The Netflix TechBlog

JANUARY 13, 2022

This blog will explore these two systems and how they perform auto-diagnosis and remediation across our Big Data Platform and Real-time infrastructure. This has led to a dramatic reduction in the time it takes to detect issues in hardware or bugs in recently rolled out data platform software.

Big Data 238

Big Data Infrastructure Metrics Hardware 238

Dynatrace

JULY 6, 2022

Monitoring and logging are fundamental building blocks of observability. Adding AIOps to automation processes makes the volume of data that applications and multicloud environments generate much less overwhelming. Similarly, digital experience monitoring is another ongoing process that lends itself to IT automation.

Artificial Intelligence 198

Artificial Intelligence Tuning Strategy Big Data 198

Scalegrid

MARCH 14, 2024

Defining Hybrid Cloud Strategy The decision-making process about where to situate data and applications is vital to any hybrid cloud solution. Defining Hybrid Cloud Strategy The decision-making process about where to situate data and applications is vital to any hybrid cloud solution.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

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

Dynatrace

DECEMBER 15, 2022

The roles and responsibilities of ITOps team members include the following: A system administrator configures servers, installs applications, monitors the health of the system, and fixes and upgrades hardware. The primary goal of ITOps is to provide a high-performing, consistent IT environment. Functionality. ITOps vs. AIOps.

Artificial Intelligence 211

Artificial Intelligence DevOps Hardware Virtualization 211

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. The data is also used by security and other partner teams for insight and incident analysis. What is BPF?

Network 325

Network Transportation AWS Cloud 325

Dynatrace

MARCH 24, 2023

This orchestration includes provisioning, scheduling, networking, ensuring availability, and monitoring container lifecycles. Apache Mesos with the Marathon DC/OS is popular for large-scale production clusters running existing workloads on big data systems, such as Hadoop, Kafka, and Spark. appeared first on Dynatrace news.

Infrastructure 195

Infrastructure Open Source Operating System Cloud 195

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

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. Azure Virtual Network Gateways. Azure Front Door.

Azure 151

Azure Cloud Big Data Virtualization 151

ScaleOut Software

JUNE 15, 2020

When analyzing telemetry from a large population of data sources, such as a fleet of rental cars or IoT devices in “smart cities” deployments, it’s difficult if not impossible for conventional streaming analytics platforms to track the behavior of each individual data source and derive actionable information in real time.

Analytics 52

Analytics IoT Lambda Big Data 52

ScaleOut Software

JUNE 15, 2020

When analyzing telemetry from a large population of data sources, such as a fleet of rental cars or IoT devices in “smart cities” deployments, it’s difficult if not impossible for conventional streaming analytics platforms to track the behavior of each individual data source and derive actionable information in real time.

Analytics 52

Analytics IoT Lambda Big Data 52

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. Analyze the data. CloudOps: Applying AIOps to multicloud operations. Execute an action plan. Achieving autonomous operations.

DevOps 205

DevOps Artificial Intelligence Healthcare Innovation 205

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. Data Mesh leverages Iceberg tables as data warehouse sinks for downstream analytics use cases.

Big Data 253

Big Data Government Analytics Processing 253

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

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

ScaleOut Software

NOVEMBER 24, 2020

However, telematics architectures face challenges in responding to telemetry in real time. Current Telematics Architecture. The volume of incoming telemetry challenges current telematics systems to keep up and quickly make sense of all the data. Challenges for Current Architectures.

Analytics 52

Analytics Architecture Scalability Software Architecture 52

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. Information Architecture. Complete Web Monitoring. Web Performance Daybook-Volume-2. Website Optimization.

Performance 75

Performance Social Media Website Website Performance 75