AIStore Observability: Logs
AIStore Observability: Logs
AIStore Observability: Logs
AIStore (AIS) provides comprehensive logging that captures system operations, performance metrics, and error conditions.
Scope. How to configure, collect, and read AIS logs.
AIS logs are the cluster’s ground truth: every proxy or target writes a chronological stream of events, warnings, and periodic performance snapshots. Well‑rotated logs let operators:
Show current values:
The new value propagates to every node within a second.
In production environments, settings are typically adjusted for higher retention and less frequent statistics collection:
At startup, AIS logs some of these settings:
AIS prepends every line with a severity prefix and—in the case of informational messages—an internal numeric level.
Tip. Temporarily crank a node:
log.modules)log.modules lets you boost just a subset of subsystems to level 5 without flooding the whole cluster.
AIS logs follow a consistent format:
Common prefixes:
config: – effective runtime configurationx-<n>: – extended (batch) action lifecyclenvmeXnY: – per‑disk I/O snapshotkvstats: – cluster‑wide key‑value metrics (see below)File names include the node ID plus a sequence number (target‑A43c.log.3). Rotation is triggered by max_size; retention is enforced by max_total.
AIS implements automatic log rotation as indicated by the header:
When logs are rotated, new log files are created and old ones are typically compressed or archived according to the retention policy.
The AIS CLI provides commands to view and collect logs:
In Kubernetes deployments, access logs using kubectl:
The startup sequence provides important information about the AIS node configuration:
AIS logs details about operations such as list, put, get:
AIS regularly logs performance metrics in two formats:
stats_time):In Kubernetes deployments, AIS logs include pod and cluster-specific details:
The key-value statistics contain valuable operational metrics:
err.<n>.n counters.util > 80% or sustained read.bps plateaus.log.level or log.modules on a single node to capture more detail.For advanced log analysis, consider forwarding logs to external systems for aggregation and visualization.
log.level=3 in production; raise to 4 or 5 only while debugging. Lower to 2 or below if you truly need silence.stats_time (≥ 60s) if logs get noisy on busy systems.ais cluster download-logs tarball to GitHub issues.