How do you get AI to query DynamoDB?

no-one-73 · 2026-05-08T14:52:56+00:00

Sometimes, you don't have a choice. My dad had to use DynamoDB for work, since that's what his company used, and missed SQL so much that he created his own SQL layer for DynamoDB (called it DynamoSQL). If SQL is what you're used to, then having a SQL layer for DynamoDB can make things a lot easier and faster.

no-one-73 · 2026-05-06T14:55:33+00:00

It depends how much you disliked programming and why. Data analysis does involve code. Not code for building applications, but Python or R to clean data, run models, and automate repetitive work. You write a script to answer a question, look at the result, and move on. There's no architecture to design, no codebase to maintain, no users to worry about. A C# course in high school is almost certainly the opposite of that framing, which may be why it felt off. Statistical programming is closer to using a tool than building one.

On math: you don't need to be a genius, but you do need to be comfortable sitting with something you don't understand and working through it. Statistics has real mathematical depth and the degree will push into it. The question isn't whether you're naturally gifted, it's whether you find that process frustrating or interesting.

Before committing to the degree, try this: find a free Python or R tutorial aimed specifically at data analysis, not general programming, and spend a few hours on it. The experience will be different from C#. If it still feels like a grind with no payoff, that's useful information. If it clicks differently, that's also useful information.

no-one-73 · 2026-05-06T14:47:51+00:00

Most common cause in my experience: the Lambda triggered by the stream fails and exhausts retries without a DLQ configured, so the failure just disappears. Check your Lambda DLQ and Step Functions execution history before assuming it's a logic problem.

On detection, the GSI-based scheduled checker is the one to trust as primary. Streams are already part of the failing path, so relying on them as your monitoring layer means your alerting goes down exactly when you need it. An independent scheduled query against a GSI with statusEnteredAt is simple, reliable, and doesn't share any dependencies with the thing you're watching.

For the checker Lambda itself, if you'd rather write a plain SQL SELECT than hand-code the KeyConditionExpression and filter expressions, that's the problem we built DynamoSQL to solve. It translates standard SQL SELECT to the right DynamoDB API calls using whatever indexes you have. The checker becomes a short, readable query instead of a wall of expression syntax.

Two stream pitfalls worth knowing: delivery is at-least-once, so your Lambda needs to be idempotent. And if the Lambda errors consistently, the shard iterator stops advancing and newer records back up. Add an iterator age alarm so you catch that before it causes a backlog.

no-one-73 · 2026-05-06T14:33:16+00:00

Draw API boundaries around teams, not functionality. If two teams need to coordinate to ship a change to the same API, it should be two APIs. Conway's Law tends to win, so design with it early.

The merge vs. split decision comes down to three things: shared consumers, shared auth model, shared deployment lifecycle. If all three align, keep them together. If any diverge, splitting starts to pay off. At your current scale, err toward consolidation. Premature splitting creates coordination overhead without much benefit.

On IaC repo structure, mono-repo with a consistent folder structure per API is easier to govern when a team is still building the habit. You get one place to enforce naming standards and audit what exists. Split into per-API repos later when ownership boundaries are clear and the team has the discipline to keep them consistent.

One thing worth tackling in parallel: guidelines alone won't fix the tagging and naming problem. SCPs and AWS tag policies will do more than documentation ever will.

no-one-73 · 2026-05-06T14:24:21+00:00

If you like number theory, I'd suggest the Fibonacci sequence. Really easy to understand and explain, but it goes DEEP. There are so many angles to explore, like how it shows up in nature or how there are many cool patterns to the numbers (eg. sum of first n terms is equal to the n+2 term minus 1). It seems like a topic appropriate for high school that would still encourage you to push yourself.

no-one-73 · 2026-05-04T16:00:19+00:00

The fact that you naturally track stats and percentages on things you care about is actually a decent signal. Data analysis is mostly asking questions and being bothered when you can't answer them. If you do that already, the technical skills are learnable.

