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Cloud & DevOps Architecture Diagrams-as-Code in Python, D2 and MermaidJS languages
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HariSekhon/Diagrams-as-Code
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Diagrams-as-Code using the awesomeD2 language,MermaidJS,Python diagrams andGraphviz.
Diagrams shown below are automatically (re)generated by GitHub Actions CI/CD 😎
I read an article that said:
the ability to create meaningful diagrams is the pinnacle of communication skills as an engineer
- Documentation
- Diagrams
- This Repo's Creation & GitHub Actions CI/CD to auto-(re)generate diagrams from code changes
- GitHub Flow with Jira ticket integration
- Git - why you shouldn't use long-lived feature branches
- AWS Web Traffic Classic
- Azure Active Directory Single Sign-On
- Jenkins CI/CD on Kubernetes
- ArgoCD - GitOps for Kubernetes
- GCP Cloudflare Web Architecture GKE
- GCP Malware Scanner with ClamAV
- Kubernetes Deployment with Horizontal Pod Autoscaler and Ingress
- Kubernetes Stateful Architecture with persistent volumes
- Kubernetes Service External Traffic Policy
- Kubernetes on Premise
- Traefik Kubernetes Ingress on GKE
- Kong API Gateway on Kubernetes (AWS EKS)
- OpenTSDB on Kubernetes and HBase
- MySQL Replica Architecture
- Kafka Pub/Sub
- Elasticsearch Queries
- Kafka Flink Elasticsearch
- Cassandra Queries
- Prometheus & Thanos
- RabbitMQ Pub/Sub
- AWS S3 Config Notify Lambda DynamoDB
- Apigee Akamai EKS
- Git - Environment Branches
- CI/CD - Separate Branch Workflows
- CI/CD - Unified Release Workflow - Trunk Based
- Mobile CI/CD iOS - Separate Branch Workflows
- Devs Test in Production
- Code, Commit, Push, Boom
- The Danger of Testing Ideas in Production
- LucidChart - GCP Architecture
- Web Basics
- Network - Layer 2 - Local - ARP
- Network - Layer 3 - Remote - IP
- Gantt Chart of my Experience
- Gantt Chart of my GitHub Repos
- Git Commits per Month for this Repo
- Git Commit Times across my Repos
- Samples Revamped
- Build from Source
- Diagram Templates
- Star History
- More Core Repos
GistfromKnowledge-Baserepo full of links to Diagrams technologies andIcon Sets.
They say a picture is worth a thousand words...
OpenREADME.md to enlarge:
Prefix Git branches with Jira ticket numbers in Jira'sAA-NNN
format for GitHub Pull Requests to automatically appear in Jira tickets (see thisdoc):
%% https://mermaid.js.org/syntax/gitgraph.html#gitgraph-specific-configuration-options%% https://htmlcolorcodes.com/%%{ init: { "logLevel": "debug", "theme": "dark", "themeVariables": { "git0": "#839192", "git1": "#2874A6", "gitInv0": "#FFFFFF", "gitBranchLabel0": "#FFFFFF", "commitLabelColor": "#FFFFFF" } }}%%gitGraph commit commit id: "branch" branch AA-NNN-my-feature-branch checkout AA-NNN-my-feature-branch commit id: "add code" commit id: "refine code" checkout main merge AA-NNN-my-feature-branch id: "merge PR" type: HIGHLIGHT tag: "2023.15 release" commit commit
*Environment Branches may be one of the few exceptions but requires workflow discipline.
See Also: 100+ scripts for Git and the major Git repo providers like GitHub, GitLab, Bitbucket, Azure DevOps in myDevOps-Bash-tools repo.
