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AI-Driven API and Microservice Architecture Design for Cloud

Dzone - DevOps

Here are some key aspects where AI can drive improvements in architecture design: Intelligent planning : AI can assist in designing the architecture by analyzing requirements, performance metrics, and best practices to recommend optimal structures for APIs and microservices.

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Moving to the Cloud: Exploring the API Gateway to Success

Daniel Bryant

It’s on the hot path of every user request, and because of this, it needs to be performant, secure, and easily configurable. Most successful organizations base their goals on improving some or all of the DORA or Accelerate metrics. You want to maximize your deployment frequency while minimizing the other metrics.

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NetOps for Application Developers: Understanding the Importance of Network Operations in Modern Development

Kentik

CTOs and other umbrella decision-makers recognize that software and network engineers must work together to deliver secure and performant applications. Something else I’ve run into is that DevOps teams often fail to fully appreciate the importance of cost optimization in cloud environments.

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Why Use Kong API Gateway

Dzone - DevOps

The Kong API Gateway is highly performant and offers the following features: Request/Response Transformation : Kong can transform incoming and outgoing API requests and responses to conform to specific formats. Monitoring and Logging : Kong offers detailed metrics and logs to help monitor API performance and identify issues.

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The Case for SLOs

Honeycomb

A part of the “service level” family , an SLO is a reliability target (for example, “99%”) driven by an SLI (which is a metric like “requests completed without error”) that organizations use to ensure user experiences are smooth and customer contracts are being met. Can we express this in clear language with common-sense metrics?

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New Relic Reports Major Spike in Volume of Log Data

DevOps.com

The report also identified logs generated by NGINX proxy software (38%) as being the most common type of log, followed by Syslog (25%) and Amazon Load Balancer […]. New Relic today shared a report based on anonymized data it collects that showed a 35% increase in the volume of logging data collected by its observability platform.

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4 Rs for Scaling your testing? The first steps towards a rewarding engagement

Trigent

With the increased adoption of DevOps, the need to scale takes a different color altogether. Further, given the blurring lines between QA and development with testing being integrated across the SDLC, there is a strong need for the partner to have strengths across DevOps, CI/CD in order to make a tangible impact on the delivery cycle.

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