Dynatrace

MARCH 24, 2023

Container technology enables organizations to efficiently develop cloud-native applications or to modernize legacy applications to take advantage of cloud services. Docker Swarm First introduced in 2014 by Docker, Docker Swarm is an orchestration engine that popularized the use of containers with developers.

Infrastructure 185

Infrastructure Open Source Operating System Cloud 185

The Netflix TechBlog

JUNE 7, 2021

Cloud Network Insight is a suite of solutions that provides both operational and analytical insight into the cloud network infrastructure to address the identified problems. The data is also used by security and other partner teams for insight and incident analysis. What is BPF?

Network 325

Network Transportation AWS Cloud 325

Dynatrace

DECEMBER 15, 2022

Adding application security to development and operations workflows increases efficiency. AIOps (artificial intelligence for IT operations) combines big data, AI algorithms, and machine learning for actionable, real-time insights that help ITOps continuously improve operations. ITOps vs. AIOps. ” The post What is ITOps?

Artificial Intelligence 201

Artificial Intelligence DevOps Hardware Virtualization 201

ScaleOut Software

JULY 19, 2021

Real-Time Device Tracking with In-Memory Computing Can Fill an Important Gap in Today’s Streaming Analytics Platforms. The Limitations of Today’s Streaming Analytics. How are we managing the torrent of telemetry that flows into analytics systems from these devices? The list goes on.

IoT 78

IoT Analytics Big Data Architecture 78

The Netflix TechBlog

MARCH 2, 2021

At Netflix, our data scientists span many areas of technical specialization, including experimentation, causal inference, machine learning, NLP, modeling, and optimization. Together with data analytics and data engineering, we comprise the larger, centralized Data Science and Engineering group.

Analytics 207

Analytics C++ Innovation Engineering 207

Dynatrace

JULY 6, 2020

Our customers have frequently requested support for this first new batch of services, which cover databases, big data, networks, and computing. See the health of your big data resources at a glance. Azure HDInsight supports a broad range of use cases including data warehousing, machine learning, and IoT analytics.

Azure 147

Azure Cloud Big Data Virtualization 147

Scalegrid

MAY 13, 2020

Greenplum Database is an open-source , hardware-agnostic MPP database for analytics, based on PostgreSQL and developed by Pivotal who was later acquired by VMware. This feature-packed database provides powerful and rapid analytics on data that scales up to petabyte volumes. What Exactly is Greenplum? At a glance – TLDR.

Big Data 321

Big Data Database Artificial Intelligence Open Source 321

Dynatrace

MAY 1, 2023

With 99% of organizations using multicloud environments , effectively monitoring cloud operations with AI-driven analytics and automation is critical. IT operations analytics (ITOA) with artificial intelligence (AI) capabilities supports faster cloud deployment of digital products and services and trusted business insights.

Analytics 187

Analytics Artificial Intelligence Big Data Open Source 187

ScaleOut Software

NOVEMBER 24, 2020

Rapid advances in the telematics industry have dramatically boosted the efficiency of vehicle fleets and have found wide ranging applications from long haul transport to usage-based insurance. Real-Time Digital Twins Can Add Important New Capabilities to Telematics Systems and Eliminate Scalability Bottlenecks.

Analytics 52

Analytics Architecture Scalability Software Architecture 52

Dynatrace

OCTOBER 4, 2022

Log management and analytics is an essential part of any organization’s infrastructure, and it’s no secret the industry has suffered from a shortage of innovation for several years. Several pain points have made it difficult for organizations to manage their data efficiently and create actual value.

Analytics 233

Analytics Artificial Intelligence Storage Serverless 233

Dynatrace

APRIL 20, 2023

With more automated approaches to log monitoring and log analysis, however, organizations can gain visibility into their applications and infrastructure efficiently and with greater precision—even as cloud environments grow. “The weakness of a data lake is they fail when you need to access them fast,” Pawlowski said.

Analytics 186

Analytics Infrastructure Storage Efficiency 186

Scalegrid

MARCH 14, 2024

In practice, a hybrid cloud operates by melding resources and services from multiple computing environments, which necessitates effective coordination, orchestration, and integration to work efficiently. Tailoring resource allocation efficiently ensures faster application performance in alignment with organizational demands.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

Scalegrid

MARCH 28, 2024

As Redis stores data, it supports extensive data key and string lengths, up to 512 MB, while offering complex data structures like: lists sets sorted sets hashes bitmaps These features make Redis much more than a basic caching engine; it is a versatile tool capable of supporting diverse data models. 3d render.

Cache 130

Cache Storage Scalability Architecture 130

The Netflix TechBlog

NOVEMBER 20, 2023

It also improves the engineering productivity by simplifying the existing pipelines and unlocking the new patterns. We will show how we are building a clean and efficient incremental processing solution (IPS) by using Netflix Maestro and Apache Iceberg. Backfill: Backfilling datasets is a common operation in big data processing.

Processing 210

Processing Big Data Efficiency Engineering 210

The Netflix TechBlog

APRIL 29, 2019

Python has long been a popular programming language in the networking space because it’s an intuitive language that allows engineers to quickly solve networking problems. Demand Engineering Demand Engineering is responsible for Regional Failovers , Traffic Distribution, Capacity Operations and Fleet Efficiency of the Netflix cloud.

