Dynatrace

MAY 1, 2023

Additionally, ITOA gathers and processes information from applications, services, networks, operating systems, and cloud infrastructure hardware logs in real time. Then, big data analytics technologies, such as Hadoop, NoSQL, Spark, or Grail, the Dynatrace data lakehouse technology, interpret this information.

Analytics 187

Analytics Artificial Intelligence Big Data Open Source 187

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. ICDE’16 (PowerDrill is a Google internal system). VLDB’19.

Big Data 57

Big Data Analytics Latency Azure 57

Uber Engineering

APRIL 5, 2018

Three years ago, Uber Engineering adopted Hadoop as the storage ( HDFS ) and compute ( YARN ) infrastructure for our organization’s big data analysis.

Systems 109

Systems Big Data Storage Infrastructure 109

DZone

FEBRUARY 1, 2023

Built on Azure Blob Storage, Azure Data Lake Storage Gen2 is a suite of features for big data analytics. Azure Data Lake Storage Gen1 and Azure Blob Storage's capabilities are combined in Data Lake Storage Gen2. For instance, Data Lake Storage Gen2 offers scale, file-level security, and file system semantics.

Azure 243

Azure Storage Big Data Analytics 243

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 187

Software Software Analytics Big Data 187

The Netflix TechBlog

JANUARY 13, 2022

The data platform is built on top of several distributed systems, and due to the inherent nature of these systems, it is inevitable that these workloads run into failures periodically. We have been working on an auto-diagnosis and remediation system called Pensive in the data platform to address these concerns.

Big Data 238

Big Data Infrastructure Metrics Hardware 238

DZone

JANUARY 31, 2023

Big data is at the center of all business decisions these days. It refers to large volumes of data generated through different sources, and this data then provides the foundation for business decisions. There are different ways through which we can process data. The size of data in batch processing is known.

Processing 235

Processing Big Data Systems 235

The Netflix TechBlog

OCTOBER 28, 2021

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. I developed many batch and real-time data pipelines using open source technologies for AOL Advertising and eBay. What is your favorite project?

Data Engineering 173

Data Engineering Engineering Big Data Software Engineering 173

DZone

JANUARY 20, 2023

Having a distributed and scalable graph database system is highly sought after in many enterprise scenarios. Do Not Be Misled Designing and implementing a scalable graph database system has never been a trivial task.

Scalability 201

Scalability Big Data Hardware Internet 201

The Netflix TechBlog

MAY 4, 2023

Behind the scenes, a myriad of systems and services are involved in orchestrating the product experience. These backend systems are consistently being evolved and optimized to meet and exceed customer and product expectations. This technique facilitates validation on multiple fronts.

Traffic 339

Traffic Latency Tuning Systems 339

All Things Distributed

AUGUST 18, 2011

Werner Vogels weblog on building scalable and robust distributed systems. 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.

Big Data 112

Big Data Analytics AWS Scalability 112

DZone

JULY 22, 2022

Honestly, these two terms have recently been doing rounds in the big data world. Over the years, EDI has become a standard document exchange system, whereas API is on its way to becoming a popular alternative to EDI.

Big Data 188

Big Data Technology Technology Systems 188

The Morning Paper

MAY 14, 2019

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., Seer is an online system that observes the behaviour of cloud applications (using the DeathStarBench microservices for the evaluation) and predicts when QoS violations may be about to occur. ASPLOS’19.

Big Data 45

Big Data Cloud Performance Hardware 45

Dynatrace

JANUARY 16, 2023

As Kubernetes adoption increases and it continues to advance technologically, Kubernetes has emerged as the “operating system” of the cloud. Kubernetes is emerging as the “operating system” of the cloud. Kubernetes is emerging as the “operating system” of the cloud. Kubernetes moved to the cloud in 2022.

Open Source 342

Open Source Java Operating System Programming 342

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 210

Tuning Efficiency Big Data Engineering 210

Dynatrace

JULY 6, 2022

While automating IT practices can save administrators a lot of time, without AIOps, the system is only as intelligent as the humans who program it. This kind of automation can support key IT operations, such as infrastructure, digital processes, business processes, and big-data automation. Big data automation tools.

Artificial Intelligence 188

Artificial Intelligence Tuning Strategy Big Data 188

Dynatrace

OCTOBER 25, 2022

Early implementations of NoOps were just ‘lift and shift’ efforts that replicated existing systems to the cloud. AIOps , a term coined by Gartner in 2016, combines big data and machine learning to automate IT operations processes, including event correlation, anomaly detection and causality determination. Evolution of NoOps.

DevOps 217

DevOps Big Data Cloud Innovation 217

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? Why is IT operations important?

Artificial Intelligence 202

Artificial Intelligence DevOps Hardware Virtualization 202

Uber Engineering

JUNE 1, 2023

Uber runs more than 100K big data workloads per day using Apache Spark–at that scale it’s crucial to write optimized apps. The Delivery Data Solutions team built Spark Analysers, a real-time system to catch anti-patterns in the Spark application at Uber scale, helping Uber developers optimize their apps.

Big Data 82

Big Data Systems Development 82

The Morning Paper

OCTOBER 26, 2020

As a production system within Microsoft capturing around a quadrillion events and indexing 16 trillion search keys per day it would be interesting in its own right, but there’s a lot more to it than that. These two narratives of reference architecture and ingestion/indexing system are interwoven throughout the paper.

