Remove Artificial Intelligence Remove DevOps Remove Efficiency
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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. They need automated DevOps practices.

DevOps 278
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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. Rather, they must be bolstered by additional technological investments to ensure reliability, security, and efficiency. However, these practices cannot stand alone.

DevOps 203
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Unlocking the Power of AIOps: Enhancing DevOps With Intelligent Automation for Optimized IT Operations

DZone

In today's rapidly evolving technological landscape, the integration of Artificial Intelligence (AI) and Machine Learning (ML) with IT operations has become a game-changer. This article explores the transformative power of AIOps in driving intelligent automation and optimizing IT operations.

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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 198
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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 219
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Why growing AI adoption requires an AI observability strategy

Dynatrace

As organizations turn to artificial intelligence for operational efficiency and product innovation in multicloud environments, they have to balance the benefits with skyrocketing costs associated with AI. The good news is AI-augmented applications can make organizations massively more productive and efficient.

Strategy 234
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What is serverless computing? Driving efficiency without sacrificing observability

Dynatrace

This allows teams to sidestep much of the cost and time associated with managing hardware, platforms, and operating systems on-premises, while also gaining the flexibility to scale rapidly and efficiently. In a serverless architecture, applications are distributed to meet demand and scale requirements efficiently.