Glad to hear that resonates. Goes without saying that we get the best reception with people who've literately done manual surges on this. Speaking from experience?
> Refactoring the logs in existing code bases today is a manual slog.
slog is shorthand for structured logs[1][2][3][4]. So refactoring the logs [without a tool] is manually converting them to a slog. You have a great pun on your hands.
> Speaking from experience?
I have a notebook laying around with a loose plan on how to get the most compression possible out of a log file. It would use ML to figure out what the log strings would be - but I think your idea of scanning the executable is even more clever. Anyway, once it knows the log strings you can probably stuff it into off the shelf column storage for great compression rates. And if the compression rates are good enough then searches should be much much faster as well.
Who do you reckon are the more important existing competitors? Grafana labs or Sonarqube?
Ahah. Totally missed that, I will admit. I gratefully accept the pun and will be using it even more going forward.
If you're willing to chat on the technical details of that notebook, we'd love to. Of course, if you're hoping to build it one day and don't feel comfortable sharing, understand. If yes, it's founders@getpatchwork.io :)
We are definitely eyeing up what can be done when you control the log strings and the rest of the payload. And along the lines of what you say, our first step would be to see how much ClickHouse could squeeze that, and then see what other clever compression could be added in advance.
Anyone crushing it in the code analysis and refactoring space is a challenger. I think for now our sense is that the full-blown agentic SWE tools have bitten off more than they can chew and aren't viewed as credible just yet. However there are people out there taking a focused, use-case-specific approach (like us) who are building impressive things. komment.ai is one that springs to mind. SonarQube looks interesting - thanks for flagging.
In terms of logging stack players, we're hoping some could be friend rather than foe, at least to begin with. We thought ClickHouse might see unstructured logs as an unlock for their customers / GTM motion. However, they have invested a lot in their query-time materialisation tech, which they said their log storage customers love. Expensive, in practice, I suspect. Grafana actually pinged me yesterday.
slog is shorthand for structured logs[1][2][3][4]. So refactoring the logs [without a tool] is manually converting them to a slog. You have a great pun on your hands.
> Speaking from experience?
I have a notebook laying around with a loose plan on how to get the most compression possible out of a log file. It would use ML to figure out what the log strings would be - but I think your idea of scanning the executable is even more clever. Anyway, once it knows the log strings you can probably stuff it into off the shelf column storage for great compression rates. And if the compression rates are good enough then searches should be much much faster as well.
Who do you reckon are the more important existing competitors? Grafana labs or Sonarqube?
[1] https://github.com/slog-rs/slog
[2] https://github.com/gookit/slog
[3] https://github.com/kala13x/slog
[4] https://pkg.go.dev/log/slog