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

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

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 197

Analytics Artificial Intelligence Big Data Open Source 197

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

DZone

DECEMBER 27, 2023

Welcome to the first post in our exciting series on mastering offline data pipeline's best practices, focusing on the potent combination of Apache Airflow and data processing engines like Hive and Spark. Working together, they form the backbone of many modern data engineering solutions.

Best Practices 130

Best Practices Data Engineering Big Data Games 130

The Netflix TechBlog

JANUARY 13, 2022

By Vikram Srivastava and Marcelo Mayworm Netflix has one of the most complex data platforms in the cloud on which our data scientists and engineers run batch and streaming workloads. Pensive collects logs for the failed jobs launched by the step from the relevant data platform components and then extracts the stack traces.

Big Data 238

Big Data Infrastructure Metrics Hardware 238

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 196

Software Software Analytics Big Data 196

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. In this way, no human intervention is required in the remediation process. Multi-objective optimizations.

Tuning 210

Tuning Efficiency Big Data Engineering 210

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 198

Artificial Intelligence Tuning Strategy Big Data 198

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. This engine is written in Java and Scala. So, what is Apache Flink?

Code 150

Code Java Big Data Open Source 150

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 225

DevOps Big Data Cloud Innovation 225

Dynatrace

APRIL 20, 2023

Causal AI—which brings AI-enabled actionable insights to IT operations—and a data lakehouse, such as Dynatrace Grail , can help break down silos among ITOps, DevSecOps, site reliability engineering, and business analytics teams. “The weakness of a data lake is they fail when you need to access them fast,” Pawlowski said.

Analytics 196

Analytics Infrastructure Storage Efficiency 196

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 157

Big Data Government Open Source Storage 157

Dynatrace

MARCH 24, 2023

Container orchestration is a process that automates the deployment and management of containerized applications and services at scale. Container orchestration enables organizations to manage and automate the many processes and services that comprise workflows.

Infrastructure 195

Infrastructure Open Source Operating System Cloud 195

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 111

Big Data Analytics AWS Cloud 111

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 243

Analytics Artificial Intelligence Storage Serverless 243

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 211

Artificial Intelligence DevOps Hardware Virtualization 211

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 189

Big Data Google Scalability Processing 189

Scalegrid

MARCH 14, 2024

Defining Hybrid Cloud Strategy The decision-making process about where to situate data and applications is vital to any hybrid cloud solution. Enterprise cloud architects and engineers require significant knowledge to ensure that private and public clouds work together compatibly.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

Dynatrace

AUGUST 10, 2021

Vikash Chhaganlal , GM of Engineering and Infrastructure at Kiwibank said it. 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. Investing in data is easy but using it is really hard”.

DevOps 246

DevOps Innovation Big Data Cloud 246

The Morning Paper

OCTOBER 26, 2020

Helios also serves as a reference architecture for how Microsoft envisions its next generation of distributed big-data processing systems being built. What follows is a discussion of where big data systems might be heading, heavily inspired by the remarks in this paper, but with several of my own thoughts mixed in.

Cloud 104

Cloud Big Data Latency Architecture 104

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.

DevOps 205

DevOps Artificial Intelligence Healthcare Innovation 205

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 151

Azure Cloud Big Data Virtualization 151

ScaleOut Software

JULY 19, 2021

And it can maintain contextual information about every data source (like the medical history of a device wearer or the maintenance history of a refrigeration system) and keep it immediately at hand to enhance the analysis. Conventional streaming analytics architectures have not kept up with the growing demands of IoT.

IoT 78

IoT Analytics Big Data Architecture 78

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? Two approaches to AIOps.

Artificial Intelligence 221

Artificial Intelligence DevOps Innovation Metrics 221

Dynatrace

JANUARY 16, 2023

Most Kubernetes clusters in the cloud (73%) are built on top of managed distributions from the hyperscalers like AWS Elastic Kubernetes Service (EKS), Azure Kubernetes Service (AKS), or Google Kubernetes Engine (GKE). Big data : To store, search, and analyze large datasets, 32% of organizations use Elasticsearch.

Open Source 349

Open Source Java Operating System Programming 349

Dynatrace

APRIL 21, 2021

To do this effectively, you need a big data processing approach. The three challenges to optimizing Core Web Vitals is exactly why the Dynatrace Business Insights team have built the Insights Analytics Engine. How do you know where to focus first with failing pages? How Dynatrace Business Insights can help.

Traffic 265

Traffic Metrics Mobile Analytics 265

Dynatrace

APRIL 25, 2023

Having access to large data sets can be helpful, but only if organizations are able to leverage insights from the information. These analytics can help teams understand the stories hidden within the data and share valuable insights. and only they have access.”

Analytics 209

Analytics Big Data Media Operating System 209

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 190

Infrastructure Cloud Azure AWS 190

Dynatrace

JUNE 1, 2020

However, with today’s highly connected digital world, monitoring use cases expand to the services, processes, hosts, logs, networks, and of course, end-users that access these applications – including your customers and employees. With our AI engine, Davis, at the core Dynatrace provides precise answers in real-time. AI-Assistance.

Artificial Intelligence 185

Artificial Intelligence Social Media Monitoring IoT 185

SQL Server According to Bob

FEBRUARY 15, 2018

Microsoft engineering is actually sending quite a few folks over the Atlantic to come talk about SQL Server 2017, SQL Server on Linux, GDPR, Performance, Security, Azure Data Lake, Azure SQL Database, Azure SQL Data Warehouse, and Azure CosmosDB. Best practices on Building a Big Data Analytics Solution – Michael Rys.

Engineering 40

Engineering Azure Best Practices Servers 40

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 210

Processing Big Data Efficiency Engineering 210

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.

Cache 130

Cache Storage Scalability Architecture 130

Dynatrace

JUNE 1, 2020

However, with today’s highly connected digital world, monitoring use cases expand to the services, processes, hosts, logs, networks, and of course end-users that access these applications – including your customers and employees. With our AI engine, Davis, at the core Dynatrace provides precise answers in real-time. AI-Assistance.

Monitoring 132

Monitoring Performance Social Media Artificial Intelligence 132

High Scalability

APRIL 14, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). this is going to be a challenging journey for any backend engineer! this is going to be a challenging journey for any backend engineer! The result is a process that doesn't get you the best employees you could. Try out their platform.

Education 105

Education Software Engineering Scalability Engineering 105

High Scalability

MAY 12, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). this is going to be a challenging journey for any backend engineer! this is going to be a challenging journey for any backend engineer! The result is a process that doesn't get you the best employees you could. Try out their platform.

Education 102

Education Software Engineering Scalability Engineering 102

High Scalability

MARCH 24, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). this is going to be a challenging journey for any backend engineer! this is going to be a challenging journey for any backend engineer! The result is a process that doesn't get you the best employees you could. Who's Hiring? Please apply here.

Education 105

Education Software Engineering Engineering Big Data 105