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bazelbuild
rules_docker
Starlark2017–2023
bazelbuild / rules_docker

rules_docker

Rules for building and handling Docker images with Bazel

13Distinct people
18Mentions
0Explicit recommenders
1.1KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Rules for building and handling Docker images with Bazel

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 12:45:45 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year18 dated mentions

Observed mentions: 2017-09-02 14:03:33 UTC to 2023-11-08 13:44:20 UTC.

02462017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20172018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 4 mentions; 0 submissions, 4 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 7 mentions; 0 submissions, 7 comments20202021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2023

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC101
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC101
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC404
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC707
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC202
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC101
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC202

What Hacker News says

2 sources
Have you considered using Bazel to build an artifact that describes your deployment configuration? This is something that I've been thinking about trying to implement for some time. Essentially I want to have a way to support defining service configurations like this: service_binary( name = "foobar", srcs = ["foobar.jsonnet"], deps = ["//jsonnet/service.jsonnet"], images = ["//a:image"], ) Then make it possible to create a class of `*_test` rules that would start up a bunch of docker containers in the same network topology they would exist in prod, run your test in the same netns, then clean everything up. It could look something like this: cc_integration_test( name = "...", services = ["//a", "//b"], srcs = ["main.cc"] ) There's some BazelCon talks about people doing similar stu
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ff but not actually open sourcing their code. P.S. if you use rules_docker please feel free to open a PR to add your company to our README: https://github.com/bazelbuild/rules_docker/#adopters > service_binary
In Evolution of code deployment tools at Mixpanel
During the last 3 years I've had the pleasure of using Bazel's rules_docker to generate all my container images (https://github.com/bazelbuild/rules_docker). In a nutshell, rules_docker is a set of build rules for the Bazel build system (https://bazel.build). What's pretty nice about these rules is that they don't rely on a Docker daemon. They are rules that directly construct image tarballs that you can either load into your local Docker daemon or push to a registry. What's nice about this approach is that image generation works on any operating system. For example, even on a Mac or Windows system that doesn't have Docker installed, you're able to build Linux containers. They are also fully reproducible, meaning that you often don't need to upload layers when pushing (either because they haven't changed, or because some colleague/CI job
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already pushed those layers). I guess rules_docker works fine for a variety of programming languages. I've mainly used it with Go, though.
In Buildpacks vs. Dockerfiles

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