All Things Distributed

JANUARY 20, 2020

A data lake is a centralized secure repository that allows you to store, govern, discover, and share all of your structured and unstructured data at any scale. Data lakes don't require a pre-defined schema, so you can process raw data without having to know what insights you might want to explore in the future.

Big Data 192

Big Data Logistics Retail Government 192

The Netflix TechBlog

NOVEMBER 20, 2023

by Jun He , Yingyi Zhang , and Pawan Dixit Incremental processing is an approach to process new or changed data in workflows. The key advantage is that it only incrementally processes data that are newly added or updated to a dataset, instead of re-processing the complete dataset.

Processing 219

Processing Big Data Efficiency Engineering 219

Dynatrace

MARCH 17, 2025

Until recently, improvements in data center power efficiency compensated almost entirely for the increasing demand for computing resources. The rise of big data, cryptocurrencies, and AI means the IT sector contributes significantly to global greenhouse gas emissions. However, this trend is now reversing.

Software Engineering 147

Software Engineering Engineering Software Software 147

DZone

FEBRUARY 23, 2023

Introduction With big data streaming platform and event ingestion service Azure Event Hubs , millions of events can be received and processed in a single second. Any real-time analytics provider or batching/storage adaptor can transform and store data supplied to an event hub.

Azure 306

Azure Big Data Storage Analytics 306

DZone

JUNE 3, 2024

This is especially the case when it comes to taking advantage of vast amounts of data stored in cloud platforms like Amazon S3 - Simple Storage Service, which has become a central repository of data types ranging from the content of web applications to big data analytics.

Big Data 278

Big Data AWS Storage Analytics 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 automates repetitive cloud operations tasks and streamlines the flow of analytics into decision-making processes.

Analytics 246

Analytics Artificial Intelligence Big Data Open Source 246

The Netflix TechBlog

JANUARY 13, 2022

This blog will explore these two systems and how they perform auto-diagnosis and remediation across our Big Data Platform and Real-time infrastructure. In the future, we are looking to automate this process. The streaming platform recently added Data Mesh , and we need to expand Streaming Pensive to cover that.

Big Data 242

Big Data Infrastructure Metrics Games 242

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 92

Big Data Analytics AWS Cloud 92

Abhishek Tiwari

DECEMBER 27, 2017

Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. Key challenges.

Big Data 63

Big Data Storage Benchmarking Hardware 63

Dynatrace

JUNE 26, 2023

This, in turn, accelerates the need for businesses to implement the practice of software automation to improve and streamline processes. This involves big data analytics and applying advanced AI and machine learning techniques, such as causal AI. Automate DevSecOps processes at scale.

Software 246

Software Software Analytics Big Data 246

Dynatrace

JULY 6, 2022

At its most basic, automating IT processes works by executing scripts or procedures either on a schedule or in response to particular events, such as checking a file into a code repository. Adding AIOps to automation processes makes the volume of data that applications and multicloud environments generate much less overwhelming.

Artificial Intelligence 246

Artificial Intelligence Tuning Strategy Big Data 246

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. The processing mode – traditional batch (with or without budget constraints), or incremental. Block processing.

Big Data 83

Big Data Open Source Processing Analytics 83

Rigor

MAY 22, 2019

Big data is like the pollution of the information age. The Big Data Struggle and Performance Reporting. The process often requires professionals to go through arduous corporate campaigns to educate key stakeholders and business leaders about the impact performance has on the business. Conclusion.

Big Data 76

Big Data Monitoring Performance Metrics 76

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. What is your favorite project?

Data Engineering 181

Data Engineering Engineering Big Data Software Engineering 181

The Netflix TechBlog

JULY 26, 2021

Netflix is known for its loosely coupled microservice architecture and with a global studio footprint, surfacing and connecting the data from microservices into a studio data catalog in real time has become more important than ever. With the latest Data Mesh Platform, data movement in Netflix Studio reaches a new stage.

Big Data 257

Big Data Government Processing Analytics 257

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. But it might also result in the entire software development process falling apart. Can organizations really function without an operations team? What is NoOps? Evolution of NoOps.

DevOps 246

DevOps Big Data Cloud Innovation 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. To achieve these AIOps benefits, comprehensive AIOps tools incorporate four key stages of data processing: Collection. Aggregation.

Artificial Intelligence 325

Artificial Intelligence Cloud Innovation Strategy 325

DZone

DECEMBER 21, 2020

Setting up a data warehouse is the first step towards fully utilizing big data analysis. Still, it is one of many that need to be taken before you can generate value from the data you gather. An important step in that chain of the process is data modeling and transformation.

Big Data 196

Big Data Google Scalability Processing 196

Dynatrace

OCTOBER 4, 2022

Data warehouses offer a single storage repository for structured data and provide a source of truth for organizations. However, organizations must structure and store data inputs in a specific format to enable extract, transform, and load processes, and efficiently query this data. Massively parallel processing.

