Migration to the Cloud: A 3-Step Guide for Enterprises

Earlier this year, Gartner published a detailed research report on migration to the cloud. By the end of 2020, over 36% of all enterprises globally are likely to operate over half their transactional systems over the cloud. The report also suggested that – over the next three years, 44.6 percent of smaller organizations along with 37.7 percent of midsize and 40.4 percent of larger organizations plan to migrate to the cloud.

According to a study by Deloitte, the top three reasons to move to the cloud include security, data modernization and cost. From a sectoral perspective, automotive, insurance and financial services, hospitality, manufacturing and healthcare are some of the key industries that are expected to migrate to the cloud.

While the current pandemic has certainly accelerated the migration from on-premise systems to cloud computing, a rapid shift has been underway for a few years now.

Broadly speaking, there are five key reasons why the shift to the cloud is imminent:

1. Scalability: The biggest advantage of cloud computing is that it is flexible and scalable. As an enterprise grows, it is easy to scale up infrastructure requirements with reduced complexity. Additionally, with the cloud is it easy to enable autoscaling. With autoscaling, one can automatically increase or decrease the computational resources delivered to a cloud workload based on need.
2. Accelerated deployment: DevOps practices, software and application deployment, even migration of data – all become easier with the cloud. It is also important to plan and design an automated, containerized deployment process, instead of a manual process.
3. Higher levels of security and disaster recovery: One of the biggest advantages of cloud computing is automatic and ‘continuously improving’ security upgrades – which is very difficult to implement in traditional on-premise systems. Additionally, modern cloud solutions adhere to a range of compliance standards including HIPAA, SOC, PCI, GDPR, ISO/IEC, to name a fee.
4. Cost control and cost-efficiency: Needless to add, cloud computing converts CAPEX to OPEX, making it easy to justify infrastructure costs as business scales. The PAYG (pay as you go) model wherein an enterprise pays as per compute usage makes it cost efficient. Cloud also makes it easy to add ad-hoc services, as per need.
5. Ease of mobility – across private, public and hybrid clouds: Of course, depending on the nature of software, application, or database, organizations may choose to implement private, public, or hybrid clouds. While hybrid cloud implementations are certainly more complex, implementation of changes to cloud infrastructure strategy is comparatively smoother. Additionally, with cloud containerization, it is easier to move software around more easily between clouds. In short, a software package or “container” becomes portable and can be run across any platform or cloud.

Over the last few years, Indium has helped a range of enterprises migrate to the cloud with a robust, methodical process. In this blog, we share a collection of best practices we’ve learned from these engagements.

At Indium, thanks to our expertise in all cloud environments including Azure, AWS, Google Cloud, IBM Cloud, Oracle Cloud and Digital Ocean, we’re able to suggest the right cloud architecture to suit each specific business case. Clients often look for is – Zero Downtime Migration. At Indium, we’re specialists in making this happen.

Best Practice #1

Plan, Prepare and Design the right cloud solution

Indium worked with one of South East Asia’s leading e-payment companies on a cloud migration project. The primary goal of the client was to move data to the cloud and ensure it was easy to do on-demand and real-time analytics. Indium designed a highly scalable data warehouse ecosystem, to ensure all data storage and processing needs of the clients are met.

We also designed the cloud architecture to include the following:

1. Implemented NiFi to get near-real-time data. For archiving and staging the data efficiently Indium leveraged Operational Data Store (ODS) using Azure BLOB.
2. From Azure Blob, data was bulk loaded to Azure SQL DW to handle huge data traffic from day-to-day transactions that were generated through contactless payment cards.
3. Another layer in the data warehouse was designed to aggregate data so that it can be presented easily to Power BI for data visualization purposes.

While this is a specific example, the point here is that cloud infrastructure was used to power insights from big data. The migration to cloud was planned keeping this requirement in mind. Structured planning and cloud migration strategy is a crucial first step.

Best Practice #2

Understand your approach to scaling and modernization. Choose your pace and transition period carefully

Cloud-based environments are designed to allow enterprises to scale and modernize with flexibility. In addition to cost-savings and change in financials (from CAPEX to OPEX), it is crucial to schedule the pace and migration carefully. Cloud testing must be done in sync with the migration process. At Indium, we’ve designed approaches for various needs and have done Scheduled scaling, Autoscaling, Containerization and even Predictive scaling.

Additionally, it is an important strategic decision to decide among Private, Public and Hybrid Cloud options. Indium has helped numerous clients with choosing the right kind of cloud solution, with a key focus on ensuring the enterprise has complete control over their cloud infrastructure.

Best Practice #3

Robust review process, post-migration

Cloud testing is a crucial part of any migration strategy. Irrespective of whether you’re migrating data or applications, an elaborate test framework is critical. In addition to functional testing, it is absolutely essential to run tests around Multi-tenancy, Autoscaling, Elasticity, Security, Compliance, High Availability and Reliability.

On the functionality side, the review process will differ based on whether it is a migration of an application or data to the cloud. If it is a migration of data management to the cloud, it is critical to take care of controls related to data migration and data security. Additionally, it is important to review processes around data transformation, appropriate Extract, Transform & Load (ETL) processes, the configuration of Data Visualization reports and dashboards for effective BI, etc.

If it is an application, it is critical to run a robust functionality, performance, security testing process on the cloud.

At Indium we understand the key challenges that customers face as they go through this journey of migration.

To alleviate some of the roadblocks we can specifically help in the following areas:

• Identify the right infrastructure requirements for a customer to leverage their data and help in its setup, helping convert CAPEX into OPEX.
• Identify the customer’s business objectives and work backward to identify the right data points to be leveraged to meet them.
• Setup the appropriate Extract, Transform & Load (ETL) processes to get the data points from their source systems into the data platform on the cloud through the right cleansing and transformation steps.
• Provision real-time, near-real-time and batch processes to make the data available at the right time.
• Leverage the data to configure and deploy Data Visualization reports and dashboards for effective BI.
• Implement and integrate machine learning, AI and other predictive models using this data to keep businesses one step ahead.
• Help customers build, deploy and maintain enterprise web and mobile applications on the cloud, thereby reducing their CAPEX.

If you’d like to speak to one of our technology leaders who specialize in cloud migration, reach out to us here: https://www.indium.tech/inquire-now/