26.02.2025 Problem:
The client faced intermittent downtimes in their PostgreSQL cluster, which is managed by Patroni for high availability. These downtimes were particularly prominent during failover events when the system failed to transition smoothly between nodes during leader elections. As a result, PostgreSQL was unable to maintain continuity of service, affecting the application performance. Logs from PostgreSQL indicated crashes, with shutdown requests and connection terminations tied to server failures. ETCD, which the Patroni system relies on for leader coordination and consensus, showed frequent leader election attempts and high load, exacerbating the instability.
Process:
Step 1: Initial Analysis of Logs
The first step involved a detailed review of the logs from both PostgreSQL and ETCD. PostgreSQL logs revealed:
- Warnings about an immediate shutdown request following server crashes.
- Connection terminations due to the crash of another server process.
The logs indicated that although the cluster was configured to perform failover automatically, the transition to a new leader during these events was inconsistent. ETCD logs showed:
- Frequent leader election attempts due to a failure in leader stability.
- High load and resource exhaustion warnings, which may have contributed to delays in processing.
Through log analysis, it was evident that the issue was related to a combination of ETCD node overload and failures in leader elections.
Step 2: Root Cause Analysis (Patroni)
A closer inspection of the Patroni logs revealed the following:
- The Patroni service was unable to trigger the leader election process promptly. This was partly due to high latency between nodes and sporadic issues with quorum formation during failover attempts.
- The lack of a stable leader, combined with inconsistent replication, led to delays in responding to client requests and prevented the cluster from recovering in a timely manner.
The recommended changes to resolve the issue in Patroni were:
- Increase timeout and lag settings: Extend the default timeouts and adjust the maximum replication lag settings. This would allow more flexibility during leader election processes and reduce unnecessary failover attempts.
- Enable detailed logging: Improve log verbosity to capture more granular details during failovers. This would help quickly diagnose issues in the future and give insight into what is happening during cluster transitions.
Step 3: Root Cause Analysis (ETCD)
Further investigation into the ETCD logs identified several key problems. High CPU load and resource contention were present, which led to delays in data synchronization between ETCD nodes, triggering frequent leader election attempts. The cluster’s ETCD setup had not been optimized for high availability and load distribution, leading to bottlenecks when multiple processes attempted to access the ETCD server simultaneously. The stress on the ETCD node was most notable when it hosted the leader, with multiple failover attempts causing high load and instability. The investigation revealed that increasing resources for the ETCD nodes would alleviate these bottlenecks, allowing for smoother leader transitions and better handling of cluster coordination.
Upon this discovery, corrective actions were recommended. These included increasing the resources allocated to the ETCD nodes, allowing them to handle additional load during leader election events. Additionally, specific configurations were adjusted to allow more efficient session handling, compression settings, and increased election timeouts to reduce the frequency of leader changes.
Step 4: Recommendations and Corrective Actions
To stabilize the cluster, several corrective actions were implemented. First, the resources allocated to the ETCD nodes were increased. Monitoring showed that the CPU and memory usage were higher than expected, and by upgrading these resources, the load distribution improved, leading to fewer election attempts and a more reliable leader election process. The network infrastructure was also reviewed, and packet loss or latency issues between ETCD nodes were eliminated to ensure fast communication, which is critical for successful leader elections. Furthermore, time synchronization across nodes was ensured using NTP to eliminate any discrepancies that could affect leader election accuracy.
On the Patroni side, a number of minor but impactful changes were made. The failover timeout settings were adjusted to ensure that failovers only occurred when necessary, reducing unnecessary transitions. The maximum replication lag and failover retries were configured to a balanced range, preventing overload during high-latency periods. These changes improved overall system stability and ensured that failovers no longer caused disruptions.
Solution:
The corrective actions aimed at stabilizing the cluster, particularly by improving resource allocation for ETCD and optimizing Patroni settings, were implemented successfully. The increased resources for ETCD nodes and the adjusted failover and replication settings in Patroni were designed to reduce downtimes and ensure smoother failovers, improving overall system reliability.
Conclusion:
The implemented changes were expected to significantly improve the system’s stability during failovers. The adjustments to ETCD’s resource allocation and the fine-tuning of Patroni’s failover and replication parameters were aimed at preventing downtimes and ensuring that failovers occurred smoothly. These actions were anticipated to reduce the risk of service interruptions and improve the overall performance of the cluster.