Open Source 279

Open Source Network Infrastructure Big Data 279

KeyCDN

OCTOBER 2, 2018

It’s awesome for discovering how grid systems, CSS animation, Big Data, etc all play roles in real-world web design. Subjects like version control, crowdfunding, database selection and code editor choices are essential to efficient modern workflows, and this is a good place to start learning about them. Visit website 12.

Development 75

Development Website Design Code 75

Dynatrace

OCTOBER 25, 2022

Organizations adopt DevOps, where developers and operations work together in a continuous loop, so they can develop software and resolve issues efficiently before they affect users. Davis®— the Dynatrace purpose-built AI engine —further uses event proximity and baselined data for automatic correlation and noise suppression.

DevOps 216

DevOps Big Data Cloud Innovation 216

The Netflix TechBlog

OCTOBER 27, 2020

By Tianlong Chen and Ioannis Papapanagiotou Netflix has more than 195 million subscribers that generate petabytes of data everyday. Data scientists and engineers collect this data from our subscribers and videos, and implement data analytics models to discover customer behaviour with the goal of maximizing user joy.

Latency 243

Latency Storage Big Data Tuning 243

Highly Scalable

JUNE 5, 2012

Intersection of sorted lists is a cornerstone operation in many applications including search engines and databases because indexes are often implemented using different types of sorted structures. When this short mask of common elements is obtained, we have to efficiently copy out common elements. in this article.

C++ 102

C++ Java Performance Testing Efficiency 102

Dynatrace

OCTOBER 17, 2022

Artificial intelligence for IT operations, or AIOps, combines big data and machine learning to provide actionable insight for IT teams to shape and automate their operational strategy. The four stages of data processing. Alert fatigue and chasing false positives are not only efficiency problems.

DevOps 195

DevOps Artificial Intelligence Healthcare Innovation 195

Dynatrace

OCTOBER 14, 2021

Gartner defines AIOps as the combination of “big data and machine learning to automate IT operations processes, including event correlation, anomaly detection, and causality determination.” A comprehensive, modern approach to AIOps is a unified platform that encompasses observability, AI, and analytics.

Artificial Intelligence 211

Artificial Intelligence DevOps Innovation Metrics 211

Dynatrace

JUNE 1, 2020

With our AI engine, Davis, at the core Dynatrace provides precise answers in real-time. Trying to manually keep up, configure, script and source data is beyond human capabilities and today everything must be automated and continuous. Some customers even say, having Davis is like having a whole team of engineers on their side.

Artificial Intelligence 182

Artificial Intelligence Social Media Monitoring IoT 182

Dynatrace

JUNE 1, 2020

With our AI engine, Davis, at the core Dynatrace provides precise answers in real-time. Trying to manually keep up, configure, script and source data is beyond human capabilities and today everything must be automated and continuous. Some customers even say, having Davis is like having a whole team of engineers on their side.

Monitoring 132

Monitoring Performance Social Media Artificial Intelligence 132

The Morning Paper

SEPTEMBER 19, 2019

AliGraph covers Alibaba’s distributed graph engine supporting the development of new GNN applications. Their dataset has about 7B edges… Meanwhile, AnalyticDB is Alibaba’s real-time OLAP RDBMS handling 10PB of data (in excess of 100 trillion rows!). .” Could it be Analyzing efficient stream processing on modern hardware ?

Blockchain 46

Blockchain Hardware Google Analytics 46

Abhishek Tiwari

DECEMBER 27, 2017

A unified data management (UDM) system combines the best of data warehouses, data lakes, and streaming without expensive and error-prone ETL. It offers reliability and performance of a data warehouse, real-time and low-latency characteristics of a streaming system, and scale and cost-efficiency of a data lake.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

Highly Scalable

MARCH 10, 2015

Although there are many books on data mining in general and its applications to marketing and customer relationship management in particular [BE11, AS14, PR13 etc.], The rest of the article is organized as follows: We first introduce a simple framework that ties together a retailer’s actions, profits and data. The models (2.1)

Retail 152

Retail C++ Analytics Metrics 152

All Things Distributed

NOVEMBER 15, 2010

Now that our ability to generate higher and higher clock rates has stalled and CPU architectural improvements have shifted focus towards multiple cores, we see that it is becoming harder to efficiently use these computer systems. Driving down the cost of Big-Data analytics. Cluster Computer, Cluster GPU and Amazon EMR.

AWS 136

AWS Latency Programming Architecture 136

Smashing Magazine

JULY 29, 2019

Notice the async keyword on the Google analytics script? Google analytics has ‘low’ priority. Read “ Efficiently load JavaScript with defer and async ” for more information. A JavaScript bundle needs to be downloaded and then parsed, compiled, executed —and there are a number of other steps that an engine needs to complete.

Cache 96

Cache Google Mobile Network 96

Testsigma

FEBRUARY 12, 2021

The usage by advanced techniques such as RPA, Artificial Intelligence, machine learning and process mining is a hyper-automated application that improves employees and automates operations in a way which is considerably more efficient than conventional automation. Gartner’s 2020 projections first included the trend of hyperautomation.

Artificial Intelligence 92

Artificial Intelligence Software Software IoT 92

Percona

JANUARY 14, 2019

What if we use ClickHouse (which is a columnar analytical database) as our main datastore? Well, typically, an analytical database is not a replacement for a transactional or key/value datastore. However, ClickHouse is super efficient for timeseries and provides “sharding” out of the box (scalability beyond one node).

Database 40

Database Analytics Blockchain Healthcare 40