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Introducing HPE InfoSight App Insights: AI-driven workload intelligence
Announcing the release of HPE InfoSight App Insights! HPE InfoSight now features advanced AI-driven workload Intelligence for end-user applications, containers and operating systems deployed on HPE infrastructure.
Traditional tools have domain level visibility
Infrastructure is a means to an end. What users really care about is the health and performance of application deployment on their infrastructure.
Application deployments are becoming increasingly more complex. A large fraction of IT-related performance issues that are dealt with by infrastructure administrators are not really in the infrastructure layer, but in the application layer. However, admins use conventional infrastructure monitoring and observability tools that only give visibility at a domain level – whether it be database, storage, compute, or the network infrastructure domain.
These tools are siloed and don’t provide visibility across domains. According to Forbes blogger Louis Columbus, ninety-three percent of IT leaders say that observability is a foundational part of running a successful enterprise in 2021. Without application context, it is increasingly hard to understand application impact on the performance of infrastructure managed by administrators who must oversee and exonerate storage/compute infrastructure from application performance issues. This creates a need for custom-built scripts to collect performance metrics and configuration information from disparate data sources across domains, such as logs, telemetry, and other sources.
This is a tedious and time-consuming process, necessitating an easier way to establish the relationship between the application and infrastructure entities, as well as the need to correlate the performance analytics across applications and infrastructure.
Visibility into apps and across domains
HPE InfoSight is well known for infrastructure monitoring and cross-stack analytics that provide visibility across both the infrastructure and virtualization layers. Our cross-stack analytics features are extensively used by our customers. These include HPE InfoSight, Cross-Stack Analytics for VMWare, and Cross-Stack Recommendations for VMWare & Storage, and generate approximately 1200 recommendations a month. Predictive analytics for VMWare automatically detects and repairs fixes approximately 700 VMWare issues per month.
App Insights extends visibility even further up the stack – expanding to industry leading applications, including containers, end user applications and operating systems like SAP HANA, Oracle, Microsoft SQL Server, and MongoDB – and combining visibility across a set of domains to deliver a holistic user experience. App Insights analyzes multiple domains, and correlates these key details back to the administrator, with details regarding the business impact.
App Insights paves the way for HPE InfoSight to provide actionable intelligence through insights embedded – within the appropriate business context – into the user’s routine workflow. This will support the user in conducting root cause analysis, decision-making, and taking preventative or recovery actions.
These insights also help prevent application level problems for all users when seen in a peer’s environment anywhere in the HPE InfoSight installed base. This feature is enabled through detection of application level anomalies, expansion of 12 years of predictive support experience by HPE InfoSight, and 5 years of prescriptive recommendations experience in relation to the application layer.
First application out-of-the-gate
The first app out-of-the-gate is for Microsoft SQL Server. The initial release of App Insights provides full stack correlations across application and infrastructure performance analytics to gain insights into potential performance and misconfiguration issues. It also provides end-to-end visibility into the application topology, thereby taking guesswork out of the picture.
The diagram below exemplifies our full stack correlations & performance analytics. Performance analytics provided are related to resource utilization, I/O operations, wait time and application-specific analytics. Topology maps the relationship between application, OS, virtualization, and compute and storage infrastructure components.
By leveraging rich telemetry on a unified dashboard, IT administrators can conduct accelerated root-cause analysis and diagnosis when problems occur, thus fixing app-level problems faster. App Insights will constantly observe performance of applications on infrastructure, and offers insights to ensure optimal application performance for your workloads as well as avoiding common pitfalls or misconfigurations, thus enabling the administrator to run highly performant apps.
Out-of-the-box insights for apps
App Insights can rapidly onboard new applications with advanced analytics, across a broad set of applications, without deep domain expertise. This is possible because we have minimized the proprietary instrumentation for each app by leveraging open source tools, and by building generic anomaly detection models that can detect aberrations for any time series data.
Anomaly detection
Conventional monitoring tools present thousands of metric charts that require the IT administrator to determine the problematic range for each chart; the admin would also need to have enormous amount of domain skill and experience to troubleshoot the root causes of issues. This can often result in the user suffering from alarm fatigue due to the high volume and false positive rate.
All of these reasons prevent our users from quickly triaging issues and doing more strategic and innovative work that is more valuable to their organizations. App Insights pro-actively detects incidents due to application as well as infrastructure anomalous behavior – for example auto-defined high latency – and provides prescriptive recommendations as a set of simple instructions to address issues identified. This guidance includes identifying symptoms, actual problems, and diagnosis. Anomaly detection adapts to changes in business context without manual tuning, and will also detect recurring shifts in historical patterns.
Easy to deploy and use
Easy to follow instructions for deploying HPE InSight App Insights will be available on the InfoSight Portal. In order to use App Insights, you will first need to deploy our software in your datacenter. Watch this video for a guided demo on how to deploy and use App Insights for Microsoft SQL Server.
Sign up for our Tech Preview program
Take advantage of an exclusive opportunity to shape the roadmap for App Insights! App Insights for Microsoft SQL Server will be available for HPE Storage and HPE Server customers who use the following HPE products: HPE ProLiant, HPE Synergy, HPE Alletra 6000, HPE Alletra 9000, HPE Nimble Storage dHCI, HPE Primera, and HPE 3PAR.
If you are interested in participating in the Tech Preview program, please email is-appinsights-preview@hpe.com to request your personal invitation.
To learn more about other exciting news from HPE announced on September 28th, please check out:
- Press release: HPE GreenLake edge to cloud platform powers data modernization with breakthrough analytics and data protection cloud services
- Newsroom Blog: New HPE GreenLake cloud services for data protection tackle cyberthreats and ransomware, Tom Black SVP & GM, HPE Storage
- Around the Storage Block blog: Introducing HPE CloudPhysics: Data-driven insights for smarter IT decisions
- Around the Storage Block blog: The next generation of data protection services: HPE Backup and Recovery Service
- Around the Storage Block blog: Industry-leading AIOPS for infrastructure extends its edge with App Insights
Meet Storage Experts blogger Anshul Madan
Anshul is passionate about reflecting the voice of the customer, and building valuable products that delight those users. He is a Product Manager for HPE InfoSight where he is responsible for workload insights and other forward-looking AIOps features. Anshul enjoys reading, yoga, spending time outdoors, and playing sports. You can connect with Anshul on LinkedIn.
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