStores ecosystem. He is also a frequent speaker in open source software conferences globally.

Be the first to comment

Leave a Reply