Whether you’re shifting to a public, private, or hybrid-cloud model, your cloud infrastructure is changing—it’s getting bigger and more complex—fast. Largely thanks to the cloud, which is vast but essential. The cloud provides the storage, processing, security, and analytics that enable your business to quickly deploy and leverage business-critical apps and the big data analytics necessary for your company to thrive. But IT often lacks visibility and control of the cloud.
To take control of your cloud infrastructure, IT should know what’s in the cloud, who’s using it, and how it’s operating. And how do you do that more efficiently? By managing your cloud data:
- 1. See it.
- 2. Understand it.
- 3. Act on it.
- 4. Tame it.
”The amount of data we produce every day is truly mind-boggling. There are 2.5 quintillion bytes of data created each day at our current pace, but that pace is only accelerating with the growth of the Internet of Things (IoT). Over the last two years alone, 90 percent of the data in the world was generated.” —Bernard Marr, Enterprise Tech
Before you can know there is a problem–and take any action to fix the problem, you need to see the data. But when you move to the cloud, you have way more data generated by more systems. How do you bring all that data together so that it means something?
To be able to use the data to provide actionable insights, it should be accurate and normalized into a common data model—an operational data lake. Because what kind of results do you expect to get if the data you’re basing your actions on is wrong? If the stakes are as costly as downtime, can you risk having data you can’t trust?
Before you can take any action to fix a problem, you should be able to understand the problem. But when you move to the cloud, knowing what’s related to what and what’s changed, and detecting performance anomalies can become unwieldy, redundant, and sometimes, even inconsequential. When a problem arises that leads to downtime, every second counts. Now that you have moved to the cloud, how quickly can you identify critical issues/anomalies, and then triage and fix business impacting problems?
Raw data and alerts generated by a vast hybrid cloud infrastructure are overwhelming. Several disparate dashboards of isolated alerts can’t lead you to a speedy resolution. And manually addressing every alert will eat time, and typical analytical tools cannot do enough to isolate the problem to what matters most.
Act on it.
Moving to the cloud means operating in a highly complex IT ecosystem that includes high volumes of shared microservices, containers, and virtual machines as well as network devices and storage units. The ability to detect pending limitations of capacity and to scale proactively has never been more immediate, but where and how to cost-effectively add capacity is often more challenging to pin down with multiple parts of the organization deploying their own cloud-based components. It’s become so easy to deploy new services that you may discover that many of your cloud resources are underused or not used at all. And that means you could be paying for resources you don’t even need.
And making changes in multi-cloud, hybrid-cloud infrastructures without being able to predict the outcomes is risky at best. How can you identify the impact of changes, either your own or those made by other parts of your organization, that affect the health, availability, and risk of your business services and applications when you lack visibility into what’s there and how it works together? More importantly, how do you respond proactively enough to those changes so that you never experience a slow-down or outage?
When you can see, understand, and act on your cloud infrastructure, you have control of your clouds. ScienceLogic SL1 has the cloud monitoring tools that can help you get that control you need to tame your clouds. SL1 is a unified IT operations platform that gives you visibility across your entire IT environment — running in your datacenters and multiple clouds. SL1 collects and stores all your big data in a clean and normalized data lake, bringing context and allowing you to see how each component works together to support your application and business services. You can see what’s being used, and by whom, so you can optimize your cloud resources. SL1 also helps you integrate and share data across your entire infrastructure in real time—applying bi-directional integrations to automate manual data and process workflows. You can track, consolidate and move resources, and release any unused resources to keep your cloud costs in check.
And the ScienceLogic SL1 platform is comprehensive for any cloud technology, including some of the broadest coverage in the industry. Beyond network, servers, and operating systems, SL1 covers all major public clouds (AWS, Azure, Google, IBM, and Alliyun) as well as multiple virtualization solutions (VMware, Hyper-V Zen, and KVM), storage arrays, unified communications, video conferencing, and wireless.
With the move to the cloud, infrastructure is more important to the future of business than ever. It’s time to take advantage of everything the cloud has to offer. It’s time to take control of it.