article thumbnail

Dynatrace on Microsoft Azure in Australia enables regional customers to leverage AI-powered observability

Dynatrace

For Dynatrace customers, this means their data and end users in the region will benefit from faster time to value and deeper integration with the Microsoft technology stack to help comply with local data privacy and security requirements. This local SaaS presence minimizes latency and maximizes the speed and reliability of data access.

Azure 278
article thumbnail

Nine ways technology executives can get significant business value with the right observability platform

Dynatrace

As a technology executive, you’re aware that observability has become an imperative for managing the health of cloud and IT services. However, technology executives face a significant challenge getting answers in time, as their needs have evolved to real-time business insights that enable faster decision-making and business automation.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

RabbitMQ vs. Kafka: Key Differences

Scalegrid

Its partitioned log architecture supports both queuing and publish-subscribe models, allowing it to handle large-scale event processing with minimal latency. Apache Kafka uses a custom TCP/IP protocol for high throughput and low latency. Apache Kafka, designed for distributed event streaming, maintains low latency at scale.

Latency 147
article thumbnail

Introducing Impressions at Netflix

The Netflix TechBlog

This nuanced integration of data and technology empowers us to offer bespoke content recommendations. This dual-path approach leverages Kafkas capability for low-latency streaming and Icebergs efficient management of large-scale, immutable datasets, ensuring both real-time responsiveness and comprehensive historical data availability.

Tuning 166
article thumbnail

Why Replace External Database Caches?

DZone

Putting an external cache in front of the database is commonly used to compensate for subpar latency stemming from various factors, such as inefficient database internals, driver usage, infrastructure choices, traffic spikes, and so on. This is a clear performance-oriented decision.

Cache 278
article thumbnail

Performance and Scalability Analysis of Redis and Memcached

DZone

Among the critical enablers for fast data access implementation within in-memory data stores are the game changers in recent times, which are technologies like Redis and Memcached. We compare throughput, operations per second, and latency under different loads, namely the P90 and P99 percentiles.

article thumbnail

Noisy Neighbor Detection with eBPF

The Netflix TechBlog

Continuous Instrumentation of the Linux Scheduler To ensure the reliability of our workloads that depend on low latency responses, we instrumented the run queue latency for each container, which measures the time processes spend in the scheduling queue before being dispatched to the CPU.

Latency 262