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

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When Amazon launched AWS Lambda in 2014, it ushered in a new era of serverless computing. Serverless architecture enables organizations to deliver applications more efficiently without the overhead of on-premises infrastructure, which has revolutionized software development. Its approach to serverless computing has transformed DevOps.

AWS 225
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How platform engineering and IDP observability can accelerate developer velocity

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“IDPs are not constrained to building microservices or a new serverless app,” Grabner noted. Observability is not only about measuring performance and speed, but also about capturing granular business analytics to support data-driven decision-making.

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The top eight DevSecOps trends in 2022

Dynatrace

AIOps, conversely, is an approach to software operations that combines AI algorithms with data analytics to automate key tasks and suggest precise answers to common IT issues, such as unexpected downtime or unauthorized data access. Serverless architecture expands. Microservices go hand-in-hand with serverless computing.

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Applying real-world AIOps use cases to your operations

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However, as organizations adopt more cloud-native technologies, such as containerized microservices and serverless platforms, operations have become exponentially more complex. This makes developing, operating, and securing modern applications and the environments they run on practically impossible without AI.

DevOps 192
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Modern approaches to observability and monitoring for multicloud environments

Dynatrace

Distributed traces across open source and cloud-native architectures — Analyze transactions end-to-end across cloud-native technologies, including OpenTelemetry, W3C Trace Context, service mesh, and serverless computing to eliminate gaps, blind spots, and incomplete traces. Turning raw data into actionable business intelligence.

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What is observability? Not just logs, metrics and traces

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Business analytics : Organizations can combine business context with full stack application analytics and performance to understand real-time business impact, improve conversion optimization, ensure that software releases meet expected business goals, and confirm that the organization is adhering to internal and external SLAs.

Metrics 363