Top ACRA Alternatives

Bacula Enterprise provides backup and recovery for enterprise, HPC, defense, government and research environments. Developed by Switzerland-based Bacula Systems, it protects physical, virtual, container, database, SaaS and cloud workloads from one platform. Support data sovereignty with on-premises deployment without mandatory cloud control planes, call-home licensing or continuous internet access. Retain control over backup location, infrastructure, encryption keys and recovery procedures. Strengthen ransomware resilience with physically air-gapped tape, offline copies, immutable storage options, encryption, MFA, access controls and file integrity verification. For petabyte-scale HPC datasets, HPC Accelerator, parallel processing and Lustre, GPFS and ZFS integrations help protect large file populations. Use disk, tape, object storage and cloud targets, with no licensing charges based on protected data volume. VM coverage includes VMware vSphere/ESXi, Hyper-V, Proxmox, Nutanix AHV, XenServer, XCP-ng, KVM, QEMU, Libvirt, Red Hat Virtualization, OpenStack, Amazon EC2 and Azure VMs. Protect Kubernetes, OpenShift and Docker containers. Database coverage includes Oracle, SQL Server, PostgreSQL, MySQL, Percona for MySQL, MariaDB, SAP HANA, Sybase ASE, IBM Db2, MongoDB and InterSystems IRIS, plus Amazon RDS integration. Other workloads include Hadoop HDFS, Microsoft 365 and Google Workspace. BWeb administration, scheduling, monitoring, reporting, deduplication and compression simplify operations. Restore files, application data, VMs and supported bare-metal systems. Its open-core architecture combines Bacula's open-source foundation with enterprise-only plugins, security features, management tools and commercial support. Configure plugins, retention policies, storage and support to match your security requirements and recovery objectives. Contact Bacula Systems for a demonstration or evaluation.

Enhancing data leakage prevention in applications is now feasible with the Acra encryption suite, which delivers strong data security for distributed systems, web, and mobile applications that leverage PostgreSQL, MySQL, and KV backends through precise encryption techniques. To comply with regulations including GDPR, HIPAA, CCPA, and PCI DSS, the encryption of sensitive and personal information is essential, aligning with the best practices in the industry. However, incorporating cryptography into distributed applications can often prove to be a complicated and overwhelming endeavor, frequently resulting in less-than-ideal security and substantial architectural trade-offs. Acra transforms this landscape by providing a comprehensive tool that integrates nine essential data security controls, effectively reducing data leakage risks while employing a defense-in-depth approach throughout the entire data lifecycle within the application. Its straightforward integration process does not require significant modifications to existing code, ensuring reliable data protection and improving key metrics such as Mean Time To Detection (MTTD) and Mean Time To Recovery (MTTR). Additionally, Acra features an integration library that allows for the encryption of any record with keys controlled by AcraServer, streamlining the implementation of data security across various platforms. By adopting Acra, organizations can concentrate on their primary operations while upholding rigorous standards for data security. This not only enhances organizational efficiency but also instills greater confidence among stakeholders regarding data protection practices.

An AI-driven platform is engineered to seamlessly fuse security and networking. By utilizing AI-enhanced data protection, the platform significantly boosts the efficiency of threat detection and response, thereby greatly diminishing the chances of human error. This leads to an elevated experience for both users and applications, while also improving overall performance and reliability through an AI-optimized network. Moreover, the total cost of ownership is reduced by simplifying infrastructure with a cohesive platform that minimizes the disorder caused by numerous point products, fragmented operations, and complex lifecycle management. VersaONE guarantees continuous connectivity and integrated security for users, devices, offices, branches, and edge locations. It offers secure access to all workloads, applications, and cloud services through a single unified platform, ensuring that data and resources remain both accessible and safeguarded across various network types, including WAN, LAN, wireless, cellular, or satellite. This all-encompassing platform approach not only simplifies network management and reduces complexity but also strengthens security, effectively tackling the challenges posed by modern IT infrastructures. Furthermore, the incorporation of AI equips organizations to proactively address potential threats while simultaneously enhancing their operational efficiencies, enabling them to thrive in an ever-evolving digital landscape.

