L.L. Bean turned to Google Cloud to fulfill its cloud requirements. By modernizing data on, it experienced faster page loads and it was able to access transaction histories more easily. It also focused on value addition instead of infrastructure management. And, it reduced release cycles and rapidly delivered cross-channel services. These collectively improved its overall delivery of agile, cutting-edge customer experience.

Data Modernization with Google Cloud for Success

Many businesses that rely on siloed data find it challenging to make fully informed business decisions, and in turn accelerate growth. They need a unified view of data to be able to draw actionable, meaningful insights that can help them make fact-based decisions that improve operational efficiency, deliver improved services, and identify growth opportunities. In fact, businesses don’t just need unified data. They need quality data that can be stored, managed, scaled and accessed easily.

Google Cloud Platform empowers businesses with flexible and scalable data storage solutions. Some of its tools and features that enable this include:

BigQuery

This is a cost-effective, serverless, and highly scalable multi-cloud data warehouse that provides businesses with agility.

Vertex AI

This enables businesses to build, deploy, and scale ML models on a unified AI platform using pre-trained and custom tooling.

Why should businesses modernize with Google Cloud?

It provides faster time to value with serverless analytics, it lowers TCO (Total Cost of Ownership) by up to 52%, and it ensures data is secure and compliant.

Read this informative post on Cloud Cost Optimization for Better ROI.

Google Cloud Features

Improved Data Management

BigQuery, the serverless data warehouse from Google Cloud Platform (GCP), makes managing, provisioning, and dimensioning infrastructure easier. This frees up resources to focus on the quality of decision-making, operations, products, and services.

Improved Scalability

Storage and computing are decoupled in BigQuery, which improves availability and scalability, and makes it cost-efficient.

Analytics and BI

GCP also improves website analytics by integrating with other GCP and Google products. This helps businesses get a better understanding of the customer’s behavior and journey. The BI Engine packaged with BigQuery provides users with several data visualization tools, speeds up responses to queries, simplifies architecture, and enables smart tuning.

Data Lakes and Data Marts

GCP’s enables ingestion of batch and stream/real-time data, change data capture, landing zone, and raw data to meet other data needs of businesses.

Data Pipelines

GCP tools such as Dataflow, Dataform, BigQuery Engine, Dataproc, DataFusion, and Dataprep help create and manage even complex data pipelines.

Discover how Indium assisted a manufacturing company with data migration and ERP data pipeline automation using Pyspark.

Data Orchestration

For data orchestration too, GCP’s managed or serverless tools minimize infrastructure, configuration, and operational overheads. Workflows is a popular tool for simple workloads while Cloud Composer can be used for more complex workloads.

Data Governance

Google enables data governance, security, and compliance with tools such as Data Catalog, that facilitates data discoverability, metadata management, and data class-level controls. This helps separate sensitive and other data within containers. Data Loss Prevention and Identity Access Management are some of the other trusted tools.

Data Visualization

Google Cloud Platform provides two fully managed tools for data visualization, Data Studio and Looker. Data Studio is free and transforms data into easy-to-read and share, informative, and customizable dashboards and reports. Looker is flexible and scalable and can handle large data and query volumes.

ML/AI

Google Cloud Platform leverages Google’s expertise in ML/AI and provides Managed APIs, BigQuery ML, and Vertex AI. Managed APIs enable solving common ML problems without having to train a new model or even having technical skills. Using BigQuery, models can be built and deployed based on SQL language. Vertex AI, as already seen, enables the management of the ML product lifecycle.

Indium to Modernize Your Data Platform With GCP

Indium Software is a recognized data and cloud solution provider with cross domain expertise and experience. Our range of services includes data and app modernization, data analytics, and digital transformation across the various cloud platforms such as Amazon Web Server, Azure, Google Cloud. We work closely with our customers to understand their modernization needs and align them with business goals to improve the outcomes for faster growth, better insights, and enhanced operational efficiency.

