While a cost-effective alternative to traditional IT legacy systems, this alternative is quickly becoming very expensive, with many organizations finding themselves approximately 24% over their allocated cloud budget.
What is the root of this budget overstep? According to the 2020 State of the Cloud Report, 30% of cloud spend budget goes to waste. Three major offenders contribute to this waste (or three prime opportunities to recover some serious cost-saving):
The cloud environment makes it easy for engineers and developers to spin up assets and applications quickly. These assets are spun up in containers, typically for single-purpose use, and are often left running.
There are likely a significant number of these assets out in the cloud for any given organization, eating up the cloud budget. Organizations should seek out and dismantle these assets as part of cost-cutting or cost-optimization efforts.
However, it is notoriously difficult to determine where these assets exist, who owns them, whether they are still in use, and whether it makes sense for organizations to reuse them.
Many organizations are also not aware that underutilized assets are an issue. If there is no targeted attempt to identify and reduce these assets, the complexity surrounding them will only grow, and it will become more challenging to address.
Solution: Cloud Right-Sizing
For an asset to stay within the cloud, the decision-maker needs information on where the asset is located, who owns it, whether teams can reuse it, etc. Unfortunately, this information is locked away in information silos across the organization.
The only way to bring this data together is to apply a graph-based, comprehensive data management platform to the problem to help map these critical components together with ease.
Using this technology and this approach, organizations can get transparency into their assets and easily leverage unique data modeling and integrations capabilities. Decision-makers can accurately identify unused assets, discard them, and develop intelligent allocation plans for cloud resources.
This process should not be a one-time exercise. Through periodic monitoring, decision-makers, armed with up-to-date, connected data, can consistently keep the number of these underutilized assets low to reduce spend now and in the future.
Garbage In, Garbage Out (GIGO) is the concept that flawed or nonsense (garbage) input produces nonsense output. The consensus is that the output from data can only be as accurate as the information entered into it. So how does this relate to cloud spend?
Cloud vendors make it very easy to consume their services, often introducing teaser rates that offer a low-cost way to start. Because of this low barrier to entry, organizations have jumped right in without a proper strategy.
The default strategy by many was and still is the "lift and shift" approach. This approach is where teams lift and shift their legacy systems, databases, and data warehouses straight to the cloud without remediating any inefficiencies. These inefficiencies include duplicate data, unused data, inefficient processes, and poorly designed data models. (Garbage in)
Pushing inefficiencies to expensive cloud platforms en masse without cleaning them up means that the meter runs on these slower, inefficient processes and creates significant costs. It also means that decision-making is based on these inaccurate and inefficient processes (Garbage out).
Solution: Clean Up Garbage
Cleaning up the garbage sounds easier said than done, but the right technology can help simplify the process. Whether loading data into cloud applications before or after, improving data and processing can help reduce cloud spend.
Organizations collect data with the hopes of generating insight and value. However, working with data in the cloud or within cloud-based applications today is quietly discouraged, as cloud consumption-based licensing costs generally run high.
Usage can be complicated to both track and forecast. As a result, bureaucratic processes tend to monitor and lockdown usage of these platforms heavily, and users go to great lengths to avoid using these services.
Ultimately, enterprises spend a great deal on housing data but focus very little on ensuring that data is used and applied throughout the organization.
Solution: Encourage Data Use
By implementing a data platform that doesn't license based on usage, users are encouraged to actively access, work with, and apply data across the organization with no compounding costs involved. By shifting away from a consumption-based model to a record-based model like Process Tempo, organizations can lower their licensing fees and generate more value across the board.
By implementing a graph-based, comprehensive data management platform like Process Tempo, organizations can lower their cloud spend by:
Other benefits of implementing the Process Tempo platform around cloud usage include:
If you're interesting in learning more about how the Process Tempo platform can help lower your cloud spend, click here to schedule a discussion.
Process Tempo is a hybrid cloud, data management & analytics platform that breaks down silos to allow people, processes, and technologies to seamlessly work together. The platform supports a secure, governed, scalable, and high-performance environment for analysts and data scientists while serving as the foundation to deliver insights to all employees. It helps to deliver markedly fast, actionable, and accurate insights, easily incorporates a semantic data layer to curate and recommend information from across the organization, and makes every employee a first-class citizen in contributing insights and feedback to make the organization smarter over time .
Analytics as a Service from Process Tempo is an analytics solution that helps your entire team make intelligent and profitable decisions by leveraging your data without a heavy, upfront investment. By choosing an efficient, fast, and cost-effective path to insights, we can help you beat your competitors in today’s data-driven, competitive digital economy. With Process Tempo as your Managed Service Provider, stakeholders can focus on achieving sustainable and predictable profitable growth. Ready to get started with a Managed Analytics Service? Read more about Process Tempo's Approach to Managed Analytics or schedule an introductory session .
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