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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.

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Perform 2023 Guide: Organizations mine efficiencies with automation, causal AI

Dynatrace

In what follows, we explore some key cloud observability trends in 2023, such as workflow automation and exploratory analytics. From data lakehouse to an analytics platform Traditionally, to gain true business insight, organizations had to make tradeoffs between accessing quality, real-time data and factors such as data storage costs.

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Fueling the next wave of IT operations: Modernization with generative AI

Dynatrace

While respondents have made progress in terms of instrumentation, This suggests there is ample opportunity for organizations to use a log management and analytics platform such as Dynatrace to ingest and analyze log data. And for DevOps, it means accelerating DevOps processes, improving agility, and speeding time to market.

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AWS Re:Invent 2021 guide: Multicloud modernization and digital transformation

Dynatrace

Its approach to serverless computing has transformed DevOps. Dynatrace extends contextual analytics and AIOps for open observability. DevOps/DevSecOps with AWS. Successful DevOps is as much about tactics as it is technology. 2021 DevOps Report. Learn more here. What is AWS Lambda? What is AWS Lambda?

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What is full stack observability?

Dynatrace

DevOps teams can also benefit from full-stack observability. With improved diagnostic and analytic capabilities, DevOps teams can spend less time troubleshooting. How full-stack observability enhances IT and DevOps. Here are a few ways full-stack observability can benefit your IT and DevOps teams.

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Dynatrace Perform 2022: Themes to watch at Dynatrace’s annual conference

Dynatrace

Understanding the difference between observability and monitoring helps DevOps teams understand root causes and deliver better applications. 5 challenges to achieving observability at scale – eBook. Upgrade to advanced observability for answers in cloud-native environments – eBook. What is DevOps?

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

Dynatrace

Therefore, organizations are increasingly turning to artificial intelligence and machine learning technologies to get analytical insights from their growing volumes of data. AI applies advanced analytics and logic-based techniques to interpret data and events, support and automate decisions, and even take intelligent actions.