0/ I’m tired of hearing about observability replacing monitoring. It’s not going to, and that’s because it shouldn’t.

Observability will not _replace_ monitoring, it will _augment_ monitoring.

Here’s a thread about observability, and how monitoring can evolve to fit in: 👇

1/ Let’s start with the diagram (above) illustrating the anatomy of observability. There are three layers:

I. (Open)Telemetry: acquire high-quality data with minimal effort
II. Storage: “Stats over time” and “Transactions over time”
III. Benefits: *solve actual problems*
2/ The direction for “Telemetry” is simple: @opentelemetry.

(This is the (only) place where the so-called "three pillars” come in, by the way. If you think you’ve solved the observability problem by collecting traces, metrics, and logs, you’re about to be disappointed. :-/ )
3/ The answer for “Storage” depends on your workload, but we’ve learned that it’s glib to expect a data platform to support observability with *just* a TSDB or *just* a transaction/trace/logging DB. And also that “cost profiling and control” is a core platform feature.
4/ But what about “Benefits”? There’s all of that business about Control Theory (too academic) and “unknown unknowns” (too abstract). And “three pillars” which is complete BS, per the above (it’s just “the three pillars of telemetry,” at best).
5/ Really, Observability *Benefits* divide neatly into two categories: understanding *health* (i.e., monitoring) and understanding *change* (i.e., finding and exposing signals and statistical insights hidden within the firehose of telemetry).
6/ Somewhere along the way, “monitoring” was thrown under a bus, which is unfortunate. If we define monitoring as *an effort to connect the health of a system component to the health of the business* – it’s actually quite vital. And ripe for innovation! E.g., SLOs.
7/ “Monitoring” got a bad name because operators were *trying to monitor every possible failure mode of a distributed system.* That doesn’t work because there are too many of them.

(And that’s why you have too many dashboards at your company.)
8/ Monitoring doesn’t have to be that way. It can actually be quite clarifying, and there’s still ample room for innovation. I’d argue that SLOs, done properly, are what monitoring can and should be (or become).
9/ So what if we do things differently? What if we do things *right*? We treat Monitoring as a first-class citizen, albeit only one aspect of observability, and we closely track the signals that best express and predict the health of each component in our systems.
10/ … And then we need a new kind of observability value that’s purpose-built to manage *changes* in those signals. More on that part in a future post. :) But the idea is to facilitate intentional change (e.g., CI/CD) while mitigating unintentional change (Incident Response).
11/ Zooming out: Monitoring will never be *replaced* by Observability: it’s not just "part of Observability’s anatomy," it’s a vital organ! Our challenge is to *evolve* Monitoring, and to use it as a scaffold for the patterns and insights in our telemetry that explain change.

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THREAD: How is it possible to train a well-performing, advanced Computer Vision model 𝗼𝗻 𝘁𝗵𝗲 𝗖𝗣𝗨? 🤔

At the heart of this lies the most important technique in modern deep learning - transfer learning.

Let's analyze how it


2/ For starters, let's look at what a neural network (NN for short) does.

An NN is like a stack of pancakes, with computation flowing up when we make predictions.

How does it all work?


3/ We show an image to our model.

An image is a collection of pixels. Each pixel is just a bunch of numbers describing its color.

Here is what it might look like for a black and white image


4/ The picture goes into the layer at the bottom.

Each layer performs computation on the image, transforming it and passing it upwards.


5/ By the time the image reaches the uppermost layer, it has been transformed to the point that it now consists of two numbers only.

The outputs of a layer are called activations, and the outputs of the last layer have a special meaning... they are the predictions!

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