Cloud 104

Cloud Big Data Latency Architecture 104

Dynatrace

MARCH 24, 2023

Containers enable developers to package microservices or applications with the libraries, configuration files, and dependencies needed to run on any infrastructure, regardless of the target system environment. This means organizations are increasingly using Kubernetes not just for running applications, but also as an operating system.

Infrastructure 185

Infrastructure Open Source Operating System Cloud 185

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. Like the development and design phases, these applications generate massive data volumes that offer relevant and actionable insights.

Artificial Intelligence 285

Artificial Intelligence Cloud Innovation Strategy 285

Scalegrid

MARCH 14, 2024

Understanding Hybrid Cloud Strategy A hybrid cloud merges the capabilities of public and private clouds into a singular, coherent system. This combination allows for the fluid movement of data and applications across different environments, facilitating shared workloads seamlessly. The tool must be compatible with your current systems.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

ScaleOut Software

JULY 19, 2021

How are we managing the torrent of telemetry that flows into analytics systems from these devices? If temperature-sensitive cargo in a long haul truck is about to be impacted by an erratic refrigeration system with known erratic behavior and repair history, the driver needs to be informed immediately. The list goes on.

IoT 78

IoT Analytics Big Data Architecture 78

Dynatrace

APRIL 19, 2023

.” Accessing business insights and data with precision and long-term context After working with Dynatrace, BCLC now has a twenty-four-seven data center team with an easy-to-share, intuitive datacenter hyper wall dashboard showing the overall health of the entire system — infrastructure, applications, networks, and user experience.

Entertainment 157

Entertainment Analytics Healthcare Games 157

Dynatrace

OCTOBER 4, 2022

Additionally, efforts such as lowered data retention times, two-tiered storage systems, shaky index management, sampled data, and data pipelines reduce the overall amount of stored data. Grail addresses today’s challenges of big data and cloud everywhere: Grail is highly scalable, cost-effective, and super-fast.

Analytics 234

Analytics Artificial Intelligence Storage Serverless 234

Dynatrace

AUGUST 10, 2021

She dispelled the myth that more big data equals better decisions, higher profits, or more customers. Investing in data is easy but using it is really hard”. The fact is, data on its own isn’t meaningful. Tricia quoted the statistic that companies typically use 3% of their data to inform decisions.

DevOps 246

DevOps Innovation Big Data Cloud 246

Dynatrace

MARCH 14, 2022

Over the past decade, the industry moved from paper-based to electronic health records (EHRs)—digitizing the backbone of patient data. As patient care continues to evolve, IT teams have accelerated this shift from legacy, on-premises systems to cloud technology to more build, test, and deploy software, and fuel healthcare innovation.

Healthcare 227

Healthcare Artificial Intelligence Innovation Strategy 227

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. The four stages of data processing. This process continues until the system identifies a root cause. Two types of root cause.

DevOps 195

DevOps Artificial Intelligence Healthcare Innovation 195

Dynatrace

SEPTEMBER 9, 2019

I love data. I have spent virtually my entire career looking at data. Synthetic data, network data, system data, and the list goes on. As much as I love data, data is cold, it lacks emotion. I still love data, but I am starting to love emotion-filled data. Dynatrace news.

Big Data 148

Big Data Metrics Virtualization Monitoring 148

Dynatrace

AUGUST 14, 2023

Analyze user behavior data Once collected, teams can then segment the data according to specific parameters. These parameters can include device type, geolocation, app version, browser, and operating system. An organization with a mature analytics practice will typically distinguish between user properties.

Analytics 229

Analytics Social Media Website IoT 229

Dynatrace

APRIL 11, 2023

Log4Shell required many organizations to take devices and applications offline to prevent malicious attackers from gaining access to IT systems and sensitive data. As a result, organizations need to be vigilant in identifying and addressing vulnerabilities to protect their systems and data.

Cloud 186

Cloud DevOps Open Source Retail 186

Scalegrid

MARCH 28, 2024

Advanced Redis Features Showdown Big data center concept, cloud database, server power station of the future. Data transfer technology. Cube or box Block chain of abstract financial data. High data availability is achieved. Synchronization of personal information. </p>

Cache 130

Cache Storage Scalability Architecture 130

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 199

Analytics Big Data Media Operating System 199

Dynatrace

SEPTEMBER 15, 2020

Supported technologies include cloud services, big data, databases, OS, containers, and application runtimes like the JVM. Akamas is comparing data across different experiments to identify the optimal configuration of your system. Automation is the key to optimizing our systems. via Cloud APIs or plain simple SSH).

Performance 185

Performance Java Metrics Cloud 185

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.” This contrasts stochastic AIOps approaches that use probability models to infer the state of systems. What is AIOps?

Artificial Intelligence 212

Artificial Intelligence DevOps Innovation Metrics 212

Dynatrace

MARCH 11, 2021

I took a big-data-analysis approach, which started with another problem visualization. This is what I wanted to optimize and avoid and many traditional (or homegrown) systems aren’t doing this. This time defines when Dynatrace will invoke the integration to 3 rd party system for a problem after it has been detected.

Tuning 263

Tuning Architecture Monitoring Big Data 263