The Morning Paper

OCTOBER 18, 2020

What really blew me away, is that this result includes the time taken to train the model used! The resulting performance depends on the quality of the model predictions, a higher quality model leads to fewer collisions, and fewer out-of-order items to be patched in the final Insertion Sort pass. The big idea.

Cache 137

Cache C++ Java Tuning 137

O'Reilly

MAY 9, 2023

Using AI means auditing the outputs of AI systems to ensure that they’re fair; it means documenting the behaviors of AI models and training data sets so that users know how the data was collected and what biases are inherent in that data. Its training data and its design must both be well documented and available to the public.

Infrastructure 88

Infrastructure Government Design Tuning 88

Percona

NOVEMBER 3, 2023

Have you tuned your environment? This entails providing comprehensive training for your staff, equipping them with both foundational and sophisticated testing methodologies. Additionally, it involves the acquisition or development of specialized testing software, which often comes with its own set of training requirements.

Database 81

Database Open Source Benchmarking Strategy 81

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. I had attended these events when I was based in the UK, but became one of the organizers.

Tuning 52

Tuning Benchmarking Engineering C++ 52

Dynatrace

DECEMBER 2, 2021

SLOs, together with service-level indicators (SLIs), deliver the performance promised in service-level agreements (SLAs) and other business level objectives (BLOs) while staying within error budgets. In layman’s terms, SLOs represent the performance or health of a service. But what are SLOs? Watch webinar now! Promote automation.

Metrics 184

Metrics Best Practices DevOps Infrastructure 184

O'Reilly

MAY 25, 2021

GPT-3 is essentially an auto-complete bot whose underlying Machine Learning (ML) model has been trained on vast quantities of text available on the Internet. Note that the dataset on which GPT-3 trained terminated around October 2019. OpenAI’s text generating system GPT-3 has captured mainstream attention.

Social Media 140

Social Media Media Internet Internet 140

The Netflix TechBlog

OCTOBER 18, 2019

They used Bayesian Optimization to perform multi-metric optimization?—?e.g., From an ML practice perspective, they also have to deal with a wide variety of development processes and ML frameworks, custom work for new use cases and challenges with reproducibility of training.

Infrastructure 126

Infrastructure Metrics Architecture Efficiency 126

The Netflix TechBlog

OCTOBER 18, 2019

They used Bayesian Optimization to perform multi-metric optimization?—?e.g., From an ML practice perspective, they also have to deal with a wide variety of development processes and ML frameworks, custom work for new use cases and challenges with reproducibility of training.

Infrastructure 100

Infrastructure Metrics Architecture Efficiency 100

Scalegrid

JANUARY 11, 2024

To combat this issue, certain strategies are recommended such as prioritizing alerts based on severity levels, reducing false positives through advanced detection techniques, automating response protocols for faster action-taking, and providing adequate training and resources for personnel responsible for managing security.

Best Practices 130

Best Practices Cloud Monitoring Strategy 130

Tasktop

OCTOBER 23, 2020

We believe that diverse teams perform better and foster an environment of belonging and inclusion. There is also the Tasktop Academy, which provides us with professional training and allows us to learn from high-quality training videos and more. Unconscious bias training. Diversity calendar to celebrate many cultures.

Tuning 52

Tuning Engineering Programming Infrastructure 52

Dynatrace

JANUARY 13, 2021

Stay tuned for an upcoming Performance Clinic ! Monitoring as Code will also be featured at Perform 2021 with a Breakout session and a dedicated virtual hands-on training ! For more information on what Monaco can do take a look the README.me and some sample configurations used for integration testing.

Open Source 138

Open Source Code Monitoring Azure 138

Dynatrace

JUNE 4, 2024

While receiving no feedback on the quality or security of new features leaves developers uncertain about feature performance, delayed feedback also increases a developer’s cognitive load. For example, the team must establish specific thresholds for desired service performance behavior.

Metrics 222

Metrics Engineering Code Tuning 222

The Netflix TechBlog

NOVEMBER 6, 2023

We have built an internal system that allows someone to perform in-video search across the entire Netflix video catalog, and we’d like to share our experience in building this system. The recent success of large-scale models that jointly train image and text embeddings has enabled new use cases around multimodal retrieval.