%% https://mermaid.js.org/syntax/gitgraph.html#gitgraph-specific-configuration-options%% https://htmlcolorcodes.com/%%{ init: { "logLevel": "debug", "theme": "dark", "gitGraph": { "mainBranchName": "master" }, "themeVariables": { "git0": "#839192", "git1": "#C0392B ", "git2": "#2E86C1", "gitInv0": "#FFFFFF", "gitBranchLabel0": "#FFFFFF", "commitLabelColor": "#FFFFFF" } }}%%gitGraph commit id: "commit 1" commit id: "branch" branch long-lived-branch checkout long-lived-branch commit id: "50 clever commits" checkout master commit id: "commit 2" checkout long-lived-branch commit id: "too clever" checkout master commit id: "commit 3" checkout long-lived-branch commit id: "too long" checkout master commit id: "commit 4" checkout long-lived-branch commit id: "try to merge back" checkout master merge long-lived-branch id: "Merge Conflict!!" type: REVERSE checkout long-lived-branch commit id: "trying to fix" commit id: "still trying to fix" commit id: "struggling to fix" commit id: "ask Hari for help" branch fixes-branch-to-send-to-naughty-colleague checkout fixes-branch-to-send-to-naughty-colleague commit id: "fix 1" commit id: "fix 2" commit id: "fix 3" commit id: "could have been working on better things!" checkout long-lived-branch merge fixes-branch-to-send-to-naughty-colleague id: "merge fixes" type: HIGHLIGHT commit id: "more commits" commit id: "because this branch only had 105 commits already" checkout master merge long-lived-branch id: "Finallly Merged!" type: HIGHLIGHT commit id: "Please never do that again"
I've administeredAzure Active Directory at a couple of companies and integrated a variety of applications including GitHub Enterprise Cloud, AWS IAM Identity Center (formerly AWS SSO), Jenkins, ArgoCD, Keycloak, Hubspot etc using the typical OIDC or SAML integration mechanisms.
azure_ad_aws_github_keycloak.d2:
A production Jenkins on Kubernetes I built for a client with auto-spawning agents for horizontal scaling and integration with Docker, SonarQube, Clair, Grype and Trivy for code & container scanning.
- GitHub repo:HariSekhon/Kubernetes-configs
- GitHub repo:HariSekhon/Jenkins
- AdvancedJenkinsfile
- Groovy Shared Library with the code & container scanning functions
- clair.groovy
- grype.groovy
- trivy.groovy,trivyFS.groovy,trivyImages.groovy
- gcrDockerAuth.groovy,garDockerAuth.groovy
- and others invars/, and don't forget about the epicJenkinsfile
screenshot:
A production internet customer facing website and apps replatform to Google Kubernetes Engine I did for an internet startup client using:
- GitHub repo:HariSekhon/Terraform
- GitHub repo:HariSekhon/Kubernetes-configs
- External DNS automatic DNS record creation in Cloudflare for any Kubernetes ingresses
- External Secrets pulling into Kubernetes from GCP Secret Manager
There are Cloudflare API scripts in theHariSekhon/DevOps-Bash-tools repo.
gcp_cloudflare_web_architecture_gke.py:
A variation using Kubernetes and Cloud Functions of this GCP malware scanner solution architecture:
kubernetes_deployment_hpa_ingress.py:
- GitHub repo:HariSekhon/Kubernetes-configs
kubernetes_stateful_architecture.py:
- GitHub repo:HariSekhon/Kubernetes-configs
kubernetes_external_traffic_policy.d2:
- GitHub repo:Kubernetes-configs
- GitHub repo:HAProxy-configs
Kubernetes withMetalLB
- GitHub repo:HariSekhon/Kubernetes-configs
Is it just me or do MetaLB think they'reStarfleet? (compare their logos)
kubernetes_on_premise_metallb.d2:
A Traefik deployment I did for a client.
kubernetes_traefik_ingress_gke.py:
kubernetes_traefik_ingress_gke.d2:
A Kong API Gateway deployment I did for a client.
kubernetes_kong_api_gateway_eks.py:
A high scale production OpenTSDB replatform I did to Kubernetes for a client, ingesting 9 billion data points per day and serving 3 million queries per day.
I also had to do advanced performance tuning of their production HBase cluster which was suffering from frequent outages at this scale due to being set up by a non-SME on the wrong hardware (I had to make do with the existing hardware of course).
This was the second client I did in-depth performance tuning of HBase for - I've published a selection of useful HBase tools - seehbase_*.py
andopentsdb_*.py
inHariSekhon/DevOps-Python-tools.
mysql_replica_architecture.d2:
See Also: Prometheus and components quick install scripts in theDevOps-Bash-tools repo.
aws_s3_config_notify_lambda_dynamodb.d2
At least they don'tonly test in Production!
