Automatically Detect the Top Performance & Scalability Issues in Distributed Architectures

This session teaches how to detect common performance and scalability issues in distributed applications, including N+1 calls, payload floods, tight coupling, and inefficient dependencies. It demonstrates automated CI/CD detection and remediation using distributed traces, Keptn, and SLI/SLO-based quality gates.

Syllabus

Intro
Distributed Trace Example from StepStone (AWS Summit Berlin 2019)
In distributed architectures we need to answer: Who is depending on me? What is the risk of change?
N+1 Call Pattern across distributed "Product Service"
LANDBAY
Cascading N+1 Query Pattern: This is a single End-2-End Distributed Trace
Payload Flood: "Doc Creation" sequential across distributed services
Refactor: Only send relevant data to specialized services
Keptn from 10000ft: Declarative Workflows + Event-Triggered Actions
Root Cause: Lengthy manual approval in existing delivery pipelines
Inspired by Dynatrace's internal „Performance Signature as Code
SLI/SLO-based evaluation implementation in Keptn
Solution: Automate Approval through SLI/SLO-based Quality Gates
Demo: Automated SLI/SLO Validation based on Dynatrace Dashboards
Keptn-Closed-Loop Remediation with Keptn 0.7
Automate Distributed Problem Detection & Remediation