Media 225

Media Social Media Tuning Efficiency 225

Percona

MARCH 23, 2023

This blog is in reference to our previous ones for ‘Innodb Performance Optimizations Basics’ 2007 and 2013. Although there have been many blogs about adjusting MySQL variables for better performance since then, I think this topic deserves a blog update since the last update was a decade ago, and MySQL 5.7

Performance 124

Performance Hardware Tuning Storage 124

The Morning Paper

JUNE 13, 2019

As we saw with the SOAP paper last time out, even with a fixed model variant and hardware there are a lot of different ways to map a training workload over the available hardware. “ For instance, Facebook applications issue tens-of-trillions of inference queries per day with varying performance, accuracy, and cost constraints.”

Hardware 58

Hardware Latency Serverless Energy 58

Tasktop

NOVEMBER 19, 2020

We believe that diverse teams perform better and foster an environment of belonging and inclusion. Everyone at Tasktop has taken training in unconscious bias and we’ve had Tasktopians volunteering to write more about that subject and others. Tasktop’s Mission : We are driving toward an inclusive company culture. iamtasktop.

Entertainment 52

Entertainment Education Tuning Metrics 52

SQL Server According to Bob

FEBRUARY 15, 2018

Microsoft engineering is actually sending quite a few folks over the Atlantic to come talk about SQL Server 2017, SQL Server on Linux, GDPR, Performance, Security, Azure Data Lake, Azure SQL Database, Azure SQL Data Warehouse, and Azure CosmosDB. Maximise compute performance with Azure SQL Data Warehouse – More JRJ on Azure DW.

Engineering 40

Engineering Azure Best Practices Servers 40

Percona

APRIL 24, 2023

Indexes are generally considered to be the panacea when it comes to SQL performance tuning, and PostgreSQL supports different types of indexes catering to different use cases. I keep seeing many articles and talks on “tuning” discussing how creating new indexes speeds up SQL but rarely ones discussing removing them.

Tuning 124

Tuning Cache Storage Database 124

The Morning Paper

OCTOBER 31, 2019

also means you can make informed decisions about model complexity vs performance trade-offs if a more complex model looks like it may perform better. “ This can substantially improve our ability to solve RiskSLIM-MINLP since MIP solvers typically exhibit better off-the-shelf performance than MINLP solvers.

Logistics 44

Logistics Programming Tuning Code 44

Dynatrace

JUNE 16, 2022

Rather than using a trained model to predict behavior, RASP watches an application’s runtime, studying the application’s task execution to detect attacks. An ideal RASP technology does not need training or fine-tuning to learn what bad application behavior looks like. Instant runtime response. Contextual analysis.

Tuning 217

Tuning Cloud Open Source Network 217

Brendan Gregg

APRIL 30, 2018

In this year's CFP we’re looking for topics covering the latest trends and best practices in cloud computing, containerization, machine learning, big data, infrastructure, scalability, DevOps, IT management, automation, reliability, monitoring, performance tuning, security, databases, programming, datacenters, and more.

DevOps 43

DevOps Network Best Practices Programming 43

Brendan Gregg

APRIL 29, 2018

In this year's CFP we’re looking for topics covering the latest trends and best practices in cloud computing, containerization, machine learning, big data, infrastructure, scalability, DevOps, IT management, automation, reliability, monitoring, performance tuning, security, databases, programming, datacenters, and more.

DevOps 40

DevOps Network Best Practices Programming 40

O'Reilly

JANUARY 17, 2023

.”) So now you tweak the classifier’s parameters and try again, in search of improved performance. You’ll try this with a few other algorithms, and their respective tuning parameters–maybe even break out TensorFlow to build a custom neural net along the way–and the winning model will be the one that heads to production.

Tuning 133

Tuning Open Source AWS Software 133

O'Reilly

NOVEMBER 28, 2023

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. Training models and developing complex applications on top of those models is becoming easier. of nonusers, 5.4%

Open Source 111

Open Source Artificial Intelligence Google Infrastructure 111

Dynatrace

APRIL 21, 2023

The Office of the CTO wanted to ensure a positive citizen experience by identifying the 200+ critical applications available within their 21 executive agencies and offering application performance monitoring (APM) as a service to those agencies. Zbojniewicz wanted to drive APM and simultaneously decommission the legacy toolset successfully.

