Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
How we built an AI code reviewer with serverles...
Search
Yan Cui
February 12, 2025
Technology
0
84
How we built an AI code reviewer with serverless and Bedrock
Slides for my talk at the Serverless London meetup on 12-Feb-2025
Yan Cui
February 12, 2025
Tweet
Share
More Decks by Yan Cui
See All by Yan Cui
Money-saving tips for the frugal serverless developer (AWS Community Summit)
theburningmonk
1
150
Money-saving tips for the frugal serverless developer
theburningmonk
1
730
Why the fuzz about serverless (with CompassDigital)
theburningmonk
0
97
Money-saving tips for the frugal serverless developer
theburningmonk
0
93
Efficient patterns for serverless development (AWS Summit London)
theburningmonk
0
120
7 ways to solve Lambda cold starts
theburningmonk
0
56
Saving Money on Serverless: Common Mistakes and How to Avoid Them
theburningmonk
0
50
3 Ways to Improve Serverless Performance
theburningmonk
0
40
Smart and efficient ways to test serverless architectures
theburningmonk
1
280
Other Decks in Technology
See All in Technology
エンジニアのキャリアパスと、 その中で自分が大切にしていること
noteinc
4
3.5k
ブレインパッド_20250311_AIxIoTビジネス共創ラボ_第2回勉強会.pdf
iotcomjpadmin
0
210
ランチの間に GitHub Copilot Agent が仕事を終わらせてくれた話
bicstone
2
390
OCI Oracle Database Services新機能アップデート(2024/12-2025/02)
oracle4engineer
PRO
2
120
Scala meets WebAssembly
tanishiking
0
150
AIxIoTビジネス共創ラボ紹介_20250311.pdf
iotcomjpadmin
0
200
Amazon Bedrock Knowledge basesにLangfuse導入してみた
sonoda_mj
2
420
セキュリティグループの”タイプ”を改めて考えてみる
masakiokuda
0
140
Webブラウザのセキュリティ対策に役立つぞ!!~DevToolsの使い方~
masakiokuda
0
100
AI_Agent_の作り方_近藤憲児
kenjikondobai
19
5.1k
書籍『入門 OpenTelemetry』 / Intro of OpenTelemetry book
ymotongpoo
10
680
いまから始めるAWS CDK 〜モダンなインフラ構築入門〜/iac-night-cdk-introduction
tomoki10
6
2.1k
Featured
See All Featured
The Art of Programming - Codeland 2020
erikaheidi
53
13k
個人開発の失敗を避けるイケてる考え方 / tips for indie hackers
panda_program
101
18k
I Don’t Have Time: Getting Over the Fear to Launch Your Podcast
jcasabona
32
2.2k
RailsConf & Balkan Ruby 2019: The Past, Present, and Future of Rails at GitHub
eileencodes
134
33k
Why You Should Never Use an ORM
jnunemaker
PRO
55
9.2k
KATA
mclloyd
29
14k
Rails Girls Zürich Keynote
gr2m
94
13k
Designing on Purpose - Digital PM Summit 2013
jponch
117
7.2k
Responsive Adventures: Dirty Tricks From The Dark Corners of Front-End
smashingmag
251
21k
Build The Right Thing And Hit Your Dates
maggiecrowley
34
2.6k
Keith and Marios Guide to Fast Websites
keithpitt
411
22k
For a Future-Friendly Web
brad_frost
176
9.6k
Transcript
How we built an AI Code Reviewer with Serverless and
Bedrock
Yan Cui http://theburningmonk.com @theburningmonk AWS user since 2010
Yan Cui http://theburningmonk.com @theburningmonk running serverless in production since 2016
Developer Advocate @ Yan Cui http://theburningmonk.com @theburningmonk
Yan Cui http://theburningmonk.com @theburningmonk independent consultant
None
evolua.io Demo
Architecture
API Gateway EventBridge Webhook
API Gateway DynamoDB Bedrock EventBridge Webhook
API Gateway DynamoDB Bedrock EventBridge Webhook
API Gateway DynamoDB Bedrock EventBridge Webhook evolua.io
None
API Gateway DynamoDB Bedrock EventBridge Webhook AppSync evolua.io
API Gateway DynamoDB Bedrock EventBridge Webhook AppSync evolua.io
None
API Gateway DynamoDB Bedrock EventBridge Webhook AppSync evolua.io Authoriser
API Gateway DynamoDB Bedrock EventBridge Webhook AppSync evolua.io Authoriser
API Gateway DynamoDB Bedrock EventBridge Webhook AppSync evolua.io Authoriser
API Gateway DynamoDB Bedrock EventBridge Webhook AppSync evolua.io Authoriser
API Gateway DynamoDB Bedrock EventBridge Webhook AppSync evolua.io Authoriser
Challenges (for an AI code reviewer) Handling sensitive data for
customers
Challenges (for an AI code reviewer) Large fi les. Large
PRs with many fi les. Handling sensitive data for customers
Why Bedrock?
