Cloud Migration
Step-By-Step Process
Since 2012, ScienceSoft has been providing cloud migration services to help businesses increase their workloads’ performance and reduce IT infrastructure operational costs.
Cloud Migration: Summary
Based on our recent projects, ScienceSoft shares some details on cloud migration:
Migration of a company’s first workload takes from 1-2 months (for small workloads) to 6+ months (for medium and large workloads). Subsequent workloads require less time to migrate due to the gained experience.
The cost of lift-and-shift migration of one application will start at $5,000, the migration requiring application re-architecting will typically fall in the range of $20,000 and $100,000.
Key project steps: cloud migration conceptualization, choosing a cloud migration strategy, cloud platform selection, cloud migration planning and design, migrating to the cloud, final testing and optimization of the cloud environment.
Cloud Migration Step-By-Step
Every cloud migration roadmap is different, depending on the scope and scale of your migration project, the chosen migration strategy, the complexity of data storing and processing requirements, and more. Below are described the typical steps we at ScienceSoft take to perform cloud migration.
1.
Cloud migration conceptualization
- Establish cloud migration goals (improving business app performance, reducing IT infrastructure costs, expanding market reach, etc.).
- Determine workloads (e.g., enterprise applications, databases, data warehouses, virtual desktops) to relocate to the cloud.
- Diagram the workloads’ topology and dependencies and perform the workloads' complexity analysis to define the scale of the cloud migration.
2.
Choosing a cloud migration strategy
Choose a cloud migration strategy (rehost, replatform, refactor, repurchase, retire, retain – or a combination of several strategies):
- Rehosting (“lift-and-shift”):
- Migrating on-premises workloads to IaaS without code modifications.
- Quick and cheap migration to the cloud with limited cloud-driven capabilities (workload resilience, performance and scalability).
- Replatforming (“lift, tinker and shift”):
- Migrating modified workloads to the cloud (no change in the workload architecture is needed).
- Improved performance, fault-tolerance, and scaling of the migrated workloads.
- Refactoring (“rearchitecting”):
- Moving on-premises workloads to PaaS by making them cloud-native (or near native).
- Full scope of cloud capabilities (including cloud auto-scaling, serverless computing, etc.)
- Repurchasing (“drop and shop”):
- Replacing an on-premises solution with a cloud software product (SaaS solution).
- Fast and low-risk cloud adoption.
3.
Choosing a cloud deployment model
Choose a cloud deployment model (single cloud, multi-cloud or hybrid cloud):
- Single cloud:
- Deploying your workloads in a single multi-tenant cloud environment.
- Risks of vendor lock-in.
- Multi-cloud:
- Migrating your workloads or their parts to different public clouds.
- Leveraging key advantages of each cloud service provider (e.g., one provider offers higher database speed, while another offers more advanced AI capabilities).
- Hybrid cloud:
- A combination of public and private (hosted and managed on-premises by the company itself) clouds.
- Placing the workloads with specific security requirements on the private cloud and enjoying the public cloud’s pricing benefits for other workloads.
4.
Cloud platform selection
- Choose one or several cloud platforms (AWS, Azure, Google Cloud Platform, etc.).
- Validate the compatibility of the workloads under migration with the cloud and a particular cloud platform with the help of a Proof-of-Concept (PoC).
5.
Cloud migration planning and design
- Calculate cloud computing resource requirements for your workloads to avoid buying redundant resources.
- Develop a risk management plan to anticipate and mitigate such risks as overpaying due to improper workload architecture, compromised data security during data migration, etc.
- Perform cloud migration cost assessment and ROI calculation.
- Establish KPIs for cloud migration (workloads’ response time, availability, error rate, etc.).
- Identify the amount of refactoring needed for the workloads under migration.
- Select tools for automated cloud migration.
- Design the architecture of the workloads to migrate.
- Prepare a cloud migration plan, prioritizing workloads to migrate and outlining a migration schedule.
6.
Migrating to the cloud
Common migration activities include:
- Creating a new production environment based on the new workload architecture.
- Migrating data related to the workloads under migration. To keep the cloud database up-to-date, data migration should be done continuously throughout the migration process.
- Migrating workloads.
- Setting up cloud monitoring tools.
7.
Final testing and optimization of the cloud environment
- Test the performance of the migrated solutions in the cloud environment.
- Conduct penetration testing of the new environment.
- Conduct regulatory compliance assessment (e.g., compliance with HIPAA, GDPR, etc.) and technical audit (to identify operational flaws) of the cloud infrastructure and the migrated workloads.
- Improve security (if needed) and optimize cloud performance.
