Operational Excellence for Data, Cloud & AI Systems
Managed Services
Sakura Sky’s Managed Services are designed to keep your cloud, data, and machine learning environments running at peak performance.
We combine automation, observability, and proactive governance to deliver stable, scalable, and secure operations across complex ecosystems.
Through our DataOps, MLOps, and CloudOps practices, we provide continuous optimization, streamlined collaboration,
and resilient infrastructure that evolves with your business needs.
Reliable, cost-efficient, and performance-driven cloud operations
CloudOps & Infrastructure Optimization
Our CloudOps services deliver continuous optimization across AWS, Google Cloud, and Azure. We manage provisioning, scaling, cost efficiency, and compliance through automation and observability - ensuring your infrastructure remains secure, resilient, and aligned with evolving business needs.
Streamlined, secure, and scalable data operations
DataOps
Our DataOps services automate and optimize the flow of data across your enterprise, embedding data quality, observability, and governance from the start. We unify data engineers, analysts, and DevOps teams through automated workflows that accelerate delivery, ensure consistency, and maintain data integrity across hybrid and multi-cloud environments.
Automation-first orchestration for complex data ecosystems
Automated Data Pipelines & Workflow Orchestration
We design and maintain automated data pipelines using orchestration tools such as Apache Airflow, NiFi, and Dagster. Our automation reduces latency, minimizes manual intervention, and ensures consistency across distributed systems - keeping analytics and AI workloads up to date.
Accelerating delivery through automation and standardization
Platform Engineering & DevOps Enablement
Our platform engineering services establish repeatable, policy-driven environments for reliable deployment and management. Through container orchestration, CI/CD pipelines, and GitOps workflows, we unify development and operations to deliver faster, more secure releases.
Operationalizing AI models with reliability and scale
MLOps & Model Lifecycle Management
We manage the full machine learning lifecycle - from data preparation and model deployment to monitoring and retraining. Our MLOps frameworks emphasize automation, version control, and CI/CD pipelines, ensuring your models perform consistently and adapt to new data with minimal manual intervention.
Managing the lifecycle and reliability of AI and agentic workflows
AIOps for Agentic Systems
Our AI Agent Operations services monitor and optimize generative and agentic AI systems. We manage prompt lifecycles, observability, and compliance to ensure safe, auditable, and efficient AI performance across enterprise environments.
Embedding security and governance into every data workflow
Security-Driven DataOps & Compliance
We integrate encryption, access control, and anomaly detection directly into your data pipelines, ensuring compliance with frameworks like ISO 27001, SOC 2, and GDPR. By combining data engineering with security-by-design principles, we enable safe, compliant, and efficient data operations across the entire lifecycle.
Unified visibility for cloud, data, and AI workloads
Platform Monitoring & Observability
We deliver full-stack observability through Prometheus, Grafana, and OpenTelemetry, integrating metrics, logs, and traces across every layer. This enables real-time insight, proactive alerting, and faster remediation - ensuring your systems remain stable, compliant, and high-performing.