Dynatrace

AUGUST 10, 2021

This year’s conference agenda was packed full of choices, including: Keynotes : Topics included accelerating digital transformation, with Dynatrace CIO Mike Maciag, and Spatial Collapse: The Great Acceleration of Turning Data Into an Asset, with Tricia Wang from Sudden Compass. We’ve all heard it: data is one of your biggest assets.

DevOps 246

DevOps Innovation Big Data Cloud 246

The Netflix TechBlog

SEPTEMBER 18, 2020

and what the role entails by Julie Beckley & Chris Pham This Q&A provides insights into the diverse set of skills, projects, and culture within Data Science and Engineering (DSE) at Netflix through the eyes of two team members: Chris Pham and Julie Beckley. What was your path to working in data? There’s us to the right!

Analytics 232

Analytics Education Innovation Engineering 232

The Netflix TechBlog

DECEMBER 21, 2020

By Anupom Syam Background At Netflix, our current data warehouse contains hundreds of Petabytes of data stored in AWS S3 , and each day we ingest and create additional Petabytes. We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits.

Storage 214

Storage Latency Efficiency Data Engineering 214

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. As much as I love data, data is cold, it lacks emotion. Often, 4s is too slow.

Big Data 153

Big Data Metrics Virtualization Monitoring 153

The Netflix TechBlog

APRIL 29, 2019

Open Connect Open Connect is Netflix’s content delivery network (CDN). video streaming) takes place in the Open Connect network. The network devices that underlie a large portion of the CDN are mostly managed by Python applications. If any of this interests you, check out the jobs site or find us at PyCon. are you logged in?

Open Source 280

Open Source Network Infrastructure Big Data 280

Highly Scalable

MAY 1, 2012

Statistical analysis and mining of huge multi-terabyte data sets is a common task nowadays, especially in the areas like web analytics and Internet advertising. Analysis of such large data sets often requires powerful distributed data stores like Hadoop and heavy data processing with techniques like MapReduce.

Analytics 191

Analytics Traffic Big Data Efficiency 191

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 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 200

Software Software Analytics Big Data 200

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. With agent monitoring, third-party software collects data and reports from the component that’s attached to the agent.

Cloud 233

Cloud Monitoring Best Practices Infrastructure 233

Dynatrace

DECEMBER 15, 2022

Complex cloud computing environments are increasingly replacing traditional data centers. In fact, Gartner estimates that 80% of enterprises will shut down their on-premises data centers by 2025. Additionally, they manage applications and services deployed on the network and provide secure access to authorized users.

Artificial Intelligence 215

Artificial Intelligence DevOps Hardware Virtualization 215

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. Modern IT environments — whether multicloud, on-premises, or hybrid-cloud architectures — generate exponentially increasing data volumes.

Analytics 246

Analytics Artificial Intelligence Storage Serverless 246

Dynatrace

MARCH 24, 2023

But managing the deployment, modification, networking, and scaling of multiple containers can quickly outstrip the capabilities of development and operations teams. This orchestration includes provisioning, scheduling, networking, ensuring availability, and monitoring container lifecycles. How does container orchestration work?

Infrastructure 198

Infrastructure Open Source Operating System Cloud 198

Scalegrid

FEBRUARY 8, 2024

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise.

Storage 130

Storage Systems Big Data Azure 130

Dynatrace

JULY 6, 2020

Azure Virtual Network Gateways. 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. Azure Front Door. Azure Traffic Manager.

Azure 153

Azure Cloud Big Data Virtualization 153

O'Reilly

SEPTEMBER 19, 2023

” I’ve called out the data field’s rebranding efforts before; but even then, I acknowledged that these weren’t just new coats of paint. Each time, the underlying implementation changed a bit while still staying true to the larger phenomenon of “Analyzing Data for Fun and Profit.” Goodbye, Hadoop.

Hardware 101

Hardware Storage Big Data Blockchain 101

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. There are four stages of data processing: Collect raw data. Analyze the data.

DevOps 209

DevOps Artificial Intelligence Healthcare Innovation 209

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. Websites, mobile apps, and business applications are typical use cases for monitoring. Continuous Automation.

Artificial Intelligence 185

Artificial Intelligence Social Media Monitoring IoT 185

All Things Distributed

DECEMBER 13, 2016

The council has deployed IoT Weather Stations in Schools across the City and is using the sensor information collated in a Data Lake to gain insights on whether the weather or pollution plays a part in learning outcomes. The British Government is also helping to drive innovation and has embraced a cloud-first policy for technology adoption.

AWS 157

AWS Cloud Artificial Intelligence IoT 157

Dynatrace

APRIL 19, 2023

At Dynatrace Perform 2023 , Ben Rushlo, Business Insights leader at Dynatrace, and Navid Mehdiabadi, BCLC’s APM expert, discuss how the right business insights are crucial to making data-driven decisions and improving business outcomes. “It’s a journey in Dynatrace,” Rushlo said. “Our players just see the frontend.

Entertainment 165

Entertainment Analytics Healthcare Games 165

Dynatrace

JUNE 29, 2022

Hybrid cloud architecture is a computing environment that shares data and applications on a combination of public clouds and on-premises private clouds. 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.

