Dynatrace

DECEMBER 30, 2021

Using automatic and intelligent observability promotes faster innovation, greater efficiency, and better business outcomes. Causal AI is also more precise and efficient. With real-time causal AI, organizations can identify the root cause of issues without having to train their data models up front. Real- time AI.

Strategy 264

Strategy Energy Cloud Innovation 264

Scalegrid

JANUARY 5, 2024

Enhanced data security, better data integrity, and efficient access to information. Despite initial investment costs, DBMS presents long-term savings and improved efficiency through automated processes, efficient query optimizations, and scalability, contributing to enhanced decision-making and end-user productivity.

Efficiency 147

Efficiency Storage Database Scalability 147

The Netflix TechBlog

NOVEMBER 6, 2023

In order to train the model on internal training data (video clips with aligned text descriptions), we implemented a scalable version on Ray Train and switched to a more performant video decoding library. These models are trained on large amounts of image-caption pairs via in-batch contrastive learning.

Media 234

Media Social Media Tuning Engineering 234

Dynatrace

JANUARY 30, 2024

Furthermore, AI can significantly boost productivity if employees are properly trained on how to use the technology correctly. “It’s But if you don’t take the time to train the workforce in the programs or the systems you’re bringing online, you lose that effectiveness.

Artificial Intelligence 246

Artificial Intelligence Government Innovation Programming 246

Dynatrace

JANUARY 31, 2024

Augmenting LLM input in this way reduces apparent knowledge gaps in the training data and limits AI hallucinations. The LLM then synthesizes the retrieved data with the augmented prompt and its internal training data to create a response that can be sent back to the user. million AI server units annually by 2027, consuming 75.4+

Cache 276

Cache Azure Infrastructure Monitoring 276

DZone

AUGUST 9, 2023

Machine learning (ML) has seen explosive growth in recent years, leading to increased demand for robust, scalable, and efficient deployment methods. Traditional approaches often need help operationalizing ML models due to factors like discrepancies between training and serving environments or the difficulties in scaling up.

Scalability 246

Scalability Best Practices Open Source Virtualization 246

Dynatrace

FEBRUARY 23, 2022

According to a Gartner report, “By 2023, 60% of organizations will use infrastructure automation tools as part of their DevOps toolchains, improving application deployment efficiency by 25%.”. With IaC enable DeSecOps teams to institutionalize these processes in code, ensuring repeatable, secure, automated, and efficient processes.

Serverless 312

Serverless Infrastructure Innovation DevOps 312

O'Reilly

NOVEMBER 19, 2024

Reasons for using RAG are clear: large language models (LLMs), which are effectively syntax engines, tend to “hallucinate” by inventing answers from pieces of their training data. See the primary sources “ REALM: Retrieval-Augmented Language Model Pre-Training ” by Kelvin Guu, et al., at Facebook—both from 2020.

Open Source 127

Open Source Entertainment Database Healthcare 127

Dynatrace

JANUARY 4, 2024

It can be difficult to understand the basis of AI systems’ decisions, particularly when they are trained on large and complex data sets. AI systems, and their data, can be biased, either intentionally or unintentionally, reflecting the biases of their creators or the data on which they are trained. AI system bias. Data in context.

Artificial Intelligence 264

Artificial Intelligence Strategy Virtualization Traffic 264

The Netflix TechBlog

FEBRUARY 13, 2023

We have been leveraging machine learning (ML) models to personalize artwork and to help our creatives create promotional content efficiently. Training Performance Media model training poses multiple system challenges in storage, network, and GPUs.

Media 297

Media Storage Infrastructure Systems 297

Dynatrace

SEPTEMBER 30, 2021

By carving the right AWS certification path, developers can even use their certification and training to advance their careers long term. Not only will they get much more out of the tools they use daily, but they’ll also be able to deliver superior functionality, efficiency, and performance to your customers.

AWS 246

AWS Best Practices Cloud Analytics 246

Dynatrace

AUGUST 8, 2024

Employee training in cybersecurity best practices and maintaining up-to-date software and systems are also crucial. Comprehensive training programs and strict change management protocols can help reduce human errors. This approach minimizes the impact of outages on end users and maximizes the efficiency of IT remediation efforts.

