I don’t think Netflix actually cancels shows after two seasons any more often than other networks do.

Somehow people got it into their heads that Netflix is far more cancel-happy than its competitors, but if you look at the numbers, traditional TV networks have had like a 50% cancellation rate for decades.

Even TOS was cancelled after two seasons!

If Netflix is more prone to cancelling shows at all, which I’m not convinced is even true, it can’t be by an enormous margin.

SQL, where injection is still in the top 10 security risks

This is absolutely true, but it’s not what it looks like on the surface, and if you dig into the OWASP entry for this, you’ll see they talk about mitigation.

You can completely eliminate the possibility of injection attacks using well-understood technologies such as bind variables, which an ORM will usually use under the covers but which you can also use with your own queries. There are many, many database applications that have never once had a SQL injection vulnerability and never will.

The reason SQL injection is a widespread security risk, to be blunt, is that there are astonishingly large numbers of inexperienced and/or low-skill developers out there who haven’t learned how to use the tools at their disposal. The techniques for avoiding injection vulnerability are simple and have been well-documented for literally decades but they can’t help if a lousy dev decides to ignore them.

Now, a case could be made that it’d be better if instead, we were using a query language (maybe even a variant of SQL) that made injection attacks impossible. I agree in principle, but (a) I think this ends up being a lot harder than it looks if you want to maintain the same expressive power and flexibility SQL has, (b) given that SQL exists, “get bad devs to stop using SQL” doesn’t seem any more likely to succeed than “get bad devs to use bind variables,” and © I have too much faith in the ability of devs to introduce security vulnerabilities against all odds.

it would be great to “just” have a DB with a binary protocol that makes it unnecessary to write an ORM.

Other people have talked about other parts of the post so I want to focus on this one.

The problem an ORM solves is not a problem of SQL being textual. Just switching to a binary representation will have little or no impact on the need for an ORM. The ORM is solving the problem that’s in its name: bridging the conceptual gap between an object-oriented data model and a relational data model. “A relational data model” isn’t about how queries are represented in a wire protocol; instead, it is about how data, and relationships between pieces of data, are organized.

So, okay, what if you get rid of the relational data model and make your database store objects directly? You can! NoSQL databases had a surge in popularity not too long ago, and before that, there have been lots of object databases.

What you’re likely to discover in an application of any real complexity, though, and the reason the industry has cooled somewhat on NoSQL databases after the initial hype cycle, is that the relational model turns out to be popular for a reason: it is extremely useful, and some of its useful properties are awkward to express in terms of operations on objects. True, you can ditch the ORM, but often you end up introducing complex queries to do things that are simple in SQL and the net result is more complex and harder to maintain than when you started. (Note “often” here; sometimes non-relational databases are the best tool for the job.)

And even in an object database, you still have to know what you’re doing! Storing objects instead of relational tuples won’t magically cause all your previously-slow queries to become lightning-fast. You will still need to think about data access patterns and indexes and caching and the rest. If the problem you’re trying to solve is “my queries are inefficient,” fixing the queries is a much better first step than ditching the entire database and starting over.

You’re not missing much power with jOOQ, in my opinion as someone who has used it for years. Its built-in coverage of the SQL syntax of all the major database engines is quite good, and it has easy type-safe escape hatches if you need to express something it doesn’t support natively.

jOOQ is really the best of both worlds. Just enough of an ORM to make trivial CRUD operations trivial, but for anything beyond that, the full expressive power of SQL with added compile-time type safety.

And it’s maintained by a super helpful project lead, too.

Here’s some Apache-licensed code that addresses this exact problem. The language files are in CSV format and get turned into JS files as a build step. It prints warnings for strings that are missing from other languages. In dev environments, there’s middleware that watches for edits to the CSV files and rebuilds the JS files.

A bit off-topic, but why do people still insist on writing its name in all caps? That was the original name, granted, and you can still find it here and there in the tool, but it has been called “Jira” for years now.

O’Reilly books were my go-to when I worked at a company that had a training budget I had to spend every year. Not hard to rack up a couple hundred dollars of book purchases.

Not just by the time of Kirk. He’s already gone by the time of “The Cage.”

EDIT: No, I got my timeline screwed up. “The Cage” predates SNW. Oops.

Thanks. Not something I’d want to do (I like my work and personal tabs in totally separate windows) but obviously that’s just personal preference.

How do multi-account containers differ from Chrome profiles?

Saw this at the Comic-Con screening and it works better than I expected, especially the physical comedy. The exaggerated cartoon antics are still there, but toned down just enough to not seem out of place in live action.

What metric did they use to determine what “top 10%” means? Because that’s the part of this that seems most ridiculous to me given how situation-dependent most engineering decisions are. To illustrate with an extreme example: is “daily+ deployment frequency” a sign of an amazing engineering org if the thing being deployed is updates to your heart monitor firmware?

The AR wall was obvious but it doesn’t bother me that much. Environments that require active suspension of disbelief have been a Star Trek staple since the 1960s.

Answering my own question: My systems do zero-downtime deployment. Some of my services are managed using ECS and some using custom deployment scripts.

It’s interesting that people mostly focus on the mechanics of launching the new code. To me, the interesting thing about zero-downtime deployment is what happens while the release is in progress, when there will be a mix of the old and new code versions accessing the same resources (databases, microservices, etc.) at the same time.

For example, you don’t want to just drop a previously-mandatory column from a SQL database: even if your new release no longer references the column, the new code will break if you deploy code before updating the database, and the old code will break if you update the database before deploying code. Obviously there are ways to do this kind of thing (roll out the change in small backward-compatible steps) but they’re extra work and can be easy to get wrong even if you’re using ECS to launch the code. Whereas, if you’re allowed to take downtime, you can do it all in one step without worrying about mixed-version environments.