Java Latency Tuning 
DZone
DECEMBER 4, 2019
Learn how to make your Java applications performance perfectly. You may also like: How to Properly Plan JVM Performance Tuning. While Performance Tuning an application both Code and Hardware running the code should be accounted for. For low latency, applications use Concurrent Mark and Sweep Algorithm — CMS or G1 GC.
Scalegrid
FEBRUARY 6, 2025
Its partitioned log architecture supports both queuing and publish-subscribe models, allowing it to handle large-scale event processing with minimal latency. Apache Kafka uses a custom TCP/IP protocol for high throughput and low latency. Apache Kafka, designed for distributed event streaming, maintains low latency at scale.
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The Netflix TechBlog
MARCH 5, 2024
If you’re interested in how we use Java at Netflix, Paul Bakker’s talk How Netflix Really Uses Java , is a great place to start. Reduced tail latencies In both our GRPC and DGS Framework services, GC pauses are a significant source of tail latencies. No explicit tuning has been required to achieve these results.
The Netflix TechBlog
JUNE 14, 2023
A single API team maintained both the Java implementation of the Falcor framework and the API Server. To determine customer impact, we could compare various metrics such as error rates, latencies, and time to render. Phase 1 Created a GraphQL Shim Service on top of our existing Monolith Falcor API.
Dynatrace
JULY 22, 2024
Traces are used for performance analysis, latency optimization, and root cause analysis. OpenTelemetry supports a variety of languages, including Java, Python, JavaScript, and more, making it accessible to most applications. Capture critical performance indicators such as request latency, error rates, and resource usage.
The Netflix TechBlog
OCTOBER 19, 2020
If we had an ID for each streaming session then distributed tracing could easily reconstruct session failure by providing service topology, retry and error tags, and latency measurements for all service calls. We chose Open-Zipkin because it had better integrations with our Spring Boot based Java runtime environment.
The Netflix TechBlog
AUGUST 22, 2019
The canary stage will determine a score based on metrics such as CPU, threads, latency, and GC pauses. Running a canary for each change and testing the AMI in production allows us to capture insights around impact on Windows updates, script changes, tuning web server configuration, among others.
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