38:12
Avoiding React Performance Pitfalls
Alex Grigoryan discusses the performance problems found and their solutions moving from Backbone/Java to React/Node.js at @WalmartLabs.
01:06:47
Java Performance Engineer's Survival Guide
Monica Beckwith provides a step-by-step approach to finding the root cause of any performance problem in a Java app, showcasing through an example a few performance tools and the performance process.
38:41
Deep Learning for Image Understanding at Scale
Stacey Svetlichnaya discusses strategies and challenges building deep learning systems for object recognition at scale, using automatic labels in Flickr image search as a case study.
44:57
Monitoring Serverless Architectures
Rafal Gancarz provides an overview of monitoring capabilities required for serverless apps -metering, logging, tracing, auditing, alerting-, and helpful AWS services.u
45:19
Do You Really Know Your Response Times?
Daniel Rolls talks about the use of histogram metrics to monitor response times, explains how reservoir sampling can help, and shares good and bad practices when monitoring response times.
38:23
Monitoring Bash Microservices at Scale
Paul Bellamy covers epic fails experienced moving to microservices using the RED method to monitor what matters, and production outages they solved with detailed telemetry.
24:05
Scaling Your Swagger-Based Web API with Google Cloud Endpoints
Guillaume Laforge presents some of the options and technical solutions to build a scalable API solution using Google Cloud.
52:02
Moving Past the Scaling Myth
Michael Feathers examines the notion of scale variant structuring and what systems design could look like without the assumption that structural reorganization at different scales is not necessary.
59:25
Achieving High Load in Advertising Technology
Peter Milne talks about the technologies used and how they are implemented to deal with the high load demanded by digital marketing. He tells some of the war stories and how problems were solved.
51:11
Scaling Instagram Infrastructure
Lisa Guo overviews Instagram's infrastructure, its history, multi-data center support, tuning uwsgi parameters for scaling, performance monitoring and diagnosis, and Django/Python upgrade.
49:46
Low Latency Trading Architecture at LMAX Exchange
Sam Adams overviews the architecture LMAX Exchange uses to deliver over $2 trillion a year through their platform, and shares their experience building a high-availability stateful system.
47:56
In-Memory Caching: Curb Tail Latency with Pelikan
Yao Yue introduces Pelikan - a framework to implement distributed caches such as Memcached and Redis. She discusses the system aspects that are important to the performance of such services.
CONTENT IN THIS BOX PROVIDED BY OUR SPONSOR
|
Find & fix app Monitor JVM health and Automatically visualize and map Flexible deployment Low production overhead
|
|
Featured Java Related Content |
Featured Blog Post
Microservices Sprawl: How Not to be Overrun
How Java’s Built-In Garbage Collection Will Make Your Life Better (Most of the Time)
The Bedrock of the Software World: C++ Programming Language
Case Studies Post
Cisco improves application visibility and business outcomes with AppDynamics
Glassdoor chooses AppDynamics to obtain clear view of performance
Citrix selects AppDynamics to monitor core applications
On-demand Webinar
Critical Capabilities for Application Performance Monitoring featuring Gartner
|
Whitepapers and Ebooks |
Top 10 Java Performance Problems
Top 5 Java Performance Metrics, Tips & Tricks
See more whitepapers and assets
|
Videos |
|
Follow us on |
