11–20 of 58 posts
> Our annualized revenue run rate is up more than 200% year over year, and net dollar retention's stayed above 200% since February. In August alone, the platform processed 1.9 trillion billable actions, up more than 350% year over year, while open source installs passed 43 million, up 134% since December 2025. We're now working with more than 4,300 paying customers, up 139% year over year, including OpenAI, Snap, NVI…
Can someone tell me why people prefer temporal over something like https://restate.dev ?
Can someone shed some lights on what temporal does? Their blog says [1] Durable Execution offers three key benefits: It improves application reliability by providing fault tolerance. It simplifies code by allowing it to focus on the goal instead of potential problems. It accelerates development by eliminating the need to write complex error-handling logic. So... like exception handling? or something like erlang's let…
Can someone shed some lights on what temporal does? Their blog says [1] Durable Execution offers three key benefits: It improves application reliability by providing fault tolerance. It simplifies code by allowing it to focus on the goal instead of potential problems. It accelerates development by eliminating the need to write complex error-handling logic. So... like exception handling? or something like erlang's let…
temporal centralizes all the error handling, retry handling, ... some web pages to manage failed, pending tasks.
it's been good for us, but a real step function in complexity of the app.
Can someone shed some lights on what temporal does? Their blog says [1] Durable Execution offers three key benefits: It improves application reliability by providing fault tolerance. It simplifies code by allowing it to focus on the goal instead of potential problems. It accelerates development by eliminating the need to write complex error-handling logic. So... like exception handling? or something like erlang's let…
In Temporal, you use their SDK to mark which code is either:
- Deterministic without external dependencies on network, disk, clock, etc.
- Non-deterministic (e.g. accesses a filesystem, dependent on clock time, talks over the network)
You can write the code without handling flakiness or retries and the Temporal control plane handles all the progress tracking and retries for you. Progress is tracked at the individual line of code for deterministic code, or for non-deterministic code, tracked at function boundaries defined by the programmer. You buy into more complexity upfront, but it makes the application code way simpler and easier to manage overall.
They do a lot of other cool stuff on top of all this, and their Temporal Worker Controller architecture is particularly well suited to running massive scale processing/AI workloads on Kubernetes (handles a lot of stuff like autoscaling without interrupting work, rainbow version rollout, etc.)
Can someone shed some lights on what temporal does? Their blog says [1] Durable Execution offers three key benefits: It improves application reliability by providing fault tolerance. It simplifies code by allowing it to focus on the goal instead of potential problems. It accelerates development by eliminating the need to write complex error-handling logic. So... like exception handling? or something like erlang's let…
It’s an async job runner that scales well. Yeah they advertise a lot of fancy features, but really what they are selling is solid failure-resistant infra. Companies could set the same thing up with an in-house team, but it’s pretty great to be able to click a button and start running workloads at tens or hundreds of thousands of RPS without needing to figure out the internals.
Can someone shed some lights on what temporal does? Their blog says [1] Durable Execution offers three key benefits: It improves application reliability by providing fault tolerance. It simplifies code by allowing it to focus on the goal instead of potential problems. It accelerates development by eliminating the need to write complex error-handling logic. So... like exception handling? or something like erlang's let…
Basically, a multi-step event handling system, where the data could be spread across multiple databases/systems, so there's no way to rollback a transaction atomically across all the databases. Instead, you explicitly codify "compensations" to undo your previous commits so that you eventually end up in a consistent state.
Temporal is the orchestrator/framework/library to implement the above in an easier way.
Can someone shed some lights on what temporal does? Their blog says [1] Durable Execution offers three key benefits: It improves application reliability by providing fault tolerance. It simplifies code by allowing it to focus on the goal instead of potential problems. It accelerates development by eliminating the need to write complex error-handling logic. So... like exception handling? or something like erlang's let…
Functionally, it's a "workflow" runner (ex - you can mostly treat it like a queue, where you've got workers that are picking up work to do).
But it wraps a couple of pretty handy features on top like:
- It preserves most arguments to actions, and it makes system details deterministic for retries (ex you can re-run a workflow at a later time, and temporal will make sure the code sees details like date and time as though it were the original run, and will yell at you if you try to write code that won't be deterministic on retries)
- It supports very long waits easily. (ex - very easy to have a workflow do a couple things, wait a week, then do some more things).
- It has decent profiling and UI tools
- It can "restart" a failed workflow deterministically from the step at which it failed (using details from the original point)
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Basically - it's a background worker service that's put a lot of time and thought into ways to handle failures better.
It absolutely still has some considerable pain points though, and I find it difficult to use for larger tasks (ex - their message gRPC size limit of 4mb is a b*&^% to work around, since it often breaks a lot of the utility they provide, and the history cap at 50mb is also really painful in certain situations.)
Really - I think it was just the right tool at the right time to make calling LLMs with long waits relatively easy and somewhat foolproof.
Can someone shed some lights on what temporal does? Their blog says [1] Durable Execution offers three key benefits: It improves application reliability by providing fault tolerance. It simplifies code by allowing it to focus on the goal instead of potential problems. It accelerates development by eliminating the need to write complex error-handling logic. So... like exception handling? or something like erlang's let…
You need to reserve some inventory, charge a card, eventually email a customer and steps can go wrong. So you have queues, and retries and ways to back things out, undo changes.
To my understanding, Temporal's idea is to factor that part out, the queues and retries, and offsetting actions, so you write the logic and not the workflow orchestration.
Can someone shed some lights on what temporal does? Their blog says [1] Durable Execution offers three key benefits: It improves application reliability by providing fault tolerance. It simplifies code by allowing it to focus on the goal instead of potential problems. It accelerates development by eliminating the need to write complex error-handling logic. So... like exception handling? or something like erlang's let…
This is a rough explanation, but generally it does a couple of things that are helpful. Functionally, it's a "workflow" runner (ex - you can mostly treat it like a queue, where you've got workers that are picking up work to do). But it wraps a couple of pretty handy features on top like: - It preserves most arguments to actions, and it makes system details deterministic for retries (ex you can re-run a workflow at a…