Security
Security Data is encrypted at rest.
www.wiz.io/blog/wiz-research-uncovers-exposed-deepseek-database-leak
aws.amazon.com/bedrock/faqs
Security Data is encrypted at rest. Inputs & Outputs are
not shared with model providers. Inputs & Outputs are not used to train other models.
API Gateway DynamoDB Bedrock EventBridge Webhook AppSync evolua.io Authoriser Fallback
Primary
privacy.anthropic.com/en/articles/7996885-how-do-you-use-personal-data-in-model-training
Serverless
Serverless Usage-based AND provisioned throughput pricing
None
None
1M Input Tokens 1M Output Tokens $0.14 v3 r1 $0.28
$0.55 $2.19 Sonnet $3.75 $15.0 Haiku $0.80 $4.00
Very cost ef fi cient!
Very cost ef fi cient! Data is stored in China.
Very cost ef fi cient! Data is stored in China.
Data might be used to train other models.
www.wiz.io/blog/wiz-research-uncovers-exposed-deepseek-database-leak
Very cost ef fi cient! Data is stored in China.
Data might be used to train other models. Operationally immature.
None
No token-based pricing yet
No token-based pricing yet “GPU-based instance type like ml.p5e.48xlarge is
recommended”
ml.p5e.48xlarge 💰💰💰💰💰💰💰💰💰💰 💰💰💰💰💰💰💰💰💰💰 💰💰💰💰💰💰💰💰💰💰 💰💰💰💰💰💰💰💰💰💰 💰💰💰💰💰💰💰💰
Other capabilities Guardrails Knowledge base (managed RAG) Agents Cross-region inference
Model evaluations
None
None
None
API Gateway DynamoDB Bedrock EventBridge Webhook AppSync evolua.io Authoriser Fallback
Primary
Lessons
Webhook
Webhook Analyse changes
Webhook Analyse changes Feedback
Condensed view…
None
Lambda timed out after 15 mins
Succeeded on automatic retry
Webhook Analyse changes Feedback LLM limits GitHub limits AWS limits
Lesson: AI is 10% of the problem
None
Reasoning ability
Context window Max response tokens API rate limit Reasoning ability
Context window Max response tokens API rate limit Reasoning ability
Cost Performance
Context window Max response tokens API rate limit Reasoning ability
Cost Performance Important selection criteria for LLMs
Doing cool AI stuff! Working around AI limits
Doing cool AI stuff! Working around AI limits Stop playing
with my bowl…
Context window Max response tokens API rate limit Reasoning ability
Cost Performance
Claude 3.5 Sonnet’s default throughput is 50 per minute
Claude 3.5 Sonnet’s default throughput is 50 per minute Can
be raised to 1,000 per minute
Claude 3.5 Sonnet’s default throughput is 50 per minute Can
be raised to 1,000 per minute Bedrock has cross- region inference
Mitigate API rate limit Raise account limits. Use Bedrock cross-region
inference.
Mitigate API rate limit Raise account limits. Use Bedrock cross-region
inference. Limit no. of parallel requests per PR.
Mitigate API rate limit Raise account limits. Use Bedrock cross-region
inference. Limit no. of parallel requests per PR. Fallback to Anthropic & less powerful models (Claude 3 Sonnet, Claude 3.5 Haiku)
Future work: incorporate other models (Nova, DeepSeek, etc.)
Future work: incorporate other models (Nova, DeepSeek, etc.) Also good
for cost control!
Lesson: LLMs are still quite expensive
None
Dif fi cult to build a sustainable and competitive business
Cost control Only analyse changed lines.
Cost control Only analyse changed lines. Good for cost control
Good for UX
Cost control Only analyse changed lines. Limit free users to
few PRs per month.
API Gateway DynamoDB Bedrock EventBridge Webhook
API Gateway DynamoDB Bedrock EventBridge Webhook Built-in retries & DLQ
Lambda timed out after 15 mins
Lambda timed out after 15 mins Reprocess fi les on
retry…
Lambda timed out after 15 mins Reprocess fi les on
retry… Duplicated side- effects (e.g. Github comments)
Cost control Only analyse changed lines. Limit free users to
few PRs per month. Use checkpoints to avoid re-processing fi les on retries
const issues = await executeIdempotently( `${event-id}-${filename}-analyze`, () => analyzeFile(file) );
... await executeIdempotently( `${event-id}-${filename}-add-gh-comment`, () => addReviewComment(filename, comment) );
Webhook Analyse changes Feedback Why not Step Functions?
Webhook Analyse changes Feedback Why not Step Functions? Checkpoints is
just easier 🤷
Lesson: Latency is a challenge
Models take 10s of seconds to analyse each fi le
Wasted CPU cycles in Lambda
Future work: try other models
Future work: make use of these CPU cycles
Lesson: Be ware of hallucinations
“Give me JSON in this format”
None
“Give me JSON in this format” “Nope!”
None
Non-existent codes, invalid URLs
Non-existent line numbers
Future works
Go to evolua.io to try it out. We’d love your
feedback!
Questions?