Remove Artificial Intelligence Remove Data Remove DevOps
article thumbnail

The keys to selecting a platform for end-to-end observability

Dynatrace

DevOps and security teams managing today’s multicloud architectures and cloud-native applications are facing an avalanche of data. This has resulted in visibility gaps, siloed data, and negative effects on cross-team collaboration. At the same time, the number of individual observability and security tools has grown.

article thumbnail

What is artificial intelligence? See how it differs from machine learning in IT ops

Dynatrace

These systems are generating more data than ever, and teams simply can’t keep up with a manual approach. Therefore, organizations are increasingly turning to artificial intelligence and machine learning technologies to get analytical insights from their growing volumes of data. So, what is artificial intelligence?

Insiders

Sign Up for our Newsletter

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

article thumbnail

Automating DevOps practices fuels speed and quality

Dynatrace

Takeaways from this article on DevOps practices: DevOps practices bring developers and operations teams together and enable more agile IT. Still, while DevOps practices enable developer agility and speed as well as better code quality, they can also introduce complexity and data silos. Dynatrace news.

DevOps 290
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. Observability of applications and infrastructure serves as a critical foundation for DevOps and platform engineering, offering a comprehensive view into system performance and behavior.

DevOps 246
article thumbnail

The State of DevOps Automation assessment: How automated are you?

Dynatrace

DevOps automation eliminates extraneous manual processes, enabling DevOps teams to develop, test, deliver, deploy, and execute other key processes at scale. Automation can be particularly powerful when applied to DevOps workflows. Automation thus contributes to accelerated productivity and innovation across the organization.

DevOps 246
article thumbnail

What is predictive AI? How this data-driven technique gives foresight to IT teams

Dynatrace

Therefore, the integration of predictive artificial intelligence (AI) in the workflows of these teams has become essential to meet service-level objectives, collaborate effectively, and boost productivity. Through predictive analytics, SREs and DevOps engineers can accurately forecast resource needs based on historical data.

article thumbnail

What is MTTR? How mean time to repair helps define DevOps incident management

Dynatrace

DevOps and ITOps teams rely on incident management metrics such as mean time to repair (MTTR). Here’s what these metrics mean and how they relate to other DevOps metrics such as MTTA, MTTF, and MTBF. Mean time to respond (MTTR) is the average time it takes DevOps teams to respond after receiving an alert.

DevOps 276