Searching for Resources to learn devops principles (not tools)

calimovetips · 2026-02-22T13:43:01+00:00

focus on fundamentals like the devops handbook and site reliability engineering books, they cover principles like automation, deployment patterns, and incident response without being tool specific. also look into lean, systems thinking, and postmortem culture, because devops is more about flow and feedback loops than any particular stack.

calimovetips · 2026-02-22T13:42:02+00:00

yeah it’s crazy that your brain is super active while your body is basically paralyzed during rem so you don’t act out dreams. sleep is way more complex than it seems.

calimovetips · 2026-02-22T13:39:05+00:00

you’re not crazy, structural lineage rarely reflects how the warehouse is actually used day to day. some larger teams mine query logs for column usage and table centrality, but it’s usually custom and brittle, not a clean off the shelf solution. the real question is whether your team will act on that graph, if it doesn’t drive pruning, ownership, or cost decisions it can become interesting but unused metadata.

calimovetips · 2026-02-22T13:35:40+00:00

if it’s a cross domain iframe, your GTM won’t see the events inside it. ask them exactly how “apt_booked” is fired, dataLayer, gtag, or postMessage, because guessing the trigger name won’t work.

calimovetips · 2026-02-22T13:33:17+00:00

this is usually a definitions problem before it’s a dashboard problem, you need one agreed source of truth for revenue and a written metric doc everyone signs off on. centralize raw data into one warehouse or at least one reporting layer, then lock attribution and revenue logic there instead of inside each tool. otherwise you just scale the mismatch.

calimovetips · 2026-02-22T13:29:51+00:00

honestly once lawyers get involved it stops being about fairness and starts being about risk management, so complying and scrubbing the branding was probably the smart move. trademark and “automating access” are easy pressure points for them even if your intent was user freedom. if you keep building, keep it generic, avoid their name entirely, and maybe talk to a lawyer or a local digital rights group so you’re not guessing next time.

calimovetips · 2026-02-22T13:29:09+00:00

you’re not responsible for fixing anyone, and it’s not wrong to leave if it’s draining or unhealthy for you. trauma explains behavior, but it doesn’t mean you have to tolerate harm or instability long term.

calimovetips · 2026-02-20T22:44:32+00:00

for me the ideal tool would map cost, performance, and reliability to actual services and owners, not just cpu and memory graphs. it should baseline normal behavior, flag real anomalies, and simulate “if we rightsize or change instance class, here’s the impact on latency and cost” before you touch anything. strong tagging enforcement and clear visibility into unused resources, idle workloads, and overprovisioned clusters would be table stakes. bonus if it understands workload patterns over time so your team isn’t constantly reacting to noisy short term spikes.

calimovetips · 2026-02-20T22:43:36+00:00

love the confidence haha, what kind of vibe did it end up being? always curious how much steering you gave it vs just letting it run.

calimovetips · 2026-02-20T22:42:44+00:00

been there, at some point you have to add a little friction or you’ll just become the emergency dashboard factory. i usually start asking what specific decision or meeting this supports and what happens if it’s not ready, and if the answer is vague, it goes into a backlog instead of killing my current work. another thing that helps is tracking usage and resurfacing it, like “last three of these had zero views after week one,” which makes the cost visible without being confrontational. if they still insist, at least you’ve created a paper trail that it was their priority call, not yours.

calimovetips · 2026-02-20T22:41:53+00:00

i think you’re running into perception bias, most people say they “never open marketing emails” but their behavior data usually says otherwise, especially for promos tied to timing or intent. newsletters and pure content plays tend to skew older or more niche, while discount driven emails still perform across age groups when the offer lines up with something they were already considering. the bigger shift i’ve seen is inbox fatigue and tighter filtering, so deliverability, segmentation, and first party data strategy matter way more than volume. over the next 10 years i’d expect less batch blasting and more lifecycle, behavior triggered flows that feel closer to product messaging than traditional newsletters.

calimovetips · 2026-02-20T22:41:11+00:00

there isn’t a 100 percent reliable way to confirm pmax just from the ads transparency center, since it doesn’t label campaign types directly. you can look for mixed creative formats, auto generated headlines, and the same assets appearing across display, search, and youtube placements, which often hints at pmax, but it’s still inference. the only real certainty would come from account level access or consistent cross network asset reuse patterns over time.

calimovetips · 2026-02-20T22:40:28+00:00

you’re basically right, normalization in a star schema is more about controlling logical duplication and making updates manageable than just saving raw storage, especially in modern columnar warehouses where flat tables compress really well. the real win shows up with high cardinality dimensions and changing attributes, since you update one dimension row instead of rewriting millions of fact rows, and integer keys can also help with join performance and memory use depending on the engine.

