Major Outages in Major Enterprises Payara Conference

This document provides an overview of Node.js application performance analysis and optimization as well as distributed system design. It discusses analyzing and optimizing CPU, memory, file I/O and network I/O usage. It also covers profiling Node.js applications using tools like Linux profiling tools, Node.js libraries, and V8 profiling tools. Lastly it discusses designing distributed systems using single machine and cluster approaches.

Talk for YOW! by Brendan Gregg. "Systems performance studies the performance of computing systems, including all physical components and the full software stack to help you find performance wins for your application and kernel. However, most of us are not performance or kernel engineers, and have limited time to study this topic. This talk summarizes the topic for everyone, touring six important areas: observability tools, methodologies, benchmarking, profiling, tracing, and tuning. Included are recipes for Linux performance analysis and tuning (using vmstat, mpstat, iostat, etc), overviews of complex areas including profiling (perf_events) and tracing (ftrace, bcc/BPF, and bpftrace/BPF), advice about what is and isn't important to learn, and case studies to see how it is applied. This talk is aimed at everyone: developers, operations, sysadmins, etc, and in any environment running Linux, bare metal or the cloud. "

Uncover the hidden challenges that plague production environments in this eye-opening session. Join us as we explore the five most common performance problems that emerge in live systems. Gain invaluable insights into detecting these issues early on, before they wreak havoc on your operations. Discover practical solutions that empower you to address these challenges head-on, ensuring optimal performance and seamless user experiences.

Discover the Top 5 Java Performance Problems in our presentation. Learn about common issues in Java coding and how to fix them. This guide helps you make your Java applications run better and faster.

The document summarizes a lightning talk given at the Chicago Java User Group Meetup on January 14, 2016. The presenter discussed finding a suitable garbage collector for OpenTSDB, an open source time series database. Tests were conducted using three different garbage collectors: Parallel GC, CMS GC, and G1 GC. Based on analysis of GC logs and metrics, G1 GC was found to perform best by allowing more short-lived objects to be handled in the young generation, leading to more efficient garbage collection.

Talk by Brendan Gregg for USENIX LISA 2019: Linux Systems Performance. Abstract: " Systems performance is an effective discipline for performance analysis and tuning, and can help you find performance wins for your applications and the kernel. However, most of us are not performance or kernel engineers, and have limited time to study this topic. This talk summarizes the topic for everyone, touring six important areas of Linux systems performance: observability tools, methodologies, benchmarking, profiling, tracing, and tuning. Included are recipes for Linux performance analysis and tuning (using vmstat, mpstat, iostat, etc), overviews of complex areas including profiling (perf_events) and tracing (Ftrace, bcc/BPF, and bpftrace/BPF), and much advice about what is and isn't important to learn. This talk is aimed at everyone: developers, operations, sysadmins, etc, and in any environment running Linux, bare metal or the cloud."

This document provides an overview of Linux performance monitoring tools including mpstat, top, htop, vmstat, iostat, free, strace, and tcpdump. It discusses what each tool measures and how to use it to observe system performance and diagnose issues. The tools presented provide visibility into CPU usage, memory usage, disk I/O, network traffic, and system call activity which are essential for understanding workload performance on Linux systems.

The document discusses garbage collection (GC) log analysis. It begins with an overview of key performance indicators (KPIs) related to GC and the anatomy of different GC log formats. It then introduces the gceasy.io tool for analyzing GC logs and provides examples of analyzing real-world GC logs to identify issues like long GC pauses, poor throughput, and memory leaks. The document aims to help understand how to extract useful insights from GC logs.

The document provides an overview of how to read and understand garbage collection (GC) log lines from different Java vendors and JVM versions. It begins by explaining the parts of a basic GC log line for the OpenJDK GC log format. It then discusses GC log lines for G1 GC and CMS GC in more detail. Finally, it shares examples of GC log formats from IBM JVMs and different levels of information provided. The document aims to help readers learn to correctly interpret GC logs and analyze GC behavior.

