Dynatrace

MAY 1, 2023

Then, big data analytics technologies, such as Hadoop, NoSQL, Spark, or Grail, the Dynatrace data lakehouse technology, interpret this information. Here are the six steps of a typical ITOA process : Define the data infrastructure strategy. Identify data use cases and develop a scalable delivery model with documentation.

Analytics 246

Analytics Artificial Intelligence Big Data Open Source 246

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. Performance.

Big Data 63

Big Data Storage Benchmarking Hardware 63

Dynatrace

JUNE 26, 2023

Software automation enables digital supply chain stakeholders — such as digital operations, DevSecOps, ITOps, and CloudOps teams — to orchestrate resources across the software development lifecycle to bring innovative, high-quality products and services to market faster. What is software analytics?

Software 246

Software Software Analytics 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. A variety of supervised, semi-supervised, and unsupervised matching techniques have also been developed. 2020, Article No.

Big Data 83

Big Data Open Source Processing Analytics 83

Dynatrace

OCTOBER 25, 2022

The need for developers and innovation is now even greater. 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.

DevOps 246

DevOps Big Data Cloud Innovation 246

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. How’s data engineering similar and different from software engineering?

Data Engineering 181

Data Engineering Engineering Big Data Software Engineering 181

The Netflix TechBlog

JULY 15, 2021

I stumbled into data engineering rather than making an intentional career move into the field. I started my career as an application developer with basic familiarity with SQL. I was later hired into my first purely data gig where I was able to deepen my knowledge of big data. What drew you to Netflix?

Data Engineering 197

Data Engineering Engineering Entertainment Big Data 197

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. A truly modern AIOps solution also serves the entire software development lifecycle to address the volume, velocity, and complexity of multicloud environments.

Artificial Intelligence 325

Artificial Intelligence Cloud Innovation Strategy 325

The Netflix TechBlog

MARCH 25, 2019

We adopted the following mission statement to guide our investments: “Provide a complete and accurate data lineage system enabling decision-makers to win moments of truth.” Nonetheless, Netflix data landscape (see below) is complex and many teams collaborate effectively for sharing the responsibility of our data system management.

Infrastructure 225

Infrastructure Big Data Transportation Architecture 225

The Netflix TechBlog

APRIL 29, 2019

Subsequently, many useful libraries get developed, making the language even more desirable to learn and use. We’ve developed a time series correlation system used both inside and outside the team as well as a distributed worker system to parallelize large amounts of analytical work to deliver results quickly.

Open Source 280

Open Source Network Infrastructure Big Data 280

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

Dynatrace

JULY 6, 2022

Developing automation takes time. This kind of automation can support key IT operations, such as infrastructure, digital processes, business processes, and big-data automation. Big data automation tools. Automating routine IT tasks eliminates the human element—and the potential mistakes that come with it.

Artificial Intelligence 246

Artificial Intelligence Tuning Strategy Big Data 246

Dynatrace

JULY 6, 2020

As adoption rates for Microsoft Azure continue to skyrocket, Dynatrace is developing a deeper integration with the platform to provide even more value to organizations that run their businesses on Azure or use it as a part of their multi-cloud strategy. See the health of your big data resources at a glance. Azure Front Door.

Azure 227

Azure Cloud Big Data Virtualization 227

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. It is an open-source framework for distributed processing of large amounts of data.

Code 159

Code Java Big Data Open Source 159

DZone

DECEMBER 28, 2020

The introduction of innovative technologies has brought the newest updates in software testing, development, design, and delivery. Nowadays, Big Data tests mainly include data testing, paving the way for the Internet of Things to become the center point. Besides, AI and ML seem to reach a new level.

Software 193

Software Software Testing Big Data 193

Dynatrace

APRIL 21, 2021

On the Dynatrace Business Insights team, we have developed analytical views and an approach to help you get started. To do this effectively, you need a big data processing approach. Not all pages are equally important, and development resources are top priority. How do you know where to focus first with failing pages?

Traffic 264

Traffic Mobile Metrics Analytics 264

Dynatrace

AUGUST 10, 2021

I had the privilege of setting everyone up for the day alongside my co-host Carrie Mott , Head of Marketing and Business Development for APAC. BPAY is in the midst of its digital transformation journey in which it is discovering the critical importance of developing “contemporary ways of designing, operating, and using” its software.

DevOps 246

DevOps Innovation Big Data Cloud 246

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. The accuracy was considered adequate by the developer. VLDB’19.

Big Data 57

Big Data Analytics Latency Azure 57

DZone

FEBRUARY 6, 2024

If the data sources are not available then customized plugins can be developed to integrate these data sources. Grafana is used widely these days to monitor and visualize the metrics for 100s or 1000s of servers, Kubernetes Platforms, Virtual Machines, Big Data Platforms, etc.

