ScaleOut Software

JULY 19, 2021

Incoming data is saved into data storage (historian database or log store) for query by operational managers who must attempt to find the highest priority issues that require their attention. The post The Need for Real-Time Device Tracking appeared first on ScaleOut Software. What’s missing in this picture?

IoT 78

IoT Analytics Big Data Architecture 78

Dynatrace

APRIL 11, 2023

Application vulnerabilities remain a key concern Application vulnerabilities—weaknesses or flaws in software applications that malicious attackers can use to exploit IT systems—exist in any type of software, including web and mobile applications. Together they equal better software. Learn more.

Cloud 180

Cloud DevOps Open Source Retail 180

The Netflix TechBlog

MARCH 2, 2021

I started working at a local payment processing company after graduation, where I built survival models to calculate lifetime value and experimented with them on our brand new big data stack. I was doing data science without realizing it. Coding with statistical software and SQL are my most widely used technical skills.

Analytics 207

Analytics Innovation C++ Engineering 207

The Netflix TechBlog

JUNE 7, 2021

Netflix software infrastructure is a large distributed ecosystem that consists of specialized functional tiers that are operated on the AWS and Netflix owned services. The data is also used by security and other partner teams for insight and incident analysis.

Network 325

Network Transportation AWS Cloud 325

Dynatrace

APRIL 20, 2023

Modern organizations ingest petabytes of data daily, but legacy approaches to log analysis and management cannot accommodate this volume of data. Traditional log analysis evaluates logs and enables organizations to mitigate myriad risks and meet compliance regulations.

Analytics 180

Analytics Infrastructure Storage Efficiency 180

Dynatrace

SEPTEMBER 15, 2020

During the Performance Clinic episode, I asked Stefano to tell us more about this changing world and how we can leverage automation, AI and machine learning to optimize modern software stacks despite the increased complexity. Akamas also enables you to automate the analysis of the experiment metrics in powerful ways.

Performance 180

Performance Java Metrics Cloud 180

ScaleOut Software

JUNE 15, 2020

Instead, most applications just sift through the telemetry for patterns that might indicate exceptional conditions and forward the bulk of incoming messages to a data lake for offline scrubbing with a big data tool such as Spark. Maintain State Information for Each Data Source.

Analytics 52

Analytics IoT Lambda Big Data 52

ScaleOut Software

JUNE 15, 2020

Instead, most applications just sift through the telemetry for patterns that might indicate exceptional conditions and forward the bulk of incoming messages to a data lake for offline scrubbing with a big data tool such as Spark. Maintain State Information for Each Data Source.

Analytics 52

Analytics IoT Lambda Big Data 52

ScaleOut Software

APRIL 3, 2020

What’s missing is a flexible, fast, and easy-to-use software system that can be quickly adapted to track these assets in real time and provide immediate answers for logistics managers. These questions can be answered using the latest data as it streams in from the field. What are real-time digital twins and why are they useful here?

Logistics 52

Logistics Analytics Scalability Cloud 52

ScaleOut Software

APRIL 3, 2020

What’s missing is a flexible, fast, and easy-to-use software system that can be quickly adapted to track these assets in real time and provide immediate answers for logistics managers. These questions can be answered using the latest data as it streams in from the field. What are real-time digital twins and why are they useful here?

Logistics 52

Logistics Analytics Scalability Cloud 52

ScaleOut Software

NOVEMBER 24, 2020

At the same time, telemetry snapshots are stored in a data lake, such as HDFS , for offline batch analysis and visualization using big data tools like Spark. The results of batch analysis are typically produced after an hour’s delay or more. A second key limitation is the lack of real-time aggregate analysis.

Analytics 52

Analytics Architecture Scalability Software Architecture 52

All Things Distributed

JANUARY 6, 2016

We believe that with the launch of the Seoul Region, AWS will enable many more enterprise customers in Korea to reduce the cost of their IT operations and innovate faster in critical new areas such as big data analysis, Internet of Things, and more.