FAQs

The post Data Modernization with Google Cloud appeared first on Indium.

According to a Deloitte study, spending waste is emerging to be a major issue in the absence of controls and governance around consumption, accounting for nearly 30% of the total IT spend.

Some of the complexities in managing costs of public cloud, according to a Gartner report, include:

• Complex billing models and multifaceted pricing structures facilitate several options and combinations, that can make selecting the best pricing option of each use case difficult.
• The bills are granular, running into several line items that can make it difficult to keep track.
• Since cloud service provisioning is very easy needing just a point-and-click and without capacity constraints, it can lead to unexpected charges.
• Cloud offerings are constantly being improved and new services, features, price reductions or new pricing models are being constantly announced, making it difficult for organizations to keep track and understand how it impacts their bills.
• Availability of alternative architectures, services and components for the same applications at varying price points can make it difficult to arrive at the most cost-effective option.
• There is no standardization of billing models across the different cloud platforms such as AWS, Microsoft Azure, and Google Cloud Platform (GCP).

Efficient use of cloud engineering services can provide tangible financial benefits and requires collaboration across disciplines such as operations, product management, governance, architecture, finance and application development. To improve return on investment (ROI), linking cloud costs with business KPIs can improve spend management and optimize costs.

Begin with Cloud Migration Planning

To have better control on cloud spends and maximize value from cloud investments, Deloitte recommends building a strong business case across the portfolio by identifying factors that contribute to tech spending. The following are the obvious costs:

• Infrastructure
• Application
• Outsourcing
• Labor costs

What is often overlooked, however, and significantly adds to the costs are:

• Region-specific cloud costs such as real estate taxes, duties, energy, and carbon penalties
• Costs of data transfer
• Security costs
• Refactoring costs that get compounded with the progress in migration efforts

Analyze the impact of spending on each of these cost factors and realign, redistribute, or reduce migration costs wherever possible without reducing performance.

Optimizing Spend on Existing Cloud Infrastructure

While the earlier recommendation was for migration planning, what about optimizing costs for your ongoing cloud operations? Some of the factors that contribute to cloud-spending waste include:

• Resources that are no longer needed but continue to run result in ghost expenditures
• Reserved capacity being used at suboptimal levels due to a lack of understanding of how hyperscaler pricing mechanisms work
• Redundant infrastructure design similar to the on-prem architecture resulting in higher costs
• Redundant subscriptions and software license costs leading to wasteful expenditure
• Workforce with legacy skills and inefficient engineering leading to overspending and loss of productivity

Optimizing Spend

Businesses can bring down their cloud costs by:

• Rightsizing you cloud infrastructure
• Shutting down unused resources
• Correct storage
• Adopting lower-cost instance types or regions

Automating optimization can help reduce inefficiencies through alerts and reports on wastes, providing greater visibility and transparency. Apart from implementing a plan to optimize cloud spending, it also requires governance for ongoing spend management with clearly defined spending guidelines, elucidate processes to maintain savings and automate the implementation of recommendations for optimization.

The governance process should focus on:

• Access provision controls
• Cost views for provisioned resources
• Resource quota management
• Automatic shutdown policies
• Reserved instance purchase strategy.

Since measuring KPIs provides insights into spends, governance efforts define the metrics for factors such as:

• For every service, the budget and the actual spend
• By how much is the spend higher or lower
• Per person tooling cost, the number of resources provisioned per month, etc.
• Forecast spend trends as well as track enterprise discounts and reserved instances to leverage them appropriately

Indium Helps Optimize AWS Investments

Indium Software, a two-decade old digital engineering solutions company, is an AWS Select Consulting partner that helps customers design, architect, build, migrate, and manage cloud solutions built on AWS. One of the key focus areas for the company is to optimize costs and maximize investments in AWS by assessing the needs of the company, provisioning appropriately to avoid redundancies, create governance models for closely monitoring resources and shutting down the unnecessary ones and automating implementation and tracking to provide visibility and transparency.

