Asserting the Construct for Higher Code Problem Winners

The outcomes are in for the Construct for Higher Code Problem, highlighting two standout options that successfully mix automation or AI with sustainability. On this problem, we requested you, the Cisco DevNet neighborhood, to make use of automation and AI to handle urgent environmental points, demonstrating the numerous position know-how can play in enhancing our ecological footprint. And we had been blown away by the neighborhood participation.

Congratulations to GreenOps Tracker and Inexperienced Monitoring! These standout entries not solely exemplify the ingenuity and sensible affect of integrating automation and AI with sustainability efforts but additionally show how focused options can considerably improve environmental sustainability. As we discover the modern applied sciences every venture employs to handle particular environmental challenges, it’s clear that our developer neighborhood possesses large potential to drive significant change. To additional optimize these profitable options, every crew will obtain mentorship from Jason Davis, Distinguished Engineer at Cisco. This mentorship will give attention to advancing AI integration inside their tasks, reinforcing Cisco’s dedication to main the dialog on AI-driven sustainability.

GreenOps Tracker: Automating Sustainability in Server Operations

GreenOps Tracker innovates server administration by optimizing useful resource utilization, thereby minimizing vitality consumption and decreasing CO2 emissions. Developed to empower server directors with real-time information, GreenOps Tracker makes use of Efficiency Co-Pilot (PCP) and Ansible Occasion-Pushed applied sciences to watch Linux servers, routinely adjusting their configurations based mostly on real-time occasions. This technique not solely reduces operational prices but additionally helps environmental sustainability targets by making certain that servers function with optimum assets, avoiding pointless vitality use.

The core of GreenOps Tracker’s performance lies in its skill to dynamically reply to modifications in server efficiency metrics comparable to CPU utilization, reminiscence load, and system temperature. By integrating PCP for monitoring and utilizing webhooks to set off Ansible playbooks, the system offers a proactive administration instrument that adjusts assets with out human intervention. This automated adjustment is essential for sustaining effectivity in information facilities the place even minor enhancements can result in important reductions in energy consumption and carbon footprints. The longer term prospects for GreenOps Tracker embrace increasing its metric help and integrating with Grafana to offer much more complete vitality consumption insights, promising additional advances in sustainable IT administration.

Discover GreenOps Tracker on Code Change >

Inexperienced Monitoring: Monitoring Sustainability in Actual-Time

Inexperienced Monitoring is a sustainable resolution engineered by a crew at Cisco that makes use of an open-source know-how stack to watch the vitality and CO2-equivalent emissions of community and information heart gadgets. It targets a spread of kit together with IOS-XR and NX-OS gadgets, Meraki switches, UCS servers, ACI APIC nodes, and third-party PDUs from Eaton and Raritan. This instrument not solely tracks vitality consumption and carbon footprints but additionally correlates these metrics with visitors, bandwidth, and prices, providing enterprises essential insights for optimizing sustainability.

The spine of Inexperienced Monitoring contains gRPC streaming telemetry, Telegraf information processing, InfluxDB for information storage, and Grafana for visualization. This setup facilitates real-time monitoring and historic evaluation, empowering customers with actionable information to boost their infrastructure’s vitality effectivity. The answer’s in depth use of open-source applied sciences lowers obstacles to entry and helps Cisco’s developer neighborhood in adapting and increasing the venture to different sustainability metrics or personalized use-cases.

Discover Inexperienced Monitoring on code change >

As you draw inspiration from the Construct for Higher Code Problem winners, proceed your exploration of AI’s position in sustainability with Cisco’s instruments and assets.

• Go to the Cisco DevNet AI Useful resource Hub to entry studying labs, pattern code, and movies on predictive and generative AI. These assets are designed that will help you develop efficient, sustainable options utilizing AI know-how.
• Missed Developer Sustainability Week? No drawback. You’ll be able to watch the recordings of our webinar and workshop to achieve insights into optimizing assets and enhancing system efficiencies for sustainability.
• Discover our weblog on AI programming languages to find which programming languages are greatest suited to varied AI duties.
• Keep engaged and broaden your community. Be part of the DevNet Webex neighborhood, the place you possibly can join with friends, share your tasks, and discover new collaboration alternatives.

Thanks to everybody who participated on this inaugural DevNet code problem! We sit up for future challenges.

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