To bolster the security of your container environments across GCP, GKE, or Anthos, it's vital to recognize that containerization significantly enhances the efficiency of development teams, enabling them to deploy applications swiftly and scale operations to levels never seen before. As enterprises increasingly embrace containerized workloads, it becomes crucial to integrate security protocols throughout every step of the build-and-deploy process. This involves ensuring that your container management system is equipped with essential security features. Kubernetes provides a suite of powerful security tools designed to protect your identities, secrets, and network communications, while Google Kubernetes Engine takes advantage of GCP's native functionalities—such as Cloud IAM, Cloud Audit Logging, and Virtual Private Clouds—alongside GKE-specific offerings like application layer secrets encryption and workload identity, ensuring unparalleled Google security for your workloads. Additionally, maintaining the integrity of the software supply chain is of utmost importance, as it ensures that the container images you deploy are secure and free from vulnerabilities, preventing any unauthorized modifications. By adopting a proactive security strategy, you can ensure the reliability of your container images and safeguard the overall security of your applications, allowing organizations to embrace containerization confidently while prioritizing safety and compliance. This comprehensive focus on security not only protects assets but also fosters a culture of accountability within development teams.

Confidential AI provides a secure infrastructure designed for private AI inference, agent environments, and confidential computing solutions specifically aimed at AI laboratories, inference service providers, routers, and organizations handling sensitive information. Its hosted inference service leverages open-weight models that run in hardware-backed trusted execution environments (TEEs), employing technologies like Intel TDX and AMD SEV-SNP confidential virtual machines, complemented by NVIDIA GPUs in a secure computing setup. This framework guarantees that prompts, responses, and workload details are protected from infrastructure operators, allowing clients to validate attestation before sharing sensitive data. Users can either implement an OpenAI-compatible API to create inference endpoints and manage agent workloads or obtain the confidential-computing stack for deployment on their own infrastructure, bare metal servers, or across leading cloud platforms. This service proves particularly advantageous in situations where model deployment requires restricting operator access to both prompts and model assets, as well as when handling sensitive AI tasks in a dedicated confidential computing environment. Furthermore, the focus on stringent security protocols cultivates trust in the management of sensitive information, empowering clients to drive innovation while maintaining privacy and confidentiality in their operations. Ultimately, this enables organizations to navigate the complexities of AI technology with greater confidence and security.

Introducing AI and Kubernetes solutions that emphasize security from the very beginning, independent of where your infrastructure resides. By creating a strong security perimeter around Kubernetes workloads, we mitigate the dangers posed by container escapes. Our methodology streamlines the execution of AI and machine learning operations through cutting-edge GPU device virtualization, driver isolation, and virtual GPUs (vGPUs). Edera Krata marks a significant evolution in isolation technology, initiating a new phase that prioritizes security. Edera redefines what is possible in terms of both security and performance for AI and GPU applications, ensuring flawless integration with Kubernetes setups. Each container runs on its own dedicated Linux kernel, effectively eliminating vulnerabilities that arise from shared kernel states among containers. This innovation significantly reduces the likelihood of container escapes, diminishes the reliance on expensive security tools, and lessens the hassle of sifting through extensive logs. With a simple configuration in YAML, launching Edera Protect is straightforward and efficient. Crafted in Rust for enhanced memory safety, this solution maintains high performance without compromise. It embodies a secure-by-design Kubernetes framework that proactively neutralizes threats before they can act, thus revolutionizing the domain of cloud-native security. This advancement not only strengthens your security posture but also facilitates a more efficient operational environment for developers.

Arkhein stands out as a forward-thinking Cloud-Native Application Protection Platform (CNAPP) that utilizes advanced graph technology to bolster security across various cloud environments. By integrating critical components such as cloud infrastructure, user identities, workloads, vulnerabilities, sensitive data, and exposure into a cohesive Security Graph, it reveals authentic attack vectors instead of offering fragmented insights. The platform combines a powerful suite of features, including Cloud Security Posture Management (CSPM), Cloud Infrastructure Entitlement Management (CIEM), Data Security Posture Management (DSPM), security for Infrastructure-as-Code, along with protections for Kubernetes and containerized applications. Its functionalities encompass agentless workload analysis, ongoing compliance monitoring, behavioral analytics, and automated remediation capabilities utilizing Terraform and GitOps workflows. Arkhein is engineered for seamless operation across leading cloud platforms like AWS, Azure, GCP, OCI, and Huawei Cloud, addressing the unique requirements of enterprises, regulated industries, and organizations with data sovereignty concerns. Additionally, it offers flexible deployment options, including SaaS, self-hosted, and air-gapped solutions, ensuring that it can effectively cater to the diverse security needs of different cloud infrastructures. This adaptability makes Arkhein an essential asset for organizations striving to safeguard their cloud environments comprehensively.

