Migrate to the AWS* Cloud

Migration Plan, Tools & Costs

In IT since 1989 and in AWS services since 2013, ScienceSoft provides comprehensive cloud migration services helping companies benefit from improved performance and optimized costs.

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Migration to the AWS Cloud - ScienceSoft

AWS Migration: The Essence

AWS migration is used to transfer an IT infrastructure or some of its elements: databases, data warehouses and data, applications, virtual desktops to the AWS environment. In the projects that ScienceSoft delivers, AWS migration can bring such benefits as optimized costs and improved performance of the services and simplified scaling of storage and compute resources up and down.

Project duration: ~5 months (strongly depends on the migration project’s scope).
Checklist of AWS migration steps: defining the migration scope and strategy, project planning, data and workloads migration to the AWS environment, optimization of the AWS environment.
Cost of migration to AWS: migration process costs from $5,000 (for lift-and-shift migration) to $20,000–$100,000 (for migration requiring application re-architecting). AWS infrastructure cost is about $95,000. Use our online calculator to get a ballpark estimate for your case.
Required team: a project manager, a cloud architect, a software developer, an IT security specialist, a database engineer, QA and DevOps engineers.

5 Steps of AWS Migration

There are multiple factors that influence your AWS migration initiative, such as the complexity of your existing IT infrastructure, the timeline and budget you have for migration.

While every migration project is unique, ScienceSoft distills the typical steps of each AWS migration that we take in our projects.

Defining the scope of AWS migration

Duration: 1-2 weeks

Drawing up a list of IT infrastructure elements to migrate (databases, data warehouses and data, applications, virtual desktops or a combination of them) based on the specific AWS migration goals.
Analyzing the interdependencies among the infrastructure elements to migrate.
Examining a data model of the migrated data: a database’s size, the number and complexity of schemas and tables.

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Deciding on the migration strategy and model

Duration: 3-4 weeks

During this stage, ScienceSoft takes the following steps:

Choosing a migration strategy – rehosting, replatforming, repurchasing, refactoring.
- Rehosting – moving the existing workloads to the AWS cloud without any changes.
- Replatforming – moving the existing applications to the AWS cloud after introducing minimal code changes and some optimization, e.g., to improve performance of the migrated app in the cloud.
- Repurchasing – dropping a legacy app that doesn’t suit the AWS cloud and taking on a new SaaS app. Under this model, there’s usually a need to migrate existing data to the new app.
- Refactoring – altering and optimizing applications, databases, etc., to make them cloud-native.
(for a refactoring strategy) Assessing the degree of change in the code of a database, app, etc., that the migration process requires.
Defining the deployment model (AWS public cloud, Amazon Virtual Private Cloud, or on-premises + AWS).
(for a refactoring strategy) Designing a target architecture of migrated IT infrastructure elements for the AWS environment.
Estimating the required cloud storage and compute resources (including at peak times).
Deciding on whether to retain or not the source databases and apps after the migration.
Deciding on a migration toolkit.

ScienceSoft’s best practice: We use automation during AWS migration projects whenever reasonable. For example, AWS Database Migration Service allows speeding up data migration from the source database to the target one.

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Planning a migration project

Duration: 1-2 weeks

At this stage, ScienceSoft takes care of the following:

Developing a project plan with the outlined resources, costs and timelines to migrate to the targeted AWS environment, approaches to risk mitigation, and a roles and responsibilities matrix (e.g., RACI).
Establishing KPIs for AWS migration (availability of critical services, memory usage, network latency, etc.).
Creating a communication plan for the stakeholders that encompasses reporting and escalation procedures.

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Migrating to the AWS environment

Duration: 10-12 weeks

Creating an AWS production environment.
Setting up DevOps tools and processes for fast delivery.
Migrating workloads and data to the AWS environment.

ScienceSoft’s best practice #1: For complex AWS migrations, e.g., with multiple dependencies among IT infrastructure elements, we execute a pilot migration. It allows loading production-equivalent test data into a beta environment to test the migrated solution’s performance and solving the identified problems (if any).

ScienceSoft’s best practice #2: We start AWS migration only after we are sure about the quality of to-be-migrated data. We get rid of duplicated, erroneous, invalid data beforehand to optimize the time and resources needed for its migration.

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Testing and optimizing the AWS cloud environment

Duration: 3-4 weeks

At this stage, ScienceSoft takes the following steps:

Testing the performance of the migrated solutions in the AWS environment.
Conducting HIPAA, GDPR or other regulatory compliance assessment, penetration testing, and technical audit (to identify operational flaws) of the AWS infrastructure and the migrated workloads.
Improving security (if required) and optimizing cloud performance.
Setting up cloud monitoring tools, e.g., Amazon EC2 Dashboard, Amazon Cloud Watch, AWS X-Ray.

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AWS Migration Services by ScienceSoft

ScienceSoft has been working with AWS-based infrastructures since 2013 and offers both advisory and practical AWS migration help.

AWS migration consulting

From our AWS migration consultants, you’ll get the following:

Audit of your current infrastructure (its complexity, interdependencies, technology stack, etc.)
AWS migration scope and strategy.
Estimated ROI and TCO of the migrated workloads.
AWS migration project plan.
The best-fitting AWS migration toolkit.
An optimal sourcing model for AWS migration.
Guidance throughout the AWS migration process.

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AWS migration outsourcing

Our AWS migration team takes on:

Developing an AWS migration strategy and a project plan.
Designing a target AWS architecture, if required.
Defining an optimal set of AWS technologies for the target architecture.
Migrating your IT infrastructure or its elements – databases, DWHs, desktops, and data – to the AWS cloud.
Testing the migrated workloads (functionality, performance) and data (correctness, validity, integrity, etc.)