Another internet facing client refused to use tagging because they didn't want to have to think up version or release numbers for their website releases.
Not everybody likes environment branches, but they worked in production for over 2 years and they are easy to use.
Also, contrary to some naysayers it's quite easy to diff environment branches as everything should be in Git, so you can get a very quick and easy difference between your environments in a singlegit diff
command. It's also easy to automate backporting hotfixes to lower environments:
%%{ init: { "logLevel": "debug", "theme": "dark", "gitGraph": { "mainBranchName": "dev" }, "themeVariables": { "git0": "red", "git1": "blue ", "git2": "green", "gitInv0": "#FFFFFF", "gitBranchLabel0": "#FFFFFF", "commitLabelColor": "#FFFFFF" } }}%%gitGraph branch staging branch production checkout dev commit id: "commit 1" checkout staging commit id: "QA fix 1 " checkout production commit id: "hotfix commit" checkout dev commit id: "commit 2" checkout staging merge dev id: "fast-forward merge" tag: "CI/CD + QA Tests" checkout production merge staging id: "fast-forward merge " tag: "v2023.1 Release (CI/CD)" checkout dev commit id: "commit 3" checkout staging commit id: "QA fix 2 " %% new MermaidJS comment format %% checkout production %% commit id: "commit 3 " checkout dev commit id: "commit 4" checkout staging merge dev id: "fast-forward merge 2" tag: "CI/CD + QA Tests" checkout production merge staging id: "fast-forward merge 2 " tag: "v2023.2 Release (CI/CD)" checkout dev commit id: "commit 5" checkout staging commit id: "QA fix 3 " %% new MermaidJS comment format %% checkout production %% commit id: "commit 5 " checkout dev commit id: "commit 6" checkout staging merge dev id: "fast-forward merge 3" tag: "CI/CD + QA Tests" checkout production merge staging id: "fast-forward merge 3 " tag: "v2023.3 Release (CI/CD)"
Note: I did eventually move this client to tagged releases usingYYYY.NN
release format, just incrementingNN
which is a no brainer (githubNextRelease.groovy). It turns out the developers had eventually started using releases in Jira labelled asYYYY.NN
to track which tickets were going into which production deployment, so when I pushed for this, it made sense to them finally as not being too great an inconvenience! It's also easy to automate by creating GitHub Releases in Jenkins (githubCreateRelease.groovy).
In some environments,devs push to different brancheswhich have diverged such that they cannot do clean Git merges from one branch to the next as per above.
This is not recommended because:
- allows for further drift between branches
- wastes one of the big advantages of Git to track and merge changes across branches
- waste of CI/CD build time minutes
- can incur additional cost
- waste of real time
- artifacts pushed to Production were not actually tested in lower environments
- untested code can be pushed to Production
- untested code can be pushed to Production branch and released to Production environmentwithout the code having been tested in lower environments
release_workflows_separate.d2:
Build once & promote the same artifact is preferred.
- build once saves physical time and CI/CD costs
- test the exact artifact output (Docker image or Mobile iOS
.ipa
or Android.apk
) - no untested code reaches Production
Concrete example ofSeparate Branch Workflows above.
At one client I hadto do this because the IPA generated in each environment had different bundle IDsand the devs would have had to make changes for me to be able to try a unified release workflow.
release_workflows_separate_mobile_ios.d2:
Iirc I created and stuck this meme pic ofThe Most Interesting Man in the World on the wall of my tech dept back in 2011 while leading the infra team of an internet Ad Tech company doing several production releases a day. We literally did test in production using a small fraction of live internet traffic via canary deployments.
If done badly though without canary release testing or similar then it can result in this...
I may have gone overboard and done so many Diagrams-as-Code I'm starting to see life this way...
karl_marx_test_ideas_in_production.d2
A sample architecture I did for a client for us to talk through, which was similar to what they had in mind (I won the gig).
This is the only diagram not as code (here for historical interest). I would embed the interactive live diagram but GitHub markdown doesn't allow HTML iframes so this is the png.
When you're trying to explain to your kids how the internet works...