Transform the outdated and vulnerable practices of handling non-human identities by adopting our automated and transparent Workload IAM solution. Manage access between workloads with the same level of oversight you would apply to users, leveraging automated, policy-driven, and identity-focused controls that enable proactive risk mitigation associated with non-human entities. Aembit significantly bolsters security by cryptographically authenticating workload identities in real-time, ensuring that only authorized workloads have access to your sensitive data. By integrating short-lived credentials into requests as necessary, Aembit removes the need for storing or protecting secrets. Moreover, it enforces access permissions dynamically, based on real-time evaluations of workload security posture, geographic location, and other vital behavioral metrics. Aembit proficiently secures access across various environments, including cloud platforms, on-premises infrastructure, and Software as a Service (SaaS) applications, offering a holistic identity management solution. This cutting-edge strategy not only streamlines security processes but also strengthens confidence in your digital infrastructure, ultimately fostering a more resilient environment for your operations.

edgeContinuum is a cloud management solution that optimizes OpenStack infrastructure by adding self-service functionalities. Through its user-friendly web interface, API, and Terraform integration, it empowers administrators to provision managed Kubernetes clusters, PostgreSQL databases, virtual machines, and application templates for internal teams or customer tenants. The platform is equipped with multi-tenancy features including organizations, projects, roles, quotas, and usage tracking to facilitate effective management. It organizes data centers and edge locations into distinct regions and availability zones, while also automating the provisioning and lifecycle management of both Kubernetes and PostgreSQL resources. Cloud and managed service providers can utilize edgeContinuum to deliver tailored infrastructure services, enabling enterprises to grant developers on-demand access while ensuring that IT governance is upheld. Furthermore, the control plane can be deployed in various configurations, whether hosted or on-premises, and can even operate in air-gapped environments, allowing workloads to run on the provider's own infrastructure. This adaptability not only meets a wide range of operational requirements but also enhances the overall efficiency of cloud resource management.

D2iQ's Enterprise Kubernetes Platform (DKP) is designed to facilitate the deployment of Kubernetes workloads at scale, making it easier for organizations to adopt and manage advanced applications across various infrastructures, including on-premises, cloud, air-gapped settings, and edge environments. By addressing the most significant challenges faced in enterprise Kubernetes deployment, DKP offers a unified management interface that streamlines the journey to production while ensuring robust control over applications in any environment. Key features include out-of-the-box Day 2 readiness without vendor lock-in, simplified Kubernetes adoption processes, and guarantees of consistency, security, and performance across distributed systems. Furthermore, DKP empowers organizations to swiftly deploy machine learning applications and fast data pipelines, all while tapping into cloud-native expertise to maximize operational efficiency. This platform not only enhances existing capabilities but also paves the way for future growth and innovation in cloud-native environments.

Klique is a vendor-agnostic enterprise AI control plane that enables organizations to manage AI infrastructure, model access, computing resources, and agentic applications through a centralized platform. The software combines three core capabilities covering intelligent AI request routing, service governance, and GPU workload orchestration. Its smart routing engine directs requests to internally hosted models, open-source models, or external AI providers based on cost, latency, availability, data sensitivity, and organizational policies. Automatic fallback mechanisms allow applications to switch between compatible model providers when preferred services become unavailable or fail to meet defined requirements. The governance engine provides centralized controls for token budgets, spending limits, usage quotas, virtual API keys, single sign-on, and role-based access permissions. Administrators can monitor AI consumption across users, departments, projects, models, and agents while maintaining audit trails and detailed infrastructure cost attribution. GPU orchestration capabilities support resource pooling, fractional GPU sharing, workload prioritization, cloud autoscaling, and allocation of computing resources across multiple clusters. The platform integrates with Kubernetes, Slurm, PBS, AWS, Google Cloud, Azure, and existing GPU infrastructure to support both AI inference and machine learning training workloads. AI development capabilities include experiment tracking, dataset management, model registries, automated pipelines, remote development environments, and deployment of managed inference endpoints. Klique also supports governed agentic development environments for tools such as Claude Code and Codex, alongside Model Context Protocol integrations and self-service application catalogs.

