Dynatrace

SEPTEMBER 29, 2021

Container technology is very powerful as small teams can develop and package their application on laptops and then deploy it anywhere into staging or production environments without having to worry about dependencies, configurations, OS, hardware, and so on. Anomaly detection and precise root-cause-analysis for fast remediation.

Open Source 309

Open Source Traffic DevOps Cloud 309

Scalegrid

JANUARY 25, 2024

These can help you ensure your system’s health and quickly perform root cause analysis of any performance-related issue you might be encountering. It’s important to note that recommended throughput levels may vary depending on factors such as operating system type, network bandwidth availability, and hardware quality.

Metrics 130

Metrics Monitoring Latency Cache 130

SQL Performance

JANUARY 23, 2020

Tom Davidson, Opening Microsoft's Performance-Tuning Toolbox SQL Server Pro Magazine, December 2003. Waits and Queues has been used as a SQL Server performance tuning methodology since Tom Davidson published the above article as well as the well-known SQL Server 2005 Waits and Queues whitepaper in 2006. The Top Queries That Weren't.

Tuning 115

Tuning Servers Monitoring Hardware 115

Dynatrace

MAY 1, 2020

This is especially the case with microservices and applications created around multiple tiers, where cheaper hardware alternatives play a significant role in the infrastructure footprint. Stay tuned for more announcements on this topic. Stay tuned for more details. The plugin module is not available at this time.

Java 133

Java Hardware Tuning Metrics 133

Percona

OCTOBER 18, 2023

Resource allocation: Personnel, hardware, time, and money The migration to open source requires careful allocation (and knowledge) of the resources available to you. Evaluating your hardware requirements is another vital aspect of resource allocation. Look closely at your current infrastructure (hardware, storage, networks, etc.)

Open Source 94

Open Source Database Hardware Strategy 94

Dynatrace

OCTOBER 26, 2020

With the rich set of features in Dynatrace for diagnostics (check out my Advanced Diagnostics with Dynatrace YouTube Tutorial ) it speeds up analysis and diagnostics for Christian significantly. So stay tuned. If you want to replicate Christians work – here are the software and hardware specs: Hardware.

Innovation 158

Innovation Metrics Hardware Games 158

Percona

AUGUST 27, 2018

assigning to a specific CPU) is a manageable resource, represented by the concept of “virtual CPU” as a term that includes CPU cores, hyperthreads, hardware threads, and so forth. We can split the task of having a good Resource Group implementation into three steps: You must perform an analysis of what you want to control.

Tuning 45

Tuning Virtualization Testing Servers 45

Dynatrace

OCTOBER 28, 2021

Once established, chaos engineering becomes an effective way to fine tune service-level indicators and objectives, improve alerting, and build more efficient dashboards, so you know you are collecting all the data you need to accurately observe and analyze your environment.

Engineering 233

Engineering Entertainment Cloud Infrastructure 233

Alex Podelko

OCTOBER 20, 2016

System’s configuration is not given anymore and often can’t be easily mapped to hardware. As already mentioned, performance testing is rather a performance engineering process (with tuning, optimization, troubleshooting and fixing multi-user issues) eventually bringing the system to the proper state rather than just testing.

Performance Testing 100

Performance Testing Architecture Testing Performance 100

Adrian Cockcroft

JUNE 21, 2022

I became the Sun UK local specialist in performance and hardware, and as Sun transitioned from a desktop workstation company to sell high end multiprocessor servers I was helping customers find and fix scalability problems. We had specializations in hardware, operating systems, databases, graphics, etc. that a lot of people used.

Tuning 52

Tuning Benchmarking Engineering C++ 52

Brendan Gregg

SEPTEMBER 25, 2021

This was a weird problem to think about: Time itself had now become a resource and target of performance analysis. As a Xen guest, this profile was gathered using perf(1) and the kernel's software cpu-clock soft interrupts, not the hardware NMI. I'm including this step as a reminder for anyone following this kind of analysis.

Speed 126

Speed Java AWS Virtualization 126

Sutter's Mill

NOVEMBER 11, 2023

0] would be easy to call “obvious” in hindsight, but it’s far from the only option and this paper’s analysis shows a thorough consideration of alternatives, including their effects on existing and future code and future language evolution. Seeing only the end result of T.[0] This is that library.

C++ 107

C++ Lambda Network Programming 107

The Morning Paper

MAY 21, 2019

Using zswap means that no new hardware solutions are required, enabling rapid deployment across clusters. These are used to perform offline analysis for potential memory savings under different cold-age thresholds. ML-based auto-tuning. Memory pages moved to zswap are compressed (but the compressed pages stay in memory).

Software 78

Software Software Google Hardware 78

Adrian Cockcroft

JUNE 2, 2023

FSD has a sense of purpose, a planning capability, has real time agency and responds to its environment via an ego model, predicting the behavior of pedestrians and other road users, and is being tuned to drive in a very human way, so that other road users interact with it as a predicable normal driver.

Social Media 98

Social Media Innovation Open Source Entertainment 98

Dotcom-Montior

OCTOBER 12, 2017

Result Analysis. Deep dive analysis of correlated results in Dynatrace. Dynatrace – Deep dive analysis. Dynatrace – Deep dive analysis Apply the filter loadtest and get the relevant requests Open the service-flow and understand the communication pattern. Big picture, start the performance analysis from there.

AWS 40

AWS Tuning Monitoring Servers 40

Dynatrace

NOVEMBER 20, 2019

The IBM Z platform is a range of mainframe hardware solutions that are quite frequently used in large computing shops. Typically, these shops run the z/OS operating system, but more recently, it’s not uncommon to see the Z hardware running special versions of Linux distributions. Stay tuned for more announcements on this topic.