Software 290

Software Software Infrastructure Network 290

Dynatrace

AUGUST 2, 2021

Using Dynatrace, VA can observe application performance and increase application visibility as well as determine application efficiency. With the cloud, developers can build more capabilities, more efficiently and responders can prevent or identify and fix problems faster. “It

Government 246

Government Strategy Cloud Efficiency 246

Dynatrace

JANUARY 4, 2024

While this approach can be effective if the model is trained with a large amount of data, even in the best-case scenarios, it amounts to an informed guess, rather than a certainty. Because IT systems change often, AI models trained only on historical data struggle to diagnose novel events. That’s where causal AI can help.

Government 263

Government Analytics Benchmarking Storage 263

Dynatrace

JANUARY 16, 2020

Part two added a few simple examples of how intellectual debt might accrue, highlighting the subtle but real drag on efficiency. Require training—learning periods—to uncover structure and commonalities and identify normal behavior. Since we began the series pointing out parallels to technical debt, let’s revisit that comparison.

Cloud 226

Cloud Artificial Intelligence Virtualization Efficiency 226

Dynatrace

JUNE 8, 2021

At Dynatrace, our Autonomous Cloud Enablement (ACE) team are the coaches or teach and train our customers to always get the best out of Dynatrace and reach their objectives. Our expert Jean Louis Lormeau suggested a training program to help you become the champion in problem resolution. We can now move to the training phase.

Metrics 242

Metrics Tuning Programming Systems 242

Dynatrace

MAY 24, 2021

The combined ability of Dynatrace and our partners to address this growing TAM with efficient, high-speed land and expand deals is underpinned by the 530+ cloud services and technology integrations available on the Dynatrace Hub. Training & Certification Award: Accenture. Partner Pro Club. Rising Star Award: Evolving Solutions.

Programming 246

Programming Cloud Virtualization Technology 246

The Netflix TechBlog

NOVEMBER 11, 2022

In semi-supervised anomaly detection models, only a set of benign examples are required for training. Data Data Labeling For the task of anomaly detection in streaming platforms, as we have neither an already trained model nor any labeled data samples, we use structural a priori domain-specific rule-based assumptions, for data labeling.

C++ 321

C++ Metrics Tuning Strategy 321

Dynatrace

MAY 24, 2021

The combined ability of Dynatrace and our partners to address this growing TAM with efficient, high-speed land and expand deals is underpinned by the 530+ cloud services and technology integrations available on the Dynatrace Hub. Training & Certification Award: Accenture. Partner Pro Club. Rising Star Award: Evolving Solutions.

Programming 243

Programming Cloud Virtualization Technology 243

Dynatrace

SEPTEMBER 21, 2023

As global warming advances, growing IT carbon footprints are pushing energy-efficient computing to the top of many organizations’ priority lists. Energy efficiency is a key reason why organizations are migrating workloads from energy-intensive on-premises environments to more efficient cloud platforms.

Energy 264

Energy Cloud Airlines Strategy 264

Edge Perspectives

MARCH 26, 2019

In our Big Shift world, we confront the imperative of institutional innovation – shifting from institutional models built on scalable efficiency to institutional models built on scalable learning. I’ve written and spoken about this a lot over the years and one of the most common pushbacks I get is – “so, are you against efficiency?”

Efficiency 89

Efficiency Scalability Innovation Programming 89

The Netflix TechBlog

MARCH 7, 2024

In addition to Spark, we want to support last-mile data processing in Python, addressing use cases such as feature transformations, batch inference, and training. There are several ways to provide explainability to models but one way is to train an explainer model based on each trained model.

Systems 235

Systems Media Cache Open Source 235

Dynatrace

JUNE 14, 2023

The Services Endorsement Program includes training and certification for partners that span unified observability and security, AIOps, and advanced DevSecOps and CloudOps. Accelerate business growth with the latest sales and technical training. Through a two-step approach, partners can become Dynatrace Services Endorsed.

Programming 245

Programming Best Practices Innovation Analytics 245

The Netflix TechBlog

MARCH 4, 2024

We have deployed Auto Remediation in production for handling memory configuration errors and unclassified errors of Spark jobs and observed its efficiency and effectiveness (e.g., For efficient error handling, Netflix developed an error classification service, called Pensive, which leverages a rule-based classifier for error classification.

Tuning 217

Tuning Efficiency Big Data Engineering 217

Dynatrace

FEBRUARY 1, 2024

You can create any new branches for new ideas and hypotheses while retaining the ability to navigate back to your initial train of thought. Character precision on a petabyte scale Security Investigator increases the speed of investigation flows and the precision of evidence, leading to higher efficiency and faster results.

