Understanding data infrastructure is a complex task, spanning multiple vendors across on-premises, multi-cloud, and hybrid environments. That complexity, combined with the diversity of workloads that utilize the infrastructure, creates challenges for teams to effectively monitor, troubleshoot, operate, and optimize their environment. NetApp Data Infrastructure Insights (formerly Cloud Insights) introduces a set of new capabilities to tackle these challenges head-on while reinforcing NetApp’s position as a leader in unified data storage. Combining machine learning-powered AIOps and a focus on managing both SAN and virtualized environments, Data Infrastructure Insights redefines how teams approach storage and virtualization management.
Elevating SAN Monitoring with Unmatched Clarity
Navigating SAN environments can be daunting given that they are often running an organization’s most critical workloads. SAN management demands the ability to quickly pinpoint performance bottlenecks and identify misconfigurations to ensure everything runs smoothly, preventing downtime and keeping critical workloads operational. Data Infrastructure Insights simplifies this with SAN Analyzer, which automatically generates an end-to-end topology of block workloads based on its understanding of infrastructure relationships and data paths. By reducing noise from unrelated components across your broad infrastructure, SAN Analyzer offers focused visibility into relationships and workloads, enabling teams to quickly diagnose the root cause of performance issues.
Beyond insightful mapping, Infrastructure Change Analysis takes operational oversight a step further. This feature tracks and correlates configuration changes to their performance impact, giving teams a clear understanding of cause and effect. For example, a slowdown in VM performance indicates that the VM store-db experienced high latency due to the activation of another VM, store-db-backup2. Since both share the same storage infrastructure, the problem was not with the QoS settings but rather with the Service Level definition. However, troubleshooting this could be a lengthy process.
Meanwhile, SAN Anomaly Detection uses AI to detect abnormalities in workload behavior, identifying potential risks before they escalate. This capability proactively prevents disruptions, ensuring SAN environments remain resilient even during periods of peak demand.
Here are some scenarios where Anomaly Detection can be particularly useful:
- When the definition of normal is not clear:
- Example Use Case: SAN error rates, which can vary depending on the port.
- How Anomaly Detection Helps: It identifies significant deviations from the norm, reducing noise, and helps pinpoint potential widespread issues.
- Changes over time:
- Example Use Case: Workloads in a FabricPool environment, where anomalies could indicate issues with automatic data movement between tiers.
- How Anomaly Detection Helps: It adapts to changes over time, identifying anomalies that could indicate issues.
- Large amounts of data where manually defining and adjusting thresholds is impractical:
- Example Use Case: Large numbers of hosts/volumes with varying workloads, each with different SLAs.
- How Anomaly Detection Helps: It seamlessly handles large datasets, identifying anomalies across varying workloads and SLAs, helping to maintain service levels.
This approach not only helps in maintaining service levels but also reduces the noise from unnecessary alerts, making it easier to focus on significant issues.
Streamlining Your VMware Strategy
Virtualized environments, particularly those utilizing VMware, rely on precision and adaptability. With the Broadcom acquisition of VMware, many customers are re-evaluating their VMware estates, creating the perfect opportunity to optimize and future-proof your virtual environment. Data Infrastructure Insights enhances performance in these setups to help teams tackle inefficiencies, ensure seamless operations, and plan for future infrastructure needs.
Host and Cluster Optimization evaluates hosts in the VMware ecosystem for performance issues and suggests actionable steps to redistribute workloads or reconfigure resources. For instance, if a host is overburdened while others in the cluster remain underutilized, Data Infrastructure Insights automatically identifies this imbalance and recommends remedies, ensuring optimal resource allocation.
When it comes to vSAN, VMware vSAN Support dives deep into cluster monitoring, capturing key metrics to proactively address potential performance issues. Whether supporting mission-critical applications or heavy workloads, teams gain the insights they need to maintain stability and high availability across virtualized storage environments.
With Storage Infrastructure Optimization and Reclamation, DII closes the loop by uncovering unused or underutilized storage resources tied to VMware environments. For example, dormant virtual disks or over-provisioned storage can be flagged for reclamation, saving costs and improving overall efficiency. These features are particularly valuable for managing VMware post-Broadcom acquisition, giving teams a roadmap to streamline storage without compromising performance.
ML-Driven Efficiency for Every User and Every Team
The powerful capabilities delivered by Data Infrastructure Insights are fueled by machine learning-driven AIOps. Rather than simply collecting and displaying performance data, the solution interprets it to deliver actionable insights. Whether troubleshooting anomalies or planning for future capacity, intelligence from Data Infrastructure Insights brings predictability and strategic advantage to IT operations.
One essential outcome of adopting Data Infrastructure Insights is its ability to benefit both technical and non-technical users. Application owners and project managers gain clarity through easy-to-understand dashboards, reducing miscommunication and enabling faster decision-making. On the technical side, IT engineers and storage administrators benefit from in-depth operational metrics and recommendations that simplify their workflows.
With its consistent data model, Data Infrastructure Insights ensures a smooth handoff from storage refresh planning to post-deployment monitoring, eliminating the disparities often found when switching between tools and platforms.
The Future of Infrastructure Management Starts Here
Data Infrastructure Insights is a catalyst for smarter IT management. By integrating VMware-specific features, SAN enhancements, and advanced AIOps capabilities, Data Infrastructure Insights enables teams to achieve unparalleled operational control and efficiency.
Don’t just adapt to the challenges of modern IT; get ahead of them. Request a demo today and experience how Data Infrastructure Insights can transform your operations for the better.