Discover how our GitLab-based DevOps platform solutions transformed development and delivery processes for our clients.
A global manufacturing company with 2,000+ IoT devices and dozens of industrial applications struggled with fragmented development processes, inconsistent security practices, and slow deployment cycles. Each application team used different tools and approaches, creating silos and compliance gaps.
We designed and implemented a comprehensive GitLab-based DevOps platform:
stages:
- build
- test
- security
- deploy
- monitor
variables:
DOCKER_TLS_CERTDIR: "/certs"
CONTAINER_IMAGE: $CI_REGISTRY_IMAGE:$CI_COMMIT_REF_SLUG
include:
- template: Security/SAST.gitlab-ci.yml
- template: Security/Dependency-Scanning.gitlab-ci.yml
- template: Security/Container-Scanning.gitlab-ci.yml
- template: Security/Secret-Detection.gitlab-ci.yml
- local: '/ci/templates/edge-deploy.yml'
build:
stage: build
image: docker:20.10.16
services:
- docker:20.10.16-dind
script:
- docker login -u $CI_REGISTRY_USER -p $CI_REGISTRY_PASSWORD $CI_REGISTRY
- docker build -t $CONTAINER_IMAGE .
- docker push $CONTAINER_IMAGE
only:
- branches
- tags
unit_tests:
stage: test
image: python:3.9-slim
script:
- pip install -r requirements-dev.txt
- pytest tests/unit
artifacts:
reports:
junit: test-reports/unit-tests.xml
integration_tests:
stage: test
image:
name: $CONTAINER_IMAGE
entrypoint: [""]
script:
- python -m pytest tests/integration
artifacts:
reports:
junit: test-reports/integration-tests.xml
security_review:
stage: security
needs: ["container_scanning", "dependency_scanning", "sast", "secret_detection"]
script:
- echo "Generating security dashboard from previous scans"
- python ci/scripts/security_dashboard.py
artifacts:
paths:
- security-report.html
only:
- main
- production
deploy_staging:
stage: deploy
image: alpine:3.15
before_script:
- apk add --no-cache curl
- curl -LO "https://dl.k8s.io/release/v1.24.0/bin/linux/amd64/kubectl"
- chmod +x ./kubectl
- mv ./kubectl /usr/local/bin/kubectl
script:
- kubectl config use-context staging
- envsubst < k8s/deployment.yml | kubectl apply -f -
- kubectl rollout status deployment/$CI_PROJECT_NAME -n staging
environment:
name: staging
only:
- main
deploy_production:
stage: deploy
image: alpine:3.15
before_script:
- apk add --no-cache curl
- curl -LO "https://dl.k8s.io/release/v1.24.0/bin/linux/amd64/kubectl"
- chmod +x ./kubectl
- mv ./kubectl /usr/local/bin/kubectl
script:
- kubectl config use-context production
- envsubst < k8s/deployment.yml | kubectl apply -f -
- kubectl rollout status deployment/$CI_PROJECT_NAME -n production
environment:
name: production
when: manual
only:
- production
monitor_deployment:
stage: monitor
image: curlimages/curl:7.83.1
script:
- |
for i in {1..10}; do
response=$(curl -s -o /dev/null -w "%{http_code}" https://$CI_ENVIRONMENT_URL/health)
if [ "$response" == "200" ]; then
echo "Deployment healthy!"
exit 0
fi
echo "Waiting for deployment to become healthy..."
sleep 30
done
echo "Deployment health check failed!"
exit 1
environment:
name: production
only:
- production
A financial services provider needed to accelerate their development cycles while maintaining strict security and regulatory compliance. Their existing processes involved multiple manual approval steps, extensive documentation, and siloed tools, resulting in 4+ week release cycles.
