Automated DevOps & MLOps
OpenCollar Technologies builds internal developer platforms, CI/CD pipelines, and ML lifecycle management systems that let your engineering teams ship faster, recover quicker, and operate at scale with confidence.
Technology Overview
DevOps and MLOps are the operational backbone of high-performing technology organizations. OpenCollar's Platform Engineering practice goes beyond simply setting up CI/CD - we build comprehensive internal developer platforms (IDPs) that abstract infrastructure complexity, enforce golden paths, and give developers self-service capabilities for provisioning environments, deploying services, and monitoring applications. Our engineers implement infrastructure as code with Terraform and Pulumi, design GitOps workflows with ArgoCD and Flux, orchestrate containers on Kubernetes with production-grade observability, and build ML-specific pipelines that handle data versioning, experiment tracking, model registry, automated retraining, and canary deployments. We measure success through DORA metrics - deployment frequency, lead time, change failure rate, and mean time to recovery - and continuously optimize your engineering velocity. For ML teams, our MLOps frameworks bridge the gap between notebook experiments and production serving, ensuring models are reproducible, auditable, and continuously improving.
Capabilities & Features
CI/CD Pipeline Engineering
Design multi-stage CI/CD pipelines on GitHub Actions, GitLab CI, and Jenkins with automated testing, security scanning, artifact management, and progressive delivery strategies.
Infrastructure as Code (IaC)
Codify your entire infrastructure using Terraform, Pulumi, and CDK with modular, reusable components, drift detection, and policy-as-code guardrails using OPA and Sentinel.
GitOps & Kubernetes Management
Implement GitOps workflows with ArgoCD and Flux for declarative Kubernetes deployments featuring automated sync, health checks, rollback, and multi-cluster management.
Observability & SRE
Build full-stack observability with Prometheus, Grafana, OpenTelemetry, and PagerDuty - covering metrics, logs, traces, and SLO-based alerting that reduces MTTR by 60%.
Internal Developer Platform
Create self-service developer portals using Backstage with service catalogs, scaffolding templates, environment provisioning, and documentation that accelerate developer onboarding.
MLOps & Model Lifecycle
Build end-to-end ML pipelines with MLflow, Kubeflow, and Vertex AI covering experiment tracking, feature stores, model registry, automated retraining, A/B testing, and model monitoring.
Real-World Use Cases
Platform Engineering Transformation
Built an internal developer platform for a 300-engineer organization that reduced environment provisioning from 2 weeks to 15 minutes and increased deployment frequency by 8x.
Zero-Downtime Deployment Pipeline
Implemented blue-green and canary deployment pipelines for a high-traffic e-commerce platform, achieving 50+ daily deployments with zero customer-facing incidents.
MLOps for Production ML
Designed an MLOps platform that manages 100+ ML models in production with automated retraining triggers, A/B testing, and model performance monitoring, reducing model update cycles from months to days.
Multi-Cloud Infrastructure Automation
Codified infrastructure across AWS and Azure using Terraform modules with 95% IaC coverage, enabling consistent, auditable, and repeatable deployments across 12 environments.
Technologies & Tools We Use
Supercharge Your Engineering Velocity
Partner with OpenCollar's DevOps and MLOps engineers to build automated platforms that let your teams ship faster, recover quicker, and innovate with confidence.
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