When it comes to cloud migration, an organization can reap multiple benefits such as avoiding the overhead of IT infra management, auto-scalability, flexibility, data centricity, security, etc.. However, as it is said that every coin has two sides, migration to the cloud also comes with certain challenges and it is always important to build a challenge overcoming strategy.
In this blog, we have tried to highlight the most common, but high-priority challenges that we have experienced while discussing and assisting our clients during data migration to the cloud.
Challenge 1: Right cloud provider (AWS/ GCP/ Azure/ Snowflake, etc.) selection
The belief that every cloud provider is going to offer a similar kind of service is wrong, therefore selection of right cloud providers often leave IT leaders and CXOs stuck at the first hurdle of digital transformation.
Budget (E.g.: migration cost and management of the future state environment) often plays a key role in formulating any decision. However, companies should also consider their primary objective behind moving to the cloud.
Different businesses have different sets of requirements and have a unique justification for adopting cloud. The key for choosing the right cloud provider, requires a defined selection and procurement process weighted towards a company’s unique set of goals, circumstances and dependencies.
Sometimes, companies may feel that their existing systems are not cloud ready and the main challenge is to connect legacy systems with newer applications that run in the cloud. Therefore, it is very important for the company to choose a vendor that provides the necessary services to support a company’s hybrid environment.
Security, compliance, architecture, manageability, service levels, support and cost are all critical factors to consider before choosing a cloud provider. However, it’s important that the partnered vendor also understands the objective of the company, as well as the motive behind their decision to move to the cloud. Without the right combination of technical expertise and services excellence, the partnership will not lead to successful cloud migration. Therefore, the alignment of the company’s goals and a vendor’s services plays a critical part of the cloud provider’s decision making process.
Challenge 2: Assessing current IT ecosystem
Any change/s in the existing IT ecosystem demands thorough discovery and analysis of current infrastructures, that forms the most challenging part of any cloud migration project. It takes a good amount of time to uncover issues, document findings and turn them into actionable insight, especially for organizations that spread their infrastructure across multiple data centers or teams. Yet, many organizations rely on manual processes to assess their current environment, which often leads to further delays and potential bottlenecks.
We always recommend that any cloud migration project should start with an Automatic assessment and analysis of on-premise / current IT ecosystem (EDW) along with workload profiles (Datametica has its own product – Eagle for performing the assessment).
A key part of this assessment is to figure out ‘what talks to what’, “knock-on effect” systems can potentially have on one another, segregate different lines of business access pattern, gap analysis and risk, if any. Company’s often fall victim to this domino effect of incompatibility, causing them to come unstuck after moving the first app to the cloud. Workload intelligence, access pattern, dependency mapping, gap analysis, data processing, etc.; adds critical insight to the decision-making process, and significantly reduces the possibility of missing dependencies during data migration to the cloud.
Challenge 3: What to modernize and what to leave behind?
Not every application and data is the candidate for the cloud migration. The prioritization of what to move and when, is very crucial to a successful cloud migration. The best applications for early migration are those with least dependencies, which can assist in dealing with unforeseeable problems while the risks are low. It also provides valuable learning and confidence before tackling more complex workloads in the future.
Also, companies should consider the impact of migration on the overall IT ecosystem and different departments. Certain use cases are more compatible with the cloud than others, especially those with variable usage patterns. Hence, it’s important to align business goals with the benefits that the data migration to the cloud brings – such as faster and frequent application releases, flexible auto-scaling, high data availability, data access, innovations, etc.
Prioritizing the application migration based on the usage pattern and dependencies could assist companies leverage numerous advantages offered in the cloud.
Challenge 4: Data security and staying compliant during the migration
Data security risk always has a greater impact on business. If data is lost, leaked, or exposed to a cyber-attack during migration it could cause serious disruption for any business. Certain companies are bound by law to protect personal customer data, concerns around IT governance and compliance which makes the migration process seem deeply unattractive for them.
A secure point-to-point migration ensures that a company’s data is transferred via a preferred routable path (such as VPN Tunnel and Interconnect) and is protected behind a firewall at all times. This ensures that the company’s personal data is not visible to any third party or lost during the migration, which eliminates the potential for non-compliance during the move.
Challenge 5: Automation capabilities
Automation is critical to a successful cloud migration both during the initial phase and ongoing cloud optimization of the environment. Efficiency and productivity are the primary motives behind automating the cloud migration process, which in turn introduces a level of consistency and repeatability unmatched by manual processes. It is always recommended that organizations should prefer – automate compatibility testing, since the cloud allows multiple data sets and applications to be tested and remediated simultaneously. Introduction of automation in cloud migration process, not only reduces migration duration but also lowers the cost of the individual workload. In addition, post cloud migration auto-validation of business processes is also crucial, to ensure that future state architecture and workloads are producing the outcomes similar to on-prem / current infra.
Conclusion
Although it can be challenging, a proper strategy can help you move to the Cloud smoothly. The whole process of migration to the cloud requires rigorous planning and impeccable expertise for successful execution. You need to ensure safe and secure cloud migration by leveraging the deep experience and skill set of cloud migration service provider like Datametica.
Contact us to simplify and accelerate migration of your workloads to the Cloud without risking your data and applications.
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About Datametica
A Global Leader in Data Warehouse Modernization & Migration. We empower businesses by migrating their Data/Workload/ETL/Analytics to the Cloud by leveraging Automation.