Artificial Intelligence 246

Artificial Intelligence Storage Analytics Government 246

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

The Netflix TechBlog

JULY 15, 2021

I was later hired into my first purely data gig where I was able to deepen my knowledge of big data. After that, I joined MySpace back at its peak as a data engineer and got my first taste of data warehousing at internet-scale. Both were appliances located in our own data center. What drew you to Netflix?

Data Engineering 197

Data Engineering Engineering Entertainment Big Data 197

DZone

JANUARY 20, 2023

There is a countless number of enterprises, particularly Internet giants, that have explored ways to make graph data processing scalable. Having a distributed and scalable graph database system is highly sought after in many enterprise scenarios.

Scalability 210

Scalability Big Data Hardware Internet 210

DZone

JULY 29, 2019

In today's world, data is generated in high volumes and to make something out of it, extracted data is needed to be transformed, stored, maintained, governed and analyzed. These processes are only possible with a distributed architecture and parallel processing mechanisms that Big Data tools are based on.

Big Data 162

Big Data Government Open Source Storage 162

The Netflix TechBlog

MARCH 25, 2019

Netflix’s diverse data landscape made it challenging to capture all the right data and conforming it to a common data model. Spark is the primary big-data compute engine at Netflix and with pretty much every upgrade in Spark, the spark plan changed as well springing continuous and unexpected surprises for us.

Infrastructure 225

Infrastructure Big Data Transportation Architecture 225

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. Website monitoring examines a cloud-hosted website’s processes, traffic, availability, and resource use. What is cloud monitoring?

Cloud 295

Cloud Monitoring Best Practices Infrastructure 295

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.

Latency 252

Latency Storage Big Data Tuning 252

Dynatrace

SEPTEMBER 9, 2019

and finally, at the end of the build process, when she was ready to send a quote to the dealer the site just spun and spun as she hit submit. I still love data, but I am starting to love emotion-filled data. Big” data helps us make the right decisions and focus on the right things. How do we know that?

Big Data 210

Big Data Metrics Virtualization Network 210

DZone

DECEMBER 21, 2020

Applications used in the field of Big Data process huge amounts of information, and this often happens in real time. Naturally, such applications must be highly reliable so that no error in the code can interfere with data processing. The PVS-Studio static analyzer is one of the solutions to this problem.

Code 159

Code Java Big Data Open Source 159

Dynatrace

OCTOBER 4, 2022

Stop worrying about log data ingest and storage — start creating value instead. Dynatrace® Grail , an additional core technology for the Dynatrace® Software Intelligence platform , is the world’s first data lakehouse with massively parallel processing (MPP) for context-rich observability, business, and security analytics.

Analytics 264

Analytics Artificial Intelligence Storage Serverless 264

The Morning Paper

SEPTEMBER 8, 2019

Experiences with approximating queries in Microsoft’s production big-data clusters Kandula et al., I’ve been excited about the potential for approximate query processing in analytic clusters for some time, and this paper describes its use at scale in production. VLDB’19. A sizable fraction of the jobs are much larger.

Big Data 57

Big Data Analytics Latency Azure 57

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 188

Big Data Cache Engineering Data Engineering 188

Dynatrace

DECEMBER 15, 2022

In fact, Gartner estimates that 80% of enterprises will shut down their on-premises data centers by 2025. This transition to public, private, and hybrid cloud is driving organizations to automate and virtualize IT operations to lower costs and optimize cloud processes and systems. So, what is ITOps? What is ITOps? ITOps vs. AIOps.

Artificial Intelligence 246

Artificial Intelligence DevOps Hardware Virtualization 246

Dynatrace

APRIL 20, 2023

-based financial services group, discussed how the bank uses log monitoring on the Dynatrace platform with an emphasis on observability and security data. To grasp the challenges of multifeatured, cross-team cooperation dealing with observability data, consider the content of the logs generated. Dissolving data silos.

Analytics 246

Analytics Infrastructure Storage Architecture 246

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. CloudOps includes processes such as incident management and event management. The four stages of data processing. Analyze the data.

DevOps 246

DevOps Artificial Intelligence Healthcare Innovation 246

DZone

JULY 17, 2023

Apache Spark is a leading platform in the field of big data processing, known for its speed, versatility, and ease of use. Understanding Apache Spark Apache Spark is a unified computing engine designed for large-scale data processing.

Big Data 130

Big Data Performance Open Source Tuning 130

Dynatrace

JANUARY 16, 2023

Redis is an in-memory key-value store and cache that simplifies processing, storage, and interaction with data in Kubernetes environments. Big data : To store, search, and analyze large datasets, 32% of organizations use Elasticsearch. Note: The survey excluded all commercial observability offerings, including Dynatrace.

Open Source 358

Open Source Java Operating System Programming 358

Dynatrace

AUGUST 10, 2021

Dynatrace CMO Mike Maciag talked about the dangers of “status quo” and failing to get where you need to go because of loyalty to legacy APM software, or hanging onto outdated processes. On the other hand, every single step you take towards intelligently observing data across your organization brings increasingly greater rewards.

DevOps 246

DevOps Innovation Big Data Cloud 246