Government 157

Government Infrastructure Innovation Monitoring 157

The Netflix TechBlog

MARCH 14, 2023

Much of the ML literature focuses on model training, evaluation, and scoring. In addition, we were able to perform a handful of A/B tests to validate or negate our hypotheses for tuning the search experience. Users have flexibility to perform multimodal search with input being a simple text term, image or short video.

Media 291

Media Innovation Energy Architecture 291

The Netflix TechBlog

DECEMBER 7, 2020

VMAF has become a de facto standard for evaluating the performance of encoding systems and driving encoding optimizations. The gathered evidence is then fused into a final predicted score using machine learning, guided by subjective scores from training datasets. VMAF stands for Video Multi-Method Assessment Fusion.

Metrics 154

Metrics Open Source Tuning Speed 154

The Netflix TechBlog

AUGUST 17, 2023

From our testing on promotional assets , we know which of these assets have performed well and which ones haven’t. Each algorithm needed a process of evaluation and tuning to get great results in AVA Discovery View. This feedback is easily accessible by our algorithm partners and used in training improved versions of the models.

Media 169

Media Scalability Architecture Strategy 169

Percona

OCTOBER 18, 2023

Community support One of the most significant advantages of open source databases is the expansive global community of users, developers, DBAs, and enthusiasts who collaborate to provide a seemingly never-ending array of how-tos, resources, guidance, and solutions to help you make your database more performant and secure.

Open Source 90

Open Source Database Hardware Strategy 90

Dynatrace

JULY 6, 2022

More than half of all respondents cited two key SRE adoption barriers: the perceived difficulty of training existing IT professionals in SRE best practices, and the cost and difficulty of finding skilled professionals. By removing physical dependencies, automation can help perform SRE at scale. Make SRE accessible.

Best Practices 181

Best Practices Open Source Tuning Infrastructure 181

All Things Distributed

MARCH 19, 2018

For example, training on more data means more accurate models. Last re:Invent, to make the problem of authoring, training, and hosting ML models easier, faster, and more reliable, we launched Amazon SageMaker. Machine learning models are usually trained tens or hundreds of times. In machine learning, more is usually more.

Scalability 159

Scalability Hardware AWS Tuning 159

Percona

MAY 15, 2023

has ceased, and while PBM may still successfully perform backups and restores, we cannot guarantee it anymore. That means that testing with 4.2 That being said, rest assured, you will not be left alone. Those that have or would like to sign up for a Percona Support Subscription will continue to receive operational support and services.

Servers 106

Servers Open Source Tuning Software 106

Tim Kadlec

JANUARY 28, 2020

On strength training days, I’ll listen to some music. I’ve always sort of mentally tuned in and out of podcasts as I listen to them, and that’s exactly why it works so well to listen to them when I run. In the warmer months, for example, I’ll switch to two long runs each week on Tuesdays and Thursdays.

Games 43

Games Entertainment Education Tuning 43

The Netflix TechBlog

OCTOBER 18, 2022

These include ETL pipelines, ML model training workflows, batch jobs, etc. Similarly, ML model training workflows usually consist of tens of thousands of training jobs within a single workflow. Advanced users can develop their own well-tuned docker image and let Maestro handle the scheduling and execution.

Java 202

Java Scalability Traffic Architecture 202

The Netflix TechBlog

JANUARY 10, 2024

This drove the approach of the “release train”. Video Inspection Service (VIS): This service takes a mezzanine as the input and performs various inspections. This service takes a mezzanine as the input and performs analysis to understand the content complexity. The results are saved to a database so they can be reused.

Processing 229

Processing Media Latency Innovation 229

All Things Distributed

NOVEMBER 29, 2017

Though the AWS Cloud gives you access to the storage and processing power required for ML, the process for building, training, and deploying ML models has unique challenges that often block successful use of this powerful new technology. The challenges begin with collecting, cleaning, and formatting training data.

Tuning 94

Tuning AWS Scalability Infrastructure 94

The Morning Paper

JULY 7, 2019

Models have a provenance tag explaining which data it has been trained on and which version of the model was used. ML-centric software also sees frequent revisions initiated by model changes, parameter tuning, and data updates, the combination of which can have a significant impact on system performance.

Software Engineering 92

Software Engineering Engineering Software Software 92