DZone

JANUARY 19, 2023

Because with the advent of cloud providers, we are less worried about managing data centers. This leads to an increase in the size of data as well. Big data is generated and transported using various mediums in single requests. Everything is available within seconds on-demand. We need to cut down on transportation.

Best Practices 262

Best Practices Transportation Big Data Latency 262

Dynatrace

MAY 1, 2023

In addition to improved IT operational efficiency at a lower cost, ITOA also enhances digital experience monitoring for increased customer engagement and satisfaction. Then, big data analytics technologies, such as Hadoop, NoSQL, Spark, or Grail, the Dynatrace data lakehouse technology, interpret this information.

Analytics 246

Analytics Artificial Intelligence Big Data Open Source 246

All Things Distributed

AUGUST 18, 2011

Driving down the cost of Big-Data analytics. The Amazon Elastic MapReduce (EMR) team announced today the ability to seamlessly use Amazon EC2 Spot Instances with their service, significantly driving down the cost of data analytics in the cloud. However, this cannot be done without efficient, scalable data analytics.

Big Data 94

Big Data Analytics AWS Cloud 94

Dynatrace

JUNE 26, 2023

Software analytics offers the ability to gain and share insights from data emitted by software systems and related operational processes to develop higher-quality software faster while operating it efficiently and securely. This involves big data analytics and applying advanced AI and machine learning techniques, such as causal AI.

Software 246

Software Software Analytics Big Data 246

Dynatrace

JULY 6, 2022

Ultimately, IT automation can deliver consistency, efficiency, and better business outcomes for modern enterprises. Automating IT practices offers enterprises faster data centers and cloud operations, as well as increased flexibility and accuracy. IT automation tools can achieve enterprise-wide efficiency. Read eBook now!

Artificial Intelligence 246

Artificial Intelligence Tuning Strategy Big Data 246

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 225

Infrastructure Big Data Transportation Architecture 225

Dynatrace

OCTOBER 4, 2022

While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. What is a data lakehouse? Data warehouses.

Artificial Intelligence 246

Artificial Intelligence Storage Analytics Government 246

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. For example: Greater IT staff efficiency. What is AIOps, and how does it work? million per year by automating key processes.

Artificial Intelligence 325

Artificial Intelligence Cloud Innovation Strategy 325

The Netflix TechBlog

MARCH 4, 2024

Operational automation–including but not limited to, auto diagnosis, auto remediation, auto configuration, auto tuning, auto scaling, auto debugging, and auto testing–is key to the success of modern data platforms. the retry success probability) and compute cost efficiency (i.e., Multi-objective optimizations.

Tuning 217

Tuning Efficiency Big Data Engineering 217

The Morning Paper

DECEMBER 13, 2020

An overview of end-to-end entity resolution for big data , Christophides et al., It’s an important part of many modern data workflows, and an area I’ve been wrestling with in one of my own projects. Dynamic approaches schedule block processing on the fly to maximise efficiency. ACM Computing Surveys, Dec.

Big Data 83

Big Data Open Source Processing Analytics 83

The Netflix TechBlog

OCTOBER 27, 2020

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. The processed data is typically stored as data warehouse tables in AWS S3. Moving data with Bulldozer at Netflix.

Latency 252

Latency Storage Big Data Tuning 252

The Netflix TechBlog

OCTOBER 28, 2021

Netflix’s unique work culture and petabyte-scale data problems are what drew me to Netflix. During earlier years of my career, I primarily worked as a backend software engineer, designing and building the backend systems that enable big data analytics. You can learn more about it from my talk at the Flink forward conference.

Data Engineering 181

Data Engineering Engineering Big Data Software Engineering 181

Uber Engineering

AUGUST 14, 2019

Maintaining Uber’s large-scale data warehouse comes with an operational cost in terms of ETL functions and storage. In our experience, optimizing for operational efficiency requires answering one key question: for which tables does the maintenance cost supersede utility?

Efficiency 110

Efficiency Engineering Design Storage 110

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 227

Azure Cloud Big Data Virtualization 227

Dynatrace

OCTOBER 4, 2022

Several pain points have made it difficult for organizations to manage their data efficiently and create actual value. Limited data availability constrains value creation. Traditional solutions and approaches are inefficient given the number of manual tasks that are required for effective log data ingest.

Analytics 264

Analytics Artificial Intelligence Storage Serverless 264

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 246

Analytics Infrastructure Storage Architecture 246

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. He meant that more and more developers are now becoming responsible for operations, and operations are becoming ingrained in developers’ job descriptions.

DevOps 246

DevOps Big Data Cloud Innovation 246

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. What is cloud monitoring? ” The post What is cloud monitoring?

Cloud 295

Cloud Monitoring Best Practices Infrastructure 295

DZone

AUGUST 23, 2023

In the era of big data, efficient data management and query performance are critical for organizations that want to get the best operational performance from their data investments.

Big Data 130

Big Data Analytics Innovation Scalability 130

Alex Podelko

DECEMBER 19, 2019

Boris has unique expertise in that area – especially in Big Data applications. Marrying Artificial Intelligence and Automation to Drive Operational Efficiencies by Priyanka Arora, Asha Somayajula, Subarna Gaine, Mastercard. How to select appropriate IT Infrastructure to support Digital Transformation by Boris Zibitsker, BEZNext.

