Went to the AWS Summit 2018, Singapore yesterday. Regretfully those pictures that were taken were meant for reporting purposes only. Should have thought of capturing more of the entire experience. Anyways…
- The commencement of a FREE & WICKED Summit.
Speaker was sharing about how companies from big to small have used AWS services to undergo digital transformation. FINRA is one of their biggest customers, which started undergoing digital transformation 5 years ago and now they are processing 500 billion transactions daily.
AWS Snowball is a new device for data transportation meanwhile AWS Snowball Edge has onboard computation capability. For an example, Oregon State University uses it for their maritime exploration. They could run AWS Lambda onsite and offline.
AWS has 360 encryption capability which ensure the security of data.
AWS SageMaker builds, trains and deploys Machine Learning models, AWS Lex is speech-to-text and Natural Language Processing ( NLP ) service, meanwhile AWS Polly is text-to-speech, single message, multiple languages.
AWS also offers elastic GPUs. AWS EKS is managed Kubernetes service which utilizes AWS containers hosting technology. AWS Fargate is container hosting without hosting servers or clusters which is parent to AWS EKS and Docker version of AWS EKS that is AWS ECS.
FinAccel allows retail customers to purchase on credit ratings. Their app revolves around 2 real time engines;
i) Real time credit risk assessment,
ii) Real time transaction.
3 steps of using their app;
ii) Connecting social media, bank, e-commerce accounts and etc, get approved
iii) Use the app like credit card.
Users can payback within 30 days without any charge or all the way up to 12 months installment plan. They are trying to solve lack of access to retail credit in Indonesia. There is only 10 % of middle class, around 7 to 8 million people in actual figure, has access to any unsecured credit product from banking institution, hence they turn to expensive consumer finance companies which charge them an arm and a leg in order to purchase something offline.
The massive drivers for retail credit are
i) the young population with 50% of the total being younger than 30 years old,
ii) High smart phones penetration, around 110 millions to 120 millions Indonesian carry a smart phone.
Indonesia is the perfect storm to the culmination of a very large young population which is mobile first, but denied access to credit.
2 major challenges when they first started up;
i) Scalable processing of unstructured data,
ii) High frequency, low latency transaction.
Fraud engine was also deploy to detect fraud in real time.
4 Business layers;
i) Application layer: OCR and credit risk approval platform,
ii) Transaction engine: Allows users to buy at e-commerce stores.
iii) Data layer: ETL, real-time data processing at 3 different points, 1) Apply, 2) Buy, 3) Collect money from user,
iv) Integration layers: connects to endpoints on both sides, users and vendors. At technical level, they have completely moved on from ec-2 instances to AWS serverless ecosystem, in microservices manner.
- 21st century modern architecture.
3 demos in 30 minutes.
i) Serverless Map Reduce
If we look at our usage of clusters, usually its only active during working hours. There’s a high wastage for the remaining 16 hours. Map Reduce is resource heavy application so a massive cluster will be required shall we decide to use servers.
ii) Selfie Challenge
The challenge is about people taking selfies that are the most relevant to various emotion categories.
iii) Peta Bencana
Crowd Source information dissemination regarding natural disaster.
Those demo was all about serverless and the message they were trying to share was probably serverless is especially useful when the usage is sporadic, intermittent like campaigns or events which would see a surge.
- Architectures in the cloud era.
5 pillars of modern day architecture:
i) Operational Excellence
360 monitoring, automation, learning from experience
All level. Trace everything. Automate responses to security events. Secure system at application, data and OS level. Automate security best practices
iii) Performance Efficiency
Use up-to-date technologies. Deploy system globally for lower latency. Use services rather than servers. Try various configurations for optimal performance. Innovation at faster pace.
Test recovery procedures, automate recovery.
v) Cost Optimization
Use managed services, do not invest in data centers, pay as you go policy for cloud.
- AWS Lambda, AWS Step Functions and Data Dog: A symphony by Data Dog.
Alex Poe was a lawyer but is now a lead solutions engineer. DataDog is SaaS-based monitoring and analytics infra. He was explaining about Single Responsibility Principle which was demonstrated through AWS Lambda, FaaS. AWS Lambda then could be orchestrated using AWS Step Functions which act like schedulers such as Azkaban and Airflow. Step functions could be built using Serverless Framework which is compatible with various cloud providers.
- You don’t need a server for that!
Long story short, there are 3 different serverless architectures, i) Synchronous (Serial), ii) Asynchronous (Parallel) and iii) Stream-based. AWS API Gateway will serve as a front from AWS Step Functions.
- Automating Serverless Deployments using GitHub, AWS Lambda and AWS CodeStar
AWS Codestar helps with CI/CD which I am not knowledgeable enough to comment. Basically it was about automating serverless deployments using Github and AWS Codestar integration.
- Getting Smarter at the Edge
AWS IoT and AWS Greengrass. AWS Greengrass is intranet IoT. Rotimatic has a very cool use case of IoT. Rotimatic basically makes roti automatically. Users will have to put in flour, water and spices and the machine will make the roti. What’s innovative was recipes in machine-form setting could be uploaded and downloaded to Rotimatic, e.g.: specifying heat, time, amount of ingredients and users could then have a new roti to try. The machine also allows user to give feedback on the roti made. Predictive maintenance is another outstanding feature.
- More Containers, Less Operations
AWS Elastic Container Registry is Docker registry ( Repository ) on AWS, AWS Elastic Container Service runs Docker images serverlessly. AWS CodeCommit is like Bitbucket or GitHub, AWS CodeBuild is like Jenkins, AWS CodePipeline is the process of unit, integration, system, acceptance testing, etc ( refer CI/ CD ). AWS Elastic Service for Kubernetes is just like AWS ECS but Kubernetes version. AWS Fargate is their parent.