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Barry O'Reilly

Barry O'Reilly

These are the best posts from Barry O'Reilly.

2 viral posts with 222 likes, 8 comments, and 4 shares.
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Best Posts by Barry O'Reilly on LinkedIn

Since we’ve already decided that GenAI is going to solve all the worlds problems, this means that all the worlds problems can be solved through statistical analysis of past data, then the cure for all diseases must exist somewhere in the data.

Since we haven’t found this magical cure yet it must be in the data we haven’t analysed.

This is why OpenAI are launching erotic chat. Since that’s the only data they haven’t gathered, the cure for all diseases must be in that data. Sam is playing 3D chess.
There’s a lot of wild guessing and chatter about the AWS outage, often to suit a narrative.

Where I differ from the resilience narratives is that I don’t believe the software system itself is complex. I think the problem that AWS suffered from was a complicated problem - hence the quick resolution and root cause analysis. The complexity lies in the human systems that place value on different things.

It is possible to build intricate software with incredibly low rates of failure - in medical, nuclear, aviation branches, this is routine. But it has an attached cost. Even then, the complexity of human systems means that the human system can shift to a new state where the previously reliable software suddenly becomes dangerous. Vigilance is always necessary and outages are always a few steps away.

AWS isn’t offering extremely low failure rates, it’s offering very low failure rates. It would make the product too expensive otherwise. The whole point of cloud is to be cheap at scale. AWS has millions of customers all with different needs around reliability. This requires a very high level of flexibility in the architecture. Making it more reliable means constraining the system - but cloud customers are buying the flexibility that this constraint would kill. The balance between flexibility and reliability is called criticality. Cloud providers are aiming for criticality across millions of customers - which is very different than perfection. As these cloud platforms move toward ever greater reliability they will do so at the cost of calcification - see mainframe systems for an example of how that looks. So the onus falls on us to build systems that can cope with failures to preserve the criticality and low cost of the underlying cloud infrastructure and benefit from the economies of scale.

So the complicated problems that start to build up in these kind of systems are priced in. There isn’t time or money to identify and work through every single issue - so we live with a little risk and invest in incident response to put the fires out. The right investment level will suffer a few outages but not too many, and have measures in place to try and only suffer a particular outage once.

Of course when customers are upset you can’t tell them this.

So all the people mocking AWS - their system is doing exactly what it’s meant to be doing. This will happen again, to all cloud providers, and if you think you’re better than them try and replicate what they’ve done - you’ll find it extremely difficult.

Reliability and resilience are the job of the software architect in each individual project. It’s possible to build this on top of platforms that aren’t completely resilient out of the box. This is also why you can’t import FAANG narratives about resilience into your project, it’s two different worlds. It’s really not fair to point fingers and mock AWS, it’s a misplaced expectation.

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