Why Visibility is the Driving Force Behind Hybrid Cloud 

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Agencies need quality operational data.

Federal cloud adoption, driven by the recently updated Cloud Smart strategy, is taking off now more than ever. Rather than a “lift-and-shift” migration to the cloud, federal agencies are increasingly taking an incremental approach, tailoring their cloud transition to accommodate their unique workload criteria and needs. Cloud is for everything, but not everything is for cloud, resulting in a growing number of hybrid and multi-cloud environments within the federal space.

While hybrid and multi-cloud environments can be beneficial, combining legacy systems and newer technologies can create visibility gaps across an agency’s IT ecosystem and lead to service disruption. With highly sensitive workloads that coordinate the well-being and safety of our government and its citizens, this risk is unacceptable. When applications go down, lives could be on the line: For example, agencies need minute-by-minute updates on their personnel stateside and abroad when emergencies happen, or when defense operations are being conducted. 

Agencies should utilize modern tools and approaches that provide a holistic operational picture and ensure always-on availability and reliability in mission-critical services—mitigating threats before there’s any impact. In instances such as the nation’s health care system or tax services, citizens have to be able to reach their information at all times, which means agencies providing that information must guarantee their back-end operational functions are running smoothly.

A service-centric approach to IT operations can help agencies ensure operational readiness, whether deployed in the cloud or already functioning in a hybrid environment. Here’s what that entails: 

Clean Data

The foundation of effective cloud monitoring and management is quality operational data. The incredible amount of data produced by applications is both a boon and a curse for federal IT operations. Bad operational data derived from multiple, disparate sources can pose a serious challenge to effective troubleshooting if it is not aligned, synchronized, standardized and de-duplicated. A clean data lake for operational data becomes a strategic asset for IT operations teams by reducing the noise often generated by employing dozens of niche tools. 


Comprehensive, clean data alone is not enough. It should also provide context to deliver insights, recommendations and, when warranted, automated actions. In today’s complex applications, many elements of infrastructure and application components must work in unison to deliver a single service. Understanding the impact of a single device or component is critical to rapid service restoration. Modern tools can help federal IT teams differentiate between normal occurrences and those that require attention and remediation—and can prioritize according to degree of urgency. Contextualized data provides IT teams the insight necessary to act quickly and efficiently, ultimately reducing the duration and impact of a service disruption.


Beyond streamlining disruption response, context promotes a service-centric approach by capturing real-time, operational data and mapping the dependencies between infrastructure components, and between those components and the applications they support. This, in turn, provides a blueprint for tracing the root cause of failures and pinpointing how infrastructure problems affect application performance.

With that blueprint established, IT teams can identify service impact, visualize and isolate root causes and initiate automated tasks to ensure availability. Automating complex processes—or actively expanding automation across the entire IT infrastructure to predict and resolve issues faster—is the premise of the Artificial Intelligence for IT Operations (AIOps) concept. 

The transition from traditional IT operations to machine-speed AIOps accelerates the sorting of operational data and optimizes and remediates IT problems, promoting better mission outcomes. With clean and contextualized data, opportunities for automation can be identified and implemented with confidence and significantly minimize disruption or avoid it altogether. 

When these key actions are taken, federal agencies can achieve visibility across mission components that enable proactive decision-making and clear-sighted action. The result? A return on investment, enhanced security and improved service delivery to the American people. 

Lee D. Koepping is principal solutions architect at ScienceLogic.