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    Benchling Engineering

    benchling.engineering · Company blog · on HN since 2015

    Benchling's engineering team writes about Postgres migrations, React performance, and CRISPR and DNA search for its biotech software.

    Visit blogHN submissions
    DatabasesDevOps & CloudProgramming
    What HN says

    HN commenters call its Lambda-based CRISPR search a compelling use case, and discuss its migration and React performance posts, with one saying the migration post is too high-level.

    Stats for nerds
    21HN people shared it
    37linked in comments
    1.1Kstory points
    May 2022last shared
    2015people per year2022

    Top posts on HN

    1. 1
      Move Fast and Migrate Things: How We Automated Migrations in Postgres
      3 people · 194 points · first shared 2019 · 54 comments on HN
    2. 2
      Performance Engineering with React, Part 1
      2 people · 158 points · first shared 2016 · 38 comments on HN
    3. 3
      Building a Regex Search Engine for DNA
      3 people · 118 points · first shared 2016 · 35 comments on HN
    4. 4
      Powering CRISPR with AWS Lambda
      3 people · 110 points · first shared 2015 · 45 comments on HN
    5. 5
      From 200K lines of CoffeeScript to zero: making decaffeinate super-stable
      1 person · 95 points · first shared 2018 · 29 comments on HN
    6. 6
      A Deep Dive into React Perf Debugging
      1 person · 83 points · first shared 2016 · 4 comments on HN
    7. 7
      Modeling Science as a Directed Graph
      1 person · 79 points · first shared 2017 · 17 comments on HN
    8. 8
      Parallel C++ on AWS Lambda for CRISPR
      1 person · 72 points · first shared 2018 · 17 comments on HN
    9. 9
      Optimizing CRISPR: Sub-second searches on a 3 billion base genome
      2 people · 70 points · first shared 2015 · 33 comments on HN
    10. 10
      Evolving to Enterprise-Grade Permissions
      1 person · 26 points · first shared 2019 · 8 comments on HN

    What HN people wrote when they linked it

    • wcjordanMay 2017

      It is, so a DOM change wouldn't occur, but in these cases you still go through a React rendering to virtual DOM phase (templating) and the DOM tree reconciliation.

      Since these can be slow (although much faster than a DOM change), it makes sense to check and skip those steps when you can.

      The focus of most of this article is how you can skip those steps when you're components input data is unchanged and common gotchas related to that.

      Some other great posts in this vein are:
      https://facebook.github.io/react/docs/optimizing-performance.html
      and
      http://benchling.engineering/performance-engineering-with-react/

    • awinter-pyMay 2022

      programming in time is hard

      (especially with migrations, because migrations take time)

      this feels too high-level -- different migration operations can afford different guarantees (esp in the multi-node case). In particular this doesn't talk about data migrations, where you might need to lock 2 tables + join them to generate a third. not all migrations are pure-sql either, they may include app code

      my favorite article about this is benchling's https://benchling.engineering/move-fast-and-migrate-things-how-we-automated-migrations-in-postgres-d60aba0fc3d4 because it talks about pre + post deploy migrations

    • dankohn1Jan 2016

      I would be thrilled if they provided an update, but Benchling's CRISPR search is what originally got me excited about Lambda. It's an incredibly compelling use case, as it enabled one second searches at any level of demand. And, their hosting costs dropped from thousands of dollars on EC2 to $60 on Lambda.

      http://benchling.engineering/crispr-aws-lambda/

    • dikaiosuneDec 2015

      I don't know the answer to how Neon would affect that, but AFAIK, you can already do this:

      http://julienblanchard.com/2015/rust-on-aws-lambda/

      But that uses a shell command. There's also this way to do so using FFI (article is about C++, but I'm pretty sure you could do the same with Rust):

      http://benchling.engineering/crispr-aws-lambda/

    • leeoniyaJun 2016

      maybe WRT to https://www.google.com/search?q=genome+sequencing+algorithms which would be needed to find unique patterns among billions of base pairs for CRISPR to target. it's microscopic big data :D

      [1] http://benchling.engineering/dna-regex-search/?hn

      [2] http://benchling.engineering/optimizing-crispr/

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