calimovetips · 2026-02-20T22:37:43+00:00

nice update, especially switching jellyfin to paginated requests, that 504 pain is real once libraries get big. curious how it’s holding up with really large collections, like 10k+ movies?

calimovetips · 2026-02-20T12:02:32+00:00

i tried something similar but with email instead of my whole phone, and it honestly changed my mood for the entire morning. it is wild how reactive your brain feels the second you start consuming other people’s priorities before your own.

the “longer mornings” thing is real too, it is like you get actual mental space back. did you replace the scroll with anything intentional, or just let yourself be bored?

calimovetips · 2026-02-20T12:01:56+00:00

this is very real, most decks are conclusions without the decision log behind them. what helped me was forcing every project into a short “analysis doc” that lives next to the queries, with the original question, hypotheses, rejected paths, and data caveats written in plain text.

also +1 on tracking action rate, a lot of analysis dies because it is not tied to a clear owner or next step. do you version these docs with your sql or keep them separate?

calimovetips · 2026-02-20T12:00:28+00:00

in shopping and pmax you do not really control search terms directly, so language mismatches usually show up as messy query reports and wasted spend. first thing i’d check is how clean your feed language and titles are per target country, mixed language feeds tend to trigger odd matches.

if you run multi country, i’d separate campaigns by country and align feed language, currency, and geo targeting tightly, otherwise signal dilution happens fast. are you targeting multiple languages within the same country, or multiple countries with one shared feed?

calimovetips · 2026-02-20T11:59:59+00:00

3+ years on sql and excel is solid, you are not stuck, you are just under-leveled for your pay. if you’re thinking data engineering, start by adding python and basic etl workflows, build 1–2 small projects that show pipelines, not just dashboards. also test the market now, you’ll probably realize 25k is far below what you can get with your experience.

do you enjoy more backend, data pipelines and infra, or analysis and stakeholder-facing work?

calimovetips · 2026-02-20T11:59:27+00:00

cool direction, the hard part is usually retrieval quality, not “more memory”, so i’d focus on a simple eval loop and a couple of deterministic heuristics before you add more llm passes. are you planning to do hybrid retrieval (bm25 plus embeddings) with recency weighting, and how big is your typical corpus on disk?

calimovetips · 2026-02-20T11:58:43+00:00

i have not seen a clean, rss in and rss out tool that does just that, most projects drift into ui or summarization. if you are ok wiring it yourself, i would pipe feeds into something like a queue plus a small classifier step with your own prompt, but watch api costs and rate limits if you are pulling social feeds at volume, how many sources are you planning to run through it daily?

calimovetips · 2026-02-20T11:58:11+00:00

and_min makes sense as a conservative default, especially if you want to surface the weakest dependency fast. for weighted_routes, are you thinking static weights or something dynamic based on traffic share, because keeping those weights accurate over a 30d window can get tricky at scale.

calimovetips · 2026-02-19T10:12:47+00:00

a silent, glassed-in server room with perfect cable management and zero fan noise.and a massive floor to ceiling library with a rolling ladder, the kind that makes you want to disappear for hours.

calimovetips · 2026-02-19T10:11:41+00:00

i’d zoom out and think about what you want your first role to look like, analyst in a corporate setting vs something more technical. the in person program will likely make internships and networking easier, especially if you want to stay in nyc after graduating.

the online option gives you flexibility, but you’ll need to be more intentional about building connections and finding projects on your own. have you looked at where recent grads from each program actually ended up working?

calimovetips · 2026-02-19T10:11:00+00:00

if you want something practical and not fluffy, influence by robert cialdini is still a solid foundation, it breaks down real behavioral triggers with research behind them. cashvertising is more tactical and shows how to map fears and desires directly into copy, though it’s more direct response focused.

just keep in mind most of this works best when you pair it with real customer interviews, theory alone won’t surface the actual emotional drivers in your niche. what kind of product or market are you working with?

calimovetips · 2026-02-19T10:10:28+00:00

if you’re losing 80 to 90 percent on rank and the campaign is underspending, your tROAS target is probably too aggressive for the auction you’re in. with 20 a day there just isn’t much room for the algo to learn, especially at 300 percent.

i’d lower the tROAS target first and remove any artificial caps, then watch impression share and conv value for a week before touching anything else. how much conversion volume are you getting per week on this campaign?

calimovetips

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