Infrastructure 194

Infrastructure Cloud Azure AWS 194

The Netflix TechBlog

OCTOBER 14, 2024

Overview At Netflix, the Analytics and Developer Experience organization, part of the Data Platform, offers a product called Workbench. Workbench is a remote development workspace based on Titus that allows data practitioners to work with big data and machine learning use cases at scale.

Latency 217

Latency Virtualization Traffic Processing 217

All Things Distributed

SEPTEMBER 5, 2013

Over the past few years, two important trends that have been disrupting the database industry are mobile applications and big data. The explosive growth in mobile devices and mobile apps is generating a huge amount of data, which has fueled the demand for big data services and for high scale databases.

Big Data 78

Big Data Mobile Latency Database 78

Scalegrid

JUNE 28, 2024

It is widely utilized across various industries, such as finance, telecommunications, and e-commerce, for managing activities, including transaction processing, data streaming, and instantaneous messaging. Key Takeaways RabbitMQ is an open-source message broker facilitating seamless data exchange across diverse systems.

IoT 130

IoT Healthcare Programming Open Source 130

The Morning Paper

MAY 14, 2019

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., Using network queue depths alone is enough to signal a large fraction of QoS violations, although smaller than when the full instrumentation is available. ASPLOS’19. Distributed tracing and instrumentation.

Big Data 45

Big Data Cloud Performance Hardware 45

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. Websites, mobile apps, and business applications are typical use cases for monitoring. Performance monitoring.

Monitoring 133

Monitoring Performance Social Media Artificial Intelligence 133

All Things Distributed

DECEMBER 20, 2017

How companies can use ideas from mass production to create business with data. In this way, designers are part of an ecosystem in which the functionalities of simulations, data and people come together, enabling them to develop better products faster. Value creation through data. Strategically, IT doesn't matter.

Artificial Intelligence 72

Artificial Intelligence Social Media Logistics AWS 72

Scalegrid

MARCH 14, 2024

Implementing a hybrid cloud solution involves careful decision-making regarding application and data placement, migration strategies, and choosing compatible cloud service providers while ensuring seamless integration and addressing security and compliance challenges. We will examine each of these elements in more detail.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

ScaleOut Software

JULY 19, 2021

Incoming data is saved into data storage (historian database or log store) for query by operational managers who must attempt to find the highest priority issues that require their attention. Unlike manual or automatic log queries, in-memory computing can continuously run analytics code on all incoming data and instantly find issues.

IoT 78

IoT Big Data Analytics Architecture 78

Highly Scalable

JANUARY 31, 2012

Applications: Log Analysis, Data Querying. Applications: Log Analysis, Data Querying, ETL, Data Validation. Solution: Problem description is split in a set of specifications and specifications are stored as input data for Mappers. Applications: ETL, Data Analysis. Distributed Task Execution.

C++ 144

C++ Network Ecommerce Processing 144

All Things Distributed

DECEMBER 8, 2016

AWS data centers in Canada will draw from a regional electricity grid that is 99 percent powered by hydropower. It adopted Amazon Redshift, Amazon EMR and AWS Lambda to power its data warehouse, big data, and data science applications, supporting the development of product features at a fraction of the cost of competing solutions.

AWS 134

AWS Cloud Lambda Innovation 134

Scalegrid

MARCH 28, 2024

In this comparison of Redis vs Memcached, we strip away the complexity, focusing on each in-memory data store’s performance, scalability, and unique features. Redis is better suited for complex data models, and Memcached is better suited for high-throughput, string-based caching scenarios.

Cache 130

Cache Storage Architecture Scalability 130

All Things Distributed

JANUARY 6, 2016

Mirae Asset Global Investments improved its web service environment and reduced annual management costs by 50% by consolidating the management of all web services, including servers, network, database, and security. Many of these enterprises are assisted by our extensive partner ecosystem in Korea.

AWS 102

AWS Cloud Games Latency 102

All Things Distributed

MARCH 2, 2011

Japanese companies and consumers have become used to low latency and high-speed networking available between their businesses, residences, and mobile devices. With the launch of the Asia Pacific (Tokyo) Region, companies can now leverage the AWS suite of infrastructure web services directly connected to Japanese networks.

AWS 92

AWS Cloud Games Latency 92

All Things Distributed

AUGUST 20, 2012

It requires substantial upfront capital investments in cold data storage systems such as tape robots and tape libraries, then thereâ??s In Amazon Glacier data is stored as archives, which are uploaded to Glacier and organized in vaults, which customers can control access to using the AWS Identity and Access Management (IAM) service.

Storage 115

Storage Cloud AWS Media 115

All Things Distributed

FEBRUARY 17, 2011

I have used a bucket policy to make all documents world readable, but you could create one that restricts it to referrers, network address range, time of day, etc. Driving down the cost of Big-Data analytics. You will also need to set access control to make sure that your content is publicly accessible.

AWS 123

AWS Website Storage Servers 123

DZone

JUNE 3, 2019

Using local SSDs inside of the GPU node delivers fast access to data during training, but introduces challenges that impact the overall solution in terms of scalability, data access, and data protection.

Storage 100

Storage Performance Network Scalability 100

Abhishek Tiwari

DECEMBER 27, 2017

ETL refers to extract, transform, load and it is generally used for data warehousing and data integration. There are several emerging data trends that will define the future of ETL in 2018. A common theme across all these trends is to remove the complexity by simplifying data management as a whole.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49