The company is a prominent provider of advanced data platform solutions, catering to industries that rely on AI, machine learning, scientific research, and high-performance computing. Their core offering is a cloud-native, flash-optimized storage system engineered for smooth deployment across both cloud and on-premises infrastructures.
Innovecs collaborated with the client to address challenges in scaling AI/ML workflows, optimizing cloud infrastructure, and improving data platform performance. By focusing on infrastructure management, cost optimization, and software development, Innovecs delivered impactful results aligned with client’s goals.
The client faced significant challenges in managing their cloud infrastructure, struggling with the seamless migration of Kubernetes clusters between providers while maintaining service continuity. Their existing cloud and edge environments were not optimized to support AI/ML pipelines efficiently, leading to performance bottlenecks.
Additionally, rising cloud infrastructure costs became a concern, as scaling operations without sacrificing performance proved difficult. Legacy systems further complicated the process, causing inefficiencies and compatibility issues, while their CLI tools lacked the performance needed to handle increasingly complex data workloads.
Successfully migrated the client’s Kubernetes clusters from AWS to Oracle Cloud Infrastructure (OCI) and created a monitoring system for the Kubernetes cluster using VictoriaMetrics.
Optimized code to enhance CLI tool speed, as well as automated package installation and virtual environment setup.
Optimized AWS Kubernetes cluster costs by implementing efficient resource management strategies and replacing Prometheus with VictoriaMetrics.
Provided on-demand DevOps services to optimize deployment pipelines and infrastructure management.
Significant cloud cost savings can be achieved, directly improving operational efficiency and reducing overhead expenses.
A robust infrastructure ensures readiness for increased workloads and accommodates future growth, particularly in emerging fields like AI and HPC.
Enhancing critical tools and systems can boost user productivity, reduce system latency, and provide a seamless user experience.
Internal teams can be upskilled by facilitating the adoption of new tools and processes, ensuring smooth transitions and effective use of technology.
