What comes first?! The function or the promise?!

Does the function return the promise or does the promise trigger the function

Curious about the core principles of Deterministic Simulation Testing?! Check out my blog post

blog.resonatehq.io/deterministic-…

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Excited about Polar Signals's innovative approach to Deterministic Simulation Testing! 🚀

I am thrilled to see the DST community expanding and pushing boundaries. 🎉

x.com/PolarSignalsIO…

When failures occur, non-distributed systems exhibit distributed system characteristics:

Forward recovery (retries) implies at-least-once delivery and processing, a hallmark issue of distributed systems.

We need idempotency to guarantee correctness

x.com/DominikTornow/…

What comes first?! The function or the promise?!

Does the function return the promise or does the promise trigger the function

Curious about the core principles of Deterministic Simulation Testing?! Check out my blog post

blog.resonatehq.io/deterministic-…

x.com/DominikTornow/…

Excited about Polar Signals's innovative approach to Deterministic Simulation Testing! 🚀

I am thrilled to see the DST community expanding and pushing boundaries. 🎉

x.com/PolarSignalsIO…

When failures occur, non-distributed systems exhibit distributed system characteristics:

Forward recovery (retries) implies at-least-once delivery and processing, a hallmark issue of distributed systems.

We need idempotency to guarantee correctness

x.com/DominikTornow/…

A core feature of Distributed Async Await is Execution Runtime Separation, which is the ability to separate the execution of a function from its runtime environment.

The Challenge

In traditional async await, when you call a function, the resulting function execution is tied to

Be mindful of the primitives you choose.

At Resonate HQ, Distributed Async Await builds on Durable Functions & Durable Promises.

Our Distributed Event Loop issues two commands, Invoke & Resume.

The entire programming model is built on recursive, dead simple primitives.

A core feature of Distributed Async Await is Execution Runtime Separation, which is the ability to separate the execution of a function from its runtime environment.

The Challenge

In traditional async await, when you call a function, the resulting function execution is tied to

Linearizability ensures that a distributed, replicated object behaves as a single, non-distributed object.

What concept provides the same for distributed computations?

x.com/DominikTornow/…

Distributed Async Await starts by assigning identities to the entities of the system: Functions & Promises.

A function execution is a computational entity, while a promise instance is a data entity.

We are familiar with assigning IDs to data entities, the idea of doing so for

Distributed Async Await assigns IDs to both functions and promises. Why?!

When we consider process crashes, we inherently touch upon aspects of distributed systems−even if there's only one process at a time.

Let's reason about a system in terms of a logical level and a

Linearizability ensures that a distributed, replicated object behaves as a single, non-distributed object.

What concept provides the same for distributed computations?

x.com/DominikTornow/…

Distributed Async Await starts by assigning identities to the entities of the system: Functions & Promises.

A function execution is a computational entity, while a promise instance is a data entity.

We are familiar with assigning IDs to data entities, the idea of doing so for

Distributed Async Await assigns IDs to both functions and promises. Why?!

When we consider process crashes, we inherently touch upon aspects of distributed systems−even if there's only one process at a time.

Let's reason about a system in terms of a logical level and a

Another example for the need of Mechanical Sympathy are Object-Relational Mappers and the n+1 query problem.

The n+1 query problem refers to an application making database queries in a loop, instead of making a single query that returns all results.

The n+1 query problem is

The concept of Sloppy Quorums highlights a crucial, somewhat unpleasant reality

In the absence of failure, a sloppy quorum guarantees linearizability. In the presence of failure, it guarantees eventual consistency.

Failure conditions are not the norm but always possible.

Sloppy Quorums in Distributed Systems

The concept of a Sloppy Quorum was introduced in the paper 2007 Dynamo: Amazon's Highly Available Key-value Store.

A quorum is the minimum number of nodes required to agree on a value to ensure linearizability.

A sloppy quorum allows for a