Eric Sloof

NFS is a reliable and viable storage option for virtualization. VMware supports both NFS version 3 and NFS version 4.1, providing features similar to those available with block-based storage like SAN. With proper configuration, vSphere on NFS delivers strong performance, stability, and a rich feature set.

Key Considerations for Deployment

   1. Networking Configuration

Efficient networking is essential for NFS performance. VMware recommends isolating storage traffic using dedicated switches or VLANs. The minimum NIC speed should be 1GbE, with 10GbE preferred for better throughput. Avoid network congestion by ensuring the LAN connection to the storage array is not over-subscribed.

   2. Throughput and Latency Optimization

NFS throughput can be enhanced using several methods:

• Jumbo Frames: Increases frame payload size for higher efficiency but requires consistent support across all devices.
• Load Sharing: Configure multiple datastores using separate IP connections to distribute network traffic.
• Link Aggregation: Multiple physical interfaces can be combined to provide redundancy and improved performance.

To reduce latency, minimize the number of network hops between ESXi hosts and storage arrays.

Security Best Practices

Security is crucial when deploying NFS:

• NFS v3 relies on root access and lacks encryption, making it essential to isolate NFS traffic on trusted networks.
• NFS v4.1 introduces support for Kerberos authentication and encryption, providing improved security with non-root access and data integrity checks.

High Availability

To ensure high availability:

• Use NIC teaming and redundant physical switches to eliminate single points of failure.
• Implement Link Aggregation Control Protocol (LACP) for improved failover and path redundancy.

Advanced Features

VMware integrates NFS with key vSphere features such as:

• Storage I/O Control (SIOC): Prevents resource contention by dynamically adjusting I/O priorities based on latency.
• Network I/O Control (NIOC): Prioritizes critical network traffic to prevent bottlenecks on shared NICs.
• Storage DRS: Balances workloads across datastores, optimizing both capacity and I/O performance.
• VAAI-NAS: Offloads storage operations to the array, improving efficiency for tasks like cloning and provisioning.

Additional Attributes of NFS Storage

NFS provides several storage advantages:

• Thin Provisioning: Efficiently allocates storage by using only the space that VMs actually consume.
• Deduplication: Some NAS arrays support deduplication, which can significantly reduce storage requirements.
• Backup and Restore: NFS offers granular backup and restore options, including the ability to restore individual files or entire datastores from snapshots.

Sizing and Configuration Tips

• There is no strict performance limitation on NFS volume size, but most datastores are typically in the tens of terabytes range.
• The recommended number of VMs per NFS datastore depends on workload intensity and backup/recovery SLAs.
• Advanced parameters such as TCP heap size, heartbeat intervals, and locking mechanisms can be tuned based on vendor recommendations.

Conclusion

NFS has evolved to become a robust storage solution for VMware vSphere environments. By following these best practices, organizations can maximize the performance, security, and availability of their virtual infrastructure. Collaboration with storage vendors ensures optimal configurations tailored to each deployment.

This guide offers a practical overview of how to leverage NFS storage effectively with VMware vSphere, ensuring reliable and high-performing virtualization.

VMware continuously enhances its vSphere platform to address scalability and reliability challenges in modern IT infrastructures. One key innovation is the vSphere Clustering Service (vCLS), introduced in vSphere 7 Update 1. Let’s explore how this service improves cluster operations and availability.

What is vCLS?

vCLS provides a distributed and decoupled control plane for clustering services, improving the reliability of features like the Distributed Resource Scheduler (DRS). Traditionally, clustering services depended on the vCenter Server’s availability. This dependency posed limitations on scalability and resilience. With vCLS, these challenges are mitigated, as it allows core clustering services to function even if the vCenter Server experiences downtime.

Architecture and Agent VMs

The vCLS architecture relies on lightweight agent VMs that are deployed automatically within each vSphere cluster. Key points include:

• Up to 3 agent VMs per cluster are created, forming a quorum to maintain service availability.
• In smaller clusters with fewer than 3 hosts, the number of agent VMs matches the number of ESXi hosts.
• These agent VMs are managed by vSphere and require no manual intervention from administrators.

