Dynatrace

MARCH 24, 2023

This orchestration includes provisioning, scheduling, networking, ensuring availability, and monitoring container lifecycles. The configuration file directs the container orchestration tool on how to retrieve container images, how to create a network between containers, and where to store log data or mount storage volumes.

Infrastructure 185

Infrastructure Open Source Operating System Cloud 185

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

Dynatrace

JULY 6, 2020

In addition to providing AI-powered full-stack monitoring capabilities , Dynatrace has long featured broad support for Azure Services and intuitive, native integration with extensions for using OneAgent on Azure. See the health of your big data resources at a glance. Gain enhanced visibility into your Azure environment.

Azure 147

Azure Cloud Big Data Virtualization 147

Dynatrace

MAY 1, 2023

With 99% of organizations using multicloud environments , effectively monitoring cloud operations with AI-driven analytics and automation is critical. IT operations analytics (ITOA) with artificial intelligence (AI) capabilities supports faster cloud deployment of digital products and services and trusted business insights.

Analytics 187

Analytics Artificial Intelligence Big Data Open Source 187

Dynatrace

AUGUST 14, 2023

As user experiences become increasingly important to bottom-line growth, organizations are turning to behavior analytics tools to understand the user experience across their digital properties. In doing so, organizations are maximizing the strategic value of their customer data and gaining a competitive advantage.

Analytics 228

Analytics Social Media Website IoT 228

ScaleOut Software

JULY 19, 2021

Real-Time Device Tracking with In-Memory Computing Can Fill an Important Gap in Today’s Streaming Analytics Platforms. The Limitations of Today’s Streaming Analytics. How are we managing the torrent of telemetry that flows into analytics systems from these devices? The list goes on.

IoT 78

IoT Analytics Big Data Architecture 78

DZone

MAY 5, 2021

Anytime, every time or sometime you would have heard someone going around with data analysis and saying maybe this could have happened because of this, maybe users did not like the feature or maybe we were wrong all the time. Any analysis and prediction in data analytics across industries experience what I call maybe syndrome.

Analytics 195

Analytics Testing Big Data Code 195

Dynatrace

FEBRUARY 16, 2023

How do you get more value from petabytes of exponentially exploding, increasingly heterogeneous data? The short answer: The three pillars of observability—logs, metrics, and traces—converging on a data lakehouse. To solve this problem, Dynatrace launched Grail, its causational data lakehouse , in 2022.

Analytics 185

Analytics Innovation Metrics Database 185

Tech News Gather

OCTOBER 7, 2023

In this digital age, where every click and interaction can be tracked, monitored, and optimized, have you ever considered the remarkable potential of a phone call tracking app? A phone call tracking app is a software tool that enables businesses to monitor and analyze incoming calls.

Strategy 52

Strategy Big Data Scalability Games 52

The Netflix TechBlog

JULY 26, 2021

This happens at an unprecedented scale and introduces many interesting challenges; one of the challenges is how to provide visibility of Studio data across multiple phases and systems to facilitate operational excellence and empower decision making. With the latest Data Mesh Platform, data movement in Netflix Studio reaches a new stage.

Big Data 253

Big Data Government Analytics Processing 253

Dynatrace

APRIL 20, 2023

Modern organizations ingest petabytes of data daily, but legacy approaches to log analysis and management cannot accommodate this volume of data. At Dynatrace Perform 2023 , Maciej Pawlowski, senior director of product management for infrastructure monitoring at Dynatrace, and a senior software engineer at a U.K.

Analytics 186

Analytics Infrastructure Storage Efficiency 186

ScaleOut Software

NOVEMBER 24, 2020

The volume of incoming telemetry challenges current telematics systems to keep up and quickly make sense of all the data. At the same time, telemetry snapshots are stored in a data lake, such as HDFS , for offline batch analysis and visualization using big data tools like Spark. Current Telematics Architecture.

Analytics 52

Analytics Architecture Scalability Software Architecture 52

Dynatrace

OCTOBER 4, 2022

Log management and analytics is an essential part of any organization’s infrastructure, and it’s no secret the industry has suffered from a shortage of innovation for several years. Several pain points have made it difficult for organizations to manage their data efficiently and create actual value.