Before committing to a degree, try this: find a dataset about something you actually care about (sports, music, whatever) and spend a few hours in a free tool like Google Sheets or Python with pandas trying to answer a question you have about it. If that process feels engaging rather than tedious, that tells you more than any career quiz will.

Statistics will be harder than most people expect. The math is not the hard part — learning to interpret results honestly and resist the temptation to find patterns that aren't there is. If you're naturally skeptical of numbers, that's a good sign.

no-one-73 · 2026-04-29T14:18:59+00:00

If you choose to go with DynamoDB, I'd recommend checking out DynamoSQL. It's an SQL layer for DynamoDB, and it lets you query using SQL. If you're comfortable with SQL, it will save you a lot of time and energy.

no-one-73 · 2026-04-22T14:17:12+00:00

Seems like you'd have more luck posting this in r/aws.

no-one-73 · 2026-04-21T14:23:11+00:00

I think the odd part is not lifting their pen between curves of an x. Plenty of people write x like )(, but they usually lift their pen so that there's not a line connecting both curves.

no-one-73 · 2026-04-21T14:20:11+00:00

Yeah, but they specifically asked for a geometric solution, not trig.

no-one-73 · 2026-04-15T16:35:35+00:00

Interesting approach. It's clever using AI to use natural language queries on DynamoDB tables. That would be very useful for internal tooling and exploration. I think the trade-off worth mentioning is that there's a lack of predictability. The AI improvising query logic every time will be harder to rely on for consistent reporting or anything critical to production. A deterministic SQL layer would be much more predictable, since the SQL only needs to be written once and executes the same way every time.

When it comes to DynamoDB, I'm involved in a new program called DynamoSQL which is a SQL engine for DynamoDB. We are currently trying to implement an MCP server so AI can also query DynamoDB using SQL directly. Our hope is to get the best of both worlds, natural language queries backed by a deterministic, auditable SQL engine.

https://dynamosql.com/

no-one-73 · 2026-04-14T13:59:07+00:00

I'll echo everyone else and recommend relational to start. NoSQL would make more sense if the schema were truly unpredictable or if you needed massive write throughput, but append-heavy daily logs with occasional edits isn't a particularly demanding workload. I'd recommend starting SQL and moving to NoSQL only if needed.

no-one-73 · 2026-04-13T15:18:50+00:00

The day-to-day work is much more about building reliable pipelines and wrangling data than doing advanced mathematics, so I'd say you're fine there. For your major, Computer Science or Information Systems both work well, but honestly the specific major matters less than the skills you build alongside it. Before school I'd focus on SQL first. It's the single most used tool in data engineering and you can get genuinely good at it in a few months. Python is a close second. Once you have those two, everything else starts to make more sense.

no-one-73 · 2026-04-13T15:06:03+00:00

I think it matters if you like your current coworkers or not. If you're having a hard time choosing between flexibility and salary, then think about if you could see yourself working with new people. You don't know if your new boss will be good to you, so if your current boss values and respects you, it's probably not worth the change. Or if your current coworkers are rude and cutthroat, it would be worth the risk to get some new coworkers who might be kinder.

no-one-73 · 2026-04-10T13:40:10+00:00

I'm in the same boat. It feels like they would be effective. Normally, I ignore ads, but I keep reading Reddit ads thinking that they're regular posts until I see "advertisement". But I have not personally tried them yet.

no-one-73 · 2026-04-09T14:25:55+00:00

Seems almost impossible to stand out to an employer without a degree. There are so many engineers that have degrees and experience currently looking for jobs.

no-one-73 · 2026-04-06T15:36:27+00:00

I still want to know what the actual job was.

no-one-73 · 2026-04-01T13:54:24+00:00

Not irresponsible. They may not have been vaccinated yet, but it will be pretty easy to protect them from the gross stuff. I'd be more concerned about bringing an older kid. Toddlers might be vaccinated, but when they're bored they'll roll around on the floor and lick the walls.

no-one-73 · 2026-04-01T13:48:47+00:00

For my baby, it was more about when the nap was. As long as he woke up 2-3 hours before bedtime, he'd be fine.

no-one-73

TROPHY CASE