Each vCLS agent VM runs a minimal configuration with a Photon OS, utilizing minimal resources:

• Memory: 128 MB (100 MB reserved)
• vCPU: 1 (100 MHz reserved)
• Disk: 2 GB (thin provisioned)
• No network adapter

Cluster Service Health

vCLS monitors and self-manages the availability of its agent VMs, with three health states:

1. Healthy: At least one agent VM is active and functional.
2. Degraded: One or more agent VMs are temporarily unavailable, though DRS operations continue.
3. Unhealthy: DRS operations are interrupted due to a lack of available agent VMs.

If any agent VM becomes unavailable, vCLS automatically re-deploys or powers it on to maintain service integrity.

Operational Guidelines

Administrators do not need to maintain or interact with the agent VMs directly. The following practices help ensure smooth operations:

• Avoid deleting, renaming, or powering off agent VMs.
• When placing a host in maintenance mode, the agent VMs are automatically migrated to another host.
• Agent VMs are visible in the vSphere Client under the vCLS folder, but not in the Hosts and Clusters view.

Automation scripts should be configured to ignore vCLS agent VMs to prevent accidental disruptions. These VMs can be identified using specific properties such as ManagedByInfo.

Why vCLS Matters

vCLS significantly enhances the resilience and scalability of VMware clusters by enabling essential services to function independently of vCenter Server. This innovation reduces service downtime risks and optimizes operations in both on-premises and cloud environments.

By leveraging vCLS, organizations can achieve a higher level of automation, stability, and performance in their virtual infrastructure. VMware’s forward-thinking approach ensures that clusters remain robust and efficient, even under challenging conditions.

In today’s fast-paced IT environments, ensuring the availability of data and applications is critical. VMware’s vSAN technology offers an innovative approach to distributed storage, delivering resilience and scalability. Let’s explore how vSAN Availability Technologies in version 8 U3 support both enterprise needs and disaster recovery.

What is vSAN?

VMware vSAN is a software-defined storage solution that aggregates storage resources from hosts in a cluster to create a single datastore. By embedding storage within the hypervisor, vSAN eliminates the need for traditional storage arrays. This architecture enhances scalability and resilience while simplifying storage management.

There are two main vSAN architectures:

• Original Storage Architecture (OSA): Uses a tiered system with cache and capacity devices.

• Express Storage Architecture (ESA): Introduced in 2022, ESA improves performance, resilience, and efficiency by eliminating the need for separate cache devices.

Resilience Through Storage Policies

vSAN’s storage policies define resilience settings through parameters like “Failures to Tolerate” (FTT). For instance, an FTT=2 policy with RAID-6 can survive two host failures without data loss. The system automatically adjusts data placement to maintain compliance with the policy, ensuring uninterrupted access even during failures.

Handling Failures and Maintenance

vSAN categorizes components of data objects into various states (e.g., active, degraded, or absent) to determine data availability. The system uses a quorum-based approach to maintain integrity, requiring more than 50% of components to be accessible for data to remain available.

During planned maintenance, vSAN offers options such as “Full data migration” or “Ensure accessibility,” optimizing data movement and availability depending on the scenario.

Advanced Features in ESA

The Express Storage Architecture introduces several enhancements:

• Durability Components: Temporary data structures created during maintenance to ensure data consistency.

• Low-level Metadata Resilience: Improved handling of Unrecoverable Read Errors (UREs) to protect critical metadata.

• Network Redundancy and Adaptive Traffic Shaping: ESA optimizes network performance with features like RDMA support for high-speed environments.

Integration with Disaster Recovery

VMware’s disaster recovery strategies, such as asynchronous replication and integration with tools like VMware Live Site Recovery, complement vSAN’s high availability features. These solutions ensure business continuity even in the face of catastrophic events.

Maximizing Uptime

By utilizing vSAN’s built-in mechanisms for proactive hardware management, degraded device handling, and network partition detection, organizations can achieve exceptional uptime and resilience. Skyline Health tools provide real-time monitoring and diagnostics to quickly address issues.