Efficiency 100

Efficiency Artificial Intelligence Scalability Performance 100

The Netflix TechBlog

JUNE 20, 2024

To handle errors efficiently, Netflix developed a rule-based classifier for error classification called “Pensive.” To address this, we propose developing an intelligent agent that can automatically discover, map, and query all data within an enterprise.

Data Engineering 206

Data Engineering Engineering Entertainment Software Engineering 206

The Netflix TechBlog

APRIL 29, 2019

Demand Engineering Demand Engineering is responsible for Regional Failovers , Traffic Distribution, Capacity Operations and Fleet Efficiency of the Netflix cloud. 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 280

Open Source Network Infrastructure Big Data 280

The Netflix TechBlog

JULY 26, 2021

At Netflix Studio, teams build various views of business data to provide visibility for day-to-day decision making. With dependable near real-time data, Studio teams are able to track and react better to the ever-changing pace of productions and improve efficiency of global business operations using the most up-to-date information.

Big Data 257

Big Data Government Processing Analytics 257

The Netflix TechBlog

NOVEMBER 20, 2023

We will show how we are building a clean and efficient incremental processing solution (IPS) by using Netflix Maestro and Apache Iceberg. IPS provides the incremental processing support with data accuracy, data freshness, and backfill for users and addresses many of the challenges in workflows. past 3 hours or 10 days).

Processing 219

Processing Big Data Efficiency Engineering 219

The Morning Paper

SEPTEMBER 8, 2019

Experiences with approximating queries in Microsoft’s production big-data clusters Kandula et al., Microsoft’s big data clusters have 10s of thousands of machines, and are used by thousands of users to run some pretty complex queries. Individual samplers need to be built to be high throughput and memory efficient.

Big Data 57

Big Data Analytics Latency Azure 57

The Netflix TechBlog

SEPTEMBER 18, 2020

I bring my breadth of big data tools and technologies while Julie has been building statistical models for the past decade. They are continuously innovating compression algorithms to efficiently send high quality audio and video files to our customers over the internet. Is the benefit uniform, or do certain cohorts of members?—?such

Analytics 230

Analytics Education Innovation Engineering 230

DZone

DECEMBER 27, 2023

In this kickoff post, we delve into the intricacies of Apache Airflow and AWS EMR, a managed cluster platform for big data processing. Working together, they form the backbone of many modern data engineering solutions.

Best Practices 140

Best Practices Data Engineering Big Data Games 140

Dynatrace

MARCH 14, 2022

The healthcare industry is embracing cloud technology to improve the efficiency, quality, and security of patient care, and this year’s HIMSS Conference in Orlando, Fla., AIOps (or “AI for IT operations”) uses artificial intelligence so that big data can help IT teams work faster and more effectively.

Healthcare 246

Healthcare Artificial Intelligence Innovation Strategy 246

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.

Artificial Intelligence 246

Artificial Intelligence DevOps Hardware Virtualization 246

Dynatrace

JUNE 26, 2024

Automation Based on the sheer volume and variety of data available to observability tools, IT automation is critical to ensure efficient operations. While human oversight is required to ensure outputs meet expectations, relying on manual processes to collect and correlate data is no longer feasible. Exploratory analytics.

Analytics 246

Analytics Infrastructure Metrics Efficiency 246

Highly Scalable

MARCH 1, 2012

Nevertheless, entry modification is generally less efficient than entry insertion in the majority of implementations. It is quite clear that a search of users that meet the criteria can be efficiently done using inverted indexes like {Category -> [user IDs]} or {Site -> [user IDs]}. in the set of users that meet the criteria).

Database 279

Database Ecommerce Efficiency Engineering 279

Dynatrace

JUNE 1, 2020

With answers at your fingertips, data backed decisions, and real-time visibility into business KPIs, Dynatrace enables you to consistently deliver better digital business outcomes across all your channels more efficiently than ever before. Dynatrace APM – Named a Leader in APM and yet, we’re much more.

Artificial Intelligence 254

Artificial Intelligence Social Media Monitoring IoT 254

The Netflix TechBlog

JUNE 7, 2021

The data is also used by security and other partner teams for insight and incident analysis. Summary Providing network insight into the cloud network infrastructure using eBPF flow logs at scale is made possible with eBPF and a highly scalable and efficient flow collection pipeline.

Network 327

Network Transportation AWS Cloud 327

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. Alert fatigue and chasing false positives are not only efficiency problems. SecOps: Applying AIOps to secure applications in real time.

DevOps 246

DevOps Artificial Intelligence Healthcare Innovation 246

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. Apache Mesos with the Marathon DC/OS is popular for large-scale production clusters running existing workloads on big data systems, such as Hadoop, Kafka, and Spark.

Infrastructure 246

Infrastructure Open Source Operating System Cloud 246

Scalegrid

FEBRUARY 8, 2024

It utilizes methodologies like DStore, which takes advantage of underused hard drive space by using it for storing vast amounts of collected datasets while enabling efficient recovery processes. These systems enable vast amounts of data to be spread over multiple nodes, allowing for simultaneous access and boosting processing efficiency.

Storage 130

Storage Systems Big Data Azure 130

The Netflix TechBlog

DECEMBER 21, 2020

We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits. This article will list some of the use cases of AutoOptimize, discuss the design principles that help enhance efficiency, and present the high-level architecture.

Storage 212

Storage Latency Efficiency Data Engineering 212