accessr
One R Markdown source, four accessible formats — and a fortnight spent patching around someone else's bug.
A side-by-side editorial comparison of Fail2Ban and SLmetrics — release velocity, themes, recent moves, and the top alternatives to consider.
Fail2Ban finally ships 1.1.1 after 14 months in beta, with a botched deb package on the way out the door
Fail2Ban watches log files for authentication failures and bans the offending addresses through the local firewall. It remains a default component of Linux server hardening, and its release cadence has never matched that prominence — six releases in the eight years before this one. The 1.1.1 final has now landed, closing a beta that had sat unfinished since June 2025, and it installs a systemd-managed socket rather than relying solely on the daemon's own startup.
A young ML metrics package rewrote its own backend twice in six months chasing speed.
SLmetrics provides supervised learning evaluation metrics for R — confusion matrices, classification and regression measures, ROC and precision-recall curves — with the computation pushed into C++. After a series of pre-releases it now runs on an Armadillo backend, supports OpenMP parallelism and LAPACK/BLAS, and reports 5-20x speedups over its earlier implementations. The API has been reshaped for extensibility, with an estimator argument replacing the fixed aggregation options.
Fail2Ban watches log files for authentication failures and bans the offending addresses through the local firewall. It remains a default component of Linux server hardening, and its release cadence has never matched that prominence — six releases in the eight years before this one. The 1.1.1 final has now landed, closing a beta that had sat unfinished since June 2025, and it installs a systemd-managed socket rather than relying solely on the daemon's own startup.
The pattern is long silences broken by releases that mostly absorb external change — Python 3.12 and 3.13 compatibility in 1.1.0, a Dovecot filter regression in 1.0.2 — with the substance deferred to a ChangeLog the feed does not carry. What is different this time is the contributor list, which runs to a dozen first-time contributors, suggesting the delay was throughput rather than abandonment. The release also had to be re-cut: the first Debian package shipped with wrong paths from a missing systemd-dev build dependency and was pulled and replaced.
Given the beta-to-final gap just closed and the volume of first-time contributors merged into it, the useful thing to watch is whether the next release arrives in months rather than years; the entries do not indicate what it would contain.
SLmetrics provides supervised learning evaluation metrics for R — confusion matrices, classification and regression measures, ROC and precision-recall curves — with the computation pushed into C++. After a series of pre-releases it now runs on an Armadillo backend, supports OpenMP parallelism and LAPACK/BLAS, and reports 5-20x speedups over its earlier implementations. The API has been reshaped for extensibility, with an estimator argument replacing the fixed aggregation options.
Every release in this timeline is about making the same metrics compute faster or compose better. The backend moved from Rcpp to plain C++, gained OpenMP, then was ported wholesale from Eigen to Armadillo with heavy templating. In parallel the author has been widening the API's joints: generic S3 signatures, an extensible estimator argument, and function signatures loose enough that wrapping packages can rename arguments. Bundled datasets and embedded formulas in the docs point at teaching and benchmarking use. The package still labels itself pre-release, which is consistent with how freely it has broken argument names along the way.
A stable non-pre-release version is the natural next step now that the backend has settled on Armadillo, though the repeated willingness to rename arguments suggests more API churn may come first.
Other Infra & APIs 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 Fail2Ban or SLmetrics.
One R Markdown source, four accessible formats — and a fortnight spent patching around someone else's bug.
The R package that installs Java for you stopped needing an update every time Java ships.
The AusTraits engine, generalised for anyone's trait database, now links measurements to real specimens.
The toolchain that gets R packages into the browser is optimising for payload size, not features.
A logging header for Rcpp packages that sat untouched for nine years, then changed how it switches on
Draggable dock panels for Shiny, learning that layout state belongs on the client
See all Fail2Ban alternatives → · See all SLmetrics alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. Fail2Ban is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Fail2Ban is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Infra & APIs products to evaluate alongside.
Top Fail2Ban alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "Fail2Ban alternatives" section above for the current picks, or visit /alternatives/fail2ban for the full list with editorial commentary on each.
Top SLmetrics alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "SLmetrics alternatives" section above for the current picks, or visit /alternatives/slmetrics for the full list with editorial commentary on each.