We implemented a comprehensive GitLab-based platform with built-in compliance:
stages:
- validate
- build
- security
- compliance
- deploy
- audit
include:
- template: Security/SAST.gitlab-ci.yml
- template: Security/Secret-Detection.gitlab-ci.yml
- local: '/ci/templates/financial-compliance.yml'
workflow:
rules:
- if: $CI_MERGE_REQUEST_ID
when: never
- if: $CI_COMMIT_TAG
when: never
- if: $CI_COMMIT_BRANCH == "main"
variables:
COMPLIANCE_FRAMEWORK: "SOC2"
ARTIFACT_RETENTION: "365"
# Validate IaC templates before building
validate_terraform:
stage: validate
image: hashicorp/terraform:1.1.9
script:
- cd terraform/
- terraform init -backend=false
- terraform validate
- cd ../
artifacts:
paths:
- terraform/
# Automated compliance checks
compliance_check:
stage: compliance
image: registry.gitlab.com/security-products/compliance-scanner:latest
script:
- compliance-scan --framework=$COMPLIANCE_FRAMEWORK --output-format=json > compliance-report.json
- python scripts/check_compliance_report.py compliance-report.json
artifacts:
paths:
- compliance-report.json
reports:
compliance_report:
format: json
paths:
- compliance-report.json
allow_failure: false
# Version-controlled schema validation
validate_database_changes:
stage: validate
image: liquibase/liquibase:4.9
script:
- cd database/
- liquibase --changeLogFile=changelog.xml validate
- python ../scripts/generate_db_doc.py
artifacts:
paths:
- database/documentation/
# Audit-ready deployment
deploy_production:
stage: deploy
image:
name: alpine:3.15
entrypoint: [""]
before_script:
- apk add --no-cache curl jq
script:
- |
# Generate pre-deployment audit record
cat > deployment-audit.json << EOF
{
"deployment_id": "$CI_PIPELINE_ID",
"timestamp": "$(date -u +"%Y-%m-%dT%H:%M:%SZ")",
"commit_sha": "$CI_COMMIT_SHA",
"approvers": $(curl -s -H "JOB-TOKEN: $CI_JOB_TOKEN" "${CI_API_V4_URL}/projects/${CI_PROJECT_ID}/merge_requests/${CI_MERGE_REQUEST_IID}/approvals" | jq '.approved_by'),
"compliance_scan": "PASSED"
}
EOF
- echo "Deploying to production..."
- sleep 10 # Simulating deployment
- echo "Deployment completed successfully"
environment:
name: production
artifacts:
paths:
- deployment-audit.json
when: manual
allow_failure: false
rules:
- if: $CI_COMMIT_BRANCH == "main"
# Generate audit documentation
generate_audit_package:
stage: audit
image: python:3.9-slim
needs:
- deploy_production
- compliance_check
script:
- python scripts/generate_audit_package.py
- echo "Audit package generated successfully"
artifacts:
paths:
- audit-package/
expire_in: $ARTIFACT_RETENTION days
rules:
- if: $CI_COMMIT_BRANCH == "main"
Our team has developed specialized GitLab implementations for diverse industry needs
We developed a comprehensive GitLab-based mobile application delivery platform that handles iOS and Android builds, automated testing across multiple device configurations, app store deployments, and beta distribution through TestFlight and Firebase App Distribution.
Our specialized GitLab CI/CD solution for embedded systems development includes custom runners for cross-compilation, hardware-in-the-loop testing integration, firmware versioning, and secure over-the-air update pipelines for IoT and industrial devices.
We implemented a sophisticated GitLab-based deployment platform for global applications, featuring multi-region cloud deployments, traffic routing strategies, geo-specific configurations, and comprehensive monitoring across worldwide infrastructure.
Our specialized GitLab solution for ML/AI teams includes data pipeline automation, model training and validation workflows, experiment tracking integration, model registry, and automated deployment of models to production environments.
We don't just configure pipelines—we create comprehensive DevOps platforms tailored to your specific business and technology requirements.
We begin by understanding your current development processes, technology stack, and business objectives. Our GitLab experts then create a tailored implementation strategy that addresses your specific needs and challenges.
We design an optimal GitLab architecture based on your requirements, including self-hosted or cloud options, high availability configurations, storage optimization, and runner strategy to support your development workflows.
We create efficient, scalable CI/CD pipelines tailored to your application types and deployment targets. This includes pipeline templates, reusable components, and optimization for performance and cost efficiency.
We implement comprehensive security scanning and compliance checks directly into your pipelines, ensuring vulnerabilities are caught early and regulatory requirements are met throughout the development process.
We connect your GitLab pipelines to your target deployment environments, implementing infrastructure as code practices, Kubernetes integration, and automated environment provisioning for consistent deployments.
We implement comprehensive monitoring of your GitLab platform and pipelines, along with continuous optimization practices to ensure optimal performance, cost efficiency, and reliability as your needs evolve.
Let our GitLab experts implement a comprehensive DevOps platform tailored to your business needs.
Schedule a ConsultationOur team of GitLab specialists brings deep experience implementing and optimizing DevOps platforms across various industries and technology stacks.
At DanSoftDev, we've specialized in GitLab platform implementation since 2015, successfully delivering over 180 enterprise-grade GitLab solutions. Our team includes GitLab-certified professionals, CI/CD specialists, and DevOps engineers with extensive experience across the entire DevOps lifecycle.