dstack is a powerful orchestration platform that unifies GPU management for machine learning workflows across cloud, Kubernetes, and on-premise environments. Instead of requiring teams to manage complex Helm charts, Kubernetes operators, or manual infrastructure setups, dstack offers a simple declarative interface to handle clusters, tasks, and environments. It natively integrates with top GPU cloud providers for automated provisioning, while also supporting hybrid setups through Kubernetes and SSH fleets. Developers can easily spin up containerized dev environments that connect to local IDEs, allowing them to test, debug, and iterate faster. Scaling from small single-node experiments to large distributed training jobs is effortless, with dstack handling orchestration and ensuring optimal resource efficiency. Beyond training, it enables production deployment by turning any model into a secure, auto-scaling endpoint compatible with OpenAI APIs. The proprietary design ensures lower GPU costs and avoids vendor lock-in, making it attractive for teams balancing flexibility and scalability. Real-world users highlight how dstack accelerates workflows, reduces operational burdens, and improves access to affordable GPUs across multiple providers. Teams benefit from faster iteration cycles, improved collaboration, and simplified governance, especially in enterprise setups. With open-source availability, enterprise support, and quick setup, dstack empowers ML teams to focus on research and innovation rather than infrastructure complexity.

Randoli functions as a holistic observability and cost management platform utilizing OpenTelemetry, specifically tailored for Kubernetes, multicloud, hybrid, and AI/ML environments. By integrating crucial aspects such as infrastructure health, application performance, logs, metrics, traces, incidents, and cloud spending into one central interface, it enables teams to transition from multiple tools to a cohesive perspective on system performance. Its federated design smartly separates the control plane from the data plane, which allows for localized telemetry analysis, extraction of relevant signals, and on-demand data access during investigations, all while reducing ingestion and egress and maintaining data sovereignty. Randoli effectively monitors a variety of components, including clusters, nodes, pods, workloads, services, dependencies, latency, errors, throughput, and resource utilization across various platforms like AWS, Azure, Google Cloud, OpenShift, and local environments. Furthermore, it employs OpenTelemetry and eBPF for seamless, low-overhead instrumentation, which not only improves filtering and enriches telemetry but also facilitates real-time signal correlation, thereby enhancing overall observability. This cutting-edge methodology not only simplifies operational insights but also equips teams with the tools they need to proactively oversee performance and manage costs effectively within their cloud infrastructures. By adopting such an integrated approach, organizations can foster greater agility and responsiveness in their operations.

k0rdent is an open-source, Kubernetes-native environment built to address the growing complexity of modern infrastructure. It provides a single platform for designing, deploying, and operating developer platforms across clouds, edge locations, and on-prem systems. k0rdent replaces fragmented tooling with a unified approach to multi-cluster lifecycle management. Platform engineers can rapidly build standardized yet flexible platforms using declarative templates and composable services. Continuous reconciliation enforces desired state automatically, enabling self-healing clusters and reducing outages. Developers benefit from self-service access that removes dependency on operations teams. Built-in GitOps compatibility streamlines updates and accelerates delivery cycles. The platform helps businesses control costs by reducing idle resources and improving infrastructure utilization. Policy-driven architecture improves resilience, governance, and compliance across distributed environments. k0rdent supports AI, ML, and other demanding workloads at scale. Its open standards approach avoids vendor lock-in and promotes long-term flexibility. k0rdent enables closer collaboration between platform teams, developers, and business stakeholders.

