Attending tech events helps to learn something new, meet some awesome people, a network that makes you feel a little less overwhelmed, and build products that can have a good impact on society. Also, it makes you realize that people are available to help you out and you just need to ask them and keep patience.

We are in 2023, and we all know what AWS is and how it makes our life easier by providing cloud services on the fly!
Still, if you are unaware, as per Wikipedia, Amazon Web Services(AWS), Inc. is a subsidiary of Amazon that provides on-demand cloud computing platforms and APIs to individuals, companies, and governments, on a metered pay-as-you-go basis. Oftentimes, clients will use this in combination with autoscaling.

So, last week on 16th March 2023, I attended AWS Cloud Connect’23. It is an event organized to bring in the cloud computing community along with various partners to learn, collaborate and connect!

image 0: AWS Cloud Connect’2023

Here, I will quickly share my takeaways from the tech sessions. All the sessions were conducted by AWS senior professionals. It includes the following topics:

• Migrating and Modernizing on AWS

• Accelerating Innovation with AI/ML on AWS

• Get More from Data using AWS

• AWS Security Best Practices

Plus cool insights at last. Read on!

Migrating and Modernizing on AWS

Migration:

‘Migration’ refers to the process of moving something from one place to another.
In the cloud, ‘migration’ is the process of moving the digital data of the company, completely or partially to the cloud. Also, moving from one cloud to another cloud is a migration.

Note: Digital data = database, application, digital assets, services and IT resources.

Why do businesses migrate to the cloud? There are various reasons for the same, a few are listed below:
- Agility and staff productivity
- Improved security and operational resilience
- Cost reduction
- Data center consolidation
- Going global quickly, mergers and acquisitions(M&A)
- Outsourcing changes; end-of-life(EOL) HW/SW
- Digital transformation
- loT and AI/ML

Find the images below with AWS Migration capabilities:

¹image 1: AWS migration capabilities: data moving

¹image 2: AWS migration capabilities: services and servers

Modernization:

‘Modernization’ is the process of progressively transforming the existing applications and infrastructure to extend into higher-value-cloud-native services that unlock new business capabilities, accelerate innovation and reduce technical debt.

In all, Enterprise Modernization \= Maximized resiliency(Infrastructure), Engineering efficiency(Architecture) and Business agility(Organizational patterns)

¹image 3: Migration and Modernization journey

¹image 4: Application Journey

Overall, AWS can do all the heavy lifting for you which eventually reduces your operational load.

Accelerating Innovation with AI/ML on AWS

AI is critical to the success of any organization in the upcoming years. AI/ML is not the future; it is present.

Let’s put light on the current market domains where AI/ML is prevalent:

• Enhance customer experience: Chatbots and virtual assistants, personalization, identity verification, fraud prevention, etc.

• Better and faster decision-making: Intelligent search, forecasting, lead scoring, churn prediction, etc.

• Improve business operations: intelligent document processing, Content moderation, Predictive Maintenance, Machine translation, MLOPs, Coding & DevOps.

• New products and services: The possibilities are endless here.

**Tools by AWS:
**‘Amazon EC2 Trn1' instances are the first EC2 instances with up to 800 Gbps of Elastic Fabric Adapter (EFA) network bandwidth with native support of PyTorch and TensorFlow. Train on Trn1 and deploy anywhere.

Amazon Sagemaker is used to prepare data and build, train, and deploy ML models for any use case. The steps involved are: Prepare, Build, Train & Tune, Deploy & Manage.
AWS Canvas, a no-code tool for ML called It generates accurate machine-learning predictions.
AWS deeplens: The world’s first deep learning-enabled video camera for developers.
ML Solution Labs: It pairs your team with ML experts to help you identify and build ML solutions to address your organization’s highest return-on-investment ML opportunities.

Key challenges to AI/ML adoption:

image 5: Bottlenecks to AI adoption | credits: O'Reilly

Get More from Data using AWS

Software development is not about delivering features, it’s about delivering value!
Business Value = Data + Insights + Actions + Outcomes

Enterprise data evolved from: Data Aware → Data Informed → Data Driven

In terms of ownership, from ‘Data is no one’s job’ to ‘Data is someone’s job’ to ‘Data helps in my job’ should be the ideal progression.

Here’s the flow of modern data strategy:

¹image 6: modern data strategy

Essential elements of an analytics solution:

• Data Movement:
  Import your data from an on-premises environment(AWS Direct Connect, AWS Storage Gateway, AWS Snowball, AWS Snowmobile) and real-time environment(AWS loT Core, Amazon Kinesis Data Firehose, Amazon Kinesis Data Streams, Amazon Kinesis Video Streams).

• Data Lake:
  Store any type of data securely from gigabytes to exabytes. It decouples storage from compute and processes data in place.
  A data lake can comprise object storage like Amazon S3, Amazon S3 Glacier Deep Archive, Amazon S3 Object Lock, and Amazon S3 Intelligent-Tiering are used, along with Amazon S3 Glacier for Backup and archive, AWS Glue for data catalog and AWS Lake Formation for Governance.