We have experience including 150+ App Migration/Modernization, 20+ Petabytes Data Migration, 70+ Cloud-native App & SaaS development, and 250+ CI/CD pipelines. We provide deep technical and domain expertise building a digital extension of our clients’ core business and increase customer intimacy. Our AWS partnership with home-grown IPs on Text Analytics and Digital Assurance, makes us well suited to deliver continuous digital improvements and help customers realize the full potential of their business applications and data on AWS.

To know more about how we can help you optimize your cloud migration and existing cloud investments, contact us now.

The post Optimizing Cloud Spends and Maximizing Value from Cloud Investments appeared first on Indium.

Most businesses regard ERP system as a significant investment in and of itself, and when it comes to critical tasks like data migration, they are likely to take it easy. This is due to insufficient time and resources being allocated, resulting in a not-so-ideal Data Migration Plan (DMP) along with insufficient testing and support.

Below are some of the most commonly faced challenges while migrating data.

1. Integrated processes: Data migration frequently involves a diverse group of people using disparate technologies. The use of such disparate systems can result in a failure to transfer data and design between the phases of analysis, development, testing, and implementation. The translation of this data may result in data loss, as well as increased costs and time waste. Organizations must seek out a platform that successfully connects the critical inputs and outputs from each stage in order to reduce errors and save time and money.
2. Lack of validation: If you don’t consider all possible possibilities, you run the risk of having problems after it’s too late. Testing your migration with real-world data allows you to cover a wider variety of obligations and run simulations for worst-case situations, which lets you remain prepared. This opportunity will be missed if more convenient data samples are used.
3. Source data: Having several systems forces you to gather data from various sources and present it in a way that ensures secure data import. This is the most basic description of the process; however, the truth is much more nuanced. Many specifics are often ignored, and attention to them is needed to keep the data clean and formatted correctly in order to make the most of it. A knowledge gap occurs when you are unaware of issues with your data, such as duplicates, incomplete data, incorrect spellings, and incorrect data. It’s easy to get complacent and believe that your data can be configured to suit the parameters of a new system.
4. Collaboration: As previously mentioned, data migration is a time-consuming process involving a diverse group of people and technologies, which may also involve a combination of internal and external contractors. Both of these elements may not even be in the same place in certain situations. Working in silos will reduce performance, generate more data silos, and lead to increased inefficiencies and misinterpretations in these situations. Collaborative tools allow all stakeholders involved in data migration to see the same image of data as it progresses through the project stages, reducing the chance of misunderstandings.

Cloud Data Migration

Any cloud migration’s overall goal or advantage is to host applications and data in the most efficient IT environment possible, based on factors like cost, efficiency, and security.

Many companies, for example, migrate on-premises software and data to public cloud infrastructure to take advantage of benefits such as greater elasticity, security, and cost savings.

Cloud Data Migration In The BFSI Sector

Moving core systems and functions to the cloud was once an ambitious aim in the financial services industry. It is now a reality in the industry.

The trend for cloud migration solutions in the financial services sector is driven by two factors: changing consumer preferences and constant pressure to improve performance. Customers in the financial services industry demand a user interface that is highly open and constantly evolving. The cloud helps financial services companies keep up with changing consumer demands by offering a highly adaptable platform.

On the financial side, the cloud allows for a quicker time to market and greater opportunity for growth. Perhaps more significantly, cloud storage also lowers costs, which is a significant benefit in an industry where top-line sales growth is often prioritised over controllable expenses. The World Bank, for example, cut its platform management costs by $8 million by simply migrating to the cloud-based Office 365. DBS Bank in Singapore lowered its data center’s operating costs by 75% by shifting it to the cloud.

Financial services firms that emphasise cloud migration will gain more committed customers and outperform in key metrics including efficiency ratio. However, conventional processes remain rooted in the financial services industry, creating actual and perceived roadblocks to implementing a cloud-forward strategy. Furthermore, finance and IT departments can be at odds at times, but when aligned and working together, they can achieve incredible results.

