Track: Sponsored Solutions Track I

10:35am - 11:25am

Grading Observability (Note: Not a Product Pitch!)

Nobody denies the importance of observability in modern production software: with microservices adding scale, concurrency, and frequent deploys, it’s getting harder and harder to answer even basic questions about application behavior. The conventional wisdom has been that metrics, logging and tracing are “the three pillars” of observability, yet organizations check these boxes and still find themselves grasping at straws during emergencies. The problem is that metrics, logs, and traces are just data – if what we need is a car, all we’re talking about is the fuel. We will continue to disappoint ourselves until we reframe observability around two fundamental activities:

(1) detection and

(2) refinement.

For effective observability, “detection” must be both robust and precise, overcoming cardinality concerns amid massive data volumes. “Refinement” revolves around rapid hypothesis testing: we must understand global context across service boundaries, decipher the side-effects of contention under peak load, and present everything with historical reference points to understand what’s changed and what’s normal behavior. In this session, we’ll summarize the contemporary observability dogma, then present a new observability scorecard for objectively reasoning about and assessing observability solutions for modern distributed systems.

11:50am - 12:40pm

Observability: The Health of Every Request

A popular approach to monitoring looks at the health of systems and infrastructure components first and then the things that run inside of it. I'd like to offer a different perspective that it is the health of every request that truly matters. In this session, we'll explore what that means, strategies around observability, tooling to that helps us find out request health, and the changing landscape of "external monitoring" to "internal observation".

1:40pm - 2:30pm

Assisted Warmup with the Zing JVM

Over the last 20 years of Java JIT compiler development, the focus has been on generating good throughput over the long run. The Zing VM is designed to eliminate most of the cold warmup time. In this talk Ivan will present three JIT compiler technologies that are designed to reach peak throughput from the first transaction. The talk also outlines the patterns in Java code that make this task difficult and tips on how to write AOT-friendly code.

2:55pm - 3:45pm

Ballerina - Cloud Native Programming Language

Crazy customer demand has caused companies like Google and Amazon to build massively disaggregated architectures in order to scale. Massively disaggregated approaches like microservices, serverless, and APIs are becoming the norm for us all. These disaggregated components are network accessible as programmable endpoints. The apps we will write increasingly depend upon these endpoints. Integration is the discipline of resilient communication between endpoints. It isn’t easy. The challenges include compensation, transactions, events, circuit breakers, discovery, and protocol handling, and mediation.

Ballerina makes it easy to write resilient services that orchestrate and integrate across distributed endpoints. It’s a language that understands protocols, endpoints, transactions, workers, JSON, XML, asynchrony, and tainted data as first-class constructs.

Ballerina is a compiled language with its own VM technology. Services execute as servers, microservices, and serverless functions packaged for deployment into any infrastructure including Kubernetes.

It’s the first language that understands the architecture around it - the compiler is environment aware, and includes or integrates circuit breakers, identity servers, API gateways, and message brokers.

This session will cover Ballerina’s language and runtime model while building a variety of integrations. We’ll also cover how the Ballerina open source community operates and how you can get involved.

4:10pm - 5:00pm

Autonomous Microservices

Everybody loves microservices, but it's difficult to do it right. Distributed systems are much more complex to develop and maintain. Over time, you may even miss the simplicity of old monoliths. In this session, we'll look at a combination of infrastructure, architecture, and design principles to bulletproof your microservices and make them easy to maintain with a combination of high scalability, elasticity, fault tolerance, and resilience.

This session will include a discussion of microservices blueprints like: asynchronous communications, avoiding cascading failures in synchronous calls, and how distributed NoSQL databases become valuable in terms of scalability and performance when combined with your microservices in a Kubernetes deployment.

5:25pm - 6:15pm

3 Common Pitfalls in Microservice Integration

Integrating microservices and taming distributed systems is hard. In this talk, I will present three challenges I've observed in real-life projects and discuss how to avoid them.

Communication is complex. With everything being distributed failures are normal so you need sophisticated failure handling strategies (e.g. stateful retry). Asynchronicity requires you to handle timeouts. This is not only about milliseconds, systems get much more resilient when you can wait for minutes, hours or even longer.

Distributed transactions cannot simply be delegated to protocols like XA. So you need to solve the requirement to retain consistency in case of failures.

I will not only use slides but also demonstrate concrete source code examples available on GitHub.