BUILDERS
Fullstack AI Engineering for GenAI Applications
ANDREAS KOLLEGGER
Lead for GenAI Innovation at Neo4j
AI Engineering is the new skillset of building solutions using LLMs. While everyone is experimenting with GenAI, everything is moving so fast that it can be intimidating to get started. This talk will guide beginners through the landscape, offering advice about where to start and how to progress.
ABSTRACT
SESSION 1: 09.40
Lambda Performance Tuning
luca mezzalira
Principal Serverless Specialist Solutions Architect at Amazon Web Services (AWS) | O'Reilly Author
A collection of techniques that will enable the audience to heavily optimise their Lambda functions. This talk will reflect some of the optimisations present in my post: https://shorturl.at/mEPV4 Plus new suggestions like a new extension I’m working on right now for remotely loading ES modules
SESSION 2: 10.30
SESSION 3: 11.30
Running billions of Agent-Based Modelling Simulations on EKS and visualising the results to predict employees career progression
Mani Kolbe & James Bradbury
Cognizant
Money-saving tips for the frugal serverless developer
YAN CUI
Independent consultant at theburningmonk.com
Dive into the world of serverless and explore common, costly mistakes and learn actionable tips for cutting down waste and reducing your AWS bill.
Whether you’re looking to cut down on CloudWatch costs or improve cost-efficiency for your serverless application, we’ve got some helpful tips for you.
SESSION 4: 12.20
Detect operational anomalies in Serverless applications with ML-based Amazon DevOps Guru
Vadym Kazulkin
Head Of Development at ip.labs, AWS Community Builder
In this talk we’ll use a standard serverless application that uses API Gateway, Lambda, DynamoDB, SQS, SNS, Kinesis, Step Functions, Aurora (Serverless) (and other AWS-managed services). We’ll explore how Amazon DevOps Guru recognizes operational issues and anomalies like increased latency and error rates (timeouts, throttling and increased latency). We will also explore DevOps Guru “Proactive Insights” which recognize configurational anti-patterns like missing failure destination on Kinesis Data Streams or DLQ on SQS or over-provisioning of AWS services like DynamoDB tables. We’ll also integrate DevOps Guru with PagerDuty to provide even better incident management.
Amazon DevOps Guru analyzes data like application metrics, logs, events, and traces to establish baseline operational behavior and then uses ML to detect anomalies. The service uses pre-trained ML models that are able to identify spikes in application requests, so it knows when to alert and when not to.
SESSION 5: 14.10
AWS No Code Challenge
CHRIS DOBSON
Senior software engineer: Trustpilot
AWS Solutions Architect Pro | AWS DevOps Engineer Pro | AWS Security Specialty | AWS Subject Matter Expert
As AWS has been adding more and more direct service integrations I thought it would be interesting to try and create a service using just service integrations without writing any code. Spoiler it was!
Rather than just a CRUD API I recreated one of my teams actual production workloads including an API, workflow orchestration and events.
This talk will show how I built the workflow using these AWS services:
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API Gateway
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DynamoDB
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EventBridge Bus
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EventBridge Pipes
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EventBridge Scheduler
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SNS
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SQS
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Step Functions
SESSION 6: 15.00
SESSION 7: 16.00
Zero to Production Serverless: 8-Week Real-World Journey
Martyn Kilbryde
Head of Engineering at Chemist4U
A large contract is signed and you are given the challenge to integrate two businesses and build a customer portal capable of taking payments, along with an admin portal. Could you and your team confidently deliver on time?
In this session, you’ll see this real-world project journey, from concept to production in only eight weeks. From choosing the technologies, utilising Infrastructure-as-Code, to the challenges of rapid development with a small team. Expect practical insights, mistakes, tips, and how using the right technologies and development process can deliver results fast.