Final Thoughts

VMware vSAN Availability Technologies offer a robust foundation for modern data centers. With adaptive storage policies, enhanced resilience, and integrated disaster recovery capabilities, vSAN supports scalable and high-performing virtualized environments.

Efficient resource management in large-scale VMware environments is critical, and tagging plays a key role in organizing virtual machines (VMs), hosts, and datastores. The latest VMware vCenter 8.0 U3 release introduces performance improvements and best practices for managing tags effectively.

1. Optimized API Calls:

   • The attach() call for associating tags to inventory items is 40% faster than the previous release.
   • attachTagToMultipleObjects() delivers a 200% speed improvement when associating a single tag to multiple VMs.
   • attachMultipleTagsToObject() provides a 31%–36% performance boost when applying multiple tags to a single VM.

2. API Choices for Tag Operations:

   • Attaching tags: For better efficiency, use attachMultipleTagsToObject() for single objects or attachTagToMultipleObjects() for bulk operations.
   • Querying tags: The listAttachedTagsOnObjects() and the pagination-based list() API are recommended to handle large-scale queries.

• Parallelism: Spread tags across multiple categories to enhance performance, especially when using multiple API clients simultaneously.
• Linked Mode Performance: Enhanced Linked Mode (ELM) allows replication of tag definitions across vCenters. In a ring topology, tag propagation latency is minimized to under 120-180 seconds in large environments with up to 15 linked vCenters.
• Scaling Limits: For optimal performance, vCenter supports up to 6,000 categories, 8,000 tags, and 150,000 tag associations per node.

While tags work well for categorical organization, scenarios requiring unique data per object (e.g., asset IDs or timestamps) are better suited to custom attributes. Balancing tag distribution and avoiding excessive associations can maintain performance stability in large deployments.

VMware vCenter 8.0 U3 tagging enhancements make it easier for organizations to manage vast virtual infrastructure with improved efficiency. By following best practices and leveraging optimized APIs, enterprises can ensure scalability and performance in dynamic environments.

The demand for AI is expanding beyond traditional GPU-based data centers to diverse environments, including edge and hybrid clouds. VMware and Intel have joined forces to bring AI capabilities to CPU-driven infrastructure, demonstrating how AI workloads can thrive without GPUs by leveraging Intel's 4th Gen Xeon Scalable Processors and VMware's Private AI infrastructure.

VMware Private AI integrates AI infrastructure with privacy, compliance, and security, built on VMware Cloud Foundation (VCF). Paired with Intel’s Advanced Matrix Extensions (AMX), it enables scalable and efficient AI operations without requiring specialized hardware like GPUs.

• Intel 4th Gen Xeon Scalable Processors with AMX:
  AMX accelerates both AI training and inference directly within the CPU, optimizing performance for workloads like large language models (LLMs).

• VMware Cloud Foundation:
  This software-defined platform virtualizes compute, storage, and networking, providing a unified management interface for containerized AI workloads using VMware Tanzu Kubernetes Grid (TKG).

In a real-world application, VMware and Intel tested the Llama 2-7B model on Intel's hardware, showing how AMX-enabled processors efficiently handle inference workloads. Key results include:

• Inference latency under 50ms for small batches with INT8 precision.
• Scalability for multiple instances per socket with sub-100ms latency, even at high token counts.

• Intel's AMX technology speeds up inference by up to 1.8x compared to BF16 models.
• VMware's integration with Kubernetes makes deploying AI models on existing infrastructure fast and seamless.

This solution is ideal for businesses looking to expand AI capabilities without investing heavily in GPU infrastructure. It offers:

• Cost Efficiency: Leverage existing CPU resources for AI tasks.
• Flexibility: Run AI workloads across cloud, edge, and on-premise environments.
• Scalability: Easily manage resource-intensive tasks like LLM inference with VMware's orchestration tools.

By combining VMware and Intel technologies, enterprises can unlock the full potential of AI with optimized infrastructure, reducing costs and simplifying deployment.

