Not so long ago, many organizations started ‘moving to the cloud’ in a concerted attempt to transform their operations. Today, that term has a completely different connotation, because the ‘cloud’ itself is completely different. It would be erroneous to even refer to the cloud in the singular, as today’s organizations often use a mix of various public and private clouds to support their already existing on-premises systems.
This type of cloud strategy is known as hybrid multicloud, and it is rapidly growing in popularity. According to the recent Nutanix Global Enterprise Cloud Index (ECI) survey, hybrid multicloud remains the dominant deployment model in India, with 44% of companies using it – a figure that surpasses all other countries surveyed. It is the ideal ecosystem to support a cloud-smart approach, which involves using the best IT environment for each application.
With an optimized hybrid multicloud, you get scalability, cost-effectiveness, the ability to deploy across multiple environments in minutes, and an ecosystem that makes the best use of your organization’s most valuable asset – your data. In a scenario where the entire world is in the midst of a data explosion, the cloud gives you access to infinite computing resources and on-demand data storage in a way that on-premises systems simply cannot match in terms of scale.
However, without a proper strategy in place, these benefits will be rendered ineffective, and new challenges will pop up in their place. Here are the top 4 challenges for Indian IT teams according to the aforementioned Nutanix survey when it comes to cloud adoption:
- Data privacy comes first, with 61% of respondents regarding it as a major challenge. Organizations have a responsibility towards their customers to protect all their sensitive data. However, different cloud providers use different IAM frameworks for their access, and not managing it seamlessly across all environments could lead to potential breaches.
- Ransomware protection & data security comes second with 60%. Having to adopt these new cloud technologies into your business can potentially lead to misconfigurations and security gaps. The IBM Cost of Data Breach 2024 indicates that breach data stored in public clouds incurred the highest average data breach cost at $5.17 million.
- Linking data from multiple environments comes third with 49%. In most enterprises, data is still locked in disparate silos. This hinders visibility & reduces productivity for users requiring more agile data.
- Finally, following guidelines on data storage and usage comes fourth with 47%. In 2024, the Indian government issued a variety of regulations with regard to data storage and security across different industries. Each comes with strict rules and timelines, making it a major challenge when having to deal with multiple IT environments. Some frameworks regarding data compliance India introduced this year include the recent telecom regulations and the CSCRF framework for SEBI-regulated entities.
If you noticed, all the aforementioned cloud challenges involve data in some capacity. Therefore, it would be apt to say that a comprehensive data strategy is key to the cloud transformation you are seeking.
A data strategy involves utilizing your resources, talent, and technology to consolidate, organize, analyze & leverage data to drive business decisions and deliver value for your customers. It consists of these 3 main pillars:
- Data governance is the process of defining clear policies and standards to ensure that your data is used in a way that is secure, ethical & compliant with relevant regulations.
- Data architecture is the design blueprint for all the systems & pathways where your data travels. It dictates how your data is collected, stored, processed & maintained.
- Finally, data management is the implementation of the aforementioned frameworks. It is real-time, efficient handling of vast data volumes across diverse systems & environments, ensuring data integrity, accessibility & security throughout.
Ultimately, by aligning your cloud and data strategy, you want to achieve 2 major goals:
So, what is an effective way of creating an alignment between these two strategies? Undertaking the following four steps will help you achieve seamless cloud data integration.
Step 1: Understanding your Data
It is not just understanding your data, but also its disparate nature. Often, you will find data located in various systems not designed to work together, creating data silos. To break these silos, you have to start understanding the context of your data. That comes from getting answers to questions like:
- How is this particular data structured?
- What is its business meaning?
- Who can access it?
- How is it used?
- Where does data reside throughout its lifecycle, from ingestion to deletion?
This context will help you chart out an ideal journey for all your data throughout your cloud environments:
Identify & classify data using consistent labels across environments → Secure it at the appropriate granular level → Track its lineage → Authorize relevant access → Audit access logs throughout the lifecycle
Having these controls right at the outset will help ensure that your data is always protected, validated, and compliant irrespective of where it resides.
Step 2: Understanding your Workload
Understanding your data is merely a stepping stone to figuring out all the myriad ways it is being used and processed in your organization. That comes from understanding all your workloads, referring to a computational task and the computing, storage, and network resources the particular task requires. In the context of cloud environments, VMs, microservices, databases, applications, and nodes are all considered workloads.
Your workloads conduct all kinds of activities with your data, such as data ingestion, data engineering, data warehousing, and data science. You must understand the strain these workloads put on your infrastructure, especially if they are perpetually running. The cloud allows you to leverage its elasticity by deploying ephemeral workloads that dynamically respond to business needs through techniques like cloud bursting and adaptive scaling. This helps you optimize your cloud resources, as you shift your focus from overall resource consumption to actual workload utilization.
Step 3: Break the Silos
Let’s illustrate this step with an example – you’re a car company trying to build a predictive model for vehicle maintenance. Some of the workloads you’ll need for this include:
- Data capturing of real-time vehicle maintenance data
- Data storage for analytical purposes
- Data engineering to create application features
- Data science to construct the entire model
- Data migration to push application back out to the users
Now, if each aspect of this application is located in individual, incompatible data silos, issues will come up both from an efficiency and security aspect. Moreover, large data sets tend to attract more data, applications, and services in a phenomenon called data gravity, which could hamper your organization in terms of latency, non-portability, and costs. More silos can be created through not identifying ideal environments – the cloud adoption India experienced a few years ago saw many organizations taking a ‘public cloud happy approach’, migrating workloads there that weren’t necessarily compatible with the particular ecosystem.
To break all the silos, you must go open source with your cloud strategy. That will alleviate vendor lock-in concerns, leverage community innovation, and ensure that your business success is not tied to any proprietary technology. For example, if you provision each of your clouds with Kubernetes as an abstraction layer, it will enable you to maintain consistent standards across all your clouds.
Step 4: Align with your business goals
After mapping out a silo-free, open-source ecosystem, it is important now to align this consolidated strategy with your business goals. Ultimately, your hybrid multicloud architecture should deliver:
- The flexibility to run modern data analytics workloads anywhere, regardless of where data resides
- The ability to move workloads to the cloud environment of your choice seamlessly, whether it is public or private
- Delivery of self-service analytics to relevant parties
- An oversight platform that unifies metadata, security and governance across all environments
Following all these steps can help bring all of hybrid multicloud’s transformative benefits to your organization:
- Identification & prioritization of your most critical assets
- Ensuring the right data is available to the right people at the right time
- Utilization of data to create better experiences for your customers
- Flexibility & elasticity to handle periods of peak processing without overcommitting otherwise idle resources
- Comprehensive support for your AI & ML-enabled initiatives
- Faster time-to-market for all your applications
However, all these benefits can only be realized by creating that perfect balance between your cloud and data strategies.
