AUTOMATION ONLY REALLY WORKS IF YOU HAVE HIGH-QUALITY DATA TO SUPPORT IT .
E X P E R T O P I N I O N hen it comes to
W managed infrastructure services , automation is the buzzword of the day . The problem is that automation only really works if you have high-quality data to support it . If you need to manage many servers , you need to know which operating system is running on each of them .
The quality of your configuration data is not just a limiting factor . It ’ s the limiting factor . IT-managed services are becoming a software-driven business that requires software engineering skills . Unfortunately , it ’ s also exposed to the same risks as software engineering – specifically , ensuring quality at enterprise scale .
Working with hyperscalers is complicated enough . Even though they are fully automated with their own control plane , API and configuration database , most large enterprises have a mix of IT environments that include on-premises or private data centres which have spilt over into the cloud . This hybrid cloud or mixed cloud setup adds another layer of complexity .
So , if you face a mix of cloud and on-prem , modern and legacy , and
You need to take human errors ( and manual data entry ) out of the equation .
Deploying automation requires very accurate and precise information about the actual state of the environment . Hence , it cannot exist without an underlying data strategy that is exhaustive , precise and of very high quality . This requires a mature , large-scale and high-quality approach to data – something along the lines of realtime data updates or a data warehousing or data governance strategy .
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AUTOMATION ONLY REALLY WORKS IF YOU HAVE HIGH-QUALITY DATA TO SUPPORT IT .
automated and manual infrastructure management processes , how can you possibly manage it all effectively ?
The trouble with manual infrastructure management
The right way to address this complexity and need for quality is to invert the equation . Start thinking about delivering infrastructure services as if they are automated – even if the processes are manual . It takes discipline and it requires behaviour change , but it ’ s worth it .
Let ’ s look at an example . If your IT environment includes legacy infrastructure , it will still require manual work . Provisioning a server , connecting it to a network , or plugging cables into a switch may all still be done manually .
However , when you have the process maturity to thoroughly document these manual processes , it makes the legacy process transparent – but that is still not enough .
Overcoming challenges with data
Documenting your infrastructure and processes is a step in the right direction but ensuring that you are capturing the correct data is an entirely different issue .
The simple truth is that if you are managing data about your infrastructure after it is deployed , you cannot fully trust it to implement automation at scale .
Before you call a data centre engineer to plug a new blade into a server rack , document it . All data about the new piece of hardware must be captured accurately at the time of request . This data is stored in a management database which not only documents the current state of your infrastructure but is the first step towards automating future processes .
It also enables traceability , rollback or recovery , and better analysis of infrastructure performance to improve the overall quality and efficiency of managed services . In addition , it may also provide the incentive needed to start working towards eliminating manual processes .
Is it possible to automate legacy infrastructure management ?
Let ’ s be clear – true transformation takes the will to change , and no company will embrace a major change without justification . However , if you can demonstrate the advantages of automation , it will push the enterprise towards automated infrastructure services on demand .
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