In today’s security-conscious world, data encryption is no longer optional—it's a critical requirement. VMware's vSAN Encryption Services provide robust security for data both at rest and in transit, ensuring compliance with organizational and regulatory standards. Here's a closer look at how VMware's latest offerings can protect your infrastructure.

• Data-at-Rest Encryption:
  Protects all data stored on vSAN clusters, encrypting it at the final stage of I/O processing.

• Data-in-Transit Encryption:
  Safeguards data transmitted across vSAN hosts without requiring a Key Management Server (KMS).

These services are enabled on a per-cluster basis, offering flexibility depending on your needs.

• Original Storage Architecture (OSA):
  Supports both encryption and space-saving features like deduplication and compression.

• Express Storage Architecture (ESA):
  Encrypts data efficiently at the upper layers of the storage stack, minimizing CPU and network overhead.

Organizations can manage encryption keys using either an External Key Management Server (KMS) or the vSphere Native Key Provider (NKP). For enhanced security, VMware recommends using Trusted Platform Modules (TPM) to store keys locally on hosts.

• Performance Impact:
  Encryption is optimized to minimize performance overhead by utilizing advanced AES-NI CPU instructions.

• Rekeying and Secure Wiping:
  Both shallow and deep rekey operations are supported, allowing administrators to rotate encryption keys without disrupting operations. Additionally, VMware offers secure device wiping options compliant with NIST standards.

• Enable both data-at-rest and data-in-transit encryption for comprehensive protection.
• Ensure proper DNS configurations for KMS to avoid connectivity issues.
• Implement TPM on all vSAN hosts to improve key persistence and recovery processes.

VMware's vSAN Encryption Services provide scalable and flexible security solutions, helping organizations meet their data protection goals with minimal complexity. Secure your infrastructure today with VMware vSAN!

As data volumes grow, efficient storage management becomes critical to controlling costs. VMware vSAN offers both opportunistic and deterministic space-saving technologies to help organizations optimize storage while maintaining performance.

• Opportunistic Techniques:
  These depend on data characteristics and conditions. Examples include:

  • Deduplication and Compression (DD&C) in the Original Storage Architecture (OSA).
  • Compression-only options for performance-sensitive workloads.
  • Thin provisioning, which allocates space as needed, and TRIM/UNMAP for reclaiming unused capacity.

• Deterministic Techniques:
  These ensure consistent savings through methods like erasure coding, which protects data using less capacity than traditional mirroring.

• Express Storage Architecture (ESA):
  ESA integrates compression at the top of the storage stack, reducing CPU and network usage while enhancing performance. Unlike OSA, ESA does not currently support deduplication but offers highly efficient erasure coding.

• Advanced RAID Options:
  ESA enables RAID-5 and RAID-6 erasure coding without performance penalties, making it suitable for both small and large clusters.

• For Performance-Driven Workloads:
  The compression-only feature in OSA is ideal. It minimizes latency and reduces the risk of storage device failure affecting the entire cluster.

• For Maximum Capacity Savings:
  Deduplication and compression, combined with RAID-5/6 erasure coding, offer substantial storage reduction in environments that can support the additional processing requirements.

• Align storage policies with workload needs.
• Use modern high-performance storage and networking hardware.
• Enable TRIM/UNMAP for automated space reclamation, particularly for thin-provisioned environments.

VMware vSAN continues to evolve, providing flexible, scalable, and efficient storage solutions tailored to meet both performance and capacity demands. By leveraging these features, organizations can better manage their storage infrastructure while reducing costs.

Ransomware attacks are on the rise, making robust disaster recovery essential. VMware Live Cyber Recovery offers an efficient, cloud-based solution by deploying a Recovery Software-Defined Data Center (SDDC) on AWS. This guide covers key considerations for deploying and managing your Recovery SDDC for ransomware recovery.

Key Points of SDDC Deployment

• Deployment Models:

  • Just-in-Time: Deploy SDDC only when needed, ideal for cost savings but requires hours to configure.
  • Persistent: Always active, providing faster recovery times but with ongoing cloud costs.