This should give you some idea of my long evolution having reached the level of lead engineer and architectby the mid-to-late 2000s.
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IOS / NX-OS : done, 2004-03-01, 2024-12-31 %%Juniper - Netscreen / SSG / SRX / ScreenOS / JunOS : done, 2007-01-01, 2013-01-18 %%Netgear : done, 2005-01-01, 2012-12-31 section Load Balancers section Security Security : crit, 2004-10-01, 2024-12-31 %%Kerberos : active, 2006-06-01, 2024-12-31 %%LDAP : active, 2006-06-01, 2024-12-31 section DevOps DevOps : crit, 2005-11-11, 2024-12-31 section Data Data : active, 2005-11-11, 2024-12-31 %%Data Validation : done, 2006-06-01, 2024-12-31 %%Data Science : done, 2013-01-18, 2024-12-31 section Architecture Architecture : crit, 2005-11-11, 2024-12-31 Web-Scale Architecture : active, 2009-11-01, 2024-12-31 MicroServices : active, 2018-10-01, 2024-12-31 Diagrams-as-Code : active, 2023-04-14, 2024-12-31 section Databases (RDBMS) Databases (RDBMS) : crit, 2004-01-01, 2024-12-31 SQL : active, 2004-01-01, 2024-12-31 Microsoft SQL Server : done, 2004-01-01, 2005-10-31 Oracle : done, 2005-11-01, 2009-09-10 MySQL : active, 2007-01-01, 2024-12-31 PostgreSQL : active, 2008-01-01, 2024-12-31 section Web & CDNs Web : crit, 2005-01-01, 2024-12-31 APIs : active, 2006-06-01, 2024-12-31 Load Balancers : active, 2009-07-01, 2024-12-31 %%LVS : done, 2009-01-01, 2009-11-11 %%Foundry - ServerIron XL / 4G : done, 2009-10-13, 2011-11-31 %%F5 BigIP : done, 2010-06-01, 2013-01-18 %%HAProxy : active, 2018-04-01, 2024-12-31 %%Kong : active, 2023-03-01, 2024-12-31 %%Traefik : active, 2023-03-01, 2024-12-31 Web-Scale Architecture : active, 2009-11-01, 2024-12-31 CDNs : active, 2009-12-01, 2024-12-31 %%UlraDNS : done, 2009-11-01, 2012-06-31 %%Cotendo : done, 2012-06-01, 2013-01-13 %%Cloudflare : active, 2020-08-20, 2024-12-31 MicroServices : active, 2018-10-01, 2024-12-31 section Virtualization & Containerization Virtualization : crit, 2005-01-01, 2024-12-31 %%VMware ESX, ESXi, VirtualBox : done, 2005-01-01, 2017-02-16 %%Vagrant : active, 2013-01-01, 2023-12-31 Containerization : crit, 2014-06-01, 2024-12-31 Docker : active, 2014-06-01, 2024-12-31 Kubernetes : active, 2018-09-01, 2024-12-31 MicroServices : active, 2018-10-01, 2024-12-31 ArgoCD : active, 2021-01-01, 2024-12-31 section IaaC & Configuration Management Configuration Management :crit, 2006-01-01, 2024-12-31 Puppet Config Mgmt : done, 2008-09-01, 2014-02-18 Ansible : active, 2014-06-01, 2024-12-31 IaaC :crit, 2008-01-01, 2024-12-31 Terraform :active, 2019-09-01, 2024-12-31 %%Terraform Cloud : active, 2021-09-01, 2022-09-31 %%Kickstart : active, 2008-01-01, 2024-12-31 %%Preseed : active, 2009-01-01, 2024-12-31 %%AutoInstall : active, 2023-01-01, 2024-12-31 section CI/CD CI/CD : crit, 2010-06-01, 2024-12-31 Jenkins : active, 2010-06-01, 2024-12-31 Travis CI : done, 2014-05-01, 2023-05-08 CircleCI : done, 2019-09-01, 2021-12-31 BuildKite : done, 2019-09-01, 2021-12-31 GitHub Actions : active, 2019-09-01, 2024-12-31 %%GitLab : active, 2019-09-01, 2022-12-31 %%Azure DevOps : done, 2019-09-01, 2022-12-31 %%Bitbucket : done, 2019-09-01, 2022-12-31 %%Concourse : active, 2019-11-01, 2020-03-20 %%TeamCity : active, 2020-08-20, 2021-02-31 CloudBuild : active, 2020-08-20, 2023-09-30 section Monitoring Monitoring : crit, 2006-06-01, 2024-12-31 Nagios : active, 2006-06-01, 2019-07-31 OpenTSDB : done, 2016-09-01, 2019-07-31 Grafana : active, 2018-01-01, 2024-12-31 Prometheus : active, 2018-06-01, 2024-12-31 %%Pingdom : done, 2020-08-20, 2023-09-17 %%Datadog : done, 2022-08-20, 2023-09-17 section Big Data Big Data : crit, 2009-11-13, 2019-07-31 Hadoop : done, 2009-11-13, 2019-07-31 %%HDFS : done, 2009-11-13, 2019-07-31 %%MapReduce : done, 2012-06-01, 2019-07-31 Cloudera / Hortonworks : done, 2012-08-01, 2020-03-20 Hive : done, 2013-01-18, 2019-07-31 HBase : active, 2013-02-01, 2019-07-31 Impala : done, 2013-04-01, 2015-06-30 Spark : active, 2014-01-01, 2019-07-31 Kafka : active, 2014-01-01, 2019-07-31 Apache Drill : active, 2014-06-01, 2018-12-31 section NoSQL NoSQL : crit, 2009-11-13, 2024-12-31 HBase : active, 2013-02-01, 2019-07-31 %%MongoDB : done, 2013-06-01, 2013-12-31 Cassandra : active, 2013-08-01, 2024-12-31 Couchbase : done, 2013-11-01, 2024-03-01 section Caching Caching : crit, 2009-11-31, 2024-12-31 Memcached : done, 2009-11-31, 2024-12-31 Redis : active, 2013-03-01, 2024-12-31 section Cloud Cloud : crit, 2012-09-01, 2024-12-31 AWS : active, 2012-09-01, 2024-12-31 GCP : active, 2018-09-01, 2024-12-31 Azure : active, 2020-08-01, 2024-12-31 section Search Search : crit, 2013-03-31, 2024-12-31 Elasticsearch : active, 2013-03-31, 2024-12-31 %%LogStash : done, 2013-03-31, 2024-12-31 %%Fluentd : crit, 2018-03-31, 2024-12-31 %%Kibana : crit, 2013-03-31, 2024-12-31 SolrCloud : done, 2013-04-01, 2024-03-01
Generated by:HariSekhon/GitHub-Repos-MermaidJS-Gantt-Chart
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Code generated by this script fromDevOps-Bash-tools.
git_graph_commit_history_gnuplot.sh
git_graph_commit_history_mermaidjs.sh
Code generated by this script fromDevOps-Bash-tools.
github_graph_commit_times_gnuplot.sh
github_graph_commit_times_mermaidjs.sh
Repo:HariSekhon/GitHub-Graph-Commit-Times
Coded usingGoNum:
These are reworked fromPython diagrams andCloudgram examples.
aws_load_balanced_web_farm.py:
aws_clustered_web_services.py:
advanced_web_services_open_source.py:
aws_serverless_image_processing.py:
Install D2, Graphviz, Python3 and 'diagrams' pip module:
git clone https://github.com/HariSekhon/Diagrams-as-Code diagramscd diagramsmake install
Create all the.png
and.svg
diagrams in theimages/
dir:
make
Generate only the D2 svg diagrams:
make d2
Generate only the Python png diagrams:
make py
Create any single D2 diagram by running the d2 script file:
./jenkins_kubernetes_docker.d2
Create any single Python diagram and have it open automatically by running the python script file:
./gcp_cloudflare_web_architecture_gke.py
Thetemplates/diagram.d2 andtemplates/diagram.py show the basics of each language.
They are a good starting point for creating your own diagrams, and come pre-loaded with many useful icons, links to docs and links to icon sets.
The rest of my original source repos arehere.
Pre-built Docker images are available on myDockerHub.
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Cloud & DevOps Architecture Diagrams-as-Code in Python, D2 and MermaidJS languages
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