Flying blind is never a practical approach. Unfortunately, we’ve seen many companies attempt their cloud migration planning without all the data and insights they need. They may collect some data to determine the server size, storage, and network bandwidth they’ll need for their current workloads. They may even explore pricing plans and compare on-premises vs. cloud-based solutions. But without a deep, comprehensive analysis, much of it is guesswork. What should result in significant cost savings at low risk turns out to be the opposite. In fact, our analysis shows that companies migrating to the cloud without leveraging all the right analytics spend 48% more than necessary (more on this is in the infographic below).
There are a lot of questions you’ll need to address throughout your cloud journey, including:
- Which cloud vendor is right for me and how much will it cost?
- What are all the applications we have and how are they connected?
- Which applications should I move to the cloud and in what order should I move them?
- Which cloud configuration is best for us?
- How do I control our cloud costs?
- How can I ensure optimal performance of our cloud?
- How can I accurately plan capacity?
Answering questions such as these requires deep insights into your IT infrastructure and available cloud options. There are two paths to getting this data: the easy way and the hard way.
Getting the Data: The Easy Way and the Hard Way
The “hard way” requires the manual collection of data over long time periods, followed by in-depth analysis and trial-and-error. This is how many IT managers migrate to the cloud, dipping their toes into the water slowly and experimenting with non-critical infrastructure first. Manual analysis, however, is time-consuming, tedious, and inaccurate – and therefore, costly. Errors you make or insights that you miss through manual analysis may cause you to inadvertently make cloud decisions that are not right for your organization and can have long-term cost, performance, and resource consequences. A manual approach to cloud migration assessment and planning typically takes at least (and usually more) than 24 weeks.
The “easy way” is to leverage automated data analysis. For example, only through automated data analysis can you capture a clear, detailed picture of your infrastructure performance profile, from slow periods through peak usage, and then benchmark all available cloud options to understand how each of your workloads will behave on particular instances when migrated, as well as project storage and network usage requirements. Crunching these millions of data points manually is nearly impossible, so critical analytics necessary for making precise cloud decisions will be missed with a manual approach. Automated data analysis is not only more accurate – it’s also faster. An automated analytics approach to cloud migration planning typically takes just 10 weeks from beginning to end.
(Learn more here about the automated analytics the Cloudamize cloud computing analytics platform provides).
Infographic: Why You Need to Automate Your Cloud Decision Making
Without the deep insights that only automated data analysis can provide, you’re flying blind into the cloud. Automated analytics sort through millions of data points to ensure you make data-driven decisions and avoid costly mistakes, which is why it's so essential for succesful cloud migration and ongoing cloud cost management. But you don’t have to simply take our word for it. We analyzed 5,777 servers at more than 20 companies migrating their cloud infrastructure to Amazon Web Services and found they could have saved $14 million if they had greater analysis prior to migrating. Check out the results in the following infographic.