8.
Switching from on-premises workloads to the cloud
At this stage, the migration is complete, and your cloud environment goes live. Upon going live, you may either turn off the on-premises infrastructure of the migrated workloads or keep it for backup or as part of a hybrid cloud deployment.
Cloud Migration Costs
The cost of cloud migration ranges from $5,000 to $100,000 depending on the scope of needed application modification.
Cloud migration cost factors
- The number and complexity of workloads to migrate.
- Chosen migration strategy (rehosting, re-architecting, etc.). The volume of the workload refactoring and configuration activities.
- Cloud deployment model (public cloud, multi-cloud, hybrid cloud). Note that multi-cloud and hybrid cloud deployment options are more expensive.
- The volume of data to transfer.
- Workload availability requirements.
- The extent of migration automation and the cost of migration automation software licenses.
- Testing efforts.
Post-migration cost factors
- Hiring an IT support team or training your in-house IT team.
- Recurring cloud charges for the infrastructure and services that will mostly depend on:
- Required storage and compute resources.
- Network bandwidth required by the application infrastructure.
- Physical location of data centers, and more.
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Professional Cloud Migration Services
ScienceSoft has been providing cloud migration services for 11 years and can offer both advisory and practical migration help.
ScienceSoft's Cloud Expertise
- 34 years in IT.
- Partnership with Microsoft based on 11 years of experience with Azure infrastructures.
- An AWS Select Tier Services Partner with 10-year experience with AWS infrastructures and access to advisory assistance directly from Amazon.
- Established DevOps practices since 2013.
- ISO 9001-based quality management system to ensure 100% value and tangible results driven from ScienceSoft’s cloud services.
- Your information security is our highest priority - our ISO 27001-certified information security management rests upon well-tried practices, advanced techs and security-savvy people.
- Included in the 2022 IAOP Global Outsourcing 100 list as one of the world’s best outsourcing service providers and advisors.
- ScienceSoft is a 3-Year Champion in The Americas’ Fastest-Growing Companies Rating by the Financial Times.
Typical Roles in ScienceSoft's Cloud Migration Projects
Project manager
- Develops a detailed plan for a cloud migration project, including the budget, milestones, risk mitigation plan, and more.
- Manages the schedule of the cloud migration project.
- Assigns tasks to the cloud migration team and supervises their implementation.
- Prepares regular progress reports on the migration project state.
Cloud architect
- Develops a cloud migration strategy.
- Designs the architecture of the workloads to migrate and provides it to the technical team for implementation.
- Ensures that the workload architecture is aligned with business requirements.
- Develops cloud cost optimization techniques.
Software developer
- Modifies the workloads to migrate according to the architecture designed by the cloud architect.
- Performs debugging of cloud workload issues.
Database engineer
- Configures cloud database(s) and data warehouse(s).
- Implements data migration tools.
- Implements data backup/recovery and database performance tuning.
DevOps engineer
- Aligns development and operation environments using an infrastructure-as-code approach.
- Establishes CI/CD pipelines.
- Configures monitoring and alerting systems to proactively resolve cloud workload issues during and after migration.
IT security and compliance specialist
- Verifies that the migrated workloads meet security and compliance requirements.
- Provides security recommendations during the cloud migration process.
QA engineer
- Develops a cloud migration testing strategy and plan.
- Verifies the integrity of the migrated data.
- Tests the migrated workloads’ functionality, performance, etc.
Cloud Migration Sourcing Models
The cloud migration process is handled in-house
Pros:
- Complete control over cloud migration.
- Full visibility into the cloud migration team productivity.
Cons:
- Specialized cloud migration resources (with experience in the chosen cloud services, legacy solution modernization, etc.) who are not profitable to hire for a one-time project may be required.
- Full managerial responsibility for the migration team.
Partial or full outsourcing of technical resources, the management is in-house
Pros:
- Quick project ramp-up.
- Cloud migration cost-efficiency due to high resources scalability up and down.
- Solid cloud migration expertise of a specialized outsourced team.
Cons:
- Challenges in the coordination of in-house and outsourced resources.
Outsourcing the full cloud migration process
Pros:
- The whole process is commissioned to a self-managed cloud migration team responsible for the migration outcome.
- Smooth and quick cloud migration due to established processes of an experienced cloud migration vendor.
Cons:
- Risks of contracting cloud migration to an underqualified vendor.
In-house cloud migration process is guided by an experienced advisory vendor
Pros:
- Access to an expert cloud migration team that provides knowledge sharing and specific tech help to your in-house migration team.
