Monitoring logs with Uptrace

Logs monitoring

TIP

To receive notifications about specific logs and errors, see Alerts and notifications.

Infrastructure logs

To monitor infrastructure logs, you can use Vector (Heroku, Fly) and FluentBit integrations.

If you are using AWS, you can also send CloudWatch Logs directly to Uptrace.

Application logs

To record application logs, you can use OpenTelemetry span eventsopen in new window. You must set the event name to log and use semantic attributesopen in new window to record the context:

log.severity to record the log severity. Must be one of TRACE, DEBUG, INFO, WARN, ERROR, FATAL, and PANIC.
log.message to record the message.
code.function to record the function name.
code.filepath to record the file path.
code.lineno to record the line number.

Go

For example, using Go programming language and OpenTelemetry events API:

span := trace.SpanFromContext(ctx)

span.AddEvent("log", trace.WithAttributes(
    // Log severity and message.
    attribute.String("log.severity", "ERROR"),
    attribute.String("log.message", "request failed"),

    // Optional.
    attribute.String("code.function", "org.FetchUser"),
    attribute.String("code.filepath", "org/user.go"),
    attribute.Int("code.lineno", 123),

    // Additional details.
    attribute.String("foo", "hello world"),
))

You can also use instrumentations for popular logging libraries which allow recording logs using a more conventional API, for example, OpenTelemetry Zap and OpenTelemetry Logrus.

Python

OpenTelemetry Python comes with a handler for Python's logging package so you can just use the standard logging API:

import logging
import uptrace

# Configure OpenTelemetry.
uptrace.configure_opentelemetry(...)

# Use logging API as usual.
logger = logging.getLogger(__name__)
logger.setLevel(logging.ERROR)

Grouping logs together

You can control how Uptrace groups logs together by providing grouping.fingerprint attribute which can be a string or a number (hash/id):

log.severity = "info"
log.message = "unstructured log message 123 456 789"
grouping.fingerprint = "unstructured log message"

You can further customize grouping using grouping rules, but this is only available in the paid version.

Propagating trace context

When collecting third-party logs with Vector or FluentBit, trace context is not automatically propagatedopen in new window and logs can't be linked with spans.

To propagate context and associate a log record with a span, use the following attribute keys in the log message:

trace_id for TraceId, hex-encoded.
span_id for SpanId, hex-encoded.
trace_flags for trace flags, formatted according to W3C traceflags format.

For example:

request failed trace_id=958180131ddde684c1dbda1aeacf51d3 span_id=0cf859e4f7510204

# Monitoring logs with Uptrace

# Infrastructure logs

# Application logs

# Go

# Python

# Grouping logs together

# Propagating trace context

# See also