Dynatrace

DECEMBER 15, 2022

This includes response time, accuracy, speed, throughput, uptime, CPU utilization, and latency. Adding application security to development and operations workflows increases efficiency. This is the number of failures that affect users’ ability to use an application by the total time in service. Performance. ITOps vs. AIOps.

Artificial Intelligence 198

Artificial Intelligence DevOps Hardware Virtualization 198

ACM Sigarch

MAY 31, 2023

Introduction Memory systems are evolving into heterogeneous and composable architectures. Heterogeneous and Composable Memory (HCM) offers a feasible solution for terabyte- or petabyte-scale systems, addressing the performance and efficiency demands of emerging big-data applications. The recently announced CXL3.0

Latency 52

Latency Hardware Cache Architecture 52

The Morning Paper

MAY 14, 2019

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., on end-to-end latency) and less than 0.15% on throughput. This tracing system is similar to Dapper and Zipkin and records per-microservice latencies and number of outstanding requests. ASPLOS’19.

Big Data 45

Big Data Cloud Performance Hardware 45

Dynatrace

JULY 6, 2020

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 supports a broad range of use cases including data warehousing, machine learning, and IoT analytics.

Azure 146

Azure Cloud Big Data Virtualization 146

ScaleOut Software

JULY 19, 2021

Today’s streaming analytics architectures are not equipped to make sense of this rapidly changing information and react to it as it arrives. This data is also periodically uploaded to a data lake for offline batch analysis that calculates key statistics and looks for big trends that can help optimize operations.

IoT 78

IoT Analytics Big Data Architecture 78

The Morning Paper

JUNE 23, 2019

The stateless + RInk (S+RInK) architecture attempts to provide the best of both worlds: to simultaneously offer both the implementation and operational simplicity of stateless application servers and the performance benefits of servers caching state in RAM. We’ve seen similar high marshalling overheads in big data systems too.)

Cache 79

Cache Latency Google Lambda 79

The Netflix TechBlog

JULY 26, 2021

Netflix is known for its loosely coupled microservice architecture and with a global studio footprint, surfacing and connecting the data from microservices into a studio data catalog in real time has become more important than ever. The audits check for equality (i.e.

Big Data 253

Big Data Government Analytics Processing 253

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

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. The processed data is typically stored as data warehouse tables in AWS S3. Moving data with Bulldozer at Netflix.

Latency 243

Latency Storage Big Data Tuning 243

The Netflix TechBlog

DECEMBER 21, 2020

We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits. This article will list some of the use cases of AutoOptimize, discuss the design principles that help enhance efficiency, and present the high-level architecture.

Storage 203

Storage Latency Efficiency Data Engineering 203

Abhishek Tiwari

DECEMBER 27, 2017

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. A unified data management (UDM) system combines the best of data warehouses, data lakes, and streaming without expensive and error-prone ETL.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

All Things Distributed

NOVEMBER 15, 2010

Building general purpose architectures has always been hard; there are often so many conflicting requirements that you cannot derive an architecture that will serve all, so we have often ended up focusing on one side of the requirements that allow you to serve that area really well.

AWS 136

AWS Latency Programming Architecture 136

The Netflix TechBlog

NOVEMBER 3, 2023

Additionally, instead of implementing business logic by composing multiple individual Processors together, users could express their logic in a single SQL query, avoiding the additional resource and latency overhead that came from multiple Flink jobs and Kafka topics.

Processing 265

Processing Engineering Infrastructure Latency 265