Bloat is still software's biggest vulnerability (2024)

Original Article ↗ Hacker News Discussion ↗

Cultural and Organizational Drivers of Bloat

  • Several comments blame management incentives: only visible features count, so cleanup, simplification, and security get cut.
  • Agile/Scrum metrics (story points, “value every sprint”) discourage refactoring and pruning, locking teams into ever-increasing complexity.
  • Some argue big tech’s security problems are not primarily about coders’ skills but slow, political decision‑making around removing bad dependencies.

Microservices, Containers, and Local Dev Hell

  • Multiple anecdotes of needing many interdependent microservices, containers, and consoles just to run or debug a feature; 20+ containers, manual auth steps, 20‑minute startup times.
  • Docker and Kubernetes are seen as both helpful (isolation, reproducibility) and a bloat amplifier (many layers, huge images, long downloads, fragile setups).
  • Desire for a “developer orchestration layer” that can easily switch services between local source, local containers, and remote endpoints.

Dependencies, Package Managers, and Supply Chain Risk

  • Easy package managers (npm, cargo, Maven, etc.) encourage enormous transitive dependency trees (hundreds or thousands of deps) where a single function pulls in megabytes of code.
  • Some praise C/C++’s painful dependency story for forcing restraint; others note this just shifts bloat into giant all‑in‑one libraries and homegrown “standard libraries.”
  • Debate over mirroring dependencies vs. relying on ecosystem tools for vulnerability tracking; no consensus on how to “know” a dep is safe.

Security, Memory Safety, and Attack Surface

  • One camp emphasizes memory-unsafe languages (C/C++) as a major security risk; another argues this is overstated compared to the impact of overall attack surface and supply‑chain bloat.
  • Heartbleed vs. Log4j is used to show major exploits occur in both unsafe and memory‑safe ecosystems.
  • Several stress that smaller, simpler binaries and fewer features reduce attack surface regardless of language.

Web, NPM, and Application Platforms

  • JavaScript’s weak standard library is blamed for the extreme dependency explosion (e.g., “is-odd,” left-pad‑style packages).
  • Some wish for a move back to native apps or WASM, others counter that browsers’ sandboxing, inspectability, and ad‑blocking are major advantages over opaque native binaries.

Reinventing vs. Reusing: Where to Draw the Line

  • Strong disagreement over “write it yourself”:
    • Pro‑reuse: you can’t realistically reimplement SSL, databases, or IAM; high‑quality shared libraries are essential.
    • Pro‑minimalism: for non‑core or simple features, bespoke code can be leaner, easier to understand, and have a smaller attack surface than pulling in a huge library.
  • Heuristics suggested:
    • The closer to your core business, the less you outsource.
    • Treat security/crypto as something to reuse carefully, but note many “expert” security products have had serious flaws too.

Bloat vs. Technical Debt and Performance

  • Some distinguish UX bloat (too many features, toolbars) from code‑level technical debt (indirection, tangled logic) and from pure performance/size issues.
  • Examples: tiny apps doing trivial tasks but shipping multi‑MB binaries; Android and modern desktop apps cited as especially egregious.
  • Tree‑shaking and link‑time optimization help but can’t remove complex, reachable features that you don’t actually need.

Operating Systems, Distros, and Minimalism

  • Nostalgia for tiny systems (Plan 9/9front, floppy‑boot Linux) contrasts with today’s multi‑GB “minimal” distros.
  • Alpine and unikernels are praised for size, but musl and ecosystem incompatibilities limit their use.
  • Debate over whether a 1 GB “minimal” Linux is a practical problem in a world of cheap SSDs vs. still significant for SBCs, phones, and constrained environments.

Developer Burnout and Cognitive Load

  • Several describe burnout and even quitting jobs due to the stress of maintaining bloated, over‑engineered systems with many moving parts.
  • One commenter coins “cognitive sovereignty”: over‑reliance on opaque tools and libraries erodes developers’ understanding of what their systems actually do.
  • Concern that AI‑assisted “vibe coding” will further accelerate code and dependency bloat.

Proposed Directions and Emerging Tools

  • Suggestions include: stricter vetting of dependencies, more granular libraries, richer standard libraries to reduce external deps, and making systems “one‑script installable.”
  • Go is cited as an example of a leaner ecosystem (strong stdlib, simpler module system, supply‑chain controls), though not everyone agrees it’s actually better.
  • Research work is mentioned on tools that automatically remove unused code from containers and shared libraries as a practical way to shrink attack surfaces.