CrowdStrike Falcon Cloud Security serves as a unified platform designed to thwart breaches from the initial coding phase through to runtime, incorporating functionalities like agentless visibility, the Falcon sensor, real-time detection, AI-enhanced analytics, and automated response mechanisms. This all-encompassing solution guarantees that organizations maintain constant surveillance of their cloud environments, equipping teams to identify threats from adversaries, streamline threat investigations, and counteract attacks in diverse multi-cloud environments. The Cloud Detection and Response feature provides immediate insights into the activities of cloud control planes while connecting cloud signals with endpoint and identity data, which allows security operations center (SOC) teams to detect threats more promptly. Moreover, the agentless posture management capability enriches cloud-risk evaluations with intelligence regarding adversaries and contextual graph information, facilitating vulnerability prioritization and minimizing the attack surface. This platform not only defends a variety of assets, including cloud workloads, containers, Kubernetes configurations, identities, and permissions, but also protects infrastructure as code, software bills of materials, and sensitive cloud-stored data, thereby ensuring a resilient security stance across all areas of cloud operations. In addition to these features, CrowdStrike Falcon also continuously updates its capabilities to adapt to emerging threats, ensuring that organizations remain a step ahead in their security endeavors.

An adaptable and user-friendly workload orchestrator, this tool is crafted to deploy and manage both containerized and non-containerized applications effortlessly across large-scale on-premises and cloud settings. Weighing in at just 35MB, it is a compact binary that integrates seamlessly into your current infrastructure. Offering a straightforward operational experience in both environments, it maintains low overhead, ensuring efficient performance. This orchestrator is not confined to merely handling containers; rather, it excels in supporting a wide array of applications, including Docker, Windows, Java, VMs, and beyond. By leveraging orchestration capabilities, it significantly enhances the performance of existing services. Users can enjoy the benefits of zero downtime deployments, higher resilience, and better resource use, all without the necessity of containerization. A simple command empowers multi-region and multi-cloud federation, allowing for global application deployment in any desired region through Nomad, which acts as a unified control plane. This approach simplifies workflows when deploying applications to both bare metal and cloud infrastructures. Furthermore, Nomad encourages the development of multi-cloud applications with exceptional ease, working in harmony with Terraform, Consul, and Vault to provide effective provisioning, service networking, and secrets management, thus establishing itself as an essential tool for contemporary application management. In a rapidly evolving technological landscape, having a comprehensive solution like this can significantly streamline the deployment and management processes.

Alibaba Cloud's Container Service for Kubernetes (ACK) stands out as a robust managed solution that combines multiple services such as virtualization, storage, networking, and security to create a scalable and high-performance platform for containerized applications. Recognized as a Kubernetes Certified Service Provider (KCSP), ACK meets the standards set by the Certified Kubernetes Conformance Program, ensuring a dependable Kubernetes experience and promoting workload mobility across various environments. This important certification allows users to enjoy a uniform Kubernetes experience while taking advantage of advanced cloud-native features tailored for enterprise needs. Furthermore, ACK places a strong emphasis on security by providing comprehensive application protection and detailed access controls, which empower users to quickly deploy Kubernetes clusters. In addition, the service streamlines the management of containerized applications throughout their entire lifecycle, significantly improving both operational flexibility and performance. With these capabilities, ACK not only helps businesses innovate faster but also aligns with industry best practices for cloud computing.

kgateway is a next-generation Kubernetes gateway platform built to support both microservices and AI agent ecosystems. It provides a unified control plane for API gateways, AI gateways, inference routing, and agent-to-agent communication. Built on Envoy and open standards, kgateway fully implements the Kubernetes Gateway API. The platform allows teams to aggregate APIs and enforce authentication, authorization, and rate limiting centrally. Kgateway secures LLM usage by protecting models, tools, agents, and sensitive data. It includes an inference gateway to intelligently route requests to generative AI workloads running in Kubernetes. Kgateway supports native MCP and agent-to-agent communication for scalable AI systems. The platform scales from small service-to-service gateways to enterprise-grade deployments handling billions of API calls. It enables advanced traffic management, resilience testing, and security controls. Originally launched as Gloo, kgateway has evolved into one of the most trusted gateways in the Kubernetes ecosystem. It supports hybrid, multi-cloud, and on-prem environments seamlessly. Kgateway empowers teams to build secure, resilient, and AI-ready infrastructure.

