We reduced 502 errors by caring about PID 1 in Kubernetes

This page summarizes the projects mentioned and recommended in the original post on news.ycombinator.com

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  • build


    Well, yeah, you're not starting it from the shell with exec. If you first tell the shell to redirect the fd for stderr to stdin, and then exec gitlab-workhorse \*, the shell would pass all execution to workhorse and then workhorse would receive the signals. No need to worry about Dockerfile CMD* syntax.

  • Nomad

    Nomad is an easy-to-use, flexible, and performant workload orchestrator that can deploy a mix of microservice, batch, containerized, and non-containerized applications. Nomad is easy to operate and scale and has native Consul and Vault integrations.

    I believe Nomad is hailed as the replacement: https://github.com/hashicorp/nomad#readme

    I would caution one against "javascript framework syndrome:" bah, this framework is too complicated, I just want something simpler ... ok, it doesn't work right in all circumstances, I'll just add this one feature(, ... ok, maybe just this one other feature)+ ... bah, this framework is too complicated!

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  • simplenetes

    The sns tool is used to manage the full life cycle of your Simplenetes clusters. It integrates with the Simplenetes Podcompiler project podc to compile pods.

  • grpc-go

    The Go language implementation of gRPC. HTTP/2 based RPC

  • kubernetes

    Production-Grade Container Scheduling and Management

    Generally when you make claims like this, giving proof (eg PR for contributing consul support that was quashed) makes the claim stronger. I looked it up and this seems to be the PR https://github.com/kubernetes/kubernetes/pull/31622.

    Reading through the discussion, it doesn’t look like it was quashed; the project owners had a reasoned debate about the pros/cons of what would happen if such a support was included at the time and its a totally reasonable argument to me.

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    Collect and Analyze Billions of Data Points in Real Time. Manage all types of time series data in a single, purpose-built database. Run at any scale in any environment in the cloud, on-premises, or at the edge.

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