What Are The Challenges?

Cloud platforms enable businesses to keep up with changing consumer demands, the majority of which revolve around timely and clear service. They also assist in the integration of data analytics, machine learning, and business intelligence into an organization’s current infrastructure.

Cloud computing provides an ideal platform for testing and integrating new services and emerging technologies that enhance the customer experience due to its elasticity. The cloud’s versatility is critical in assisting companies in continually bolstering interaction with new customer-facing solutions.

Cloud computing provides an ideal platform for testing and integrating new services and emerging technologies that enhance the customer experience due to its elasticity. The cloud’s versatility is critical in assisting companies in continually bolstering interaction with new customer-facing solutions.

1. Security: Security is a top priority for IT and C-suite executives charged with safeguarding customer data and IT systems.
2. Resistance: The financial sector’s deeply embedded resistance to new technology adoption can stymie executive buy-in for cloud initiatives.
3. Compliance: The financial sector’s regulatory environment adds another layer of complexity to new technology initiatives.

However, competing priorities between IT, finance, and other business units across the organisation are one of the most significant barriers to cloud migration in the financial sector. Cloud migration is never solely an IT project. It is a project that necessitates the support and participation of CFOs and other business stakeholders.

To successfully migrate to the cloud, financial institutions must recognise the win-win situation for both IT and finance. CFOs and other financial decision makers can work with IT to maximise the financial benefits of cloud infrastructure for their organisation. Cloud migrations, in our experience, produce positive results when finance and IT collaborate.

The Bottom Line

Financial institutions are under pressure to migrate critical applications to the cloud as soon as possible. However, industry-specific roadblocks, such as silos with competing priorities, jeopardise the ability to successfully migrate to the cloud.

Banks and credit unions can free up capital and create the tractability needed to generate and adapt growth by migrating to the cloud. But, more importantly, cloud migration enables banks and credit unions to benefit from faster and more efficient processes, which reduce labour requirements and other costs in many cases.

Implementation of Data migration services to improvise the data migration to the cloud is most essential for success. Finally, the financial advantages of cloud migration go far beyond reduced capital expenditures. Although a cloud migration may result in boosted annual maintenance and operating costs, gains in efficiency, captured revenue, and scalability can result in financial and efficiency rate improvements.

The financial gains of cloud migration should persuade CFOs to play a more active role in cloud migration decisions and rollouts. Finance can use cloud migration to streamline processes, increase revenue opportunities, cut costs, and improve efficiency ratios by collaborating with IT.

The post Data Migration And Cloud Data Migration Challenges In The Financial Sector appeared first on Indium.

According to a McKinsey Global Survey of executives, digitization of internal operations and customer and supply-chain interactions have accelerated up by three to four years with the share of digital or digitally enabled products in their portfolios having speeded up by an astounding seven years. To meet the increasing demand in times of lockdown and social distancing, businesses had to adopt at least temporary digital solutions to cope and maximize revenues.

This has definitely had an impact on the DNA of the organizations as many of these changes are expected to be more long-lasting with a corresponding increase in funding for digital initiatives as well. Cloud is at the forefront of all digital initiatives and all digitization efforts begin with the migration of at least a part of the data and apps to the cloud.

And this trend is expected to continue. According to an IDC forecast, nearly 90% of businesses globally are expected to opt for hybrid, private or multiple public cloud environments to meet their growing infrastructure needs by 2022 to be agile and scale up quickly to meet the increasing demands.

Have a Long-Term Strategy for Your Cloud Migration

While migrating to the cloud sooner or later is inevitable, the cloud is not just a technology but should be part of a digitization strategy. In the pandemic situation, most businesses adopted the cloud as a reaction and response to the changing environment rather than a proactive and deliberate approach.

Like all transformations, migration to the cloud too needs plans, goals, processes and so on. Businesses need to have a clear understanding of why they want to migrate, the process they should follow, the timing, which parts of their business, where to locate their cloud server and so on before making the irretrievable investment. Creating a long-term strategy will enable businesses to derive the best value from these investments.