Effortlessly manage and connect applications across different clusters, cloud platforms, and data centers. Utilize a unified management solution to enable application connectivity within varied infrastructures. Effectively integrate traditional workloads into your cloud-native application architecture. Create organizational tenants to enforce precise access controls and editing rights for teams utilizing shared infrastructure. Maintain an exhaustive change history for services and resources from the outset. Ensure efficient traffic management across potential failure domains, keeping your customers oblivious to any disruptions. TSB works at the application edge, operating at cluster ingress and among workloads in both Kubernetes and conventional computing settings. Edge and ingress gateways skillfully route and balance application traffic across numerous clusters and cloud environments, while a mesh framework governs service connectivity. A centralized management dashboard provides oversight for connectivity, security, and visibility across your entire application network, guaranteeing thorough control and monitoring. This comprehensive system not only streamlines operational workflows but also significantly boosts overall application performance and reliability. Additionally, it empowers teams to respond swiftly to changes, ensuring a resilient and adaptable infrastructure.

Nife acts as a unified operational platform for cloud, edge, and AI environments, enabling engineering teams to deploy, manage, and scale applications effortlessly across various settings, including public cloud, edge, Kubernetes, bare-metal, and private infrastructures via a single control dashboard. By consolidating application delivery, infrastructure management, cost transparency, and integrated AI Site Reliability Engineering (SRE), Nife significantly boosts operational productivity. Teams can commence deployments using Git, Docker, or source code, as well as oversee applications, clusters, and virtual machines while running workloads across multiple regions. Additionally, Nife supports incident investigation and resolution through its AI SRE capabilities, optimizes cloud spending, and guarantees thorough monitoring, logging, alerting, and observability across their infrastructure. In essence, Nife simplifies the intricate processes of contemporary application deployment and management, proving to be an indispensable resource for teams striving to elevate their operational effectiveness. Ultimately, Nife not only enhances productivity but also fosters a more agile development environment.

The CardinalOps platform serves as an AI-powered tool for effectively managing threat exposure, providing organizations with a holistic view of their prevention and detection strategies across multiple areas, including endpoint, cloud, identity, and network. By integrating insights from misconfigurations, vulnerable internet-facing assets, lack of hardening protocols, and weaknesses in detection or prevention, it offers a thorough assessment of vulnerabilities and prioritizes necessary actions based on their relevance to the business and the tactics of potential adversaries. This platform not only aligns its detections and controls with the MITRE ATT&CK framework, enabling users to assess their coverage comprehensively and identify ineffective or missing detection rules, but also generates customized, deployment-ready detection content through seamless API integration with leading SIEM/XDR solutions such as Splunk, Microsoft Sentinel, and IBM QRadar. Furthermore, its capabilities for automation and operationalizing threat intelligence empower security teams to remediate vulnerabilities more quickly and efficiently. Ultimately, this robust solution significantly enhances an organization’s agility in responding to threats, reinforcing its overall security posture and resilience against cyber risks. With continuous updates and improvements, the platform ensures that security measures remain effective against evolving threat landscapes.

Leverage the power of the enterprise workload engine to improve efficiency, enhance security measures, and foster innovation within your company. The newest iteration of vSphere delivers essential services designed for the current hybrid cloud landscape. It has been revamped to include integrated Kubernetes, enabling traditional enterprise applications to run smoothly alongside modern containerized solutions. This transformation aids in updating on-premises infrastructure through efficient cloud integration. By adopting centralized management systems, obtaining global insights, and applying automation, productivity can be significantly enhanced. Furthermore, you can take advantage of additional cloud services to optimize your operations. In response to the needs of distributed workloads, networking capabilities on the DPU are fine-tuned, resulting in better throughput and lower latency. This strategy also frees up GPU resources, which can be utilized to accelerate the training of AI and machine learning models, even those that are more complex. Ultimately, this cohesive platform not only simplifies operations but also facilitates your organization’s advancement in a rapidly changing digital environment, allowing for sustained growth and adaptation.

