Trillian log sequencing: demystified?

One way to view Trillian is as a database with an append-only Merkle tree. That Merkle tree is managed by a separate component called a log signer. It runs in a dedicated process that basically merges pending leaves that have yet to be incorporated into the Merkle tree. This part of the log signer is structured as a sequencing job that runs periodically. I spent a few hours learning more about the details and thought shared knowledge is better.

Problem definition and overview

Trillian’s log signer comes with a whole bunch of configuration options that are spread across several different files. Some of these options are more difficult to grasp than others, such as num_sequencers , sequencer_interval , and batch_size. I don’t mean difficult as in understanding that there may be several sequencers t hat run periodically, but rather what that actually means in terms of concurrency and how much can be sequenced per time unit.

The short answer is as follows:

  1. Regardless of how many sequencers you configure there will be no concurrent sequencing of a particular Merkle tree. The number of sequencers is only relevant if there are multiple Merkle trees.

In other words, to avoid building up a large backlog you need to consider how often the sequencer runs and how much work it is willing to do every time. The longer answer is detailed below, and it includes a little bit of additional context regarding what you may (not) do with these three parameters. For example, the sequencer job is most reliable if it runs often over small batches.

Log signer

The most central part of the log signer is probably its forever loop. For reference it is implemented by Trillian’s operation manager, see the OperationLoop function. In a nutshell, the log signer wakes up, performs some jobs, and goes back to sleep. Pretty much a busy working day!

Coordination

Before proceeding you need to know that a log signer may manage multiple different Merkle trees. It might sound odd at first, but hopefully less so if you think about the existence of transparency applications that use temporal sharding: the split of one transparency log into multiple smaller ones so that the leaves are grouped by, say, yearly relevance like 2020 and 2021. This allows parts of the log to be retired as soon as they are no longer needed. You can also run multiple different log signers to avoid single points of failure. At most one log signer is responsible for a particular Merkle tree at a time though. This requires coordination, which is one part of the forever loop.

Sequencing

The other part is log sequencing. After waking up once per interval as defined by the configured sequencer_interval , the log signer takes a pass over all Merkle trees that it manages. A sequencing job is scheduled for each Merkle tree that the log signer is currently the master for. It is determined by an election protocol which is used for coordination in the case of multiple log signers, otherwise master is assumed as there is nothing to coordinate. Next, these jobs are distributed to a number of concurrent sequencers that work on different Merkle trees. This means that there is no concurrency whatsoever when a particular Merkle tree is being sequenced. Moreover, what is selected for sequencing is deterministic based on Trillian’s internal timestamp order and the number of leaves that the sequencer is willing to process per job.

In other words, there is no point setting num_sequencers higher than the number of Merkle trees that you manage. You may set it lower, in which case at least one sequencer will move on to a different sequencing job (and thus a different Merkle tree) once it is done. Now it is also evident that the configured sequencer_interval and batch_size determines an upper bound for the number of writes per time unit. It is an upper bound because your hardware might not be capable of handling, say, 10k writes per second.

Concluding remarks

When I noticed the sequencer_interval parameter I wondered if it could be used to configure a tree head frequency, such that the Trillian front-end personality would only see a fixed number of updates per time interval. For example, you might want that because the second version of Certificate Transparency requires control over it and some gossip-audit models assume it. If not supported by the Trillian back-end, the front-end personality has to take on the role. While it is trivial in the case of a single personality instance (e.g., pick a tree head every hour), it might require some additional coordination if there are multiple concurrent instances running. So, it would be convenient if the already coordinated log signer could enforce a tree head frequency.

In theory it is of course possible to set the sequencer interval and batch size to accommodate both a frequency and an upper bound for writes per second. In practice it is apparently recommended to use short intervals and batch sizes of up to 1000 leaves. This recommendation involves quite a bit of nuance, and relates to things like which back-end is used for the underlying database. If tree head frequencies are generally useful it might land as a back-end feature at some point. For now, it is better enforced by the front-end personality.

Acknowledgments

This story is sponsored by my System Transparency employment at Mullvad VPN. Martin Hutchinson and Pavel Kalinnikov provided valuable insights as part of a conversation in the Trillian slack. Mistakes, if any, are my own.

PhD student at Karlstad University, Sweden. Into things like transparency logging, the web’s public-key infrastructure, and privacy-enhancing technologies.

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