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

The Netflix TechBlog

JUNE 7, 2021

Cloud Network Insight is a suite of solutions that provides both operational and analytical insight into the cloud network infrastructure to address the identified problems. Flow Collector consumes two data streams, the IP address change events from Sonar via Kafka and eBPF flow log data from the Flow Exporter sidecars.

Network 325

Network Transportation AWS Cloud 325

Dynatrace

APRIL 11, 2023

Cloud application security remains challenging because organizations lack end-to-end visibility into cloud architecture. As organizations migrate applications to the cloud, they must balance the agility that microservices architecture brings with the complexity and lack of transparency that can also come with it.

Cloud 195

Cloud DevOps Open Source Retail 195

The Netflix TechBlog

MAY 26, 2020

Cloud Network Insight is a suite of solutions that provides both operational and analytical insight into the Cloud Network Infrastructure to address the identified problems. It is easier to tune a large Spark job for a consistent volume of data. These events represent a specific cut of data from the table.

Network 150

Network Tuning AWS Big Data 150

Scalegrid

MARCH 28, 2024

Key Takeaways Redis offers complex data structures and additional features for versatile data handling, while Memcached excels in simplicity with a fast, multi-threaded architecture for basic caching needs. Memcached shines in scenarios where a simple, fast, and efficient caching solution is required without data persistence.

Cache 130

Cache Storage Scalability Architecture 130

Dynatrace

DECEMBER 15, 2022

AIOps (artificial intelligence for IT operations) combines big data, AI algorithms, and machine learning for actionable, real-time insights that help ITOps continuously improve operations. Collect raw data in virtual and nonvirtual environments from multiple feeds, normalize and structure the data, and aggregate it for alerts.

Artificial Intelligence 211

Artificial Intelligence DevOps Hardware Virtualization 211

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. CloudOps includes processes such as incident management and event management. CloudOps: Applying AIOps to multicloud operations.

DevOps 205

DevOps Artificial Intelligence Healthcare Innovation 205

Dynatrace

MARCH 24, 2023

Using Marathon, its data center operating system (DC/OS) plugin, Mesos becomes a full container orchestration environment that, like Kubernetes and Docker Swarm, discovers services, balances loads, and manages application containers. Mesos also supports other orchestration engines, including Kubernetes and Docker Swarm.

Infrastructure 195

Infrastructure Open Source Operating System Cloud 195

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 221

Artificial Intelligence DevOps Innovation Metrics 221

The Netflix TechBlog

NOVEMBER 20, 2023

For example, a job would reprocess aggregates for the past 3 days because it assumes that there would be late arriving data, but data prior to 3 days isn’t worth the cost of reprocessing. Backfill: Backfilling datasets is a common operation in big data processing. append, overwrite, etc.).

Processing 210

Processing Big Data Efficiency Engineering 210

Abhishek Tiwari

DECEMBER 27, 2017

A common theme across all these trends is to remove the complexity by simplifying data management as a whole. In 2018, we anticipate that ETL will either lose relevance or the ETL process will disintegrate and be consumed by new data architectures. Unified data management architecture.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

ScaleOut Software

APRIL 3, 2020

The real-time digital twin software tracks and updates this information using incoming messages whenever significant events affecting the ventilator occur, such as when it moves from place to place, is put in use, becomes available, encounters a mechanical issue, has an expected repair time, etc.

Logistics 52

Logistics Analytics Scalability Cloud 52

ScaleOut Software

APRIL 3, 2020

The real-time digital twin software tracks and updates this information using incoming messages whenever significant events affecting the ventilator occur, such as when it moves from place to place, is put in use, becomes available, encounters a mechanical issue, has an expected repair time, etc.

Logistics 52

Logistics Analytics Scalability Cloud 52

All Things Distributed

SEPTEMBER 30, 2010

Visiting future customers is equally exiting as you get a change to understand their current architecture, if it is a migration, and how they plan to exploit cloud services in their new setup. AWS Startup Event in Tel Aviv on October 12 with customers Porticor , SemantiNet , Live Definition. Driving down the cost of Big-Data analytics.

AWS 75

AWS Storage Cloud Best Practices 75

SQL Server According to Bob

FEBRUARY 15, 2018

I have the blessed opportunity to speak at many customer events. Microsoft engineering is actually sending quite a few folks over the Atlantic to come talk about SQL Server 2017, SQL Server on Linux, GDPR, Performance, Security, Azure Data Lake, Azure SQL Database, Azure SQL Data Warehouse, and Azure CosmosDB.

Engineering 40

Engineering Azure Best Practices Servers 40

Highly Scalable

MARCH 10, 2015

Although there are many books on data mining in general and its applications to marketing and customer relationship management in particular [BE11, AS14, PR13 etc.], The rest of the article is organized as follows: We first introduce a simple framework that ties together a retailer’s actions, profits and data. Sale events.

Retail 152

Retail C++ Analytics Metrics 152