Diagrams are key for top architects and engineers.
The ability to create meaningful diagrams is the pinnacle of communication skills as an engineer
There are GUI architecture tools, but they tend to be more difficult to reproduce, you're often starting from scratch for each client.
The cutting edge is Diagrams-as-Code.
- Real World Architecture Diagrams
- Templates
- Diagrams-as-Code Languages
- GUI / Online Diagrams tools
- Important Icon Sets
- Interactive Playground Editors
- GraphViz
- Hex Colour Codes
- Diagram Design
- Diagram of Diagrams-as-Code Tools
- UML Class Diagrams
See also the Documentation and Markdown pages for tips on things like embedding
diagrams in README.md
, as well Badges.
HariSekhon/Diagrams-as-Code - ready made architecture diagrams
Mainly D2lang, Python diagrams, MermaidJS, GNUplot and a little Draw.io / LucidChart.
GitHub Actions CI/CD pipelines auto-regenerate the diagrams upon any code changes and they appear
directly in the rendered README.md as the resultant .png
images are sourced in the markdown code.
Templates for D2 language and Python diagrams are found here, especially diagram.d2 and diagram.py.
Text-to-Diagram Comparison Playground
Diagrams-as-Code are both cool, easier to reuse prior work and often easier to maintain.
A quick edit and they reshuffle themselves.
The lack of placement layout control (D2 issue #1285, Python Diagrams issues #44 and #819) is the main problem on more complex diagrams, for which you may want to switch to one of the top GUI tools from the next section.
- MermaidJS - excellent multi-format flexible diagram language with code rendering directly
inside GitHub markdown (
README.md
) files thanks to GitHub integration- see MermaidJS doc page for details
- D2 lang - excellent, easy to use DSL for Cloud & Architecture diagrams, my favourite
- Python Diagrams - my prior favourite
- good for basic Cloud & Architecture diagrams with icons
- See thse Python Diagrams Code files
- GraphViz - the classic
- its
dot
format is output by Terraform'sterraform graph
command - this is the technology under the hood of Python diagrams above which makes it easier to use for Pythonistas
- its
- GNUplot - classic code diagram CLI tool that can plot from data files in different formats
and output in many different formats
- See these GNUplot Code files
- Go Diagrams - Golang a port of Python Diagrams
- Cloudgram - another DSL language
- Structurizer - C4 architecture diagrams
- PlantUML - creates UML diagrams eg. class diagrams, sequence diagrams, use case diagrams
- MarkMap - visualize your Markdown as mindmaps, nice, can open your GitHub repo's Markdown directly, although it looks like my DevOps-Bash-tools repo is far too huge a map
Best Comparison Site (run by D2)
For more control and complex architecture diagrams.
- Draw.io - mature and can export to XML
- integrates with Confluence to embed diagrams straight into Confluence wiki pages
- LucidChart - used this for a GCP architecture diagram for a startup interview (I got the job)
- pre-made VPC, region, zones - quicker to start
- CloudCraft - cloud focused diagrams
- still only AWS and Azure diagrams as of March 2024
- Creately - AWS, Azure and GCP diagrams
- Excalidraw - simple whiteboard style drawings - also useful for ad-hock drawings to explain things to colleagues
- Miro - collaborative workflow and diagram tool
- Prezi - focused on presentations
- Sketch
- Cacoo
- Gliffy
- Visual Paradigm - enterprise, does archimate diagrams, complicated, I used this at an investment bank, not my favourite, fine for enterprise architects rather than engineers
- Cloudairy - new, buggy UI when I tried it
- Swimm - AI to generate diagrams from code and documentation sources
Especially to import into D2, but also to supplement other languages and libraries as necessary.
Python Diagrams has the best in-built library, some highlights are below, but check their adjacent categories too:
- Python Diagrams On-Premise
- Python Diagrams AWS
- Python Diagrams GCP
- Python Diagrams Azure
- Python Diagrams Generic - OS, Virtualization, Network Hardware
- Python Diagrams Kubernetes
- Iconify.design - Massive 200,000 open source SVG icon set
- Text-to-Diagram Comparison Playground
- D2 lang
- MermaidJS
- CloudGram
- GraphViz:
- MarkMap Online REPL
- Draw.io:
- Draw.io pre-loaded with AWS, GCP and Azure icons
- Draw.io pre-loaded with AWS icons
- Draw.io pre-loaded with Azure icons
- Draw.io pre-loaded with GCP icons
- Supported URL parameters - to instantly load the above icon sets, set dark etc.
- LucidChart
- CloudCraft
- Creately
- Visual Paradigm
- Structurizer
generate .png
using the dot
command:
dot -T png template.gv -o file.png >/dev/null
open the generated .png
file:
if uname -s | grep -q Darwin; then
open file.png # Mac
else
sxiv file.png # Linux
fi
or better use the imageopen.sh
script from the DevOps-Bash-tools repo
which tries more different tools on Linux to open the image:
HariSekhon/DevOps-Bash-tools - imageopen.sh
See Visualization doc's Colours section.
Diagrams-as-Code languages currently have no placement control placement layout control (D2 issue #1285, Python Diagrams issues #44 and #819).
This limits the complexity of diagrams that can be generated from code because they can very quickly get out of control and ugly as a result, costing you lots of time trying to get them to generate sane looking diagrams.
For complex diagrams you really need to switch to GUI tools for better control.
However, that being said, one diagram can only become so complicated before it becomes difficult for humans to easily interpret due to too much detail.
For this reason, I recommend favouring an approach of multiple levels of simpler diagrams:
- an architecture overview diagram
- sub-diagrams that drill down into the implementation details of the different components eg. how it runs on Kubernetes or with high availability
The diagrams can be more easily read one after another.
You see examples of diagrams at different levels of drill-down from architecture to Kubernetes components in the HariSekhon/Diagrams-as-Code repo.
Some components like Grafana and Vault are very relevant in architecture diagrams and should be present but can be represented by a since simple icon, with their implementation showing how they're running on Kubernetes or achieving high availability being left to separate diagrams for each one.
Ported from various private Knowledge Base pages 2020+