Intelligent CIO North America Issue 08 | Page 32



With an increased reliance on cloud services , making dedicated management and protection measures necessary , we asked industry experts how IT leaders can ensure better visibility around cloud access in the workplace . To start us off , here ’ s the response from Kunal Agarwal , CEO , Unravel Data .

We ’ ve built our DataOps platform to address cost , performance and reliability concerns , for every cloud platform . It interfaces nicely with governance and security concerns such as those described above . So we discuss these issues with customers all the time .

So this question about cloud access is valuable but it ’ s tactical . It ’ s part of a bigger question : How can IT leaders have better visibility over access to all of an organization ’ s data processing tools and all of its data ? Whether the code and data involved are on-premises , in any cloud , or in transit .
You should always have access to your current and budgeted spending for all your data services . We think of this as a DataOps issue . DataOps is the intersection between data engineering , data processing and operations . It ’ s like DevOps but it starts with data flows first .
When software is in development and being run against test data , or copies of existing data , it can more easily be kept controlled . But when software and data are used in production , you get operational concerns .
These questions gain a sharper edge in the cloud because it ’ s new , so let me answer this directly .
Governance controls need to be implemented and maintained at the technical level in order to meet a wide variety of concerns , including security of code , data and metadata . Metadata leaks , at very large scale , have been hugely embarrassing and costly to some of the companies that have suffered them .
Cost concerns also come up forcefully in the cloud . On-premises , costs are largely sunk – you paid for a certain number of servers , within a deliberative process and any large expenditure is closely scrutinized . The cloud is ‘ pay as you go ’; if you turn that around , it means , ‘ as you go , you pay .’ When you ’ re working at scale , it ’ s easy to run up a six-figure bill in the cloud in just a couple of days , even if you ’ re just testing a new service on production-type volumes of data .
We have careful performance and resource use tracking in the Unravel data platform . As people have moved to cloud , we are adding in explicit cost reporting and controls . You can put a ‘ stop loss ’ on cloud spending for a job – for example , alerting you , or even pausing a job if spending on a workload reaches , say , four figures in cost .
So it may be that moving some workloads to the cloud is exposing the fact that you didn ’ t have the controls needed – which , perhaps , you should have had – on-premises , as well . Take a holistic approach to your entire data and processing estate . ‘ Solve the problem ’ across your organization , rather than playing ‘ whack-a-mole ’ as questions get asked , or problems arise .
You ’ ll sleep better at night and so will your customers and other stakeholders .
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