• Configuration Essentials:
  Recovery SDDC setup involves resource groups, virtual networks, folder structures, and vCenter tags to support recovery plans. Firewall rules and network access configurations are also critical for smooth operations.

• Scalability:
  SDDC can scale up or down based on workload needs. Elastic Disaster Recovery Services (DRS) automate scaling but can also be managed manually by administrators.

Recovery Planning and Management

• Recovery plans require an active SDDC for compliance and testing. Persistent SDDCs simplify this by maintaining configurations, while Just-in-Time deployments demand manual reconfigurations with each deployment.

• Plan Deactivation:
  Before removing an SDDC, deactivate recovery plans to prevent compliance alerts from inactive recovery sites.

Cost vs. Speed Tradeoff

Organizations can choose between lower costs with Just-in-Time deployment or faster recovery with persistent SDDCs. Each option supports scaling and integration with critical services like VPN, DNS, and stretched networks.

VMware Live Cyber Recovery streamlines ransomware recovery with flexibility, scalability, and easy integration, making it a strong solution for modern cyber resilience.

VMware Cloud Foundation (VCF) Automation offers a robust framework to streamline infrastructure-as-a-service (IaaS) delivery through a self-service catalog. This adoption path is designed to guide organizations in building modern private cloud environments that integrate traditional and modern workloads with enhanced automation capabilities.

The journey begins with vSphere Supervisor, a powerful tool that enables seamless workload management by integrating core services like Kubernetes, VM, and network management. By configuring vSphere Namespaces, users can establish governance, workload isolation, and optimized resource allocation for both developers and administrators.

Key services include:

• VM Service: Deploy and manage virtual machines using declarative configurations.
• Kubernetes Integration: Simplify Kubernetes cluster deployments and management.
• Data Services Manager (DSM): Offer self-service access to deploy and manage databases for application teams.

VCF Automation enhances IaaS delivery by creating scalable and adaptable automation layers:

• Cloud Abstraction Layer: Separate storage, networking, and compute for multi-cloud agility.
• Infrastructure as Code (IaC): Develop reusable automation templates in YAML, integrated with version control systems like GitHub.
• Cloud Consumption Interface (CCI): Enable application teams to deploy services efficiently through customizable templates and cloud-init scripts.

Organizations can implement robust governance policies to ensure compliance and proper resource placement. The self-service catalog empowers users to deploy infrastructure resources such as Kubernetes and databases via API or user interface. Additionally, the VCF Orchestrator enables complex workflow automation, supporting various programming languages to automate extensive data center operations.

VCF Automation 5.2 offers a guided adoption path designed to help organizations leverage cloud automation effectively. This roadmap covers all phases of automation, from setting up basic workloads to managing complex deployments with advanced features.

Begin your automation journey by adding cloud environments and organizing resources. VCF Automation makes it easy to:

• Add cloud accounts to manage virtual machines, networking, and storage.
• Perform quick actions on discovered resources for immediate results.
• Organize resources and users into projects for better control.
• Use a quick-create wizard to deploy virtual machines rapidly.

Once you're familiar with the basics, VCF Automation enables advanced resource management:

• Cloud Abstraction Layer: Separate compute, storage, and networking to create cloud-agnostic deployments.
• Infrastructure as Code (IaC): Develop reusable automation templates using YAML and integrate them with platforms like GitHub.
• Lifecycle Management: Automate deployment lifecycle events to enhance efficiency through extensibility.

Take automation to the next level by incorporating advanced features such as:

• Network Automation: Integrate network policies and dynamically provision networks to support workload flexibility.
• Kubernetes Automation: Deploy and configure Kubernetes clusters with VCF Automation templates.
• Custom Catalog Request Forms: Build tailored forms to enhance user experience and streamline resource requests.

Empower users with a self-service catalog where they can deploy infrastructure resources "as a service." Built-in governance policies ensure compliance and control over resource deployments.

Whether you’re just starting out or looking to optimize your automation strategy, VCF Automation 5.2 provides a comprehensive toolkit to improve productivity, agility, and operational efficiency. Ready to take the next step? Explore the hands-on labs and tutorials available to deepen your expertise!