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 group, to make use of automation and AI to handle urgent environmental points, demonstrating the numerous function know-how can play in enhancing our ecological footprint. And we have been blown away by the group 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 exhibit how focused options can considerably improve environmental sustainability. As we discover the revolutionary applied sciences every mission employs to handle particular environmental challenges, it’s clear that our developer group possesses large potential to drive significant change. To additional optimize these successful options, every crew will obtain mentorship from Jason Davis, Distinguished Engineer at Cisco. This mentorship will concentrate on 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 power consumption and lowering 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 observe Linux servers, routinely adjusting their configurations primarily based 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 sources, avoiding pointless power use.

The core of GreenOps Tracker’s performance lies in its potential to dynamically reply to modifications in server efficiency metrics reminiscent of CPU utilization, reminiscence load, and system temperature. By integrating PCP for monitoring and utilizing webhooks to set off Ansible playbooks, the system gives a proactive administration device that adjusts sources with out human intervention. This computerized 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 long run prospects for GreenOps Tracker embody increasing its metric assist and integrating with Grafana to supply much more complete power consumption insights, promising additional advances in sustainable IT administration.

Discover GreenOps Tracker on Code Trade >

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 observe the power and CO2-equivalent emissions of community and information middle units. It targets a spread of apparatus together with IOS-XR and NX-OS units, Meraki switches, UCS servers, ACI APIC nodes, and third-party PDUs from Eaton and Raritan. This device not solely tracks power consumption and carbon footprints but additionally correlates these metrics with site 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 reinforce their infrastructure’s power effectivity. The answer’s intensive use of open-source applied sciences lowers limitations to entry and helps Cisco’s developer group in adapting and increasing the mission to different sustainability metrics or personalized use-cases.

Discover Inexperienced Monitoring on code trade >

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

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