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Release Bets
20 December, 2024The Problem
So you’re a big wig at some tech company and you want to make a big jump in quality. A common and reasonable sounding thing to woud be to bring in some bar raisers. You don’t have enough people you trust to do it at the Pull Request level so you decide to have them review releases yet. (Continuous Deployment isn’t happening for …. reasons….). Now you hae an interesting incentive problem.
Bar raisers don’t have much incentive to get the code out but they have a big inentive not to let a bad hange out. Type I vs Type II errors. The bar raisers don’t have much signal about what releases/changes are dangerous or not so they’re gonna want to talk about each change. You’ll end up spending a constant amount of time on low risk releases eating up alot of the review time budget. Higher risk release might get LESS disussion just beause low risk items ate up available time. So how do you get a better signal?
Enter the bet
If you want to make a release you should give the bar raisers odds their release will cause an outage (defining outages is hard but lets assume we have one). If I’m really save I migh say this release only has a 1% chance of causing an outage (anyone that says 0% is a fool). Then the bar raiser now has some information and if they want to talk about the issue they need to ante a minimum amount of money to the bet (lets say $10). If after disucssion the odds don’t change the bet is locked. If the odds change (a good thing new information being exposed!) then releaser forfeits the ante and the bar raiser can still take whatever odds that come out if they want. This both focuses the discussions using time most effetively and aligns incentives to bring out truth rather than block or override.
This works best for single change releases. If you do bulk you need PR reviewers to all give preditions and aggregate them which is harder but still doable. This is basically a prediction market. It works better the more people that can participate and the more liquid the market is. Ideally I’d be able to go bet against the release of some division far from me if I have reason to doubt. Insider Trading is a goodness here!
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Kubecon SLC 2024
16 November, 2024kubecon post thoughts.
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PodDisription Conidtions and Eviction Backpressure on replicasets-deployments and stateful sets. Started an issue 128815 to get a condition on for blocked evictions. The former should help k8s-pdb-autoscaler along but the latter should make it not necessary. The idea of back pressure is replicasets controllers would monitor their pods and update their own status if they’re seeing seeing eviction blocked on pod status. Deployment controller could then scale up if its the most recent replicaset or if there is a newere replicaset that can’t make progress scale that down then scalue up the older defacto replicaset to unblock evictions.
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Antonio’s/Network-Sig’s kube-network-policies may be able to be trivailly adapted to windows with this tailscale windows filter library. Theorically you could use ebpf to send packets into user space as well.
- Cilum Scaling. Several good presentations thoug many stared with cluster mesh. Not really a desire for us to got etcd but there are limitations
- CBOR Serializer may help some
- Maybe using apiserserv-mesh in built etcd as a proxy as that is what kvstoremesh is doing.
- Ryan was excited about replacing watch with a messaging system. I am not sure that solves our problems but loves the thinking
- Should definitely tighten up our identity garbage collection but also why isnt the identity the hash.
- Sig API maching thought streaming lists were going to help a lot. Of course growing
- Talks: Hemeth Clustermesh scalability, etcd vs api server, Ryan Drews clustermesh scalabiluy of cluster mesh , Plea for help testing
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Api server Server roll back is being worked on! Need to catch up
- Api Server backed by Postgresql was a little dissapointing. Need to measure watch performnce and write a follow up using azure postgres on cosmosdb
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