Remove platform application-observability
article thumbnail

How observability, application security, and AI enhance DevOps and platform engineering maturity

Dynatrace

DevOps and platform engineering are essential disciplines that provide immense value in the realm of cloud-native technology and software delivery. One of these key investments includes observability. One of these key investments includes observability. However, these practices cannot stand alone.

DevOps 190
article thumbnail

Enable full observability for Linux on IBM Z mainframe now with logs

Dynatrace

Mainframe is a strong choice for hybrid cloud, but it brings observability challenges IBM Z is a mainframe computing platform chosen by many organizations with a hybrid cloud strategy because of its security, resiliency, performance, scalability, and sustainability.

Insiders

Sign Up for our Newsletter

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

Trending Sources

article thumbnail

Stream logs to Dynatrace with Amazon Data Firehose to boost your cloud-native journey

Dynatrace

Real-time streaming needs real-time analytics As enterprises move their workloads to cloud service providers like Amazon Web Services, the complexity of observing their workloads increases. Log data—the most verbose form of observability data, complementing other standardized signals like metrics and traces—is especially critical.

Cloud 217
article thumbnail

How platform engineering and IDP observability can accelerate developer velocity

Dynatrace

As organizations look to expand DevOps maturity, improve operational efficiency, and increase developer velocity, they are embracing platform engineering as a key driver. The pair showed how to track factors including developer velocity, platform adoption, DevOps research and assessment metrics, security, and operational costs.

article thumbnail

Bridging the Observability Gap for Modern Cloud Architectures

DZone

At Perform 2024, Dynatrace announced three major platform enhancements aimed squarely at bridging this observability gap for engineering teams. According to Steve Tack , SVP of Product Management at Dynatrace, a key goal is to "help organizations adopt new technologies with confidence."

article thumbnail

Kubernetes health at a glance: One experience to rule it all

Dynatrace

The complexity and numerous moving parts of Kubernetes multicloud clusters mean that when monitoring the health of these clusters—which is critical for ensuring reliable and efficient operation of the applicationplatform engineers often find themselves without an easy and efficient solution.

article thumbnail

Technology predictions for 2024: Dynatrace expectations for observability, security, and AI trends

Dynatrace

That’s why many organizations are turning to generative AI—which uses its training data to create text, images, code, or other types of content that reflect its users’ natural language queries—and platform engineering to create new efficiencies and opportunities for innovation. 4: Data observability will become mandatory.