Picture this: you’ve popped into your local grocery store for a box of breakfast cereal. Upon finding the cereal aisle, you’re confronted with a dizzying array of choices––sweet, savory, name brand, store brand, fruity, chocolate, honey nut, whole grain, and on and on the possibilities go. In the end, overwhelmed by the options, you settle for what you know, even if it’s not the best choice you could make.
Sound familiar?
In modern society, we like to think that having more choices is always a good thing. And while there is some truth to this, making too many choices at once is overwhelming and exhausting.
This is especially true when it comes to cloud migration planning. From choosing between public cloud platforms, to VMware-on-Cloud vs. Cloud Native virtualization, to Bring-your-own vs. License included, there is no shortage of choices to make when planning a migration to the cloud.
The problem is that without adequate planning and weighing all your options, you will likely end up over-paying for cloud storage and services you don’t need. Sifting through all possible cloud configurations is necessary to maximize savings in the cloud.
Artificial intelligence (AI) in cloud migration planning does this modeling for you, running through all available configurations to identify the most cost-effective option in minutes. AI can accelerate and simplify cloud migration decisions in each step of the planning process.
Stage 1: Gathering
The first step of any cloud migration is data gathering. Understanding your current environment is necessary to understand what is already working and where you can increase capacity or decrease costs. Information on asset inventory, capacity, and performance are critical data points to collect.
Traditional data gathering methods tend to be quite invasive. Typically, you would need to get security clearance or perform a security audit on the cloud cost modeling software. Next, the software would install agents on all bare metal servers and VMware virtual hosts in your data center, or on the cloud for cloud-to-cloud migrations.
Finally, you would wait for several weeks while the installed agents collect the inventory and capacity information. This process involves:
- Enumerating and discovering servers both physical and virtual
- Determining which workloads belong to which physical hosts
- Application inventory
- Network mapping
- Performance monitoring
As you can see, this process is long and arduous. It also requires you to share all your data with a third-party software, and so can be risky and invasive. This is a particular problem for companies that deal with sensitive customer information (i.e. health centers, government agencies, etc.).
Akasia Universal Translator offers an alternative, non-invasive option for collecting data. All data centers have active monitoring tools that are already running, which have been pre-approved and vetted for acceptable security.
Because of this, Akasia Universal Translator is designed to use the tools that already exist in the data center and import that information into our cloud cost modeling software, Akasia Infrastructure Modeler. Akasia Universal Translator is compatible with pre-existing tools such as vCenter, Rvtools, SCOM, CMDBs, and Cloudwatch.
Non-invasive data gathering is made easy with Akasia Universal Translator.
Stage 2: Ingestion
Once data has been gathered, the next step in the cloud migration planning process is exporting this data from the monitoring tools and importing into your cloud modeling software. The use of common monitoring tools can alleviate security concerns and expedite data gathering by eliminating the monitoring time period.
This can present a problem: converting data to a format that the cloud cost modeling solution can ingest.
Normalizing and transforming data into something a cloud cost modeling software can import is no easy task.
Akasia Universal Translator solves this problem by using AI to automatically learn the translation between any source file produced by any monitoring solution used in the data center. It maps source fields to target fields automatically and self-learns how to map fields from all customers and their monitoring tools.
Machine learning applies its field mapping knowledge across the entire Akasia customer base, which enhances customer experience. It can save weeks or even months of time per client or partner, reducing the process to only days or in some cases, hours.
For added security, Akasia Universal Translator offers the ability to optionally anonymize the source data prior to upload into Akasia’s cloud assessment software.
Stage 3: Cost modeling
Once all necessary data has been gathered, the final step in cloud migration planning is cost modeling.
Modeling potential cloud environments by hand is time-consuming, painstaking, and in some cases impossible. With over a million configurations available, utilizing a reliable cloud modeling AI solution is essential.
That’s why Akasia Cloud exists—to take the guesswork out of cloud migrations and help you plan the most cost-effective lift-and-shift workload migration.
Akasia makes cloud cost optimization and migration decision-making easy by enabling cost comparisons between:
- All major cloud platforms: AWS, Azure, GCP, IBM Cloud and Oracle Cloud
- VMware-on-Cloud vs Cloud Native virtualization
- On-Premises vs Cloud
- As-is vs Right-sized infrastructure
- Always-On vs Pause-and-Resume infrastructure
- BYOL vs License Included
Akasia Infrastructure Modeler provides cost planning for lift-and-shift migrations from one on-premises or cloud environment to another. It discovers on-premise resources and provides equivalent and right-sized cloud templates in minutes. Akasia’s automatically generated reports provide a complete cloud bill of materials and costs that form a starting point for lift and shift migrations.
Akasia is unique because of its easy to use models for on-premises to cloud or cloud to cloud migration planning, highly sophisticated VM and resource mapping algorithms, and unbiased cost comparison of the full stack of cloud services beyond just VMs. Akasia Infrastructure Modeler is road tested and proven to save our clients time and money, with over 1.5 million customer VMs modeled.
Conclusions
The first step in cloud migration is planning, and the first part of planning is always gathering asset inventory data.
Gathering accurate asset inventory dat takes a long time, particularly with traditional agent-based solutions which are often invasive and have serious privacy concerns.
Akasia Universal Translator offers an alternative solution that leverages data that has already been collected by existing monitoring solutions, including vCenter, RVtools, and Cloudwatch.
AI-based tools can transform and normalize data suitable for ingestion by cloud migration planning tools, expediting and therefore shortening the entire cloud migration planning process by weeks or months.
You can learn more about Akasia Infrastructure Modeler in our comprehensive whitepaper and on our website. Contact us here.
