As multi-cloud adoption grows, organisations struggle to estimate accurate data and usage needs. But how do you curb cloud waste and overspending?
Multi-cloud promises businesses to eliminate yesterday’s IT legacy, reduce costs and give applications more performance when needed. Companies can select and use resources à la carte. Managed service providers do the tuning and tooling for you. In reality, it achieves just that and more. According to a Flexera report, 89 percent of surveyed organisations have implemented multi-cloud strategies. They also expect cloud spending to grow 29 percent over the next year.
Curb Wasted Cloud Spend
What the cloud offers, it can also take back. And rapid adoption can create chaos and complexity that companies are dying to solve. IT departments overspend their cloud budgets by an average of 13 percent, according to the Flexera study, acting on maximum requirements and not actual needs. This resulted in waste that totaled over $14 billion in the last year alone. Respondents themselves estimated that 32 percent of cloud spending is wasted.
As a result, 59 percent of companies that responded to the Flexera survey have addressed and prioritised multi-cloud optimization for the sixth straight year. Directly behind this initiative is the plan to increase cloud usage and migrate even more workloads. If organisations struggle to control waste and spending, how can they contain it before adding complexity even more?
Multi-Cloud: Accept Fluctuation And Change In The Cloud
There’s a slight problem with calling multi-cloud adoption a “journey.” It implies that one has arrived at one’s destination, but it is not simply a journey. To prevent waste and keep budgets in check, companies must anticipate change. And develop an infrastructure that supports this flexibility. If your adoption of multi-cloud has been piecemeal and de facto, you should take the time to conduct an audit.
The Following Factors Should Be Evaluated
- Workloads in the cloud can be most easily divided into static and dynamic types. They require different types of storage, services, and runtimes. Which ones have to run 24×7? Which can be safely stored in a data lake or solution that doesn’t require ultra-low latency or real-time processing?
- The overall capacity requirements: A buffer makes sense on both sides to have reserves during a burst but not to leave too much unused.
- The licences and resources the organisation pays for and uses: This can be verified as workloads change. Acquiring new services faster than they can be used can create waste.
- The resources that have auto-scaling: is there an option to shut them down as requirements change? This way, organisations don’t pay for services they no longer need when they move workloads.
- The applications and data that need to be mobile, shared, and break free from silos: The most important thing is the ability to move, access, and share data. Watch out for bottlenecks, as some legacy storage solutions can’t quite keep up with the pace of change in the cloud.
Also Read: 5 Benefits Of A Cloud Platform
Multi-Cloud: Choose Flexible Consumption Models
It is, therefore, important to regularly review the strategy for multi-cloud at a high level. Workloads will change, and some may evolve to be better-served on-premises. This is where interoperability can play a critical role, and having the data mobility and resiliency to support these changes is critical. Monthly subscriptions to underutilised or underutilised services are the root cause of overspending. Flexible consumption models are the easiest way to protect budgets when workloads fluctuate. With these, customers only pay for what they use.
As-a-Service models solve one of IT decision makers’ most significant concerns: accurate capacity planning. Case in point: Evergreen//One uses a flexible consumption model for data storage that allows storage to be treated as a utility. Customers pay for what they use, not a fixed amount of storage they may over- or under-use. This has a significant advantage, especially for multi-cloud environments. It reduces complexity between different providers, both on-premises and off-site, with a single subscription to manage multiple cloud services simultaneously. The hybrid cloud has never been so lightweight.
Better Visibility Through Advanced Analytics And AI-Powered Monitoring
The best way to avoid over-provisioning is visibility in the cloud environments. A lack of it is another central problem area in data centres. Here, as-a-service models like Evergreen//One can provide portals with metering and monitoring capabilities to give organisations a clear view of their costs and usage. Effective IT analytics and reporting can also help generate accurate forecasts and eliminate waste. The 24/7 workload that drives up costs would be noticed sooner by companies with better analytics.
However, IT analytics can be challenging, especially when companies have adopted more a la carte cloud services. What is the solution? Governance is a must but can be time-consuming when done manually. IT infrastructure management (ITIM) tools, spend management, and cloud services monitoring can help organisations move closer to an optimised cloud. But here, too, one faces the problem of complexity.
Automation, artificial intelligence (AI), and API-based tools can make this much more accessible. AI can spot anomalies, predict trends in capacity requirements, and anticipate waste before it hits the bottom line. Pure, Pure Storage’s AI-powered monitoring platform, can identify trends that indicate when customers need more or less storage capacity. Here, Pure is made aware of problems before they occur.
Focus On Application Portability, Data Mobility, And Interoperability
An enormous appeal of the multi-cloud model is the avoidance of dependencies, but there are tradeoffs. In particular, where and how organisations store their data can create tradeoffs that hurt their multi-cloud ROI. Ironically, better on-premises storage can be an excellent place to start.
And why? Cloud provider lock-in and silos can come into play at the data layer. Add in platform-specific APIs, and a diverse multi-cloud environment can quickly resemble the legacy environment you came from. Storing duplicate records across multiple clouds sounds like a solution, but it can introduce compliance and governance complexities that nobody wants.
Here, developing an infrastructure for seamless multi-cloud mobility is crucial. A solution like Evergreen//One helps companies reduce data gravity in the cloud with a single interface between vendors, both on-premises and in the cloud. It also eliminates the often costly task of moving data between clouds.
Consolidation Of Data Gravity In The Multi-Cloud
A hybrid solution that mixes public and private cloud environments is one of the wisest investments a company can make, and it doesn’t have to be a messy cost centre. The key is to get a handle on analytics and treat services like utilities. However, the underlying technology should not be underestimated.
Real clouds may defy gravity, but data does not. A good cloud strategy has one primary focus: a unified, modern data solution consolidating the complexity that creates waste. With a modern platform, organisations get a unified subscription across public and on-premises clouds so they can do what they want when they want. That alone can help cut unnecessary costs and eliminate waste without cutting back on critical, strategic resources that can move the business forward. If organisations view multi-cloud adoption as a journey, the first step should be getting their data in order—and the proper storage solution can help them get there.