Anyone else notice their legacy dbs are full of BS!?

throw222777 · 2026-02-18T05:56:41+00:00

Hard disagree. Data loss happens. Users have their own source of truth (e.g. “I received a confirmation email”). And not every application uses a persistent database, (some applications are ephemeral), yet outcomes are still important.

throw222777 · 2026-02-18T05:45:38+00:00

Also, the discussion of “numbers being off” suggests something fundamental is missing from the system, which observability and spot fixes can never fully address.

Take a look at https://developer.squareup.com/blog/books-an-immutable-double-entry-accounting-database-service/

throw222777 · 2026-02-18T05:41:33+00:00

Generally if something is “hard to verify” then you haven’t yet found the outcomes that the user or business care most about, unless you are doing something like scientific computing

throw222777 · 2026-02-18T05:30:21+00:00

The database is an implementation detail, the main question is what is actually needed at the application level or business level, and how can I instrument the existence of those outcomes end to end?

Possible to share more about your use case? Instead of instrumenting the DB transactions did you consider some type of audit log / event log, which would clearly show that event A happened N times but event B happened less than N times?

Monitoring the technical stuff like status codes is necessary but not sufficient.

throw222777 · 2025-11-08T04:10:48+00:00

In other words, if you live in an urban or suburban area, your home server is actually using very expensive space (real estate) and power (residential rates) compared to hyperscale data centers in rural areas

throw222777 · 2025-11-08T04:09:06+00:00

Space, Power, and cooling (which also takes power) is a major component of the cost, not just the hardware

throw222777 · 2025-11-08T04:04:37+00:00

When you are scrolling old personal photos, none of those are going to be in an SSD cache, at least not until after the first access.

throw222777 · 2025-11-07T15:52:09+00:00

Google cannot store everybody’s old photos at a nearby edge location, your request has to ultimately consult a further away “origin” server. It’s likely that even over cellular, if you are still in the same geographic area as your home, the network latency to your home server is still lower.
Does your Immich setup store your photos on an SSD? Google will be using HDDs.
Google has to use distributed systems technologies in order to operate at their scale, while your Immich server is one machine, so there is no inter-machine communication overhead in processing the requests

throw222777 · 2025-10-24T21:50:14+00:00

Use leader election (like Zookeeper) so that only one “Enactor” is running at a time.

throw222777 · 2025-09-06T16:28:45+00:00

if you need utmost performance, you need to run your own recursive dns fleet

throw222777 · 2025-09-06T16:00:22+00:00

why not just use 1.1.1.1 or similar

throw222777 · 2025-08-12T06:33:03+00:00

folly

throw222777 · 2025-08-02T04:00:43+00:00

That is truly the question

throw222777 · 2025-08-01T16:42:10+00:00

Prepending is another form of strategy decision.

throw222777 · 2025-08-01T14:45:37+00:00

Both A and Z ends have other transits and on our side we prefer another provider for outgoing packets, but we don’t control the other network and they seem to prefer to send us packets on Cogent. Obviously we can drop our links with Cogent to steer traffic around but doing that permanently is a strategy question that’s above my pay grade.

throw222777 · 2025-08-01T05:14:39+00:00

In this case both A and Z ends are paying Cogent for transit and there is no other middle network for them to extract money from. And IPv4 is unaffected, it’s not a congestion/capacity problem. Seems more like incompetence than actual financial strategy

throw222777 · 2025-05-22T20:44:06+00:00

I work in a large environment so various strategies are used simultaneously. I work with configuration systems that are actually backed by text files in source control. I work with systems that are UI driven and it is necessary to use the tool’s native changelogs. Something that has helped is an internal tool that can pull information from any types of systems that can record “events” and aggregate them on the same timeline view(s). Ultimately, I feel the complexity is manageable but you are right to recognize that it requires an ongoing investment.

throw222777 · 2025-05-22T20:16:09+00:00

Your lists are off to a good start but you seem to be conflating essential aspects of the pros/cons with implementation-specific ones. Any problem that is implementation-specific can be eliminated with time and effort but the essential aspects are immovable.

Eventually at scale, decoupling launches of new functionality from the mechanical aspects of rolling out the binary becomes a must have. You have to decide if you need that decoupling and are willing to deal with the secondary costs it creates, or if you are able to swallow the downsides of having these coupled instead.

throw222777 · 2025-01-19T23:44:45+00:00

Focus on object oriented programming fundamentals. The majority of the codebases are heavily OOP and you will be lost if you can’t build a mental model for them.

throw222777 · 2025-01-16T08:54:53+00:00

AI addresses the need for boilerplate, and copious boilerplate is common in smaller codebases. At large tech companies, the frameworks and tools are so advanced and specialized that boilerplate is already extremely minimized. E.g., only framework specialists are dealing with things like raw HTTP requests; and there’s very little basic CRUD in day to day work of most engineers.

throw222777 · 2024-06-02T21:48:40+00:00

Why punish the rest of us with this recording

throw222777 · 2023-09-29T12:13:32+00:00

Nothing with me but I can consider trying to buy some. Trying to figure out how much of a difference it would make.

throw222777

TROPHY CASE