It’s indisputable, new data-driven applications are moving to, or starting life running in the cloud. The increasing automation and resilience of current cloud infrastructure is an ideal environment for running modern data pipelines. For many companies and institutions, their cloud first strategy is becoming a cloud only strategy.
Native online business’ such as Netflix as well as mainstream Enterprises such as Capital One have multi $Billion valuations and almost no physical data centers. Public cloud providers will account for over 60% of all capital expenditures on cloud infrastructure – disks, CPUs, network switches and the like. Given this momentum, there is increased pressure on IT teams to prove that they are getting the most of their cloud and big data investments.
Against this backdrop Unravel Introduces the Industry’s First AI-Powered Cloud Platform Operations and Workload Migration Solution for Data Applications, delivering new AI-powered and Unified performance optimization for planning, migrating, and managing modern data applications on the AWS, Azure and Google Cloud Platforms.
Some of the new capabilities that IT teams will gain from this latest release include:
Unified management of the full big data stack on all deployment platforms – Unravel Cloud Migration covers AWS, Azure and Google clouds, as well as on-premises, hybrid environments and multi-cloud settings. Customers get AI-powered troubleshooting, auto-tuning and automated remediation of failures and slowdowns with the same user interface.
Full stack visibility – Unravel uses automation to provide detailed reports and metrics on app usage, performance, cost and chargebacks in the cloud.
Recommendations for the best apps to migrate – Unravel baselines on-premises performance of the full big data stack and uses AI to identify the best app candidates for migration to cloud. Organizations can avoid migrating apps that aren’t ideal for the cloud and having to repatriate them later.
Mapping on-premises infrastructure to cloud server instances – Unravel helps customers choose cloud instance types for their migration based on three strategies:
- Lift and shift – A one-to-one mapping from physical to virtual servers ensures that a cloud deployment will have the same (or more) resources available. This minimizes any risks associated with migrating to the cloud.
- Cost reduction – Provides the most cost-effective instance recommendations based on detailed dependency understanding for minimizing wasted capacity and over provisioning.
- Workload fit – Takes into account data collected over time from the on-premises environment, making recommendations for instance types based on the actual workload of applications running in a data center. These recommendations will be based on the VCore, memory, and storage requirements of a customer’s typical runtime environment.
Cloud capacity planning and chargeback reporting – Unravel can predict cloud storage requirements up to six months out and can provide a detailed accounting of resource consumption and chargeback by user, department or other criteria.
Migration validation – Unravel can provide a before and after assessment of cloud applications by comparing on-premises performance and resource consumption to the same metrics in the cloud, thereby validating the relative success of the migration.
All indications point to a massive shift in data deployments to the cloud, but there are too many unknowns around cost, visibility and migration that have prevented this transition to the cloud from occurring more quickly.
We are incredibly proud of this latest release and the value we believe it can deliver as organisations either begin their cloud journey for their modern data applications or look to optimize performance and cost efficiencies for those data workloads already operating in the cloud.
Unravel is available today for a full-featured 30-day free trial on the Azure Marketplace and the AWS Marketplace. See it for yourself. Or come visit us this week at AWS Summit Santa Clara and at the Strata Data Conference in San Francisco.