Dynatrace

FEBRUARY 16, 2023

As teams try to gain insight into this data deluge, they have to balance the need for speed, data fidelity, and scale with capacity constraints and cost. To solve this problem, Dynatrace launched Grail, its causational data lakehouse , in 2022. Logs on Grail Log data is foundational for any IT analytics.

Analytics 182

Analytics Innovation Metrics Database 182

Scalegrid

MARCH 14, 2024

Effective hybrid cloud management requires robust tools and techniques for centralized administration, policy enforcement, cost management, and modern infrastructure practices like Infrastructure-as-Code (IaC) and containers.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

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? Reduced redundancy.

Artificial Intelligence 205

Artificial Intelligence Analytics Storage Government 205

Scalegrid

MARCH 28, 2024

Snapshots provide point-in-time captures of the dataset, which are efficient for recovery on startup. On the other hand, an append-only file ensures data safety by recording every write operation that modifies the dataset, allowing for complete data reconstruction in the event of a restart. Data transfer technology.

Cache 130

Cache Storage Scalability Architecture 130

KeyCDN

OCTOBER 2, 2018

Check out the Almanac for CSS property and selector-specific insights, or dive straight into the Snippets to grab some reusable code. It’s awesome for discovering how grid systems, CSS animation, Big Data, etc all play roles in real-world web design. Visit website 4. Visit website 12. Visit website 14. Visit website 17.

Development 75

Development Website Design Code 75

Testsigma

MAY 7, 2020

IBM Big Data and Analytics Hub website cited a case study, where a US insurance company was estimating 15% of their testing efforts to be just test data collection for the backend system and the frontend system. The test data required by testing team to test an application can be of two types: 1.

Testing 60

Testing Storage Database Processing 60

The Netflix TechBlog

APRIL 29, 2019

Demand Engineering Demand Engineering is responsible for Regional Failovers , Traffic Distribution, Capacity Operations and Fleet Efficiency of the Netflix cloud. We are heavy users of Jupyter Notebooks and nteract to analyze operational data and prototype visualization tools that help us detect capacity regressions.

Open Source 279

Open Source Network Infrastructure Big Data 279

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

The Netflix TechBlog

NOVEMBER 20, 2023

We will show how we are building a clean and efficient incremental processing solution (IPS) by using Netflix Maestro and Apache Iceberg. IPS provides the incremental processing support with data accuracy, data freshness, and backfill for users and addresses many of the challenges in workflows. past 3 hours or 10 days).

Processing 210

Processing Big Data Efficiency Engineering 210

Highly Scalable

JUNE 5, 2012

At GridDynamics, we recently worked on a custom database for realtime web analytics where fast intersection of very large lists of IDs was a must for good performance. When this short mask of common elements is obtained, we have to efficiently copy out common elements. in this article.

C++ 102

C++ Java Performance Testing Efficiency 102

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. But before that new code can be deployed, it needs to be tested and reviewed from a security perspective. Taking AIOps to the next level.

DevOps 192

DevOps Artificial Intelligence Healthcare Innovation 192

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. Therefore, we must efficiently move data from the data warehouse to a global, low-latency and highly-reliable key-value store.

Latency 243

Latency Storage Big Data Tuning 243

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 208

Artificial Intelligence DevOps Innovation Metrics 208

Dynatrace

JUNE 1, 2020

The variables that can impact the performance of an application vary; from coding errors or ‘bugs’ in the software, database slowdowns, hosting and network performance, to operating system and device type support. User Experience and Business Analytics ery user journey and maximize business KPIs.

Artificial Intelligence 181

Artificial Intelligence Social Media Monitoring IoT 181

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.

AWS 166

AWS Cloud Artificial Intelligence IoT 166

Dynatrace

JUNE 1, 2020

The variables that can impact the performance of an application vary; from coding errors or ‘bugs’ in the software, database slowdowns, hosting and network performance, to operating system and device type support. User Experience and Business Analytics ery user journey and maximize business KPIs.

Monitoring 132

Monitoring Performance Social Media Artificial Intelligence 132

All Things Distributed

MAY 21, 2018

We already have an idea of how digitalization, and above all new technologies like machine learning, big-data analytics or IoT, will change companies' business models — and are already changing them on a wide scale. The workplace of the future. A voice command creates a lot more productivity.

Artificial Intelligence 76

Artificial Intelligence Technology Technology IoT 76

Smashing Magazine

JULY 29, 2019

Minification removes unnecessary spaces and characters, but uglification actually ‘mangles’ the code to be shorter. The tell-tale sign is that the code contains short, machine-generated variable names rather than untouched source code. But I suspect a lot of it is tracking code and advertising setup. Large preview ).

Cache 96

Cache Google Mobile Network 96

Testsigma

FEBRUARY 12, 2021

The usage by advanced techniques such as RPA, Artificial Intelligence, machine learning and process mining is a hyper-automated application that improves employees and automates operations in a way which is considerably more efficient than conventional automation. Gartner’s 2020 projections first included the trend of hyperautomation.

Artificial Intelligence 92

Artificial Intelligence Software Software IoT 92