Resource Management in Cloud Computing
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Did you know that by 2020, 83% of all enterprise workloads will live entirely in the cloud?
To say that the market for cloud services is growing fast is an understatement. According to Gartner, enterprise IT spend on cloud services is accelerating faster than investments made for traditional, non-cloud IT services. The market research firm projects that a full 28% of spending in key enterprise IT markets will move to the cloud by 2022—up from 19% in 2018.
Companies of all sizes are embracing cloud resources management as a stepping stone in their digital transformation. And while a cloud migration is a great step indeed, it’s only the beginning. To really push the value of cloud computing enough to produce bottom line results, you’ll need to pay special attention to the way you handle resources within your cloud ecosystem.
Resource Management In Cloud Computing
Resource management has some of the highest potential for generating ROI through optimization, and as such, should be a focal point of your cloud strategy. This applies to issues like capacity planning:
- How much traffic can your server support?
- Are there any system or application bottlenecks that restrict performance?
- And how does your provider account for unexpected (or planned) surges in server load?
Keep these issues in mind as you choose how many servers to deploy. If you have a large number of shared resources, you might be tempted to deploy extensive or redundant servers to prevent congestion, but with each investment, your capital expenditures rise.
Balance your investment against your projected need and make sure your provider can configure your servers to accommodate your cloud resources. Some companies find that more extensive investments in Cloud Database Management Systems (CDMS) provide the flexibility they need to scale, while others prefer to operate with a leaner approach.
Benefits of Cloud Resource Management: Get Visibility Into Cloud Assets
As we mentioned, cloud usage is nothing unique, even when talking in terms of infrastructure. In fact, more than 77% of enterprises use it in that way, as noted by this recent IDG cloud computing study from 2018. But while many companies are quick to jump on board with the cloud, fewer take the time to consider how their new system of cloud and on-premise architecture will work together.
After all, you can’t manage cloud resources without knowing what you’re managing and how each asset performs. Underutilized assets may eat away at your budget while operating silently in the background, or end users may activate new services without going through the appropriate IT channels.
This is another area where a CDMS can pay dividends. These virtualization tools offer the visibility and control of traditional databases, tailored specifically for managing assets across the cloud and on-premise architecture. It’s a different way of corralling IT assets that helps operators manage multi-cloud environments, recurring subscriptions, and the resources that live on each server.
And beyond visibility itself, this type of management can help fine-tune your IT costs overall. For example, how did you approach migrating your applications to the cloud environment? If you didn’t assess each application’s dependencies and integrations before the switch, you may be working with a patchwork system of assets that don’t work well together.
Moving to a smarter, more comprehensive system of cloud resource management is the easiest way to clean up these inefficiencies and guarantee that your applications and processes are working together as they should.
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Predictive Management of Cloud Resources
Every cloud provider can adjust and move your resources manually—but this process is time-consuming, requiring detailed logs of historical data that let providers estimate resource usage. Clearly, this type of workload forecasting isn’t easy or tenable at scale.
But with predictive management of cloud resources, you can automate this critical step. Predictive models in enterprise platforms like JDE assess your system’s resource demands over time and come up with pattern-based approaches for scaling. These patterns are applied to your resource allocations and proactively move cloud assets, offering the resource agility and efficiency you’d expect from cloud architecture.
More than anything else, this type of prediction reduces the time you spend managing your cloud assets and cuts the operational costs inherent to forecasting.
Managing Cloud Resources Through Data
The real secret behind the efficiency, agility, and cost-effectiveness of computer resource management lies the wealth of data that comes part and parcel with cloud infrastructure. Primarily, this comes down to using the analytic tools at your disposal to monitor performance, balance loads, and analyze trends to make service more predictable.
And best of all, platforms like JDE that specialize in cloud resource management offer a wealth of analytic and reporting tools that support real time managing of resources.
Take your network performance data, internet speed, or server access time. Each of these metrics provides information on the state of your data centers and computer resources management overall, but it also provides valuable data for bigger picture decision-making.
If you’re expanding your cloud resources and need ancillary servers, for example, this performance data can help you determine whether to move forward with a public, private, or hybrid cloud ecosystem. It’s all contextual data that offers insight into the best way to manage your investments. You may find that it’s worthwhile to leverage more cutting-edge solutions, such as Wide Area Networks (WANs) for more resilient computing resource management.
Getting More Out of the Cloud
Moving forward, we expect the future of cloud resource management to be defined by smarter, more contextually-aware systems that let operators use their data to drive results. Companies should be aware of their options and prioritize systems that let them stay agile and adaptable as they grow. This flexibility is a crucial part of any company’s digital transformation, cloud or not. But when dealing with optimizations based around cloud resources, this adaptability is the most important piece of the puzzle.