[Column] Gerhard Fourie: Streamlining data management in a multi-cloud environment
Many organizations find themselves in a situation where they have multiple clouds to manage. This often results from using numerous Software as a Service (SaaS), Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) solutions.
Moreover, the cloud is fast becoming the preferred method of delivery for an ever-increasing range of services and solutions across the globe. However, a multi-cloud environment vastly increases the complexity of data management, especially when data resides in various clouds both public and private in a number of different countries. To prevent costs from spiraling and loss of control over data, it is essential to reduce this complexity. Streamlining data management is more important than ever in a multi-cloud environment.
More clouds, more complexity
Cloud service providers are rapidly expanding their geographies, driven by requirements for reduced latency and data sovereignty. The result is an increasing number of places where data could potentially be stored. This is further complicated by the various data governance regulations around the world, which have an impact on data management.
The General Data Protection Regulation (GDPR) pushed out by the European Union has had the most significant impact. This regulation has effectively forced organizations to understand what data they have and where they are keeping it. South Africa’s Protection of Personal Information (PoPI) Act has similar requirement.
Essentially people want transparency and accountability from organizations around their personal data. While there are penalties for improper data collection and handling, the reputational damage that could result from data mismanagement is the biggest risk factor. Knowledge is key. Enterprises must have a handle on what data they have, how they should classify it, how sensitive it is, and where they are storing it. Multi-cloud environments compound this challenge, as data can be more difficult to manage when it resides across multiple public and private cloud platforms as well as on premises.
Siloes and security concerns
In an effort to remove data siloes, data management became increasingly centralized. Now, with the emergence of multi-cloud environments, the challenge has once again reared its head. Data has once again become decentralized, and with it the potential for siloes of information. The ease of obtaining cloud solutions means that often business units will simply ‘buy’ a new tool without informing IT. With each department having its own systems and services, there is once again a lack of single view of the customer. These systems may not be part of the organizational backup and recovery strategy, leaving data vulnerable.
Security also remains a challenge. While every cloud is secure, as cloud vendors stake their reputation on delivering secure infrastructure, it is the responsibility of a business to secure the workloads, data and applications that are being stored in the cloud. It is essential to understand where data could be exposed, and ensure that data is protected at rest, in transit and in storage. It is essential to examine infrastructure, solutions and data across the board to ensure that various clouds, their data, are included in management strategy.
Leveraging the benefits of multi-cloud while minimizing the complexity
Multi-cloud offers the flexibility to leverage the strengths of each platform to obtain best of breed tools and resources for every business requirement. However, the nature of multiple solutions inevitably increases complexity. Organizations need to pay attention to integration, data flows, data protection and data management.
Minimizing complexity begins with having a data management strategy in place, and understanding what data you have and where it resides. The second step is to consolidate tools. May organizations have multiple tools for backup, disaster recovery, archiving and so on, and there is often a lot of overlap. A single data management toolset for cloud and on premises data significantly streamlines the work. It also ensures that a single view of data can be obtained for increased speed and efficiency.
A platform that offers automation, orchestration, artificial intelligence and machine learning options can help organizations save both time and effort by replacing manual tasks. In addition, a platform that has native integration with clouds enables a single interface to be used for backup and recovery across the board, saving time and reducing complexity. Finally, any data management solution should incorporate the ability to quickly move large workloads and data volumes, and should support the various tools used to achieve these migrations.
Multi-cloud is the reality of data management infrastructure, and the challenges will only continue to grow as cloud becomes increasingly available and pervasive. Organizations need to simplify and streamline their data management to reduce cost and complexity as well as to manage data regulation and compliance objectives.