Speed 263

Speed Games Efficiency Processing 263

All Things Distributed

NOVEMBER 22, 2016

A set of programming models has emerged to help developers define and train AI models with deep learning; along with open source frameworks that put deep learning in the hands of mere mortals. Amazon EC2, with its broad set of instance types and GPUs with large amounts of memory, has become the center of gravity for deep learning training.

AWS 163

AWS Open Source Scalability Programming 163

Dynatrace

SEPTEMBER 20, 2022

DevSecOps best practices provide guidelines to help organizations achieve efficient and secure application design, development, implementation, and management. Organizations should train DevOps teams to understand security best practices and how to operate any new tooling implementations. Download the 2021 DevOps Report.

Best Practices 312

Best Practices DevOps Serverless Education 312

The Morning Paper

AUGUST 25, 2019

Snuba: automating weak supervision to label training data Varma & Ré, VLDB 2019. It’s tackling the same fundamental problem: how to gather enough labeled data to train a model, and how to effectively use it in a weak supervision setting (supervised learning with noisy labels). It took me quite a while to get my head around this!

Logistics 76

Logistics Efficiency Design Performance 76

The Netflix TechBlog

JANUARY 30, 2023

An example of the features we might capture for this image include: number of people (two), where they’re facing (facing each other), emotion (neutral to positive), saturation (low), objects present (military uniform) We can use pre-trained models/APIs to create some of these features, like face detection and object labeling.

Media 262

Media Design Innovation Mobile 262

Dynatrace

OCTOBER 17, 2022

This increased automation, resilience, and efficiency helps DevOps teams speed up software delivery and accelerate the feedback loop — ultimately allowing them to innovate faster and more confidently. It works without having to identify training data, then training and honing. A huge advantage of this approach is speed.

DevOps 246

DevOps Artificial Intelligence Healthcare Innovation 246

Dynatrace

OCTOBER 31, 2023

In attempting to address this difficult workforce challenge, chief information security officers (CISOs) are considering automation and artificial intelligence (AI) defense tools as a cost-effective, highly efficient option. During the 14 th annual Billington Cybersecurity Summit in Washington, D.C.,

Artificial Intelligence 246

Artificial Intelligence Energy Government Technology 246

Dynatrace

JULY 6, 2022

Ultimately, IT automation can deliver consistency, efficiency, and better business outcomes for modern enterprises. AI that is based on machine learning needs to be trained. IT automation tools can achieve enterprise-wide efficiency. By tuning workflows, you can increase their efficiency and effectiveness. Read eBook now!

Artificial Intelligence 246

Artificial Intelligence Tuning Strategy Big Data 246

Percona

NOVEMBER 9, 2023

Kubernetes can be complex, which is why we offer comprehensive training that equips you and your team with the expertise and skills to manage database configurations, implement industry best practices, and carry out efficient backup and recovery procedures.

Efficiency 117

Efficiency Cloud Healthcare Open Source 117

The Netflix TechBlog

APRIL 26, 2022

We built Axion primarily to remove any training-serving skew and make offline experimentation faster. We make sure there is no training/serving skew by using the same data and the code for online and offline feature generation. Our machine learning models train on several weeks of data.

Storage 195

Storage Design Scalability Latency 195

Dynatrace

FEBRUARY 1, 2024

For example, a CNBC report found that training just one LLM can cost millions of dollars, and then millions more to update. That looks like modernizing data centers from the ground up with sustainability and efficiency in mind and identifying underutilized infrastructure. Generative AI and LLMs are compounding these figures.

Cloud 246

Cloud Energy Innovation Infrastructure 246

Dynatrace

APRIL 21, 2023

State and local agencies must spend taxpayer dollars efficiently while building a culture that supports innovation and productivity. APM helps ensure that citizens experience strong application reliability and performance efficiency. million annually through retiring legacy technology debt and tool rationalization.

Government 239

Government Infrastructure Innovation Monitoring 239

Dynatrace

SEPTEMBER 3, 2020

Such a solution needs to collect a substantial amount of data at first for then having a dataset (training data) that an algorithm can use to learn from. Inevitably, this leads to one very important question addressing the efficiency of ML: can such an AI ever keep up with frequent changes and deployments? Traditional AIOps is Slow.

Software 264

Software Software Artificial Intelligence Metrics 264