This presentation was given to the system adminstration team to give them an idea of how GC works and what to look for when there is abottleneck and troubles.

The document discusses various tools and techniques for Java profiling and diagnostics. It describes JVM diagnostic interfaces like JMX and JVMTI, the Attach Protocol, performance counters, and flight recording. It also summarizes tools like SJK and BTrace that provide command line interfaces for profiling, analyzing garbage collection, tracking CPU usage, working with heap dumps, and more. These tools exploit JVM interfaces and allow ad-hoc instrumentation to gather detailed insight into a running JVM.

These slides may not be self explanatory. Updated for the benefit of attendees of Colombo Java Meetup keynote.

A brief history of Instagram's adoption cycle of the open source distributed database Apache Cassandra, in addition to details about it's use case and implementation. This was presented at the San Francisco Cassandra Meetup at the Disqus HQ in August 2013.

Michael Hennecke, Chief Technologist, HPC Storage and Networking, Lenovo DAOS User Group event, November 2020.

In this webinar, following topics were discussed 1) Production outages that happened in major enterprises in their JVM applications. 2) Analyzing the actual thread dumps, heap dumps, GC logs, and other artifacts captured at the time of the problem.

The Open Street Map project provides invaluable data that keeps driving users toward the PostGIS and PostgreSQL stacks. Loading today’s full Planet data set takes a 120GB XML file and unrolls it into over a terabyte of database data. Crunchy’s benchmark labs have followed the expansion of that Planet data over the last six database releases, as the re-ignition of the CPU wars combined with parallel execution features landing in the database. We’ll take a look at that data evolution, which server configurations worked, and which metrics techniques still matter in the all SSD era.

Netflix tunes Amazon EC2 instances for maximum performance. In this session, you learn how Netflix configures the fastest possible EC2 instances, while reducing latency outliers. This session explores the various Xen modes (e.g., HVM, PV, etc.) and how they are optimized for different workloads. Hear how Netflix chooses Linux kernel versions based on desired performance characteristics and receive a firsthand look at how they set kernel tunables, including hugepages. You also hear about Netflix's use of SR-IOV to enable enhanced networking and their approach to observability, which can exonerate EC2 issues and direct attention back to application performance.

Are you ready to unlock the secrets hidden within Java thread dumps? Join us for a hands-on session where we'll delve into effective troubleshooting patterns to swiftly identify the root causes of production problems. Discover the right tools, techniques, and best practices while exploring *real-world case studies of major outages* in Fortune 500 enterprises. Engage in interactive lab exercises where you'll have the opportunity to troubleshoot thread dumps and uncover performance issues firsthand. Join us and become a master of Java thread dump analysis!

Even though at surface level ‘java.lang.OutOfMemoryError’ appears as one single error; underlyingly there are 9 types of OutOfMemoryError. Each type of OutOfMemoryError has different causes, diagnosis approaches and solutions. This session equips you with the knowledge, tools, and techniques needed to troubleshoot and conquer OutOfMemoryError in all its forms, ensuring smoother, more efficient Java applications.

In our everyday Java programming, we rely on familiar APIs without fully realizing their hidden performance impacts. This session aims to unveil the concealed performance aspects of common Java APIs and shed light on how they can influence your application's performance. Join us to explore the unnoticed performance effects of these APIs and learn strategies to mitigate their impact. Whether you're a seasoned developer or new to Java, this paper equips you with essential knowledge to optimize your applications.

Embark on a journey into the depths of java.lang.OutOfMemoryError as we unravel its complex nature. Discover the nine distinct faces of this memory-related challenge and gain valuable insights into their unique causes and solutions. This session equips you with the knowledge, tools, and techniques needed to troubleshoot and conquer OutOfMemoryError in all its forms, ensuring smoother, more efficient Java applications.