IBM Cloud™ Data Shield enables users to run containerized applications securely within an enclave on the IBM Cloud Kubernetes Service host, thereby providing protection for data in use. This cutting-edge service allows user-level code to create private memory areas called enclaves, which are shielded from processes with higher privileges. With enhanced support for Intel Software Guard Extensions (SGX), it expands the array of programming languages available from just C and C++ to also include Python and Java™, while offering preconfigured SGX applications compatible with widely-used tools such as MySQL, NGINX, and Vault. By leveraging the Fortanix Runtime Encryption platform along with Intel SGX technology, this solution equips organizations that manage sensitive data to confidently embrace cloud computing. The integration of IBM Cloud Data Shield allows businesses handling critical information to deploy and capitalize on cloud services without compromising security. Additionally, this platform guarantees that sensitive tasks are performed within a secure environment, thereby further fostering confidence in cloud-based applications and enabling organizations to innovate without fear of data breaches. As a result, enterprises can focus on growth and efficiency while relying on robust security measures.

NVIDIA Confidential Computing provides robust protection for data during active processing, ensuring that AI models and workloads are secure while executing by leveraging hardware-based trusted execution environments found in NVIDIA Hopper and Blackwell architectures, along with compatible systems. This cutting-edge technology enables businesses to conduct AI training and inference effortlessly, whether it’s on-premises, in the cloud, or at edge sites, without the need for alterations to the model's code, all while safeguarding the confidentiality and integrity of their data and models. Key features include a zero-trust isolation mechanism that effectively separates workloads from the host operating system or hypervisor, device attestation that ensures only authorized NVIDIA hardware is executing the tasks, and extensive compatibility with shared or remote infrastructures, making it suitable for independent software vendors, enterprises, and multi-tenant environments. By securing sensitive AI models, inputs, weights, and inference operations, NVIDIA Confidential Computing allows for the execution of high-performance AI applications without compromising on security or efficiency. This capability not only enhances operational performance but also empowers organizations to confidently pursue innovation, with the assurance that their proprietary information will remain protected throughout all stages of the operational lifecycle. As a result, businesses can focus on advancing their AI strategies without the constant worry of potential security breaches.

Agent Substrate is an open-source runtime that enables the creation and management of isolated, stateful agent and code-execution sandboxes tailored for Kubernetes ecosystems. It efficiently oversees the lifecycle of actors and workers, directing active workloads to a shared pool of resources, and can pause inactive sandboxes while preserving their memory and filesystem states for later utilization. By leveraging gVisor or Cloud Hypervisor microVMs for enhanced isolation, these sandboxes are equipped with distinct identity and networking controls for every actor. This platform is specifically designed for infrastructure and platform teams engaged in developing services for agent hosting, coding environments, and other activities that may involve untrusted or intermittent execution. The core framework is built to be portable across Kubernetes, with Google Cloud offering specialized deployment tools that are fine-tuned for GKE. Furthermore, users have the option to incorporate Filestore agent volumes to ensure that workspaces remain intact and retrievable throughout suspension and resumption cycles, thereby increasing the reliability of the development environment. By enabling such capabilities, Agent Substrate proves to be an indispensable resource for contemporary cloud-native applications, empowering teams to streamline their operations and maximize efficiency in managing complex workloads.

A consolidated dashboard facilitates efficient management across diverse environments, encompassing physical, virtual, and hybrid-cloud configurations. This method guarantees the security of workloads across the entire continuum, from local systems to cloud platforms. It automates the safeguarding of dynamic workloads, effectively eliminating potential vulnerabilities while offering strong protection against sophisticated threats. Moreover, it features tailored host-based protections specifically designed for virtual instances, thereby minimizing the impact on the overall system. Leverage threat defenses crafted explicitly for virtual machines to implement effective multilayered safeguards. Improve your visibility and protect your virtualized environments and networks from external attacks. This comprehensive strategy includes protective measures such as machine learning, application containment, anti-malware fine-tuned for virtual machines, whitelisting, file integrity monitoring, and micro-segmentation to reinforce workload security. Additionally, it streamlines the assignment and oversight of all workloads by enabling the integration of AWS and Microsoft Azure tag data into Trellix ePO, thereby enhancing both operational efficiency and security posture. By adopting these cutting-edge solutions, organizations can bolster their infrastructure resilience against evolving threats, ultimately fostering a more secure digital landscape. The implementation of these strategies will not only improve response times but also reduce the complexity of security management in increasingly intricate environments.