Availability 32

Availability Hardware Java Tuning 32

Adrian Cockcroft

NOVEMBER 13, 2023

In the simplest case, you have a growing workload, and you optimize it to run more efficiently so that you don’t need to buy or rent additional hardware, so your carbon footprint stays the same, but the carbon per transaction or operation is going down. I’ve written before about how to tune out retry storms.

Energy 52

Energy Cloud Traffic Transportation 52

Dynatrace

AUGUST 8, 2019

The IBM Z platform is a range of mainframe hardware solutions that are quite frequently used in large computing shops. Typically, these shops run the z/OS operating system, but more recently, it’s not uncommon to see the Z hardware running special versions of Linux distributions. Stay tuned for more announcements on this topic.

Availability 25

Availability Hardware Java Tuning 25

Percona

AUGUST 29, 2023

Its query engine not only parallelizes incoming SQL queries for time series but also has the ability to create column-wise tables making it ideal for OLAP analysis duties. Depending on the configuration, one can tune a hardware RAID for either performance or redundancy. The same can be said for Citus data sharding.

C++ 81

C++ Database Storage Testing 81

O'Reilly Software

APRIL 4, 2018

Those were the days when “connected” meant having some web presence, “interactions” were measured in number of clicks, and the analysis happened in batch overnight processes. The data shape will dictate capacity planning, tuning of the backbone, and scalability analysis for individual components. At least once? At most once?

Architecture 80

Architecture Scalability Google Operating System 80

Brendan Gregg

SEPTEMBER 25, 2021

This was a weird problem to think about: Time itself had now become a resource and target of performance analysis. As a Xen guest, this profile was gathered using perf(1) and the kernel's software cpu-clock soft interrupts, not the hardware NMI. I'm including this step as a reminder for anyone following this kind of analysis.

Speed 40

Speed Java AWS Virtualization 40

Brendan Gregg

SEPTEMBER 5, 2017

Linux has been adding tracing technologies over the years: kprobes (kernel dynamic tracing), uprobes (user-level dynamic tracing), tracepoints (static tracing), and perf_events (profiling and hardware counters). My rock solid experience with Ubuntu is on an LTS release. ## Crash Dump Analysis It can be done.

Virtualization 76

Virtualization AWS Engineering Hardware 76

KeyCDN

AUGUST 15, 2019

Before you begin tuning your website or application, you must first figure out which metrics matter most to your users and establish some achievable benchmarks. Prepare the testing environment: Make sure your hardware and network configurations closely reflect real world conditions. What is Performance Testing?

Testing Tools 55

Testing Tools Best Practices Performance Testing Testing 55

SQL Performance

MARCH 8, 2021

This can make it difficult to draw sound performance-tuning conclusions. This uses hardware, typically a crystal oscillator, that produces ticks at a very high constant rate regardless of processor speed, power settings, or anything of that nature. SQL Server uses the high-precision QueryPerformanceCounter API to capture timing data.

Servers 95

Servers Tuning Architecture Processing 95

John McCalpin

JANUARY 22, 2018

Hardware performance counter results for a simple benchmark code calling Intel’s optimized DGEMM implementation for this processor (from the Intel MKL library) show that about 20% of the dynamic instruction count consists of instructions that are not packed SIMD operations (i.e., addl $1, %eax vfmadd213pd %zmm16, %zmm17, %zmm29.

Latency 40

Latency Hardware Code Testing 40

O'Reilly

NOVEMBER 28, 2023

AI users say that AI programming (66%) and data analysis (59%) are the most needed skills. Even with cloud-based foundation models like GPT-4, which eliminate the need to develop your own model or provide your own infrastructure, fine-tuning a model for any particular use case is still a major undertaking.

Open Source 107

Open Source Artificial Intelligence Google Infrastructure 107

The Netflix TechBlog

APRIL 29, 2019

Such applications track the inventory of our network gear: what devices, of which models, with which hardware components, located in which sites. Our Infrastructure Security team leverages Python to help with IAM permission tuning using Repokid. It serves as an entry point into any new analysis.

Open Source 279

Open Source Network Infrastructure Big Data 279

O'Reilly

SEPTEMBER 19, 2023

Doubly so as hardware improved, eating away at the lower end of Hadoop-worthy work. A common audience question was “can Hadoop run [my arbitrary analysis job or home-grown algorithm]?” Google goes a step further in offering compute instances with its specialized TPU hardware. And, often, to giving up.

Hardware 98

Hardware Storage Big Data Blockchain 98

All Things Distributed

MARCH 19, 2018

Amazon SageMaker training supports powerful container management mechanisms that include spinning up large numbers of containers on different hardware with fast networking and access to the underlying hardware, such as GPUs. Post-training model tuning and rich states. Principal Component Analysis (PCA).

Scalability 160

Scalability Hardware AWS Tuning 160

All Things Distributed

NOVEMBER 30, 2016

Effectively applying AI involves extensive manual effort to develop and tune many different types of machine learning and deep learning algorithms (e.g. automatic speech recognition, natural language understanding, image classification), collect and clean the training data, and train and tune the machine learning models. Amazon Lex.

AWS 166

AWS Lambda Artificial Intelligence Mobile 166

High Scalability

NOVEMBER 25, 2019

Eventually, we resorted to caching the events in memory for a short duration and also tuning the GC settings on those nodes as we are doing a lot of young generation collections. Nagios, Grafana and New Relic and some internal proactive exception analysis are used. How are software and hardware upgrades rolled out?

Architecture 52

Architecture Cache Azure Storage 52