Remove Analytics Remove Hardware Remove Latency
article thumbnail

RabbitMQ vs. Kafka: Key Differences

Scalegrid

Kafka is optimized for high-throughput event streaming , excelling in real-time analytics and large-scale data ingestion. Its architecture supports stream transformations, joins, and filtering, making it a powerful tool for real-time analytics. Apache Kafka uses a custom TCP/IP protocol for high throughput and low latency.

Latency 147
article thumbnail

Optimize your environment: Unveiling Dynatrace Hyper-V extension for enhanced performance and efficient troubleshooting

Dynatrace

It enables multiple operating systems to run simultaneously on the same physical hardware and integrates closely with Windows-hosted services. Therefore, they experience how the application code functions and how the application operations depend on the underlying hardware resources and the operating system managed by Hyper-V.

Insiders

Sign Up for our Newsletter

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

article thumbnail

What is ITOps? Why IT operations is more crucial than ever in a multicloud world

Dynatrace

Besides the traditional system hardware, storage, routers, and software, ITOps also includes virtual components of the network and cloud infrastructure. Although modern cloud systems simplify tasks, such as deploying apps and provisioning new hardware and servers, hybrid cloud and multicloud environments are often complex. Performance.

article thumbnail

What is observability? Not just logs, metrics and traces

Dynatrace

In these modern environments, every hardware, software, and cloud infrastructure component and every container, open-source tool, and microservice generates records of every activity. Observability relies on telemetry derived from instrumentation that comes from the endpoints and services in your multi-cloud computing environments.

Metrics 363
article thumbnail

The Three Types of Performance Testing

CSS Wizardry

Things always always feel fast when we’re developing because, more often than not, we’re working on high-spec machines on dedicated networks, and also serving from localhost which removes the bulk of the latency and bandwidth issues that a real user would suffer. How: RUM tooling, analytics, monitoring. What This Means for Developers.

article thumbnail

Redis® Monitoring Strategies for 2025

Scalegrid

Identifying key Redis metrics such as latency, CPU usage, and memory metrics is crucial for effective Redis monitoring. To monitor Redis instances effectively, collect Redis metrics focusing on cache hit ratio, memory allocated, and latency threshold.

Strategy 130
article thumbnail

Redis® Monitoring Strategies for 2024

Scalegrid

Identifying key Redis® metrics such as latency, CPU usage, and memory metrics is crucial for effective Redis monitoring. To monitor Redis® instances effectively, collect Redis metrics focusing on cache hit ratio, memory allocated, and latency threshold.

Strategy 130