Analytics 233

Analytics Artificial Intelligence Storage Serverless 233

Dynatrace

OCTOBER 4, 2022

While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. What is a data lakehouse? How does a data lakehouse work?

Artificial Intelligence 208

Artificial Intelligence Analytics Storage Government 208

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

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. Monitoring both the frontend and backend is critical to achieving its strategic goals.

Entertainment 157

Entertainment Analytics Healthcare Games 157

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

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

Rigor

JANUARY 13, 2020

Take, for example, The Web Almanac , the golden collection of Big Data combined with the collective intelligence from most of the authors listed below, brilliantly spearheaded by Google’s @rick_viscomi. Data-driven strategies and battle tested techniques will make you a master of mobile-and improve your non-mobile design, too!

Performance 75

Performance Social Media Website Website Performance 75

Dynatrace

JUNE 1, 2020

Application Performance Monitoring (APM) in its simplest terms is what practitioners use to ensure consistent availability, performance, and response times to applications. Websites, mobile apps, and business applications are typical use cases for monitoring. Performance monitoring. Application monitoring. Dynatrace news.

Monitoring 132

Monitoring Performance Social Media Artificial Intelligence 132

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. Enhanced automation.

Artificial Intelligence 284

Artificial Intelligence Cloud Innovation Strategy 284

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.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

The Netflix TechBlog

APRIL 29, 2019

Device interaction for the collection of health and other operational data is yet another Python application. We are heavy users of Jupyter Notebooks and nteract to analyze operational data and prototype visualization tools that help us detect capacity regressions. We also use Python to detect sensitive data using Lanius.

Open Source 279

Open Source Network Infrastructure Big Data 279

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 195

DevOps Artificial Intelligence Healthcare Innovation 195

Dynatrace

APRIL 21, 2021

The Business Insights team at Dynatrace has been working with our largest Digital Experience Monitoring customers to help them turn the Core Web Vitals data they’re collecting with Dynatrace into actionable insights they can use to optimize pages ahead of this June 2021 change in Google’s search ranking algorithm. 28-day lookbacks.

Traffic 263

Traffic Metrics Mobile Analytics 263

All Things Distributed

JANUARY 19, 2011

To battle this complexity, developers who do not need control over the whole software stack often use development platforms that help them manage their application development, deployment and monitoring. Driving down the cost of Big-Data analytics. and Engine Yard , Springsource users have CloudFoundry.

AWS 115

AWS Cloud Java Operating System 115

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

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.” A comprehensive, modern approach to AIOps is a unified platform that encompasses observability, AI, and analytics.

Artificial Intelligence 211

Artificial Intelligence DevOps Innovation Metrics 211

Dynatrace

JUNE 1, 2020

Application Performance Monitoring (APM) in its simplest terms is what practitioners use to ensure consistent availability, performance, and response times to applications. Websites, mobile apps, and business applications are typical use cases for monitoring. APM can be referred to as: Application performance monitoring.

Artificial Intelligence 182

Artificial Intelligence Social Media Monitoring IoT 182

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 166

AWS Cloud Artificial Intelligence IoT 166

All Things Distributed

FEBRUARY 25, 2011

They also setup Auto Scaling, EC2 and RDS Security Groups, configure CloudWatch monitoring and alarms, and use SNS for notifications. Driving down the cost of Big-Data analytics. There are several resources required: Elastic Load Balancers, EC2 instances, EBS volumes, SimpleDB domains and an RDS instance.

AWS 121

AWS Cloud Scalability Storage 121

Testsigma

FEBRUARY 12, 2021

When more companies transition into digital-first projects, there must be an expanded number of processes and IT data departments to keep IT teams on track. The DevOps workflow is strongly connected to continuous monitoring activities aimed to maximise the consistency of the product and eliminate corporate risk.

Artificial Intelligence 92

Artificial Intelligence Software Software IoT 92

Percona

JANUARY 14, 2019

What if we use ClickHouse (which is a columnar analytical database) as our main datastore? Well, typically, an analytical database is not a replacement for a transactional or key/value datastore. This information can be a mix of analytical (OLAP) queries (i.e. Analytical databases are optimized for a low number of slow queries.

Database 40

Database Analytics Blockchain Healthcare 40