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Typical Roles in Our AWS Migration Projects

Project manager

Oversees that the milestones and goals of the AWS migration project are met while adhering to the approved budget and project timelines.
Manages the AWS migration team, allocates tasks.

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Supervises the quality of AWS migration deliverables.
Regularly reports on the AWS migration project progress.

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Cloud architect

Develops an AWS migration strategy.
Designs the target architecture in the AWS environment for the workloads to migrate.

Software developer

Modifies the workloads to migrate according to the target architecture design in the AWS environment.
Resolves workload issues in the AWS environment during and after migration.

Database engineer

Configures the target database(s) and data warehouse(s) in the AWS cloud.
Migrates the data to the target architecture.
Implements data backup/recovery.
Tunes database performance.

DevOps engineer

Incorporates an infrastructure-as-code approach, deploys continuous integration and delivery (CI/CD) automation.
Configures monitoring and alerting systems to proactively resolve workload issues in the AWS environment during and after migration.

IT security specialist

Before the migration, elaborates on security requirements for data transfer, server and data access.
Ensures that the migrated workloads meet security and compliance requirements.

QA engineer

Develops a testing strategy and a plan for an AWS migration project.
Verifies the success of data migration to AWS: the absence of data loss, the accuracy of data values after migration.
Assures the functionality and performance of the migrated workloads.

AWS Migration Sourcing Models

The whole migration to AWS is performed by an internal team

The management and the migration team are internal, some technical resources are outsourced

Project sponsor is in-house, the rest is outsourced

Pros:

Maximum control over the migration process.

Cons:

High risk of the project’s late start as you need to have resources on board with extensive knowledge of both AWS services and the technologies your current IT infrastructure relies upon, as well as hands-on experience in migration.

Pros:

Possibility to kick off your AWS migration project quickly.
Ability to stay flexible and efficiently scale available resources up and down, staying within the project’s timelines and budget.
Competence that outsourced resources bring in.

Cons:

Efforts required to have an internal team as experienced and competent as the hired external resources.
Efforts in establishing smooth communication between the in-house and outsourced resources.

Pros:

Competence and best practices that an outsourced team brings in.
Simple control over the AWS migration progress thanks to the established KPIs.

Cons:

A risk of entrusting your AWS migration project to an unreliable outsourcing partner.

Entrust Your Migration to Professionals

As an AWS Select Tier Services Partner, ScienceSoft can provide both consulting and practical help with your AWS migration project.

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AWS Migration Software* ScienceSoft Recommends

In our AWS migration projects, we use the following AWS services:

DESCRIPTION

Supports a wide range of databases, such as PostgreSQL, MySQL, Microsoft SQL. Both homogeneous (such as Oracle to Oracle) and heterogeneous migrations (such as Oracle to Amazon Aurora) are possible.
Allows no downtime for the source database during the migration, as a result of the continuous replication of changes to the target database.

BEST FOR

Heterogeneous migrations for analytical purposes.

DESCRIPTION

Automatically converts source servers from physical, virtual, or cloud infrastructures to run natively on AWS.
Enables continuous replication that leads to no performance disruption.

BEST FOR

Lift-and-shift app migrations to AWS.

DESCRIPTION

Provides visibility into the status of migration across multiple applications and key migration metrics and progress updates via creating a unified console/dashboard.
AWS Migration Hub Refactor Spaces allows for incremental application refactoring to microservices.

BEST FOR

Centralized tracking of migration processes in multiple regions.

DESCRIPTION

Transfers data and metadata between on-premises IT infrastructures and AWS, as well as between AWS storage services.
Ensures end-to-end data security, encryption and validation.
Accelerates data migration thanks to a purpose-built network protocol.
Schedules data transfer via AWS DataSync Console (no need for writing scripts).

BEST FOR

Migrating large data sets.

DESCRIPTION

Supports multiple user authentication methods, e.g., Microsoft Active Directory and Lightweight Directory.
Stores data natively in AWS Storage services, which allows getting insights from big data that was earlier unavailable for analytics purposes.
Available to both internal and external users thanks to configurable client access.

BEST FOR

Migrating file transfer workflows.

Not Sure What AWS Software to Choose for Your Migration?

ScienceSoft’s experienced cloud consultants will advise you on the optimal tools for your AWS migration project.

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The Costs of AWS Migration

The cost of AWS migration ranges between $5,000 and $100,000 depending on the project scope and requirements. For instance, the migration costs for an IT infrastructure of 30 virtual machines with a Kubernetes cluster, 20 virtual desktops, 3 MySQL clusters, 3 Redis clusters, and 10TB data storage will be around $100,000.

Assuming that a target AWS-based solution is completely based on cloud services, yearly infrastructure costs may reach $95,000.

Want to find out the cost of your AWS migration project?

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Main AWS migration cost factors:

The complexity of the current IT infrastructure (e.g., a database size – how many schemas and tables should be migrated).
The data volume to be migrated.
The chosen migration strategy, e.g., rehosting requires less effort than refactoring, therefore it’s less expensive.
The current IT infrastructure’s migration readiness.
The extent of migration automation and the cost of migration automation software licenses.
Testing coverage.

About ScienceSoft

With 35 years in IT overall and 12 years in cloud computing, ScienceSoft is a US-headquartered provider of AWS consulting and migration services. As an AWS Select Tier Services Partner, we guarantee the success of our clients’ AWS projects. Being ISO 9001 and ISO 27001 certified, ScienceSoft relies on a mature quality management system and guarantees cooperation with us does not pose any risks to our clients’ data security.

*AWS, Amazon Web Services, AWS Database Migration Service, AWS Application Migration Service, AWS Migration Hub, AWS DataSync, AWS Transfer Family are trademarks of Amazon.com, Inc. or its affiliates in the United States and/or other countries.