Video and slides synchronized, mp3 and slide download available at URL https://bit.ly/2IK5Gsk. John Chapin describes the nuts and bolts of building large-scale serverless applications using Java. He walks through the efficacy of a Java approach to a variety of serverless use cases, and through live examples demonstrates pragmatic approaches to developing scalable, evolvable, multi-Lambda applications. Filmed at qconlondon.com. John Chapin is a co-founder of Symphonia, an expert Serverless and Cloud Technology Consultancy based in NYC. He has over 15 years of experience as a technical executive and senior engineer. He was previously VP Engineering, Core Services & Data Science at Intent Media, where he helped teams transform how they delivered business value through Serverless technology and agile practices.

1. Serverless and Java in the Real World
@johnchapin | john@symphonia.io

2. InfoQ.com: News & Community Site
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serverless-java
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3. Purpose of QCon
- to empower software development by facilitating the spread of
knowledge and innovation
Strategy
- practitioner-driven conference designed for YOU: influencers of
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Highlights
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Presented at QCon London
www.qconlondon.com

5. Fearless AWS
Lambdas
QCon NYC 2017
https://bit.ly/symph-qcon-fearless

6. Learning Lambda
Mike Roberts
mike@symphonia.io
https://bit.ly/symph-ll

7. Agenda
1. Choosing Java for Serverless (and AWS Lambda)
2. Structuring a Serverless Java project
3. Logging and metrics
4. Building and deploying
5. Live examples

8. Choosing Java for Serverless
(and AWS Lambda)

9. AWS Lambda runtimes
• Node.js
• Python
• Java (and Scala, Clojure, Kotlin...)
• Go
• C#
• Anything else you want, via a Node.js shim

10. How do we choose a runtime?

11. Business/Technical Decision
Is there a
requirement for
long-tail, low-latency,
synchronous
operations?
Probably not Java (or C#).

12. Team Decision
Does the team
have (or want to
have) experience with a
specific runtime?
Make the team happy.

13. The best use case for Serverless Java

14. Kinesis processing
Latency tolerant
Regular, frequent invocations
Not particularly bursty
Computationally intensive

15. Asynchronous, high-throughput

16. Structuring a Serverless Java Project

17. What is a project?

19. Domain-Driven
Design
Eric Evans, 2003

20. One service = one project
• Service = bounded context (probably)
• A "service" in the AWS Serverless world might be made up
of several Lambda functions, and some associated
infrastructure.
• The "backbone" infrastructure of the system may not
belong to a specific service (but should be owned by a
single team).

22. Multi-module Maven project
• Hierarchical POM files
• Parent
• Lambdas
• Libraries
• AWS Bill of Materials
(BOM) at top-level

23. The Lambda diet
Fewer classes = faster startup
- Ruthlessly cull dependencies
- AWS libraries can be bloated!
mvn dependency:tree, sbt dependencyStats

24. Other useful libraries
• https://github.com/aws/aws-lambda-java-libs
• Recently updated, more events and Log4J2 support!
• https://github.com/symphoniacloud/lambda-monitoring
• Logging + metrics, PRs welcome!

25. Logging and Metrics

26. The Present and Future of Serverless Observability
- Yan Cui, yesterday here at QCon

27. Logging
• System.out/err goes to CloudWatch Logs
• One “log group” per Lambda (by default)
• Within “log group”, one “log stream” per container
• From CloudWatch, can aggregate/forward

28. System.out.nope
• System.out.println is bad for the normal reasons
• *Real* logging is better
• Lambda runtime can add RequestId to Log4J logs
• NEW! aws-lambda-java-log4j uses Log4J 2

29. lambda-logging
• SLF4J + Logback
• Sane default configuration w/ AWS RequestId
• Open Source (Apache 2 license)
• io.symphonia/lambda-logging “1.0.1”
• - github.com/symphoniacloud/lambda-monitoring/

30. package io.symphonia;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
public class LoggingLambda {
Logger LOG = LoggerFactory.getLogger(LoggingLambda.class);
public void handler(String input) {
LOG.info("Hello, {}", input);
}
}
START RequestId: 084c7cbf Version: $LATEST
[2017-04-02 00:32:10.486] 084c7cbf INFO i.s.LoggingLambda - Hello, John
END RequestId: 084c7cbf
REPORT RequestId: 084c7cbf Duration: 1.52 ms Billed Duration: 100 ms …

