You have a ton of things to consider before moving your workloads to the Cloud. To get the ball rolling, you can ask your team to find answers to these questions…
- Who is to be contacted in case things run amok? Identify who is in charge of your cloud workload management.
- How does each workload impact business? Assess how crucial they are to business.
- What time of day do the workloads run? Find out if they’re continuous or at specific hours of the day.
- Where do workloads run? See if they’re on the public cloud, private cloud, or in both.
5 Workloads Most Migrated to the Cloud
Here are some key features of these 5 WLs, not in a specific order here.
1. High performance workloads
- These require scientific or technical specialization and strong compute capabilities. Optimized public clouds provide a suitable environment for these complex workloads.
2. Batch workloads
- Think data for sets of cell phone or online transactions, so they run regularly. Economy of scale in public cloud works well, but the best place to execute these workloads depends on business rules, governance, and security regs.
3. Analytical workloads
- Business partners have to benchmark the success of partnerships. Depending on numbers, they make adjustments to further success. In this workload type, data embedded across public websites, private clouds, and the data warehouse gets analyzed.
4. Transactional workloads
- Includes the kind of automation used for things like billing and order processing. These workloads are complex as they reach across various partners’ computing environments. As such, private clouds provide the best environment for them.
5. Database workloads
- This kind of cloud workload affects almost every environment in the data center and the Cloud. Data workloads may be small or massive, requiring a sophisticated approach. Either way, they need to be tailored to the service that uses that data.
All 5 types of workloads impact business when deployed in the Cloud. Why?
It has to do with tools that optimize things. It’s kind of a chicken-or-egg-first type of question. Are workloads moving to the Cloud in droves because tools are accessible there? Or do tools develop first, drawing more and more workloads to the Cloud?
Whichever the case, the impact on business is substantial. Let’s look at one HUGE way in which DataStax Enterprise is impacted. The company “can now build a complete data services infrastructure within days.”
This is not an isolated case — which is why we’ve seen a mass exodus to the Cloud in the past 3 years. In 2015 almost $70 billion was spent on cloud services. But by 2019 we expect more than double that amount to be spent — $141 Billion!
Why Are Cloud Workloads Changing?
The change is largely driven by the need to store more and more data. And the need to access information ever more quickly. With this in mind, three reasons for the change are that…
- On-premise data centers are becoming obsolete
- IoT is growing
- User/workload proximity is changing
On this last point, cloud workloads are moving closer to customers to reduce latency (delay between a user’s request and a cloud service provider’s response). I hear you nodding your head knowingly. It’s a critical point in business–often a deciding factor for customers choosing a cloud provider.
Listen, tens of thousands of people are going crazy over 3 particular Microsoft applications in the Cloud. They are, in a nutshell…
- Office 365
We dug up some stats that suggest the impact of access to these applications in the cloud. We slapped them onto an infographic so you can ponder them for a minute. You’ll need to stop for coffee because some of these numbers will blow your mind.
Why Choose Public Cloud Over Private?
Similar questions were asked in a recent poll conducted by Logic Monitor. They wondered what’s driving public cloud engagement. They found that drivers are…
- Digital transformation
- IT agility
- AI machine learning
A takeaway from that poll is “automate to improve efficiency”. To get even more insight on efficiency…and cloud workload management, keep reading.