In the finance sector, where data integrity and performance are paramount, storage administrators play a crucial role in ensuring the seamless operation of the data infrastructure. Financial institutions process vast amounts of transactions every second, and any disruption can lead to significant financial losses and reputational damage.
The ability to quickly detect and resolve performance degradation is crucially important, especially when this degradation can be resolved before it has an impact on production services. This is where the anomaly detection feature of NetApp® Data Infrastructure Insights (formerly Cloud Insights) comes in. Early detection of unexpected elevation in storage latency or saturation can mean the difference between a costly disruption and business as usual.
This blog post highlights how anomaly detection in Data Infrastructure Insights empowers storage administrators to maintain optimal performance and reliability.
Anomaly detection is a technique that storage administrators use to identify unusual patterns or behaviors in data that deviates from the norm. In a previous blog post we’ve already discussed how detecting anomalies in users’ interactions with files can detect and stop ransomware and other insider threats. but what about detecting anomalies in key performance indicators such as latency, for storage or other infrastructure?
Business and application teams’ expectations have never been higher for storage performance and usability, because storage in 2025 is faster and more flexible than ever. NetApp’s block-optimized ASA eliminates the trade-off between operational simplicity and high-end storage capabilities, and combined with the SAN Analyzer in Data Infrastructure Insights, admin teams can be sure that they’re on top of any potential configuration risks.
But with near-unlimited performance comes the expectation of sub-millisecond latency. In the financial services sector, unexpected increases in storage latency can be costly, potentially affecting multiple workloads. An application team may have an SLA of 1ms, but when storage latency breaches this point the damage is already done, for this application and any others that share the same infrastructure.
Anomaly detection lets these teams get out ahead of potential issues by notifying storage administrators when unusual increases in latency are detected. For example, consider the following example.
Although the storage system latency remains under 1ms for the duration of this window, this scenario is still worth investigating, even if the alarm bells haven’t gone off yet.
The administrator can see that during the same time window 2 weeks ago there was a slight elevation in latency that precedes this much more significant spike. It seems that if things are left unchecked, whatever is causing this hiccup is likely to lead to an SLA breach next week.
Although this incident might seem minor, in financial workloads, even small deviations can have significant consequences. Increased latency can delay transaction processing, affecting trading operations and customer transactions.
To determine the cause of this potential problem, the storage administrator can use Data Infrastructure Insights’ automatic workload contention and infrastructure change analysis to determine and remediate the cause the next working day, rather than waiting for the SLA to be breached and receive an unwelcome midnight callout.
For both the storage teams and the application owners consuming storage services,
the ability to detect and address anomalies in data infrastructure before they lead to incidents is invaluable. Early detection and resolution of anomalies prevent minor issues from becoming major problems, reducing downtime and ensuring smooth operations.
Data Infrastructure Insights, with its robust anomaly detection capabilities, gives storage administrators the tools they need to maintain stability, proactively detect issues that may lead to an SLA breach, and deliver exceptional performance.
If you’re looking to enhance the stability and performance of your financial data infrastructure, you can learn more about NetApp Data Infrastructure Insights as an integral part of your storage manageability and observability.
Joshua is a Principal Technologist within the Cloud Analytics team at NetApp, and has spent many years in the field helping clients achieve their business goals with NetApp technology. He has a service provider background where, prior to his tenure at NetApp, held architecture and service strategy roles within a global systems integrator. His primary focus is on identifying where and how Cloud Analytics can help organizations better meet their service level objectives, cost constraints and business goals in the near term, and more effectively realize their hybrid cloud strategy in the long term.