Dana CazacuDiscover how Atmosphere simplifies data workloads by uniting VMs and Kubernetes for AI, big data, and IoT with seamless scalability and automation.
The demand for data-intensive applications continues to surge across industries, fueled by the exponential growth of data generation. By 2025, the global data volume is expected to reach a staggering 181 zettabytes, according to Statista. Industries like artificial intelligence (AI), the Internet of Things (IoT), finance, healthcare, and e-commerce, leveraging massive datasets to drive innovation, improve decision-making, and deliver personalized experiences.
However, managing these large-scale data workloads comes with significant challenges. Scalability is critical as workloads expand, and infrastructure must keep pace with ever-increasing demands. Performance becomes a key concern when dealing with real-time analytics, machine learning (ML) training, or IoT data processing, where low latency is crucial. Additionally, the operational complexity of provisioning, managing, and scaling infrastructure often stretches IT teams to their limits.
This is where Atmosphere comes in. Built on OpenStack, Atmosphere is designed to simplify and enhance the management of data-intensive workloads. By integrating OpenStack services with Kubernetes, Atmosphere provides a unified platform that bridges traditional cloud infrastructure with modern, cloud-native patterns. This innovative approach reduces operational complexity, improves scalability, and ensures the performance needed to handle even the most demanding data-driven applications.
§ OpenStack as the Backbone
OpenStack serves as a robust foundation for managing data-intensive workloads, providing essential infrastructure components that are both flexible and scalable. Its modular architecture makes it particularly well-suited for traditional VM-based workloads, offering the reliability and performance required for demanding applications.
At its core, OpenStack delivers three key infrastructure services:
- Compute (Nova)
Enables the provisioning of high-performance virtual machines and bare-metal instances, giving organizations the flexibility to run diverse workloads with ease. - Storage (Cinder, Swift)
Offers scalable block storage (Cinder) for low-latency, high-throughput applications and object storage (Swift) for massive datasets, making it ideal for big data and analytics. - Networking (Neutron)
Provides advanced networking capabilities, enabling low-latency, high-throughput connections essential for data-intensive applications.
Strengths of OpenStack for Traditional VMs
OpenStack is particularly effective for legacy applications or workloads that require predictable resource allocation and stable infrastructure. These include monolithic architectures and long-running batch jobs, where consistent resource availability is critical for optimal performance.
For example, organizations often deploy Hadoop clusters on OpenStack virtual machines to process large datasets. Each Hadoop node is provisioned as a VM, ensuring the predictable resource allocation needed for efficient big data processing. Similarly, batch processing jobs in industries like finance and healthcare benefit from OpenStack’s ability to scale resources and maintain stability.
By leveraging OpenStack’s core infrastructure, organizations can build reliable environments for their legacy applications while maintaining the flexibility to scale as their data workloads grow. This makes OpenStack a powerful choice for businesses looking to modernize their infrastructure without disrupting existing operations.
§ Atmosphere’s Advantage
Atmosphere builds on OpenStack to create a unified platform that bridges the gap between traditional VM-based workloads and Kubernetes-native containerized applications. This unique approach allows organizations to manage hybrid environments seamlessly, enabling the best of both worlds for diverse data-intensive workloads.
- Unified Platform for VMs and Kubernetes Workloads
Atmosphere enables businesses to manage both traditional virtual machines and modern containerized applications within the same platform. This flexibility simplifies operations and ensures compatibility for a wide range of workloads. - Hybrid Workload Support
Atmosphere is designed to handle hybrid workloads, where traditional and modern applications coexist. For example, an organization might run Hadoop clusters on VMs for batch data processing while deploying Spark or TensorFlow on Kubernetes for real-time analytics or AI/ML workloads. - Kubernetes-Driven Architecture
Atmosphere leverages Kubernetes as its foundation, enabling features like auto-scaling, self-healing, and rolling upgrades. These capabilities ensure that containerized workloads are highly efficient, resilient, and easy to manage. - Seamless Storage Integration
Atmosphere seamlessly integrates OpenStack’s block storage (Cinder) and object storage (Swift) with Kubernetes using the Container Storage Interface (CSI). This allows big data tools like Hadoop and Spark to access persistent and scalable storage, optimizing data workflows and simplifying storage management.
By combining the strengths of OpenStack and Kubernetes, Atmosphere empowers organizations to run hybrid workloads efficiently, scale dynamically, and simplify the management of complex cloud environments. This advantage positions Atmosphere as a key enabler for businesses navigating the transition to cloud-native computing while supporting their existing legacy systems.
If you want to learn more about this, you can also do read this blog post, Modernizing Legacy Applications with Atmosphere.
§ Traditional VMs vs Kubernetes for Workloads
As organizations continue to embrace cloud computing, many find themselves managing both traditional VM-based workloads and modern, containerized applications. Each approach has its strengths, and Atmosphere is purpose-built to seamlessly integrate and manage these two paradigms within a unified platform.
VM-Centric Approach
Virtual machines provide a stable and predictable environment, making them ideal for legacy applications or workloads that require consistent resource allocation. For example, Hadoop clusters are often deployed on VMs to ensure reliability and performance during big data processing tasks.
Kubernetes-Native Approach
Kubernetes is built for agility and scalability, making it the go-to solution for containerized workloads. Applications like Spark for real-time analytics or AI/ML pipelines benefit from Kubernetes features such as auto-scaling, self-healing, and rolling updates, enabling rapid deployment and efficient resource usage.
