Some deployments need to disambiguate multiple senders sharing an IP,
for example autossh or similar tunnel setups. Exposing the source port
improves observability and lets pipelines key on a stable tuple.
Impact: new property/JSON field; tcps_sess IF v4; out-of-tree modules
must rebuild.
Before: messages exposed fromhost and fromhost-ip only.
After: messages also expose fromhost-port and jsonmesg includes it.
Introduce PROP_FROMHOST_PORT and wire it through msg.{h,c}. For TCP,
capture the remote port on accept, store it in tcps_sess, and attach it
to the msg on submit. For other inputs, resolveDNS derives the port from
the sockaddr when available; local inputs return an empty string. Add a
getter, duplication and destructor handling, and name<->ID mapping. Add
the field to jsonmesg output. Update docs, lexer keywords, and the
external plugin interface doc (property is modifiable). Bump
tcps_sessCURR_IF_VERSION to 4 and add SetHostPort() to the interface.
Include a focused test (fromhost-port.sh) that verifies the property.
Non-technical rationale: allow identification by (fromhost-ip,
fromhost-port) where IP alone is shared across systems (e.g., autossh).
With help from AI-Agents: ChatGPT
Motivation: code coverage reports were incomplete. This lays a better
base for consistent reporting via GitHub Actions, with room for follow-ups.
It also removes a test flake source in Kafka jobs.
Impact: CI/tests only; no runtime behavior or ABI changes expected.
Before: Coverage uploads were inconsistent; Kafka tests could hang while
reading from /dev/urandom to generate topic names.
After: Coverage is collected with lcov and uploaded via a dedicated GH
Action; Kafka topics use fast $RANDOM-based hex, avoiding early-boot
entropy stalls.
Technical details:
- Add two workflows: "codecov base" and "codecov kafka" on Ubuntu 24.04.
Use lcov capture with unexecuted blocks and prune common noise; upload
with token for same-repo PRs and tokenless for forks.
- Update .codecov.yml: add path fixes for container (/rsyslog) and
runner layouts; explicitly set comment: false and patch: false.
- Bump actions/checkout to v4 in existing workflows; add an actionlint
job to catch YAML problems early.
- Switch codecov jobs in container matrix to 24.04 images.
- Improve run-ci.sh lcov invocation to be more tolerant of line/macro
mismatches.
- Testbench: replace /dev/urandom topic generation with 8-char hex from
$RANDOM; adjust diag.sh path/quoting for zookeeper helper.
Add a RainerScript function to convert strings to uppercase. The
implementation mirrors tolower() but operates per-byte using
toupper(). Tests demonstrate the new function, documentation and
ChangeLog entries added.
closes: https://github.com/rsyslog/rsyslog/issues/3666
With the help of AI-Agent: ChatGPT
The civetweb library is not packaged in a thread-safe way and as such
TSAN always fails due to a civetweb data race by calling gmtime.
Nothing to do so far against that.
We try sid to gain early access to new compiler versions. It needs
to be show if sid causes too many false positives (due to its own
instability) and if we manage to regenerate the compiler frequently
enough.
The docs build has been failing because doc/source/conf_helpers.py was
removed, but Sphinx imports it from conf.py. This reintroduces the
helper module so the documentation can be built again.
Regression introduced by:
ba762b6533
Impact: restores local and CI doc builds; no runtime behavior change.
Before: sphinx-build failed with ImportError for conf_helpers.
After: sphinx-build completes successfully.
Replace deprecated bash uploader with Codecov's official uploader.
The script now downloads the uploader binary, verifies its SHA256
checksum, and runs it to submit coverage results.
The change keeps run-ci.sh CI-agnostic.
With the help of AI-Agent: ChatGPT
kafkacat has been renamed to kcat, as it looks for trademark issues.
Kafka module tests depend on that utility and are skipped if command
is not available. This was now always the case for newer development
containers.
Name was now adjusted in all tests.
* mmnormalize: split parameter docs into reference pages
- Split Module and Action parameters into dedicated reference files
- Replace inline blocks with list-tables and included summaries
- Add hidden toctree; remove legacy parameter section; fix anchors
With the help of AI-Agents: ChatGPT, Gemini
