IMS Automation: Things To Keep In Mind
IT infrastructure forms the bedrock of an enterprise. The demands placed on the IMS (Infrastructure Management and Security) team are many—to maintain the optimal level for service on a daily basis, reduce disruptions to avoid critical system failures and to enhance the user experience, and respond quickly to any new requests and changes that may arise. However, the ability to respond rapidly is often undermined by the sheer volume of routine tasks that must be undertaken to maintain service standards. Moreover, these can divert much of the effort and resources away from transforming the infrastructure to meet new demands. It is here that automation can play a significant role—routine processes and the maintenance of core assets can be automated, freeing the team to focus on application management, user experience, etc.; thus, reducing the burden on infrastructure management.
Rapidly evolving technology has resulted in multiple technology silos within the enterprises that are complex to manage. For IT to become more profitable, it must be easily accessible, standardized, responsive, and cost-cutting. The means to this end? Again, automation. By automating routine tasks and creating tools to handle exceptions, IT can be made more responsive and agile.
Cloud computing has complicated this mix by introducing new processes and a whole set of new tasks to administer, monitor and provision which are time-consuming and tedious tasks with high scope for human error – yet another area where automation can make an impact. It takes away much of the tedium and prone-to-error aspects of infrastructure management by precisely defining how different routine processes must run. These rules or scripts allow environments and processes to be replicated by a machine, leaving no room for deviation or errors.
Points to keep in mind when automating IMS:
· Study the as-is state of automation and define the end-state. Sometimes, automation tools are implemented one area at a time to keep the process flexible and iterative. Sound in principle, this, however, often results in further silos, with multiple tools that share no common architecture and are difficult to integrate. To avoid this, it is recommended to first precisely define where automation is needed, and how these can be integrated seamlessly. This will offer a coherent image of the end-state while detailing how it can be reached in iterative steps.
· The chosen strategies and automation tools should accommodate future technological changes and evolving business needs.
· The plan for IMS automation should be clearly tied into the business value it delivers. If the benefits derived from automating the configuration and installation of servers, for instance, are no greater than the investment into scripting that feature, business stakeholders are not going to buy into the initiative. In the same way, there is absolutely no value in automating one-off tasks.
Benefits of automation
- Increased productivity: Automating routine, everyday IMS tasks allows the IT team to improve their performance and focus on transformational initiatives that have a high impact. The result—efficiency and productivity gains across IT teams and the enterprise, respectively.
- Cost savings: The automation of everyday tasks necessitates less human intervention and effort, reducing costs.
- Risk mitigation: By reducing human errors, automation mitigates risk, of special importance in today’s highly regulatory environment.
- Documentation availability: Every automated process is precisely scripted and detailed documentation is provided around it; again, a boon when the auditor makes his rounds.
Automation is transforming the IMS landscape, and will continue to do so as technologies evolve. This is precisely why it must be an iterative process, regularly adjusted for environment changes.
While it does offer considerable benefits, not everything needs to be automated. Rather, it depends on the scale of infrastructure and complexity. Additionally, there is no replacement for human skill. Where a tool fails to discover an issue or a glitch, human intervention is required.
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