• Analytics:
  Analyze your data with the broadest selection of analytics services. Some of them are Amazon Athena for interactive analytics, Amazon EMR for big data processing, Amazon Redshift for data warehousing, Amazon Kinesis for real-time analytics, Amazon OpenSearch for operational analytics, and Amazon QuickSight for dashboards and visualizations.

• Machine Learning:
  Predict future outcomes, and prescribe actions for rapid response. Available tools like AWS Deep Learning AMIs(DLAMI) for frameworks and interfaces, platform services like Amazon SageMaker, and backup and archive include solution-oriented APIs for computer vision and natural language processing.

In all, you can reinvent your business in 3 ways:

¹image 7: Modernise | Unify | Innovate

• Modernise your databases: Data infrastructure with the most scalable, trusted, and secure cloud providers.

• Unify data: Put data to work with secure practices like data lakes, the purpose of building, and security practices.

• Innovate using AI/ML/Analytics: Build new experiences by using AI/ML.

AWS Security Best Practices

Security is the key aspect of building trust and scaling businesses.
The customer is responsible for security in the cloud whereas, AWS is responsible for the security of the cloud. Always set high standards for data security and privacy by meeting data residency requirements, implementing encryption at scale, complying with local data privacy laws, and building compliant infrastructure.
Keep people away from data.

Detective controls: Gain the visibility you need to spot issues before they impact the business, improve your security posture, and reduce the risk profile of your environment.

Pillars of AWS Well-Architected:

• Operational Excellence

• Security

• Reliability

• Performance Efficiency

• Cost Optimization

• Sustainability

Security design principles:

• Implement a strong identity foundation

• Enable traceability

• Apply security at all layers

• Automate security best practices

• Protect data in transit and at rest

• Keep people away from data

• Prepare for security events

¹image 8: Best Practices-Infrastructure Protection

Tools by AWS for security, identity, and compliance:

• Identity & access management: AWS Identity & Access Management (IAM), AWS Single Sign-On-IAM Identity Center, Amazon Cognito, AWS Directory Service, AWS Resource Access Manager, and AWS Organizations.

• Detection: AWS Security Hub, Amazon GuardDuty, Amazon Inspector, AWS Config, AWS CloudTrail, and IoT Device Defender.

• Network & Application protection: AWS Network Firewall, AWS Shield, AWS Web Application Firewall, and AWS Firewall Manager.

• Data protection & compliance: Amazon Macie, AWS Key Management Service (KMS), AWS CloudHSM, AWS Certificate Manager, AWS Secrets Manager, AWS Artifact, and AWS Audit Manager.

• Incident response: Amazon Detective, AWS Elastic Disaster Recovery, and CloudEndure DR.

Cool insights via Fire Side Chat

AquaPay (Nitin Chavan, CEO) | IFANOW (Ronak Hindocha, CEO) | Probus (Prashant Pandey, CTO)

This was an open session that includes the host talking to the three leaders (details mentioned above) of the financial companies, let’s go ahead and see what were the major learnings from the session!

• The industrial revolution played a big part in the success of businesses and the economy. Right from the first industrial revolution with Coal in 1765 to the second industrial revolution with Gas in 1870 to the third industrial revolution with electronics and nuclear in 1969 to the fourth industrial revolution which brings internet and renewable energy in 2000.
  So, if you see in the tech world, Technology is the business!

• Knowing the two models of the business:
  Apple has revolutionized the world with its world-class products and the great way to present the same. So, it won’t be wrong to say that there are two models of business: the Apple Model and the Non-Apple Model

The Apple Model: We know the customer!
The Non-Apple Model: Customers know what they want.

• For B2B products, build ecosystems not based on happy scenarios, but based on unhappy scenarios as the stakes are high. Cloud is not just a technology, it’s fundamental to doing any business in the modern world. To prepare for the scale,
  - design a cloud architecture in a way that even with 10X growth, the cost remains the same.
  - the cloud can be a single point of failure. So, we have to design our cloud architecture in a way that will serve our business at all costs, Sky computing is a good way to proceed but the marriage between different cloud providers is critical for sky computing!

• ChatGPT and the Large language models(LLMs) are taking the world by storm with their insane capabilities to automate the existing process and assist professionals better! ***AI/ML will play a big role in Finance.
  ***In finance, improving the payment journey is the need of an hour. It’s at a very early stage, and the only way to get ahead is to

Go Big in the experimentation Mode.

• Data drives the business. Data is the new oil. Data-driven decisions are the best way to move forward and the more data you possess, the more power you hold and more data will eventually come to you based on your execution using the existing data.

As money attracts money, data attracts data!

To learn more about AWS, check out the skill builder program.

Thank you for reading along! Hope you’ve learned something new! Explore around, build something new, and ask for help whenever you are stuck even after putting in your efforts to navigate the solution.

Have a great week ahead!

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