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The world is not a binary place, and organizations can't really choose between being simply on-prem or completely on cloud
![](https://www.manageengine.com/itom/spotlight/images/aditya-kammula.png)
Aditya Kammula,
Ecosystem Partner Manager
![](https://www.manageengine.com/itom/spotlight/images/nutanix-logo-black.png)
In our recent ITOM Spotlight discussion with industry experts—featuring Aditiya Kammula, Ecosystem Partner Manager at Nutanix; Gowrisankar C, Director of Product Management at ManageEngine ITOM; and Cyril Emmanuel G, Senior Evangelist at ManageEngine ITOM—the focus was on the evolving landscape of infrastructure and operations to meet business challenges.
The conversation delved into the obstacles organizations face in navigating the complexities of modern applications, databases, and networks across multi-cloud environments. Given below are a few excerpts from the topics discussed.
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The Nutanix paradigm: Architecting the future of application modernization
Navigating the nuances
"The world is not a binary place, and organizations can't really choose between being simply on-premise or completely on cloud," observes Aditiya Kammula.
The onset of the COVID-19 pandemic accelerated the adoption of cloud-native approaches; however, a trend towards normalization was always apparent. Some organizations required immediate scalability through public clouds for their elastic applications, while others needed infrastructure capable of supporting year-round applications and workloads with predictable demands.
Nutanix's key role
This is where Nutanix played a significant role by integrating the convenience of public cloud services into a hybrid platform. Leveraging its expertise in hybrid cloud infrastructure, Nutanix strategically partnered with industry giants like AWS and Azure, creating a unified platform for migrating applications from on-premises data centers to efficient hybrid cloud infrastructures.
Observability in the age of complexity
Traditional tools versus observability
Traditionally, IT administrators would use distinct tools for monitoring stack components. However, as businesses shift to hybrid and multi-cloud environments, the significance of observability for gaining comprehensive insights is becoming increasingly apparent. Relying solely on key performance indicators (KPIs) and metrics is no longer sufficient; instead, business leaders now seek in-depth analysis that extends beyond traditional CPU and memory monitoring.
In this context, observability plays a crucial role by offering comprehensive visibility throughout various layers, spanning from applications to networks. The integration of AI and ML not only enriches observability but also ensures a smooth scaling
The Nutanix paradigm: Architecting the future of application modernization
Navigating the nuances
"The world is not a binary place, and organizations can't really choose between being simply on-premise or completely on cloud," observes Aditiya Kammula.
The onset of the COVID-19 pandemic accelerated the adoption of cloud-native approaches; however, a trend towards normalization was always apparent. Some organizations required immediate scalability through public clouds for their elastic applications, while others needed infrastructure capable of supporting year-round applications and workloads with predictable demands.
Nutanix's key role
This is where Nutanix played a significant role by integrating the convenience of public cloud services into a hybrid platform. Leveraging its expertise in hybrid cloud infrastructure, Nutanix strategically partnered with industry giants like AWS and Azure, creating a unified platform for migrating applications from on-premises data centers to efficient hybrid cloud infrastructures.
Observability in the age of complexity
Traditional tools versus observability
Traditionally, IT administrators would use distinct tools for monitoring stack components. However, as businesses shift to hybrid and multi-cloud environments, the significance of observability for gaining comprehensive insights is becoming increasingly apparent. Relying solely on key performance indicators (KPIs) and metrics is no longer sufficient; instead, business leaders now seek in-depth analysis that extends beyond traditional CPU and memory monitoring.
In this context, observability plays a crucial role by offering comprehensive visibility throughout various layers, spanning from applications to networks. The integration of AI and ML not only enriches observability but also ensures a smooth scaling experience during the shift from conventional servers to containers and microservices.
AI and ML integration
Despite these advancements, traditional monitoring tools often struggle to manage the vast amount of data generated by these changes. This underscores the importance of AI and ML, which are essential for efficiently sifting through extensive data and generating actionable analytics. As a result, observability—which encompasses metrics, events, logs, and traces (MELT)—emerges as a holistic approach that takes center stage.
Furthermore, recent market trends reveal a strategic evolution, with security emerging as a fundamental pillar of observability. This shift underscores the essential role observability plays in not just monitoring, but in fortifying the security posture of modern, complex infrastructures.
AIOps: The backbone of observability
Innovations in AIOps
AI forms the cornerstone of observability, seamlessly integrating advancements like adaptive thresholds to lighten the load of configuring numerous metrics. Utilizing automatic base-lining, a prominent feature of AIOps, plays a crucial role in promptly alerting end users to any breaches in thresholds, thereby reducing the necessity for manual intervention.
A practical use-case
Let's consider a simple use-case where a virtual machine (VM) in Nutanix experiences a drop in memory capacity due to a temporary spike in usage. This can result in cascading failures and cause downtime.
With the help of ManageEngine and Nutanix X-Play (pronounced CrossPlay), you can trigger a webhook when an alert is generated, which interacts with Prism Central to initiate a Playbook to allocate additional resources to the cluster. Without these automated processes, managing a complex IT setup would be much more challenging. Working together, ManageEngine and Nutanix streamline infrastructure management, facilitating seamless scaling across on-premises and cloud environments for modern applications and AI workloads.
From a business standpoint, this integration of ManageEngine and Nutanix delivers crucial visibility across an enterprise's technology stack. This includes understanding the Nutanix clusters supporting each application, thereby creating a comprehensive map from the application front end to infrastructure layers.
Additionally, the support for digital experience monitoring within the Applications Manager module completes the toolkit, empowering organizations to get full-stack visibility over their IT enterprises.
We invite you to watch our full ITOM Spotlight interview to gain further insights and a comprehensive understanding of our discussions with industry experts.