Cons:
- Building a collaboration process between the in-house team and the advisory vendor takes time and effort.
Benefits of Cloud Migration with ScienceSoft
Cost efficiency
We map out an individual pragmatic migration strategy for each component to reduce the re-development. We continuously rightsize resources, use Reserved/Spot instances, and more to keep your cloud costs optimal.
Only reasonable migrations
Each cloud journey with ScienceSoft starts with a business case creation, where we outline the benefits, risks and costs of alternative migration strategies. When it is safe to go ahead with the migration, we proceed with the project.
Mature processes and infrastructures
We design and implement cloud-native infrastructures and architectures that encompass microservices and containerization, IaC and serverless approach, CI/CD pipelines so that you could reach the next level of IT maturity.
Business continuity
We plan and carry out migration without hindering your business processes. We design applications’ architecture which is able to survive a failure.
High performance
We plan the required cloud resources and leverage auto scaling to cope with peak-time workloads painlessly.
Top-notch security
Since 2003, ScienceSoft’s security experts help businesses prevent, detect, and respond to security incidents. We heavily invest in a mature information security system compliant with ISO 27001 and sustainable security culture, retain top security experts on board and follow CIS, NIST, OWASP requirements and recommendations.
Cloud Migration Software We Recommend
The choice of cloud migration tools depends on the type of solutions you want to migrate and the cloud migration strategy you implement. Here are the tools we use for data migration:
Apache NiFi
Used for
Migrating databases from an on-premises server to the cloud.
Description
- Graphical user interface for easier creation of various dataflows.
- Priority-based queuing with single/multiple prioritization schemes that guide how data is retrieved from a queue.
- Creating templates of frequently utilized dataflows to automate the data migration process.
- Possibility to relocate data to multiple clouds at a time.
Pricing
Free.
Rsync
Used for
Data migration from on-premises to the cloud.
Description
- Rsync accelerates data transfer by sending only the difference in the files across the link.
- Reduced latency for multiple files due to internal pipelining.
- Supported SSH to transfer data within a secure environment by encrypting network traffic between hosts. What is more, Rsync supports RSH and direct sockets for data transferring.
Pricing
Free.
Microsoft Azure
Description
- 200+ services (including compute, containers, CI/CD, integration, migration, databases, IoT, AI).
- 60+ availability zones.
- Storage: Azure Blobs, Azure Files, Azure Tables, Azure Queues, Azure Disks.
ETL: Azure HDInsight.
Analytics: Azure Databricks, Azure Stream Analytics, Azure Data Factory, Azure Data Lake Analytics, etc.
Machine learning: Azure Machine Learning.
Business Intelligence: Power BI, Azure Analysis Services, Azure Synapse Analytics.
- Compliance with CIS Benchmarks; ISO 20000-1:2011, ISO 22301, ISO 27001, ISO 27017, ISO 27018, ISO 9001; SOC, WCAG, HIPAA, HITRUST, FERPA, FDA CFR Title 21 Part 11, FFIEC, GxP, SEC 17a-4, SOX, CCPA.
- Discount for long-term usage (1–3 years): Microsoft Enterprise Agreement (up to 72% discount).
Pricing
AWS
Description
- 200+ services (storage, databases, containers, serverless computing, application integration, migration, application management, ML, AR & VR, IoT, etc.).
- 99 availability zones.
- Storage: Amazon Simple Storage Service (S3), Amazon Elastic File System, Amazon Elastic Block Store, Amazon RDS.
Analytics: Amazon Data Pipelines, Amazon Redshift, Amazon Kinesis Analytics, Amazon Elasticsearch Service, etc.
Machine learning: Amazon SageMaker, Amazon AI: Intelligent Search, Amazon Comprehend, Amazon Lookout for Vision, Amazon Lookout for Merics, Amazon Personalize, and more.
Business intelligence: Amazon QuickSight.
- Compliance with CSA; ISO 9001, ISO 27001, ISO 27017, ISO 27018; PCI DSS Level 1; SOC 1, 2, 3; FERPA, GxP, HIPAA; HITRUST CSF, MPAA, PIPEDA, SEC Rule 17a-4(f), etc.
- Discount for long-term usage (1–3 years): EC2 reserved instances provide up to 72% discount.
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About ScienceSoft
ScienceSoft is a global IT consulting and software development company headquartered in McKinney, TX. Since 2012, we’ve been providing cloud migration services to help businesses increase their workloads’ performance and reduce IT infrastructure operational costs. Being ISO 9001 and ISO 27001 certified, we rely on a mature quality management system and guarantee cooperation with us does not pose any risks to our customers' data security.