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Scalability Challenges in Microservices Architecture: A DevOps Perspective

Unite.AI

DevOps methodologies, particularly automation, continuous integration/continuous delivery (CI/CD), and container orchestration, can enhance the scalability of microservices by enabling quick, efficient, and reliable scaling operations. How can DevOps practices support scalability? CI/CD tools. Infrastructure as Code (IaC).

DevOps 294
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AI in DevOps: Streamlining Software Deployment and Operations

Unite.AI

As emerging DevOps trends redefine software development, companies leverage advanced capabilities to speed up their AI adoption. That’s why, you need to embrace the dynamic duo of AI and DevOps to stay competitive and stay relevant. How does DevOps expedite AI? How will DevOps culture boost AI performance?

DevOps 310
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5G network rollout using DevOps: Myth or reality?

IBM Journey to AI blog

This requires a careful, segregated network deployment process into various “functional layers” of DevOps functionality that, when executed in the correct order, provides a complete automated deployment that aligns closely with the IT DevOps capabilities. that are required by the network function.

DevOps 242
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How Can a DevOps Team Take Advantage of Artificial Intelligence?

Analytics Vidhya

DevOps and artificial intelligence are covalently linked, with the latter being driven by business needs and enabling high-quality software, while the former improves system functionality as a whole. The DevOps team can use artificial intelligence in testing, developing, monitoring, enhancing, and releasing the system.

DevOps 293
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Operationalize automation for faster, more efficient incident resolution at a lower cost

IBM Journey to AI blog

Together, IBM Instana and IBM Turbonomic provide real-time observability and control that everyone and anyone can use, with hybrid cloud resource and cost optimization so you can safely automate to unlock elasticity without compromising performance. Ops teams can automate optimization to assure app performance at the lowest cost.

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Achieve DevOps maturity with BMC AMI zAdviser Enterprise and Amazon Bedrock

AWS Machine Learning Blog

This is achieved through practices like infrastructure as code (IaC) for deployments, automated testing, application observability, and complete application lifecycle ownership. Lead time for changes and change failure rate KPIs aggregate data from code commits, log files, and automated test results.

DevOps 114
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Debunking observability myths – Part 5: You can create an observable system without observability-driven automation

IBM Journey to AI blog

The notion that you can create an observable system without observability-driven automation is a myth because it underestimates the vital role observability-driven automation plays in modern IT operations. Why is this a myth? Reduced human error: Manual observation introduces a higher risk of human error.