31. CloudWatch Metrics
• No built-in business metrics
• Lambda platform metrics
• Errors, Duration, Invocations, Throttles
• Naive metrics collection approach is dangerous!
• Cloudwatch has account-level API limits 🔥

32. CloudWatch Metric Filters
• Built into Cloudwatch! Scalable!
• Scrape Cloudwatch Logs data using special (finicky)
patterns
• Generates and posts Cloudwatch metrics in batch

33. lambda-metrics
• Codahale metrics and lambda-logging
• Maven plugin builds Metric Filters to scrape logs, post to
CloudWatch Metrics
• Open Source (Apache 2 license)
• io.symphonia/lambda-metrics “1.0.1”
• github.com/symphoniacloud/lambda-monitoring

34. package io.symphonia;
import com.codahale.metrics.Counter;
import io.symphonia.lambda.annotations.CloudwatchMetric;
import io.symphonia.lambda.metrics.LambdaMetricSet;
import org.slf4j.*;
public class MetricLambda {
Logger LOG = LoggerFactory.getLogger(MetricLambda.class);
private class Metrics extends LambdaMetricSet {
@CloudwatchMetric
Counter inputBytes = new Counter();
}
public void handler(String input) {
Metrics metrics = new Metrics();
metrics.inputBytes.inc(input.length());
metrics.report(LOG);
}
}

35. START RequestId: 084c7cbf Version: $LATEST
084c7cbf METRIC i.s.Lambda type COUNTER name
io.symphonia.Lambda.Metrics/inputBytes count 3
END RequestId: 084c7cbf
REPORT RequestId: 084c7cbf Duration: 1.52 ms Billed
Duration: 100 ms …
[request_id, level=METRIC, logger, type_label,
type=COUNTER, name_label,
name=”io.symphonia.Lambda.Metrics/inputBytes”,
count_label, count]

36. START RequestId: 084c7cbf Version: $LATEST
084c7cbf METRIC i.s.Lambda type COUNTER name
io.symphonia.Lambda.Metrics/inputBytes count 3
END RequestId: 084c7cbf
REPORT RequestId: 084c7cbf Duration: 1.52 ms Billed
Duration: 100 ms …
[request_id, level=METRIC, logger, type_label,
type=COUNTER, name_label,
name=”io.symphonia.Lambda.Metrics/inputBytes”,
count_label, count]

37. START RequestId: 084c7cbf Version: $LATEST
084c7cbf METRIC i.s.Lambda type COUNTER name
io.symphonia.Lambda.Metrics/inputBytes count 3
END RequestId: 084c7cbf
REPORT RequestId: 084c7cbf Duration: 1.52 ms Billed
Duration: 100 ms …
[request_id, level=METRIC, logger, type_label,
type=COUNTER, name_label,
name=”io.symphonia.Lambda.Metrics/inputBytes”,
count_label, count]

38. Building and Deploying

39. Continuous Delivery in an Ephemeral World
O'Reilly SACON NYC 2018
https://conferences.oreilly.com/software-architecture/sa-ny/public/schedule/detail/63860

40. Build pipeline
• Infrastructure as code!
• AWS CodePipeline / CodeBuild
• Separate repository
• e.g., "serverless-app-build" repository
• Cache dependencies (via CodeBuild caching)

41. Application and infrastructure
• Continuously deploy code *and* infrastructure
• Alongside the application source code
• buildspec.yml
• sam.yml

42. SAM vs Serverless Framework
• Serverless Application Model
• AWS-specific
• Different flavor of CloudFormation
• Serverless Framework
• 3rd-party, supports multiple cloud vendors
• CloudFormation under the hood (for AWS)
• Plugin architecture

43. Reproducible builds
• Maven-produced JAR files are non-deterministic
• Datetime stamp in "pom.properties"
• Other timestamps, file ordering, etc
• SAM relies on file hashes to detect updates

44. Examples
https://github.com/symphoniacloud/qcon-london-2018

45. Flash sale!
http://bit.ly/symph-qcon-2018-demo

46. In conclusion
• For the right use-case, choose the Java runtime!
• Services = multi-module Maven projects
• Log and collect metrics correctly and scalably
• Infrastructure as code, continous delivery are paramount

47. Questions?
@johnchapin | john@symphonia.io

48. Watch the video with slide
synchronization on InfoQ.com!
https://www.infoq.com/presentations/
serverless-java