hadolint
incubation-engineering
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hadolint | incubation-engineering | |
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24 | 18 | |
9,707 | - | |
1.8% | - | |
2.3 | - | |
about 23 hours ago | - | |
Haskell | ||
GNU General Public License v3.0 only | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
hadolint
- Dockerfile Linter
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Writing a Minecraft server from scratch in Bash (2022)
To skip the "move your scripts to standalone files" step some devs don't like, consider something like https://github.com/hadolint/hadolint which runs Shellcheck over inline scripts within Containerfiles.
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I reduced the size of my Docker image by 40% – Dockerizing shell scripts
This is neat :)
I love going and making containers smaller and faster to build.
I don't know if it's useful for alpine, but adding a --mount=type=cache argument to the RUN command that `apk add`s might shave a few seconds off rebuilds. Probably not worth it, in your case, unless you're invalidating the cached layer often (adding or removing deps, intentionally building without layer caching to ensure you have the latest packages).
Hadolint is another tool worth checking out if you like spending time messing with Dockerfiles: https://github.com/hadolint/hadolint
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Top 10 common Dockerfile linting issues
With Depot, we make use of two Dockerfile linters, hadolint and a set of Dockerfile linter rules that Semgrep has written to make a bit of a smarter Dockerfile linter.
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hadolint - Dockerfile linter
# Download hadolint wget https://github.com/hadolint/hadolint/releases/download/v2.12.0/hadolint-Linux-x86_64 # Download SHA256 checksum wget https://github.com/hadolint/hadolint/releases/download/v2.12.0/hadolint-Linux-x86_64.sha256 # Validate the checksum sha256sum -c hadolint-Linux-x86_64.sha256 # Make the file executable chmod + ./hadolint-Linux-x86_64 # Rename the file mv hadolint-Linux-x86_64 hadolint
- Haskell Dockerfile Linter
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Is adding a USER best practice?
The most common linter I've seen and used it Hadolint, which does: https://github.com/hadolint/hadolint/wiki/DL3002 I didn't bother checking to see if alternatives also support this as well though.
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Checkmake: Experimental Linter/Analyzer for Makefiles
Some discussion on that here:
https://github.com/koalaman/shellcheck/issues/58
The hadolint project does shell checking for Dockerfiles and it uses shellcheck:
https://github.com/hadolint/hadolint
So the approach is definitely feasible, but you do need a new project and probably it needs to be written in Haskell.
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Dokter: the doctor for your Dockerfiles
how does this compare to something like hadolint?
Also, have you run across Hadolint for linting? https://github.com/hadolint/hadolint
incubation-engineering
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Why Postgres RDS didn't work for us
However if you really want to optimize data currently residing in Postgres for analytical workloads, as the original comment suggests - consider moving to a dedicated OLAP DB like ClickHouse.
See results from Gitlab benchmarking ClickHouse vs TimescaleDB: https://gitlab.com/gitlab-org/incubation-engineering/apm/apm...
Key findings:
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Automating Your Homelab with Proxmox, Cloud-init, Terraform, and Ansible
ansible: stage: configure image: alpine rules: - if: $ANSIBLE_SETUP_VM != "" && $ANSIBLE_SETUP_HOST != "" variables: ANSIBLE_HOST_KEY_CHECKING: "False" script: - apk add curl bash openssh python3 py3-pip - pip3 install ansible paramiko - ansible-galaxy collection install -r ansible/requirements.yml - curl --silent "https://gitlab.com/gitlab-org/incubation-engineering/mobile-devops/download-secure-files/-/raw/main/installer" | bash - mkdir /root/.ssh && cp .secure_files/ansible.priv /root/.ssh/id_rsa && chmod 600 /root/.ssh/id_rsa - ansible-playbook ansible/main.yml -i ansible/inventory --extra-vars vyos_host=$ANSIBLE_SETUP_VM --limit $ANSIBLE_SETUP_HOST,$ANSIBLE_SETUP_VM ```
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Float Compression 3: Filters
Interesting to match with the observations from the practice of using ClickHouse[1][2] for time series:
1. Reordering to SOA helps a lot - this is the whole point of column-oriented databases.
2. Specialized codecs like Gorilla[3], DoubleDelta[4], and FPC[5] lose to simply using ZSTD[6] compression in most cases, both in compression ratio and in performance.
3. Specialized time-series DBMS like InfluxDB or TimescaleDB lose to general-purpose relational OLAP DBMS like ClickHouse [7][8][9].
[1] https://clickhouse.com/blog/optimize-clickhouse-codecs-compr...
[2] https://github.com/ClickHouse/ClickHouse
[3] https://clickhouse.com/docs/en/sql-reference/statements/crea...
[4] https://clickhouse.com/docs/en/sql-reference/statements/crea...
[5] https://clickhouse.com/docs/en/sql-reference/statements/crea...
[6] https://github.com/facebook/zstd/
[7] https://arxiv.org/pdf/2204.09795.pdf "SciTS: A Benchmark for Time-Series Databases in Scientific Experiments and Industrial Internet of Things" (2022)
[8] https://gitlab.com/gitlab-org/incubation-engineering/apm/apm... https://gitlab.com/gitlab-org/incubation-engineering/apm/apm...
[9] https://www.sciencedirect.com/science/article/pii/S187705091...
- ClickHouse Cloud is now in Public Beta
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Dokter 1.4.0 released
Documentation of rules is now available: https://gitlab.com/gitlab-org/incubation-engineering/ai-assist/dokter/-/blob/main/docs/overview.md
- Dokter: the doctor for your Dockerfiles
What are some alternatives?
trivy - Find vulnerabilities, misconfigurations, secrets, SBOM in containers, Kubernetes, code repositories, clouds and more
orchest - Build data pipelines, the easy way 🛠️
dockle - Container Image Linter for Security, Helping build the Best-Practice Docker Image, Easy to start
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
docker-bench-security - The Docker Bench for Security is a script that checks for dozens of common best-practices around deploying Docker containers in production.
v4
stan - 🕵️ Haskell STatic ANalyser
ClickBench - ClickBench: a Benchmark For Analytical Databases
hlint - Haskell source code suggestions
databooks - A CLI tool to reduce the friction between data scientists by reducing git conflicts removing notebook metadata and gracefully resolving git conflicts.
grype - A vulnerability scanner for container images and filesystems
clickhouse-operator - Altinity Kubernetes Operator for ClickHouse creates, configures and manages ClickHouse clusters running on Kubernetes