Hybrid Scenarios
Many organizations operate in hybrid environments where legacy applications run on VMs while modern, containerized workloads are deployed on Kubernetes clusters. For example, a company might process historical data with Hadoop on VMs while using Kubernetes to run real-time AI inference models with TensorFlow.
If you want to learn more about this topic, check out our Kubernetes vs. Virtual Machines on OpenStack (Where Each One Wins) blog post.
How Atmosphere Bridges the Gap
Atmosphere provides a unified control plane that simplifies the management of both VMs and Kubernetes workloads, ensuring seamless integration and centralized operations. Its Kubernetes-driven architecture powers containerized OpenStack services, enabling businesses to benefit from modern cloud-native features like automated scaling and rolling updates while still supporting VM-based applications.
If you want to learn more about how Atmosphere orchestrates Kubernetes and Openstack for scalable infrastructure, you can read this blog post.
Atmosphere’s ability to leverage OpenStack’s core infrastructure (e.g., Nova, Cinder, Neutron) alongside Kubernetes-native tools ensures that hybrid environments are optimized for performance and efficiency.
Additionally, Atmosphere enables resource optimization by dynamically allocating resources based on workload requirements, whether for stable VM-based applications or agile Kubernetes deployments. Its declarative provisioning and automation tools reduce complexity, providing businesses with the flexibility to transition to cloud-native patterns without compromising their legacy systems.
By harmonizing these approaches, Atmosphere empowers organizations to leverage the strengths of both VMs and Kubernetes, ensuring flexibility, scalability, and operational efficiency across diverse workloads—all within a single, integrated platform.
§ Benefits of Atmosphere for Data Workloads
Atmosphere delivers a range of benefits for organizations managing data-intensive workloads, enabling them to address both legacy and modern application requirements with ease. By combining the best of OpenStack and Kubernetes, Atmosphere simplifies cloud operations while driving innovation and efficiency.
- Flexibility to manage both legacy and modern workloads seamlessly
Atmosphere supports hybrid environments, allowing organizations to run legacy applications on traditional VMs while embracing modern, containerized workloads with Kubernetes. This flexibility ensures that businesses can operate efficiently without being forced into all-or-nothing transitions. - Scalability and efficiency through Kubernetes-driven automation
Atmosphere’s Kubernetes-driven architecture provides advanced features like auto-scaling, self-healing, and rolling upgrades, ensuring workloads can scale dynamically based on demand. This automation reduces manual intervention, optimizes resource usage, and enhances operational efficiency. - Centralized management simplifies operations and reduces complexity
Atmosphere offers a unified control plane for managing both VMs and Kubernetes clusters, consolidating operations into a single platform. This centralized approach reduces the complexity of managing hybrid environments and streamlines workflows for IT teams. - Enables gradual transitions to cloud-native approaches without disrupting existing systems
Atmosphere allows businesses to modernize at their own pace, supporting legacy systems while enabling the adoption of cloud-native patterns. Organizations can run traditional workloads alongside containerized applications, ensuring continuity while gradually transitioning to Kubernetes-based architectures.
With Atmosphere, businesses can simplify the complexities of managing diverse workloads, achieve greater scalability, and adopt modern cloud practices—all while maintaining the stability and performance of their existing systems.
§ Use Cases
Atmosphere’s ability to manage both traditional VMs and Kubernetes-native workloads makes it a powerful platform for addressing diverse, data-intensive use cases across industries. Here are some real-world examples of how Atmosphere supports complex workloads:
- AI/ML training
Atmosphere enables organizations to provision GPU-accelerated VMs for resource-intensive AI/ML training tasks, ensuring high performance for deep learning models. At the same time, Kubernetes clusters can be used to deploy real-time inference workloads, allowing AI applications to process data dynamically and at scale. - Big data processing
Atmosphere supports hybrid big data environments by running Hadoop clusters on VMs for batch data processing and historical analysis, while simultaneously deploying Spark clusters on Kubernetes for real-time analytics. This combination allows businesses to handle both structured and unstructured data workflows efficiently. - IoT data streams
For IoT applications that require processing massive amounts of real-time data, Atmosphere leverages Kubernetes clusters to enable real-time data stream processing. Integrated storage solutions, such as block storage (Cinder) and object storage (Swift), provide scalable and persistent data storage for IoT workloads.
§ Conclusion
Atmosphere represents a transformative approach to managing data-intensive workloads, combining the reliability of OpenStack with the agility of Kubernetes. By providing a unified platform, Atmosphere empowers organizations to seamlessly manage traditional VM-based applications alongside modern, containerized workloads, enabling a smooth transition to cloud-native architectures.
From AI/ML training to big data processing and real-time IoT analytics, Atmosphere addresses the unique challenges of diverse workloads with features like GPU-accelerated VMs, Kubernetes-driven automation, and seamless storage integration. Its flexibility, scalability, and centralized management allow businesses to innovate and scale while maintaining operational stability.
Whether modernizing legacy systems, adopting Kubernetes-native solutions, or managing hybrid environments, Atmosphere provides the tools necessary to simplify operations and drive efficiency. In a world where data is growing exponentially, Atmosphere is the key to unlocking the full potential of data-intensive workloads.
If you’d like to bring Atmosphere into your organization with the help of our team of experts, reach out to our sales team today!