To thrive in this post-pandemic world and to continue on their transformation journey, businesses need to now pause and evaluate the effectiveness of their current approach. What is driving the migration to the cloud?

• Is it because of the pressure to meet consumer needs that is driving you to use your digital budget on the cloud?
• Is it to provide data analytics to boost sales?
• Are you trying to rationalize and reorganize the data architecture?
• Is it driven by governance needs to strengthen compliance protocols and protect the brand reputation?
• Is it to support expansion into new markets or release new products or service lines?

A Holistic Approach Customized to Your Needs

Identifying the specific objective will influence the course of the path you choose for the migration. It will require collaboration and agreement across the organization to ensure you stay on the path and achieve the goals. To develop an enterprise-wide strategy:

• Gather needs and goals from across the business and developing a balanced approach
• Identify what can be moved to the cloud
• Prioritize migration

More than the actual migration, what is more difficult is to decide on the right destination, the right path, and routing the right map for the migration to the cloud. To some extent, this will depend on the maturity of your current cloud deployment.

Over time, you may have to change your strategic decisions based on the changing needs of the organizations and the different maturity levels at the various functions. Cloud’s flexibility and scalability facilitate data management with ease but getting it right initially is crucial to future-proofing your business and protect your investment.

Cloud Migration (along with data migration) with Indium Software

Indium Software, which delivers data-driven solutions for businesses of all sizes across industries, offers cloud migration services that are designed from the ground-up for your context. We design bespoke solutions based on the unique needs of our customers leveraging our proven cloud migration expertise.

Specifically, we help identify all the cloud migration options available to you (including in most cases a hybrid cloud environment), the right infrastructure options for your context, your enterprises’ data and analytics needs, and overall modernization roadmap.

Indium Software’s team of data and cloud experts bring to the fore proven expertise and experience to understand our customers’ need to scale, modernize and be cloud-native. We have a dedicated managed cloud solutions team to enable scheduled scaling, auto-scaling, containerization, or predictive scaling for your migration.

Not just support and deployment of private, public, or hybrid cloud, but Indium’s team of cross-domain experts can choose the right kind of ownership, access, and size as well as empower our customers with complete control over their cloud infrastructure.

Our team also takes a structured approach to optimize security, quality, and speed based on best practices to enable data migration. This enables:

• Driving analytics by generating data sets profiles.
• Establishing data migration processes using templates and guides.
• Identifying and implementing data inadequacy detection rules.
• Establishing data validation processes.
• Driving specification of requirements on the identification of legacy sources for data migration.
• Developing, reviewing, and securing approvals for mapping and transformations.
• Reducing data migration costs and ensuring on-time delivery.

If you would like to embark on your cloud migration journey, contact us now:

The post Cloud Migration Done Right: Don’t do it ALL in one go appeared first on Indium.

The numbers confirm this too: as per a survey of 500+ IT leaders and executives, the number-one driver of cloud migration is security and data protection. Fifty-eight percent of the respondents ranked security as one of their main priorities.

Then we have data modernization, which involves transferring the data from legacy to modern databases. According to the survey, 55 percent of respondents concurred that data modernization is a key factor in their companies shifting to the cloud. Cost savings and performance of IT operations rank third in the survey results. Cost is less of a factor compared to other key benefits of the cloud, which is a key enabler for organizations’ digital transformation efforts.

QA or Quality assurance and testing services are an indispensable part of any company’s cloud migration journey. For they help organizations avoid issues around cloud scalability, server breakdown, databases, website crashes and more which could potentially tarnish a brand’s reputation while costing time and resources.

In terms of application testing for cloud migration, the focus areas mainly include the following:

• Functional validation
• Integration testing
• Scalability and performance testing
• Security testing

Functional validation

This type of testing mainly validates the production readiness for applications moved to the cloud. The validation process typically involves the verification of key facets of migrated applications and whether they are performing according to the service level agreements (SLAs).