AWS 110

AWS Cloud Games Latency 110

ACM Sigarch

MAY 31, 2023

Heterogeneous and Composable Memory (HCM) offers a feasible solution for terabyte- or petabyte-scale systems, addressing the performance and efficiency demands of emerging big-data applications. Also, besides the hardware, we see the software ecosystem starts to appear (e.g., About CXL hardware availability with academia.

Latency 52

Latency Hardware Cache Architecture 52

Dynatrace

OCTOBER 4, 2022

Still, it is critical to collect, store, and make easily accessible these massive amounts of log data for analysis. Full access to all relevant observability, security, and business data is essential to address unforeseen issues and enable proactive efforts to prevent service degradation and outages.

Analytics 227

Analytics Artificial Intelligence Storage Serverless 227

All Things Distributed

DECEMBER 20, 2017

By knowing this, Kärcher can generate new top-line revenue in the form of subscription models for its analysis portal. These examples underline that the purpose of software today is not solely to support business processes, but that software solutions have broadly become an essential element in multiple business areas.

Artificial Intelligence 79

Artificial Intelligence Social Media Logistics AWS 79

Dynatrace

JULY 5, 2022

AIOps combines big data and machine learning to automate key IT operations processes, including anomaly detection and identification, event correlation, and root-cause analysis. To achieve these AIOps benefits, comprehensive AIOps tools incorporate four key stages of data processing: Collection. Aggregation.

Artificial Intelligence 278

Artificial Intelligence Cloud Innovation Strategy 278

Dynatrace

MAY 1, 2023

IT operations analytics is the process of unifying, storing, and contextually analyzing operational data to understand the health of applications, infrastructure, and environments and streamline everyday operations. ITOA collects operational data to identify patterns and anomalies for faster incident management and near-real-time insights.

Analytics 181

Analytics Artificial Intelligence Big Data Open Source 181

Scalegrid

FEBRUARY 8, 2024

Speedier access to stored information within distributed storage is achieved by leveraging software-defined storage solutions and strategies like sharding or distributing sections of large databases and improving scalability by dividing tasks among many servers.

Storage 130

Storage Systems Big Data Azure 130

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. This second solution picks up at data collection, aggregation, and analysis, preparing it for execution. Deterministic AI.

DevOps 189

DevOps Artificial Intelligence Healthcare Innovation 189

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.” But what is AIOps, exactly? And how can it support your organization? What is AIOps? Why is AIOps needed?

Artificial Intelligence 205

Artificial Intelligence DevOps Innovation Metrics 205

The Netflix TechBlog

JULY 21, 2022

We at Netflix, as a streaming service running on millions of devices, have a tremendous amount of data about device capabilities/characteristics and runtime data in our big data platform. With large data, comes the opportunity to leverage the data for predictive and classification based analysis.

Big Data 179

Big Data Cache Engineering Data Engineering 179

Testsigma

MAY 7, 2020

IBM Big Data and Analytics Hub website cited a case study, where a US insurance company was estimating 15% of their testing efforts to be just test data collection for the backend system and the frontend system. What is test data? The other two approaches are usually avoided due to the cost involved and data sensitivity.

Testing 60

Testing Storage Database Processing 60

Dynatrace

OCTOBER 25, 2022

NoOps is a concept in software development that seeks to automate processes and eliminate the need for an extensive IT operations team. 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. What is NoOps?

DevOps 210

DevOps Big Data Cloud Innovation 210

Brendan Gregg

APRIL 30, 2018

Today's LISA attracts attendees working on all sizes of production systems, and its attendees include sysadmins, systems engineers, SREs, DevOps engineers, software engineers, IT managers, security engineers, network administrators, researchers, students, and more.

DevOps 43

DevOps Network Best Practices Programming 43

Brendan Gregg

APRIL 29, 2018

Today's LISA attracts attendees working on all sizes of production systems, and its attendees include sysadmins, systems engineers, SREs, DevOps engineers, software engineers, IT managers, security engineers, network administrators, researchers, students, and more.

DevOps 40

DevOps Network Best Practices Programming 40

Dynatrace

FEBRUARY 16, 2023

As teams try to gain insight into this data deluge, they have to balance the need for speed, data fidelity, and scale with capacity constraints and cost. To solve this problem, Dynatrace launched Grail, its causational data lakehouse , in 2022.

