Unlocking the Real Value of Data by Modernizing MS SQL Workloads on AWS Cloud

Data is the new oil in this digital era and most of the organizations are vouching for the same as a direct enabler for their business growth. Capturing maximum data and mining it holds the key for all businesses especially for retail, banking, telecommunication and entertainment streaming as it allows them to be faster when it comes to launching new products and for efficient customer service experience. This in turn leads to the explosion of data and the challenges due to this are many-fold specific to Infrastructure that can support this exponential growth. The key challenges are data storage, scalability, usability of the same for analytics through various integrations etc. Handling such a scale in on-prem even by using prominent databases like MS SQL can be a big challenge for any customer. We will discuss on how Cloud can handle this with its scalable, elastic and cloud native architecture that can also bring out the real value which Microsoft SQL as a database offers. AWS being the pioneer cloud platform, offers all capabilities that is needed to host, migrate, run MS SQL and integrate with different advance services to reap the real benefits. 

AWS offers a long list of services and tools on their platform to support migration of Microsoft SQL workloads from on-prem to cloud. Depending on the type of workloads, data size, business requirements and the move strategy finalized during the assessment phase, the right target landing zone is decided, whether it will be IaaS/PaaS/container based and use the respective migration tool. There are multiple migration paths defined for the SQL database and the same is portrayed in a workflow as below.  

Microsoft SQL Modernization Path on AWS

As you see above AWS provides a plethora of tools to rehost SQL engines to run on Windows or Linux platforms and enhance flexibility to reap the cloud benefits. Organizations can embark into a pay as you go model or move into an open source model that will reduce the licensing cost and enhance performance per core. Replatforming SQL into RDS using AWS DMS/SCT reduce management overhead of patching, taking backups etc that will further reduce FTE cost for the customer and teams can focus on innovations. AWS also offers ECS and EKS for running SQL on containers that will bring in scalability, elasticity and optimum resource usage. Product development lifecycle are shortened with faster deployment on AWS native Kubernetes platform. This brings in more orchestration capabilities and will enhance business agility. Overall multiple options are provided for customers to modernize their Microsoft SQL workloads on AWS makes it easy for organizations decide on the embracing the right migration path. 

Now that we discussed about moving workloads into AWS as a first step of modernization but unless the hyperscaler provides the capability of running them in cloud native mode we cannot reap the real benefits. From this perspective there are two critical aspects of running SQL workloads on AWS. 

1.    How do we run the workloads on AWS with maximum automation, governance, and guardrails in place?

2.    How do we consume the data effectively and efficiently using different cloud native services and the integrations it offers? 

This is portrayed below using a reference architecture on how differently SQL workloads can run on AWS. AWS offers rich automation capability using its Infra as a code in automating cloud foundation, application lifecycle management through its native DevOps pipeline, serverless functions and API’s to integrate between services to form data lakes, perform analytics through data mining services and use the insights for better business growth and innovation. 

Reference Architecture – Integrated Ecosystem on AWS for Data Modernization

The ecosystem shown above in the architecture can be explained well through the modernization use cases (Foundation, migration & operations) and how AWS helps customers in achieving this with its platform, services and tools.

1. Authentication

Windows applications on AWS can be integrated with On-Prem AD using AWS Managed AD offerings. This will ensure continuity with existing Single Sign on authentications for users to connect to SQL Databases

2. Cloud Foundation

Fully automated cloud foundation setup using AWS Infra as a code capabilities like Cloud Formation, Lambda and API programming for hosting apps and DBs and integrate them with other services for various business functions.

3. Reliability

Robust Infrastructure provided by geographically separated Availability Zones offer best in class reliability for Apps on Windows. Better RTO/RPO

4. HA & DR

AWS auto scaling capabilities across AZ’s along with Database snapshots that can moved across regions ensure business to restore in case of any catastrophe. Active-Passive & Active–Active replication models ensures high availability.

5. Performance

Utilization of CPU cores based on the SQL workloads by moving them into containerized architecture (SQL on Linux, Containers) supported by AWS. This will give better performance as well by reducing CPU cycle wastage and optimize licensing cost as well. Better capacity planning and overall cost reduction.

6. Migrate

AWS offers multiple migration paths for SQL workloads depending on the right ‘R’ strategy. Depending on the workload, SQL EOL support it can be hosted on EC2, RDS, Aurora etc. Have plethora of tools and services like AWS SMS, DMS, CloudEndure, Backup & Restore, Storage Gateway, DataSync, FSx, S3, EBS.

7. Agile Operations

AWS can bring in the right governance for the MS SQL workloads by enabling automated monitoring using CloudWatch, CloudTrail and Lambda. Be compliant with AWS Systems manager patching and monitor the patching activities by eliminating vulnerabilities. Vigorous backup capability through different backup plans by AWS Backup.  

8. Integrations

Use cloud native big data capabilities with MS SQL using advanced AWS services by creating data lakes for Analytics, Dashboarding and Reporting using S3, Glue, Kinesis, QuickSight. AWS brings in best in class integrations to inject data and mine the same for business insights. 

9. Service Management

AWS offers API programming and serverless capabilities to integrate with service management platform like ServiceNow to monitor and remediate DB issues proactively. Creates source of records for all incident, problems and changes that occur and update CMDB.

In conclusion we are unlocking maximum value of data modernized on AWS using the migration ecosystem it offers. This is realized through a robust Infrastructure governed by inbuilt automation and guardrails in place. Best in class integrations through API programming using the Cloud Native architecture enables migrated Microsoft SQL data on AWS cloud to create Data Lake formation. It can help in creating blueprints and meaningful business workflows and apply machine learning modules for better decision making and develop business insights. So why the wait? Get Set and embrace AWS Cloud for your Windows SQL workloads!!!