Sidekiq VS Capistrano

I'd say Sidekiq is the top competitor here.

There's something wrong at Redislabs, it took them over a year to get RESP3 rolled out into their hosted service, you'd expect a rollout of that to be a bit quicker when they're the owner of Redis.

It affected us when upgrading Sidekiq to version 7, which dropped support for older Redis, and their Envoy proxy setup didn't support HELLO and RESP3: https://github.com/sidekiq/sidekiq/issues/5594

That depends on how the `maxmemory-policy` is configured, and queue systems based on Redis will tell you not to allow eviction. https://github.com/sidekiq/sidekiq/wiki/Using-Redis#memory (it even logs a warnings if it detects your Redis is misconfigured IIRC).

Sidekiq https://sidekiq.org/: This one started as an open source project, once it got enough traction, the developer made a premium version of it, and makes money by selling licenses to businesses.

Sidekiq will drop in-progress jobs when a worker crashes. Sidekiq Pro can recover those jobs but with a large delay. Sidekiq is excellent overall but it’s not suitable for processing critical jobs with a low latency guarantee.

https://github.com/sidekiq/sidekiq/wiki/Reliability

> I'm not sure feature withholding has traditionally worked out well in the developer space.

I think it's worked out well for Sidekiq (https://sidekiq.org). I really like their model of layering valuable features between the OSS / Pro / Enterprise licenses.

I was studying Sidekiq's page on rate limiters. The first type of rate limiting mentioned is the concurrent limiter: only n tasks are allowed to run at any point in time. Note that this is independent of time units (e.g. per second), or how long they take to run. The only limitation is the number of concurrent tasks/requests.

The code above isn't idempotent. If you run it twice, it will create two copies, which is probably not what you intended. Why is this important? Because most backend job processors like Sidekiq don't make any guarantees that your jobs will run exactly once.

If you don't want to go down the NFS share route then Capistrano is a useful tool if you're willing to write a little bit of ruby. It comes with some built in goodies like rollbacks. It's an oldie (pre-dockerize everything), but still useful.

https://github.com/capistrano/capistrano

You can start by deploying from your machine to simultaneously get it deploying across all your servers, then I'd consider having a CI/CD pipeline take over and run Capistrano for you.

- Integrate automation deployment: [capistrano](https://github.com/capistrano/capistrano)

Integrate automation deployment: capistrano

The deployment process generally includes making the new version available, directing traffic from the old to the new version, and stopping the old versions. Capistrano has been doing this since 2006. However, what makes Kubernetes deployments better is the minimum number of pods required, and its rollout strategy minimizes or eliminates downtime. For example, a rolling update strategy can ensure new pods gradually replace old pods with configs like maxSurge and maxUnavailable. Because this is done in a declarative way, as a user or operator, you only need to ask Kubernetes to apply a given deployment and Kubernetes does the rest. Next up is the Kubernetes config map.

[1] https://github.com/capistrano/capistrano

Capistrano

What I had considered was writing a deployment script where upon successful build in a separate folder, it'd swap out the deployed folder, similar to how Capistrano works. It has a "current" folder and it'll build in a temporary folder and then replace the symlink to a newer build.

capistrano with plugins for deployment

deployer is a deployment tool written in PHP. It comes with "Zero Downtime Deployments" out of the box and can be extended by writing simple PHP code. (capistrano would be the equivalent in the Ruby world).

Capistrano, if you like Ruby.