Analytics, Java and Latency - Technology Performance Pulse

Scalable Annotation Service?—?Marken

The Netflix TechBlog

JANUARY 25, 2023

The service should be able to serve real-time, aka UI, applications so CRUD and search operations should be achieved with low latency. All data should be also available for offline analytics in Hive/Iceberg. Unlike Java, we support multiple inheritance as well. Search latency for the generic text queries are in milliseconds.

Scalability

Scalability Latency Media Architecture

Enhanced AI model observability with Dynatrace and Traceloop OpenLLMetry

Dynatrace

DECEMBER 4, 2023

Utilizing an additional OpenTelemetry SDK layer, this data seamlessly flows into the Dynatrace environment, offering advanced analytics and a holistic view of the AI deployment stack. How OpenLLMetry works OpenLLMetry supports AI model observability by capturing and normalizing key performance indicators (KPIs) from diverse AI frameworks.

Open Source

Open Source Metrics Latency Java

Mastering MongoDB® Timeout Settings

Scalegrid

DECEMBER 14, 2023

For example, your payment history might be on one database cluster and your analytics records on another cluster. If your analytics server is down, then each operation will wait for a default of 30 seconds before failing (which may or may not be what you want). x+ in Java).

Java

Java Network Servers Database

The Power of Integrated Analytics Within an IMDG

ScaleOut Software

JULY 21, 2020

ScaleOut StateServer® Pro Adds Analytics to In-Memory Data Grids . By transparently distributing stored objects across a cluster of servers (physical or virtual), it automatically scales performance for fast-growing workloads and maintains consistently low access latency. Java applications use a similar mechanism.).

Analytics

Analytics Airlines Cache Scalability

The Power of Integrated Analytics Within an IMDG

ScaleOut Software

JULY 21, 2020

ScaleOut StateServer® Pro Adds Analytics to In-Memory Data Grids . By transparently distributing stored objects across a cluster of servers (physical or virtual), it automatically scales performance for fast-growing workloads and maintains consistently low access latency. Java applications use a similar mechanism.).

Analytics

Analytics Airlines Cache Scalability

Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

OCTOBER 19, 2020

If we had an ID for each streaming session then distributed tracing could easily reconstruct session failure by providing service topology, retry and error tags, and latency measurements for all service calls. We chose Open-Zipkin because it had better integrations with our Spring Boot based Java runtime environment.

Infrastructure

Infrastructure Transportation Storage Open Source

Data Reprocessing Pipeline in Asset Management Platform @Netflix

The Netflix TechBlog

MARCH 10, 2023

Production Use Cases Real-Time APIs (backed by the Cassandra database) for asset metadata access don’t fit analytics use cases by data science or machine learning teams. For fast processing of the events, we use different settings of Kafka consumer and Java executor thread pool.

Media

Media Traffic Processing Design

Adding New Capabilities for Real-Time Analytics to Azure IoT

ScaleOut Software

JULY 14, 2021

Whether it’s health-tracking watches, long-haul trucks, or security sensors, extracting value from these devices requires streaming analytics that can quickly make sense of the telemetry and intelligently react to handle an emerging issue or capture a new opportunity.

IoT

IoT Azure Analytics Serverless

Data Movement in Netflix Studio via Data Mesh

The Netflix TechBlog

JULY 26, 2021

Operational Reporting is a reporting paradigm specialized in covering high-resolution, low-latency data sets, serving detailed day-to-day activities¹ and processes of a business domain. CDC events can also be sent to Data Mesh via a Java Client Producer Library. tactical) in nature. Currently Iceberg sink is appended only.

Big Data

Big Data Government Analytics Processing

The road to observability demo part 3: Collect, instrument, and analyze telemetry data automatically with Dynatrace

Dynatrace

MAY 17, 2023

The next level of observability: OneAgent In the first two parts of our series, we used OpenTelemetry to manually instrument our application and send the telemetry data straight to the Dynatrace analytics back end. Garbage collection count Garbage collection is JVM related and indicates how often the Java GC ran.

Metrics

Metrics Monitoring Database Network

Probabilistic Data Structures for Web Analytics and Data Mining

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. This approach often leads to heavyweight high-latency analytical processes and poor applicability to realtime use cases. Clifford, I.

Analytics

Analytics Traffic Big Data Efficiency

Embrace event-driven computing: Amazon expands DynamoDB with streams, cross-region replication, and database triggers

All Things Distributed

JULY 14, 2015

No matter which mechanism you choose to use, we make the stream data available to you instantly (latency in milliseconds) and how fast you want to apply the changes is up to you. Also, you can choose to program post-commit actions, such as running aggregate analytical functions or updating other dependent tables.

Database

Database Lambda AWS IoT

A Management Maturity Model for Performance

Alex Russell

MAY 9, 2022

This is a complex topic, but to borrow from a recent post , web performance expands access to information and services by reducing latency and variance across interactions in a session, with a particular focus on the tail of the distribution (P75+). Consistent performance matters just as much as low average latency. Photo by von Vix.

Performance

Performance Latency Metrics Engineering

Declarative recursive computation on an RDBMS

The Morning Paper

SEPTEMBER 12, 2019

Though some of this discrepancy was due to the fact that we implemented our ideas on top of a research prototype, high-latency Java/Hadoop system, reducing that gap is an attractive target for future work. VLDB’19. The RDBMS was slower than TensorFlow for GPU-based implementations of neural networks, however.

Network

Network Database Programming Hardware

Technology Performance Pulse

Scalable Annotation Service?—?Marken

Enhanced AI model observability with Dynatrace and Traceloop OpenLLMetry

Trending Sources

Mastering MongoDB® Timeout Settings

The Power of Integrated Analytics Within an IMDG

The Power of Integrated Analytics Within an IMDG

Building Netflix’s Distributed Tracing Infrastructure

Data Reprocessing Pipeline in Asset Management Platform @Netflix

Adding New Capabilities for Real-Time Analytics to Azure IoT

Data Movement in Netflix Studio via Data Mesh

The road to observability demo part 3: Collect, instrument, and analyze telemetry data automatically with Dynatrace

Probabilistic Data Structures for Web Analytics and Data Mining

Embrace event-driven computing: Amazon expands DynamoDB with streams, cross-region replication, and database triggers

A Management Maturity Model for Performance

Declarative recursive computation on an RDBMS

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