KubeVirt technology effectively addresses the challenges faced by development teams that are moving to Kubernetes but still need to handle legacy workloads based on Virtual Machines, which cannot be easily transitioned to containers. It creates a unified development environment where developers can design, modify, and deploy applications that coexist as both application containers and virtual machines within the same framework. The benefits of this methodology are significant and transformative. Teams that depend on traditional virtual machine workloads can quickly convert their applications to a containerized format, which boosts their operational productivity. By embedding virtualized workloads into their development workflows, teams can incrementally break down these workloads while still relying on the remaining virtualized components as necessary. This forward-thinking platform enables the merging of existing virtual workloads with newly engineered container workloads. Moreover, it paves the way for developing microservice applications in containers that can interact fluidly with previously implemented virtual applications, thus promoting a seamless and cohesive development experience. Ultimately, KubeVirt fosters innovation by allowing teams to navigate the complexities of modern application development without losing sight of their legacy infrastructure.

Idira is an innovative identity security platform developed by Palo Alto Networks, specifically designed for enterprises leveraging artificial intelligence, and it focuses on protecting various forms of identities—whether human, machine, or agentic—through a unified control system. This platform transforms the landscape of privileged access management by expanding the oversight of privileges to include all identities capable of engaging with sensitive systems, which involves a wide array of elements such as data, applications, cloud services, workloads, endpoints, secrets, certificates, SSH keys, and AI agents. By pinpointing potential identity risks, Idira dynamically modifies access privileges and oversees the entire lifecycle from the moment access is granted to the end of a session. Transitioning away from a conventional, always-available access model, it prioritizes dynamic privileges, just-in-time access, and zero standing privilege while ensuring ongoing verification and policy-driven controls with real-time enforcement that considers identity, device, and contextual factors. Furthermore, for human identities, Idira integrates privileged access management, workforce access, endpoint privilege management, and identity governance, equipping organizations with essential tools to effectively combat privilege sprawl. This holistic strategy not only fortifies security measures but also enhances operational efficiency across the entire organization, ultimately leading to a more secure and streamlined environment for all users.

OneSource Cloud focuses on designing, constructing, and overseeing sovereign AI infrastructure specifically for organizations operating in regulated industries where public cloud services are not viable for sensitive tasks, including sectors like healthcare, financial services, government, energy, legal, and research. Our offerings comprise dedicated GPU compute as a managed service, which involves cluster design, hardware procurement, data center colocation, deployment, and continuous maintenance. These clusters utilize NVIDIA GPUs linked through InfiniBand to enable effective multi-node training and inference, supplemented by high-performance storage and exclusive private networking. Each client enjoys a distinct, isolated environment that guarantees their data and models are never shared with others, thereby preserving confidentiality and security. In addition, our managed services encompass capacity planning, provisioning, workload scheduling, system monitoring, patch management, and customer support, ensuring a comprehensive approach to client needs. Each setup is carefully tailored to adhere to the client’s compliance requirements, including critical regulations like NIST 800-171 and specific data residency mandates. Currently, we manage a fleet of over 20,000 GPUs across more than 96 data centers, which allows us to effectively address the intricate demands of our clients in a landscape where data sensitivity is paramount. This vast infrastructure not only enhances our capability to provide secure AI solutions but also solidifies our position as a frontrunner in serving organizations that must navigate stringent regulatory landscapes while leveraging advanced technology.

Streamline the identification of anomalies to meet service level agreements while managing the entire network environment. Improve digital interactions by updating security measures through an agentless, AI-powered approach that leverages your existing infrastructure. Enforce a least privilege access policy and implement identity-based security measures that cover applications, devices, and the complete infrastructure. Receive prompt notifications for any escalations and analyze detailed session activities using integrated logging solutions. Enable device fingerprinting to gain essential insights into network structure while ensuring compatibility with current systems. Simplify connectivity and governance from on-site facilities to cloud services. With Lumeus, companies can utilize AI to monitor and detect escalations, control traffic to prevent unauthorized lateral movement, and strengthen user access security by adopting multi-factor authentication and zero trust strategies, all from a unified platform. Furthermore, Lumeus features a cloud management portal that integrates effortlessly with your infrastructure via API, providing improved oversight and governance. This comprehensive strategy empowers organizations to proactively tackle threats and effectively refine their security posture while fostering a safer digital environment for users. By integrating these advanced solutions, businesses can stay ahead of potential risks and ensure compliance with industry standards.