Undertow
Undertow 2.4.0 clears three CVEs and finally lands long-open HTTP/2 and timeout requests
Comparison · DevOps
NumPy vs WildFly
A side-by-side editorial comparison of NumPy and WildFly — release velocity, themes, recent moves, and the top alternatives to consider.
NumPy vs WildFly: at a glance
What is NumPy?
NumPy cut distutils loose and is quietly rebuilding for free-threaded Python.
NumPy is in the maintenance rhythm of a foundational library: a transitional minor release followed by a run of patch releases cleaning up what it broke. 2.5.0 removed distutils, expired a large batch of 2.0-era deprecations, and dropped Python 3.11. The patch line since has been about compatibility surfaces — a Cython datetime API fix so downstream can still target pre-2.5, a GCC minimum bump, and wheels for Python 3.15 release candidates.
What is WildFly?
WildFly's quarterly train is really a stability ladder, and OIDC keeps climbing it
WildFly is four majors into a metronomic release train — 38 through 41 in about eight months — where each cycle pairs a Beta with a Final roughly two weeks later that restates the same feature list. The substantive work splits cleanly in two: Jakarta EE 11 and MicroProfile spec implementations that land first in WildFly Preview, and an explicit stability ladder (preview to community to default) that individual features climb one release at a time. OIDC is the feature getting the most of that attention, with scope attributes, request/request_uri parameters, and logout each promoted across the last three cycles.
NumPy vs WildFly: editorial side-by-side
NumPy
2.5DEVOPS
NumPy cut distutils loose and is quietly rebuilding for free-threaded Python.
◆ Current state
NumPy is in the maintenance rhythm of a foundational library: a transitional minor release followed by a run of patch releases cleaning up what it broke. 2.5.0 removed distutils, expired a large batch of 2.0-era deprecations, and dropped Python 3.11. The patch line since has been about compatibility surfaces — a Cython datetime API fix so downstream can still target pre-2.5, a GCC minimum bump, and wheels for Python 3.15 release candidates.
◆ Where it's heading
Two forces are steering releases. One is Python itself: NumPy is tracking 3.15 before it ships and steadily improving free-threading support, including fixing an ABI leak in the free-threading-compatible stable ABI. The other is the array-api standard, which is pulling NumPy's own semantics into line — descending sorts landed for exactly that reason.
◆ Prediction
Expect the 2.5.x line to keep absorbing free-threading and Python 3.15 fallout; the entries suggest the interesting work now happens at the C API and build-system layers, not in array semantics.
WildFly
2.5DEVOPS
WildFly's quarterly train is really a stability ladder, and OIDC keeps climbing it
◆ Current state
WildFly is four majors into a metronomic release train — 38 through 41 in about eight months — where each cycle pairs a Beta with a Final roughly two weeks later that restates the same feature list. The substantive work splits cleanly in two: Jakarta EE 11 and MicroProfile spec implementations that land first in WildFly Preview, and an explicit stability ladder (preview to community to default) that individual features climb one release at a time. OIDC is the feature getting the most of that attention, with scope attributes, request/request_uri parameters, and logout each promoted across the last three cycles.
◆ Where it's heading
The direction is consolidation rather than expansion: features already written are being graduated to supported status instead of new subsystems appearing. In parallel the runtime baseline is moving underneath users — 40.0.1 shipped container images for JDK 25 on UBI 10 and flagged it as the last release carrying JDK 17 images. Expect the EE 11 work now sitting in Preview to graduate into standard WildFly on the same ladder OIDC has been walking.
◆ Prediction
WildFly 42 should ship container images on JDK 21 and JDK 25 only, with the remaining Preview-stability EE 11 integrations promoted toward default.
Alternatives to NumPy and WildFly
Other DevOps products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either NumPy or WildFly.
Betaflight
Betaflight grew a real autopilot: waypoint missions, geofence RTH and MAVLink ground control
OceanBase
OceanBase is rebuilding itself as a RAG backend without giving up the HTAP story
QGroundControl
QGroundControl rebuilt its flight UI around touch screens, then went quiet for ten months
Pelican
Pelican now ships roughly once a year, and 4.12 is theme housekeeping
RESTEasy
Jakarta REST implementation in pure maintenance across two parallel branches.
See all NumPy alternatives → · See all WildFly alternatives →
Recent activity from NumPy and WildFly
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1d agoNumPyPython 3.15rc1 wheels; StringDType struct made opaque under the free-threaded ABI
- 25d agoWildFlyWildFly 41 promotes OIDC scope and request-object support
- 1mo agoNumPyCython datetime API fix restores downstream support for older NumPy
- 1mo agoWildFlyWildFly 41 Beta adds transactions during graceful shutdown
- 1mo agoWildFlyWildFly 40.0.1 moves container images to JDK 25, drops JDK 17
- 1mo agoNumPyDistutils removed, 2.0-era deprecations expired, descending sorts added ⚡
- 2mo agoNumPyRelease candidate for the 2.5.0 transitional release
- 2mo agoWildFlyWildFly 40 lands Jakarta Pages 4.0 and WebSocket 2.2 in Preview
- 2mo agoNumPyQuick fix for an arr.conj() regression in 2.4.5
- 2mo agoNumPyPatch release: typing fixes, s390x CI, f2py complex mapping
- 3mo agoWildFlyWildFly 40 Beta fixes an Elytron brute-force CVE
- 6mo agoWildFlyWildFly 39.0.1 backports the Elytron brute-force CVE fix
Frequently asked questions
What is the difference between NumPy and WildFly?
They serve adjacent needs but don't currently overlap on shipped themes. NumPy and WildFly are shipping at a similar cadence (velocity 2.5 vs 2.5, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is NumPy better than WildFly?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. NumPy and WildFly are shipping at a similar cadence (velocity 2.5 vs 2.5, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other DevOps products to evaluate alongside.
What are the best alternatives to NumPy?
Top NumPy alternatives in DevOps are ranked by recent ship velocity. Browse the "NumPy alternatives" section above for the current picks, or visit /alternatives/numpy for the full list with editorial commentary on each.
What are the best alternatives to WildFly?
Top WildFly alternatives in DevOps are ranked by recent ship velocity. Browse the "WildFly alternatives" section above for the current picks, or visit /alternatives/wildfly for the full list with editorial commentary on each.