edejong

7 ms·

31.
by edejong 3y ago
I wish we rephrased stuff by mentioning actors: “Our careless actions have resulted in an unprecedented and alarming heatwave in the sea.”
32.
by edejong 3y ago
Really curious: Half of the code base in LoC or in functionality?
33.
by edejong 3y ago
A good programmer knows the limits of the type system. They lean on that knowledge to determine which tests to write.
34.
Microsoft mitigates 0-day, allowing forged AD tokens(msrc.microsoft.com)
1 points by edejong 3y ago|1 comments
35.
by edejong 3y ago
He’s not acting toxic. You just proved to have a thin skin.
36.
by edejong 3y ago
Luckily Popper explained to us we have something in science called falsifiability. I suggest you try to falsify one single theory of our current climate science. Or, alternatively, show that any of the theories is unfalsifiable. Just going
37.
by edejong 3y ago
I understood the article just fine. The "Let It Crash" philosophy is scale invariant. Please read the last three paragraphs in [0]: "a well-designed application is a hierarchy of supervisor and worker processes" and &quo
38.
by edejong 3y ago
Let it crash is anti-fragile. Either you understand that, or you try to make super robust and super expensive applications.
39.
by edejong 3y ago
In the 27 minutes after you wrote your comment, our CI/CD rebuild two containers from a latest snapshot. No manual work involved.
40.
by edejong 3y ago
CPU/Memory: scale horizontally when needed. Monitor cost. Disk: essentially limitless. If disk of VM runs out, node will crash, new node will start. Service should keep running on other nodes meanwhile. If restarts happen too often, th
41.
by edejong 3y ago
* k8s helps because you keep your application online during rolling updates. You keep your changes relatively small and can test your changes in isolation. * microservices help security because for each service you write, you create a minim
42.
by edejong 3y ago
In the meantime, your PHP app had 40 major security flaws, no meaningful monitoring, a DB that wasn't backed up and major data consistency problems. Also, when your box's hdd crashed, you lost all those minor changes you had vim&#
43.
by edejong 3y ago
Remastered often equals compressed to the max. It means that soft passages become as loud as the loud passages. Read about it more by googling 'loudness war'.
44.
by edejong 3y ago
I totally agree. JSON at the application level is too simple of an abstraction, leading to unnecessary complexity.
45.
by edejong 3y ago
Absolutely. The lasting ideas are KISS and Occam's Razor.
46.
by edejong 3y ago
But you know what happened to SOAP? It was smothered by its own success. The allure of interoperability and extensibility attracted everyone and their cat to the party. With so many stakeholders involved, it became a classic case of "t
47.
by edejong 3y ago
As I think about all the technologies that have come and gone, it's good to find some sturdy rocks as well. Here are some techs that withstood the test of time in my personal journey: * Simple, but reliable file formats: My old photos
48.
by edejong 3y ago
If an IP-address is PII, then so should be a VIN and chassis number.
49.
by edejong 4y ago
I prefer olive oil butter over any margarine. For almost all applications, I prefer it over butter.
50.
by edejong 4y ago
We decided it’s better to present this in a curated program called education.
51.
by edejong 4y ago
It seems the whole research community is in flux.
52.
by edejong 4y ago
Yes, that’s an interesting topic, especially given the prevalence of distributed compute nowadays and the rising awareness of cloud costs. In the end, the distribution is not really poisson, of course. So, you might be interested in low pas
53.
by edejong 4y ago
What are spike workloads? Is this poisson? What’s the distribution?
54.
by edejong 4y ago
True, my example is an oversimplification. In reality you want to account for rapidly and slowly changing demands. This can be solved with elasticity of systems or by overprovisioning. You can get deep, with time series analysis, low pass f
55.
by edejong 4y ago
Poisson. And 1.0 variance in request processing time.
56.
by edejong 4y ago
Queues should have an ideal size based on your latency requirements. Say, you have 100 requests coming in per second. Each consumer of your queue requires 0.3 seconds per request. Now, you can optimise for the number of consumers. Would you
57.
by edejong 4y ago
Queues should absolutely not be empty. If they are often empty, you're over provisioning your consumers. There is an ideal size to a queue, based on the balance equation ( https://en.wikipedia.org/wiki/Balance_equ
58.
by edejong 4y ago
Required.
59.
by edejong 4y ago
At a Dutch CS study we had an SQL course that started with first-order logic, relational algebra and went to on to project that into SQL. It also taught 3NF/4NF and BCNF, indices, r-trees, query planning and optimisation.
60.
by edejong 4y ago
Because there is more to life than coding? Family, friendship, health, leisure… Other professionals actively try to separate these from their daily duties, regardless of whether they like their jobs.

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