One of the most prominent challenges our customers encounter revolves around understanding and managing their cloud expenses. This issue stems from inadequate visibility and intricate cost attribution, resulting in user confusion. While the cloud provides scalability and flexibility, it also presents new challenges, including limited resource visibility  into resource usage.

In a world where workloads constantly scale up and down, and cloud billing occurs hourly in units of milliseconds, effectively analyzing, forecasting, and optimizing your cloud environment based on daily spend is nearly impossible.

To address these challenges, we are thrilled to announce the launch of our new feature – “Hourly Granularity,” into cloud cost analysis of AWS data. This feature provides cloud users with access to hourly usage graphically, offering enhanced cost visibility, cost allocation, and predictive analysis.

The Hourly Granularity is set to revolutionize cloud visibility, offering businesses enriched monitoring capabilities, real-time insights, and resource optimization. An exceptional aspect of nOps' Hourly Granularity is its capacity to monitor costs on an hourly basis within a 30-day timeframe, contrasting with the traditional 14-day period on AWS. This expanded scope offers a richer and more comprehensive comprehension of your expenses, greatly improving your ability to monitor costs astutely and strategize effectively.

Moreover, nOps' "Cost Allocation" feature empowers users to establish filters that significantly enhance the efficiency of tracking various categories, far surpassing the manual approach. For instance, with specified filters, you can skillfully analyze the distinct services contributing to expenditures. Furthermore, the integration of "Cloud Cost Analysis" allows you to interactively view real-time costs directly on the nOps dashboard, delivering unparalleled insights.

To efficiently monitor costs on an hourly basis and allocate your cloud costs across suitable business units in nOps, see nOps Business Contexts

In addition, addressing underutilization stands as a paramount challenge at nOps. Given AWS' billing model, commitments are allocated in hourly segments, rendering a daily cost overview insufficient for grasping the dynamic commitment patterns that shift by the hour. By adopting an hourly resolution, users gain a magnified perspective into their resources, allowing for a more insightful analysis.

The visual depicts the "Daily View" of resource utilization spanning a two-day timeframe. The graph portrays a notably steady and elevated usage level, implying the feasibility of opting for a higher usage limit. However, it's essential to note that this portrayal does not precisely mirror the genuine usage pattern.

Whereas this visual depiction illustrates the hourly distribution of resource usage over the same two-day timeframe. The graphical representation vividly underscores the irregular patterns characterizing the usage trend. Opting for the elevated usage threshold recommended by the daily overview may lead to incurring avoidable cloud expenses during intervals of notably diminished usage that falls below the prescribed limit.

With an hourly perspective, gaining a comprehensive grasp of your overall EC2 usage and its hourly fluctuations becomes notably simpler. Consider this scenario: under the daily view, if a user commits to covering usage costs at a $2.75 per hour rate and later observes a decrease to $1.50 per hour, they remain bound by the higher rate, even during periods of lower usage. In contrast, the hourly view offers a finer understanding of resource consumption, leading to informed decisions and substantial savings.

The Hourly granularity serves as a foundation for data-driven decision-making, fostering enhancements in both performance and cost-effectiveness. This method ensures that each choice is rooted in a comprehensive understanding of the organization's financial well-being.
It empowers organizations with the precision to forecast expenditures, enabling seamless adoption of FinOps, curbing cloud waste, and fostering alignment between procurement and engineering teams.

It also functions as a robust troubleshooting tool for engineers, granting them the ability to delve into service usage, performance, cost allocation, and hourly-based cost concerns. It facilitates the identification of hourly resource usage cycles, thereby assisting in well-informed determinations about when to activate or pause resources based on usage patterns.

To read to know about how it works, click here. Try nOps Business Contexts today! 

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