For robust cloud migration, organizations must verify SaaS (short for software as a service) and cloud services function and validate the end-to-end application’s function.

When it comes to cloud testing an application, the following test cases must be executed to check:

• Whether a valid input generates the expected results
• Whether object references and page layout work as expected
• Cross-platform compatibility
• Service integration with applications
• If the automated test suite is compatible with cloud applications

Integration testing

It must be noted that cloud migration is not only about moving the in-house workload to the cloud, but it also includes managing different variables such as authorization, authentication, integration, security, compatibility, testing and security.

Of the variables, integration with third-party tools is significant. Organizations must ensure their applications are well-integrated with third-party applications and communicate seamlessly without glitches.

It is also mandatory to identify dependencies among applications and the service level agreement with each app – because dependencies between systems and applications can make integration testing potentially challenging.

QA and testing teams must consider the following when performing integration testing:

• Cloud testing with third-party tools when varying service level agreements are at play
• Uncover coordination glitches in the cloud
• Application configuration within the cloud environment
• Resources for integration testing and validation
• Systems and interfaces that are part of integration testing
• Integration of multiple applications can complicate migration

Performance testing

This is a significant element of an organization’s cloud migration success while also being a critical part of application development.

When migrating an application to a cloud service, factors such as scalability and response time must be validated. Through automated performance testing process, a software or an application is tested for issues that require attention.

When it comes to performing performance testing, QA engineers and testers must consider the following:

• Identify the architecture of an incompatible application
• Identify the monitoring needs and setup tools
• Keep track to validate response time with regard to service level agreements
• Carry out load testing in parallel
• Record performance under different loads that meet service level agreements
• Check service level agreements, business transactions and end-to-end flow of applications

Security testing

Security is one of the main concerns of cloud migration, with service providers spending millions of dollars to provide optimal protection for their clients’ workloads.

Given the sophistication and sheer volume of cyberattacks, advanced cybersecurity measures must be put in place to ensure confidential organizational data is secure.

Business process security testing, user privacy security testing, application transaction security testing, data privacy and data security testing are the main types of testing a cloud application. 

Security testing helps eliminate the security risks of software systems and applications. The primary focus for organizations is user validation to go with validating data security in transit, during use and at rest.

The following factors must be considered at the time of security testing:

• How is data stored when idle?
• What are the different compliance requirements?
• Who has access to the data?
• Where, when and why users access data?
• What sensitive data is used, stored or transferred?
• Identify legacy applications running on obsolete systems
• Ensure only authorized users access the cloud network
• Ensure appropriate measures are put in place against Distributed Denial of Service (DDoS) attacks
• Validate application, frontend and backend processes

Plan for disaster recovery and business continuity

Despite taking all necessary precautions before cloud migration, organizations must brace themselves for possible worst-case scenarios.

The measures may include simple data recovery, taking stock of the various attacks, disaster recovery practice and more.

Organizations must validate their disaster recovery strategies in the event of cloud outages. The following practises will help:

• Periodically test, measure and update business continuity practises
• Update business continuity plan based on test results
• Run simulations and assess team’s readiness
• Validate application instances to automatically restore in case of hardware failures

Summary

As per a recent study, 77 percent organizations believe that cloud technology gives them a competitive advantage—which partly explains why an increasing number of them are transitioning to the cloud. Cloud is powering organizations’ digital transformation efforts and enabling them to build innovative, digitally-collaborative and customer-friendly products and solutions at scale. It is also helping organizations respond to opportunities with greater agility.

Not with standing all the key benefits of cloud migration, organizations must follow the above QA testing checklist to the letter to ensure they avoid security, performance, functionality issues and potentially extra costs, time and resources during IT migration.

The post The 5-step QA testing checklist for successful cloud migration appeared first on Indium.

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.indiumsoftware.com/inquire-now/

The post Migration to the Cloud: A 3-Step Guide for Enterprises appeared first on Indium.