By now, we all know that both the volume and importance of data are growing, with the sheer amount that needs to be managed and protected higher than it’s ever been before, leading to ever greater management and protection costs. On top of that is the fact that enterprises aren’t experiencing data growth in a homogeneous way, and looking back over the years, there have been a number of enterprise IT paradigm shifts that have had a defining impact on how organisations collect, store, and manage data today, says Stuart Abbott, area vice president & general manager of UK & Ireland at Commvault.
From mainframes to client-server architectures to virtualisation, cloud containers, microservices and SaaS, organisations everywhere operate siloed enterprise data estates that are fragmented and inefficient to manage. In addition to data growth and fragmentation, the importance of data to enterprises today brings about greater risks when the data can be potentially compromised.
However, despite the fact that enterprises are in a constant race to keep up with the pace of innovation, the need to continuously add and protect newer workloads should not be a challenge in itself. Indeed, data protection should be an easy and intuitive process that aligns with the arrival and implementation of new and innovative technologies.
With this in mind, how can organisations address the lack of efficiency, greater risk, and higher costs associated with enterprise data management?
Currently, increasing operational efficiency is key to any organisation that’s trying to do more with less and making sure that as they do so, they are not introducing the additional burden that comes with technical debt.
In this scenario, automation technologies are having a growing impact on the ability of IT teams to deliver seamless integration and workload protection across their technology stack. From a security response and recovery perspective, for instance, having a comprehensive view of the IT estate, including data protection environments, are key requirements, especially as data-protected copies now serve as an ‘insurance policy’ for enterprises to recover from no matter what the crisis.
Building upon the power of automation to increase efficiency, there are also a number of use cases where automation can be used to help mitigate risks. A prime example of this is Disaster Recovery Orchestration (DRO) and the role of automated compliance reporting.
Ideally, DRO will make use of a runbook a detailed procedural guide designed to execute both planned and unplanned failovers, as well as failback operations. The primary advantage of this approach is its potential to significantly reduce the risk of data loss and downtime, while it also mitigates the risk of human error a common occurrence when executing complex manual processes.
In practical terms, a Disaster Recovery runbook is used so that the steps required to execute failover and failback operations can be automated. Initiating this process via a one-click failover button ensures the necessary steps are executed in sequence.
In the case of a planned failover, the process begins by powering off the production Virtual Machine (VM). Next, an incremental backup of the production VM is executed, followed by a replication process to ensure the Disaster Recovery VM is synchronised with the production VM. Subsequently, any further replication is disabled, and the Disaster Recovery VM is then powered on, executing the planned failover.
However, the process slightly differs for an unplanned failover. Given the unexpected nature of such a scenario, there’s no opportunity to run an incremental backup or synchronise any changes. Despite this, an effective automated system helps to mitigate any potential damage or loss, and as a result, integrating automation with disaster recovery orchestration provides a mechanism for minimising risk and ensuring business continuity, even during unforeseen circumstances.
In the current economic climate, cost reduction is a critical consideration for organisations everywhere, and automation has a significant role to play in delivering meaningful and sustainable savings.
For example, organisations can see considerable benefits by leveraging the power of artificial intelligence (AI) and machine learning (ML) to deliver more efficient and effective use of cloud-based services, such as compute resources.
Similarly, these automation technologies can also be used to reduce Disaster Recovery (DR) costs. And by integrating cloud-native solutions, users can avoid unnecessary expenses often associated with static cloud wastage. This integration also ensures a more streamlined and cost-effective approach to data management.
The advent of cloud technology has undoubtedly introduced an important paradigm shift in how businesses plan and implement their digital transformation strategies. Given the pay-as-you-go model prevalent in cloud services, substantial time and effort are being invested to plan for optimal resource utilisation. Simultaneously, the inherent elasticity of the cloud allows businesses to scale their operations efficiently.
Embracing an approach where automation can be scaled according to need aligns well with this shift. It provides the ability to add new workloads, compute nodes, and then appropriately size them based on the growth of the workload. This alignment represents another way businesses can ensure they’re getting the most value from their cloud usage, and by definition, creating a more cost-effective and efficient data management strategy.
Ultimately, the growing complexity of enterprise data management can be significantly mitigated through the strategic application of automation, which can act as a route to enhanced efficiency. From fostering seamless IT ecosystem integration to ensuring automated workload protection, automation contributes significantly to risk reduction through disaster recovery (DR) orchestration, automated compliance reporting, and the automated identification and remediation of sensitive data. Organisations that successfully embrace these capabilities will be ideally positioned to ensure they deliver an efficient and cost-effective data management and protection strategy for the long term.
The author is Stuart Abbott, area vice president & general manager of UK & Ireland at Commvault.
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