Analytics 179

Analytics Innovation Metrics Database 179

The Netflix TechBlog

APRIL 29, 2019

Various software systems are needed to design, build, and operate this CDN infrastructure, and a significant number of them are written in Python. Orchestration The Big Data Orchestration team is responsible for providing all of the services and tooling to schedule and execute ETL and Adhoc pipelines.

Open Source 279

Open Source Network Infrastructure Big Data 279

Dynatrace

JANUARY 11, 2023

As cloud and big data complexity scales beyond the ability of traditional monitoring tools to handle, next-generation cloud monitoring and observability are becoming necessities for IT teams. With agent monitoring, third-party software collects data and reports from the component that’s attached to the agent.

Cloud 217

Cloud Monitoring Best Practices Infrastructure 217

Dynatrace

AUGUST 14, 2023

How behavior analytics works User behavior analytics works by first collecting, then analyzing user behavior data. Collect user behavior data Organizations typically use analytics software to collect a large volume of data on user behavior from relevant sources.

Analytics 223

Analytics Social Media Website IoT 223

Rigor

SEPTEMBER 11, 2019

Rick is a software engineer on the Google Chrome team, “leading an effort to make the web just work for developers.” Find his research and analysis on the HTTP Archive Discussion forums. Would you like to be a part of Big Data and this incredible project? Rick Byers. Rick Byers. Patrick Hamann. Patrick Hamann.

Performance 89

Performance Education Google Website 89

Dynatrace

OCTOBER 4, 2022

While data lakehouses combine the flexibility and cost-efficiency of data lakes with the querying capabilities of data warehouses, it’s important to understand how these storage environments differ. Data warehouses. Data warehouses were the original big data storage option.

Artificial Intelligence 201

Artificial Intelligence Storage Analytics Government 201

The Agile Manager

FEBRUARY 27, 2012

The Financial Times recently ran analysis and guest op-eds that sought to explain value in and from IT. The rise of Big Data - the ability to store and analyze large volumes of structured and unstructured, internal and external data - promises to let companies react more nimbly than ever before.

Ecommerce 45

Ecommerce Social Media Retail Airlines 45

The Netflix TechBlog

MARCH 25, 2019

Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and Efficiency By: Di Lin , Girish Lingappa , Jitender Aswani Imagine yourself in the role of a data-inspired decision maker staring at a metric on a dashboard about to make a critical business decision but pausing to ask a question?—?“Can

Infrastructure 219

Infrastructure Big Data Transportation Architecture 219

All Things Distributed

OCTOBER 7, 2015

We live in a world where massive volumes of data are generated from websites, connected devices and mobile apps. In such a data intensive environment, making key business decisions such as running marketing and sales campaigns, logistic planning, financial analysis and ad targeting require deriving insights from these data.

Cloud 137

Cloud Big Data AWS Analytics 137

Dynatrace

JUNE 29, 2022

A hybrid cloud, however, combines public infrastructure and services with on-premises resources or a private data center to create a flexible, interconnected IT environment. Hybrid environments provide more options for storing and analyzing ever-growing volumes of big data and for deploying digital services.

Infrastructure 175

Infrastructure Cloud Azure AWS 175

All Things Distributed

DECEMBER 13, 2016

With the launch of the AWS Europe (London) Region, AWS can enable many more UK enterprise, public sector and startup customers to reduce IT costs, address data locality needs, and embark on rapid transformations in critical new areas, such as big data analysis and Internet of Things. Fraud.net is a good example of this.

AWS 166

AWS Cloud Artificial Intelligence IoT 166

All Things Distributed

APRIL 4, 2017

In making the switch to AWS, WOW air has saved between $30,000 and $45,000 on hardware, and software licensing. Among the APN Technology Partners and independent software vendors (ISVs) in the Nordics using AWS to deliver their software to customers around the world are Basware, eBuilder, F-Secure, Queue-it, Xstream, and many others.

AWS 116

AWS Airlines Latency Games 116