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OpenTelemetry Metrics Explained: A Guide for Engineers

Honeycomb

Among these signals, OpenTelemetry metrics are crucial in helping engineers understand their systems. In this blog, well explore OpenTelemetry metrics, how they work, and how to use them effectively to ensure your systems and applications run smoothly. What are OpenTelemetry metrics?

Metrics 69
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Navigating the cloud maze: A 5-phase approach to optimizing cloud strategies

CIO

It prevents vendor lock-in, gives a lever for strong negotiation, enables business flexibility in strategy execution owing to complicated architecture or regional limitations in terms of security and legal compliance if and when they rise and promotes portability from an application architecture perspective.

Cloud 147
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How Much Should I Be Spending On Observability?

Honeycomb

Get your free copy of Charity’s Cost Crisis in Metrics Tooling whitepaper. download Model-specific cost drivers: the pillars model vs consolidated storage model (observability 2.0) Because the cost drivers of the multiple pillars model and unified storage model are very different. and observability 2.0. understandably).

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There Is Only One Key Difference Between Observability 1.0 and 2.0

Honeycomb

phenomenon We’ve all heard the slogan, “metrics, logs, and traces are the three pillars of observability.” You probably use some subset (or superset) of tools including APM, RUM, unstructured logs, structured logs, infra metrics, tracing tools, profiling tools, product analytics, marketing analytics, dashboards, SLO tools, and more.

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Deploy DeepSeek-R1 Distilled Llama models in Amazon Bedrock

AWS Machine Learning - AI

DeepSeek-R1 distilled variations From the foundation of DeepSeek-R1, DeepSeek AI has created a series of distilled models based on both Metas Llama and Qwen architectures, ranging from 1.570 billion parameters. Sufficient local storage space, at least 17 GB for the 8B model or 135 GB for the 70B model.

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Asure’s approach to enhancing their call center experience using generative AI and Amazon Q in Quicksight

AWS Machine Learning - AI

Moreover, Amazon Bedrock offers integration with other AWS services like Amazon SageMaker , which streamlines the deployment process, and its scalable architecture makes sure the solution can adapt to increasing call volumes effortlessly. This is powered by the web app portion of the architecture diagram (provided in the next section).

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Prerequisites for evolutionary architectures

CircleCI

Designing software that is flexible and changeable is arguably the most important architectural property. However, if we optimise our architecture for change (evolvability), when we discover a performance issue or a security vulnerability we can change our system to help address it. Without mandating a specific architecture (e.g.