This page includes a video of our Prime Minister, in English. You should listen to what he says. The time of depending on America's security umbrella is over.
If the owner of the stack (Logio or whatever it was called, see upthread) doesn't understand it, the consultants will run wild and soon it will require a hectare-sized datacenter running a zillion containers, and another DC for HA of course.
Right. And in some ways, that is disappointing, and exasperating, at the same time. Strong privacy regulations would be a better way to go about it. (Note that this criticism is not specific to Netherlands - a lot of countries are, in my opinion, treating "digital sovereignty" as a matter of control between one or more countries and corporates without any real consideration for the individuals right.)
This is a direct result of Trump being in power. Before his regime, we (The Netherlands) trusted USA 1000%, this takeover would not even have been news.
This stance has shifted completely. And you can thank one guy for it.
No, monitoring for HTTP response code is a subset of observability and not one that generally gives you the best insights into which subsystems are misbehaving nor why.
There are synthetic tests, where you can generate API request calls or even simulate an entire user journey. These allow you to control the user agent, the payloads, and thus you know anything errors back are actual errors. These are triggered by the observability platform (think like running a cron-job) and thus you're not tied to user activity to see when problems arise.
There are other metrics outside of HTTP response codes too. Think like free RAM, CPU usage, disk space, etc. This is just naming some obvious ones because these types of metrics are generally bespoke to the type of application your monitoring. And with these types of monitors, you'd not just have an alert when things have failed, but ideally have alerts when an irregular trend is showing that things are likely to fail too. This latter type of monitors helps you get ahead of the problem before it become customer facing.
Then you have more traditional stuff like logs. This will also be bespoke to the application. But you'd expect errors in logs to get surfaced quickly. Assuming Github have good hygiene in what's being logged.
Tie that up with APMs, RUM, and other goodies like that and you'll have diagnostics to investigate issues when they appear.
(this is just a super high level view of observability too)
> Even a synthetic probe needs a few failures to trigger an alert.
It doesn't "need" that. That just how most people set it up because it’s an easy sane default that allows for network jitter without inexperienced engineers thinking about different conditions triggering different types of responses.
If you’re measuring internal APIs from an observablity solution that’s has nodes already inside you’re network enclave, then there is a strong argument for alerting early.
> You should not alert on cpu, ram, etc
That’s not true to say as an absolute statement. And a generalisation it heavily depends on the system your monitoring and how it behaves under pressure.
But in any case, I wasn’t suggesting CPU alerts were the end goal. I said:
> these types of metrics are generally bespoke to the type of application your monitoring.
Ie you’ll use metrics but those metrics will be highly specific.
The CPU examples were an illustration as to what a “metric” is (it might seem obvious but not everyone is an expert) but the point was HTTP response codes aren't the only types of metrics one should be capturing and watching.
Ah, yes, I misunderstood. And I have seen cases where a direct CPU alert makes sense, but 99 times out of 100 times I see it, it's nothing but trouble. Worse, I tend to see the cpu alert when there are no end to end synthetic alerts, 500 alerts, queue depth alerts, etc.
If your requests are fast and cheap, you can probe frequently relative to your goals, but often that's not really possible (think, long SQL queries, or scheduling a container/pod). There you need several datapoints, or possible fewer augmented with other signals.
Talking about long SQL queries, I quite like throwing CPU alerts on database servers. They'll be a low priority alert (ie no out of hours "pagers") so just something that goes into a slack channel. But they're a good indicator of when developers have poorly optimized SQL, or the DB schema is poorly defined (eg missing indexes), or the DB server itself is poorly sized.
This wouldn't be something you'd expect to need in production and definitely not something you'd rely on as a notice of a production outage. But it is an example of one of those 1% occasions where a CPU alert does add value to the overall observability of the application.
But this also ties into your excellent point about how you'd use CPU and other data points to build a picture of what's happening in your application.
It's short compared to the previous bubbles. The capital in the previous bubbles went into things that survived the bubble, networking infrastructure and rail networks.
If you plan to take out a 10-15 year loan to buy those GPU's then it's extremely short. So short the bank won't give you the loan due to lack of collateral.
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