Big Data 173

Big Data Open Source Virtualization Metrics 173

The Netflix TechBlog

JUNE 20, 2024

On April 18th, 2024, we hosted the inaugural Data Engineering Open Forum at our Los Gatos office, bringing together data engineers from various industries to share, learn, and connect. At the conference, our speakers share their unique perspectives on modern developments, immediate challenges, and future prospects of data engineering.

Data Engineering 206

Data Engineering Engineering Entertainment Software Engineering 206

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

MARCH 24, 2023

By embracing public cloud and hybrid cloud computing environments, IT teams can further accelerate development and automate software deployment and management. Container technology enables organizations to efficiently develop cloud-native applications or to modernize legacy applications to take advantage of cloud services.

Infrastructure 246

Infrastructure Open Source Operating System Cloud 246

Dynatrace

DECEMBER 15, 2022

We’ll discuss how the responsibilities of ITOps teams changed with the rise of cloud technologies and agile development methodologies. Adding application security to development and operations workflows increases efficiency. So, what is ITOps? What is ITOps? CloudOps teams are one step further in the digital supply chain.

Artificial Intelligence 246

Artificial Intelligence DevOps Hardware Virtualization 246

Dynatrace

JANUARY 16, 2023

The immense growth of Kubernetes presents new security challenges in runtime and increased complexity in hardening CI/CD pipelines in development. Big data : To store, search, and analyze large datasets, 32% of organizations use Elasticsearch. Andreas Berger, Dynatrace Senior Principal Application Security.

Open Source 358

Open Source Java Operating System Programming 358

The Netflix TechBlog

JULY 26, 2021

Processors with Different Inputs/Outputs Data Mesh allows developers to contribute processors to the platform. Processors are not necessarily centrally developed and managed. However, the Data Mesh platform team strives to provide and manage the most highly leveraged processors (e.g. Iceberg, ElasticSearch, etc).

Big Data 257

Big Data Government Processing Analytics 257

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 15, 2020

In my recent Performance Clinic with Stefano Doni , CTO & Co-Founder of Akamas , I made the statement, “Application development and release cycles today are measured in days, instead of months. Supported technologies include cloud services, big data, databases, OS, containers, and application runtimes like the JVM.

Performance 260

Performance Java Metrics Cloud 260

Dynatrace

APRIL 19, 2023

“We also have some big data analytics use cases that help extend the Dynatrace platform, see how performance is affecting behavior, and identify long-term trends,” Rushlo said. ” BCLC has started onboarding developers into Dynatrace and monitoring additional services.

Entertainment 237

Entertainment Analytics Healthcare Games 237

Dynatrace

APRIL 11, 2023

The focus on bringing various organizational teams together—such as development, business, and security teams — makes sense as observability data, security data, and business event data coalesce in these cloud-native environments. As organizations develop new applications, vulnerabilities will continue to emerge.

Cloud 246

Cloud DevOps Open Source Retail 246

Dynatrace

AUGUST 14, 2023

As organizations become more familiar with baseline trends in user behavior, teams can develop hypotheses for why users are taking certain actions, and later verify with relevant analytics. When rolling out new features, user behavior analysts can use these capabilities to track customer adoption and make sure goals are proceeding on track.

Analytics 246

Analytics Social Media Website IoT 246

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 155

AWS Cloud Artificial Intelligence IoT 155

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 makes developing, operating, and securing modern applications and the environments they run on practically impossible without AI.

DevOps 246

DevOps Artificial Intelligence Healthcare Innovation 246

Dynatrace

APRIL 25, 2023

Exploratory analytics with collaborative analytics capabilities can be a lifeline for CloudOps, ITOps, site reliability engineering, and other teams struggling to access, analyze, and conquer the never-ending deluge of big data. These analytics can help teams understand the stories hidden within the data and share valuable insights.

Analytics 246

Analytics Big Data Media Operating System 246

O'Reilly

AUGUST 15, 2023

To follow up on our previous survey about low-code and no-code tools, we decided to run another short survey about tools specifically for software developers—including, but not limited to, GitHub Copilot and ChatGPT. We’re interested in how “developer enablement” tools of all sorts are changing the workplace.

Development 98

Development Programming Speed Open Source 98

Dynatrace

MARCH 14, 2022

With containers, microservices, applications, and other components that are constantly broken down and rebuilt as part of the software development lifecycle (SDLC), IT teams struggle to identify true issues and deliver software that enables doctors and nurses to deliver care. Today’s enterprise environments are dynamic and complex.

Healthcare 246

Healthcare Artificial Intelligence Innovation Strategy 246

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.

Tuning 217

Tuning Efficiency Big Data Engineering 217

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. My work is typically developed in R or Python. [Chris] Julie and I joined the Streaming DSE team at Netflix a few years ago and have been close colleagues and friends since then. Do they cause less errors?

Analytics 230

Analytics Education Innovation Engineering 230