Going to Strange Loop was a huge check off my conference bucket list (lanyard?). I’d always heard about this slightly-weird, highly academic collision between academia and industry, skewing toward programming languages you haven’t heard of (or, at the very least, you’ve never used in production). I anticipated sitting at the feet of gray-haired wizards and bright-eyed hipsters with Ph.Ds.

The conference did not disappoint. And it was not quite what I expected-I less sat at the feet of geniuses than I did talk with them, peer-to-peer, about topics of interest. All around me people were saying “Don’t be afraid to ask questions. Don’t feel stupid - nobody knows everything.” Speakers were tweeting about how much they were learning. It was comforting, because lots of topics I had come to see were those in which I had no. freakin. clue. about.

The following is culled from my notes from different sessions I attended. I will focus on brevity. I will keep it clear. Here we go:

Opening Keynote: “I see what you mean” - Peter Alvaro

• Instructions, behaviors & outcomes.
• It “feels good” to write in C (a hardcore 1000 liner)
• But a declarative program (e.g. SQL) works well, but is harder to come up with.
• The declarative world - as described in the work done in Datalog
• How can we take concepts from Datalog and apply to real-world resources like network actors (distributed systems)?
• It becomes easier to model these systems declaratively when we explicitly capture time.
• Enter Dedalus: extension to Datalog where time is a modeling construct.
• (Show off usage of @next and @async annotations
• Computation is redezvous - the only thing that you know is what YOU know at that point in time.
• Takeaway: Abstractions leak. Model them better (e.g. with time)
• Inventing languages is dope.

Have your Causality and your Wall Clocks Too (Jon Moore)

• Take concept of Lamport clocks and extend them with hybrid clocks.
• And extend them one further with: Distributed Monotonic Clocks
• These DMCs use population protocol (flocking) to each actor in the system communicate with another, updating their source of truth to eventually agree on a media time w/in the group
• DMC components:
  1. Have a reset button by adding epoch bit
  2. Use flocking (via population protocol) to avoid resets
  3. Accomodates for some clockless nodes
  4. Explicitly reflects causality

Building Isomorphic Web Apps with React - Elyse Gordon

• Vevo needed better SEO for SPAs. Old soln was to snapshot page and upload to S3.
• Beneficial for SEO crawlers
• React in frontend. Node in backend.
• Vevo-developed pellet project as Flux-like framework to organize files.
• Webpack aliases/shims
• Server hands off to browser, bootstraps React in client.
• Alternatives: Relay, Ember

Designing for the Worst Case: Peter Bailis (@pbailis)

• Designing for worst case often penalizes average case
• But what if designing for the worst case actually helps avg case?
• Examples from dstbd systems:
  • Worst case of disconnected data centers, packet loss/link loss. Fix by introducing coordination-free protocols. Boom, you’ve now made your network more scalable, performant, resistent to downtime.
  • Worst case: hard to coordinate a distributed transaction between services. What do you do? You implement something like buffered writes out of process.
    • CRDT, RAMP, HAT, bloom
    • Suddenly, you have fault tolerance
  • Tail latency problem in microservices: the more microservices you query, the higher the probability of hitting a slow server response.
    • Your service’s corner case is your user’s average case
  • HCI: accessibility guidelines in W3C lift standards for all. Make webpages easier to navigate. Side effect of better page performance, higher conversion.
  • Netflix designing CC subtitles also benefits other users.
  • Curb cuts in the real world to help ADA/mobility-assisted folks also benefit normal folks too
• Best has pitfalls too: your notion of best may be hard to hit, or risky. You may want to optimize for “stable” solution. (Robust optimization)
• When to design for worst case?
  • common corner cases
  • environmental conditions vary
  • “normal” isn’t normal
• worst forces a conversation
  • how do we plan for failures?
  • what is our scale-out strategy?
  • how do we audit failures? data breaches?

Ideology by Gary Bernardt

• Rumsfeld: known knowns, known unknowns, and unknown unknowns.
• Ideology is the thing you know you do not know you know
• Conflict between typed vs dynamic programmers:
  • Typed: “I don’t need tests, I have types”
  • Dynamic: “I write tests, so I don’t need types”
• In reality, they are solving different places in the problem domain, but they have different beliefs about the world that are hidden in the shadows:
  • Typed: “Correctness comes solely from types”
  • Dynamic: “Correctness comes solely from example”
• “I need nulls” -> You believe nulls are the only way to represent absence
• “Immutable data structures are slow” -> You believe all immutable types are slow
• “GC is impractical” -> you believe GC algorithms won’t get faster.
• Read CSE 341 Type systems, Dan Grossman

Building Scalable, Stateful Services: Caitlin McCaffrey

Sticky connection: always talk to the same machine

Building sticky connections:

• persistent connections (load balancing cannot rebalance server)
• implement backpressure (d/c connection)

dynamic cluster membership

• gossip protocols -> availability
• consensus systems -> consistency (everybody needs to have the same worldview.

work distribution:

random:

• write anywhere, read from all

consistent hashing: on session ID

hash space -> node dynamoDB, Manhattan

con: can have hotspots, could have uneven distribution of resources cannot move work.

distributed hash table

statefully store hash

Real world

Scuba (Facebook)

• distributed in-memory DB

Ringpop (Uber)

• Node.js swim gossip protocol, consistent hashing

Orleans (MS Research)

• actor model
• gossip
• consistent hash
• distributed hashtable

Idalin “Abby” Bobé: From Protesting to Programming: Becoming a Tech Activist

• Tech to resist exploitation
• Technologists as activists
• Idalin Bobé -> Changed name to “Abby” to get a job.
• Pastor Jenkins - magnifying glass vs paper
• Philadelphia Partnership Program:
  • 1st to college
  • work <> school
• Difficult to balance.
• Mills MBA, CS
• Joined Black Girls Code
  • Apply technology in the right way
• Ferguson happened
  • Thoughtworkers joined on the ground
  • Hands Up United: www.handsupunited.org
• “Do not be led by digital metrics” - even though the activists had digital tooling, the tools were being used against activists. Phone calls, chats monitored. Movement tracked.
• New group starting up in St. Louis called “Ray Clark, Sr.” - named after a black man who played a strong role in the founding of Silicon Valley.
• 21st century technologists need 21st century skillsets.
• Dream Defenders
• “it is our duty to fight for our freedom/it is our duty to win/we must love and support one another/we have nothing to lose but our chains”