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 had been blown away by the group participation.
Congratulations to GreenOps Tracker and Inexperienced Monitoring! These standout entries not solely exemplify the ingenuity and sensible influence of integrating automation and AI with sustainability efforts but additionally exhibit how focused options can considerably improve environmental sustainability. As we discover the progressive applied sciences every venture employs to handle particular environmental challenges, it’s clear that our developer group possesses great potential to drive significant change. To additional optimize these profitable options, every workforce will obtain mentorship from Jason Davis, Distinguished Engineer at Cisco. This mentorship will deal with 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 knowledge, GreenOps Tracker makes use of Efficiency Co-Pilot (PCP) and Ansible Occasion-Pushed applied sciences to observe Linux servers, mechanically adjusting their configurations primarily based on real-time occasions. This method not solely reduces operational prices but additionally helps environmental sustainability objectives by making certain that servers function with optimum assets, avoiding pointless power use.
The core of GreenOps Tracker’s performance lies in its capability to dynamically reply to modifications in server efficiency metrics similar to 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 instrument that adjusts assets with out human intervention. This computerized adjustment is essential for sustaining effectivity in knowledge facilities the place even minor enhancements can result in vital reductions in energy consumption and carbon footprints. The long run prospects for GreenOps Tracker embody increasing its metric help and integrating with Grafana to offer much more complete power consumption insights, promising additional advances in sustainable IT administration.
Discover GreenOps Tracker on Code Alternate >
Inexperienced Monitoring: Monitoring Sustainability in Actual-Time
Inexperienced Monitoring is a sustainable answer engineered by a workforce at Cisco that makes use of an open-source know-how stack to observe the power and CO2-equivalent emissions of community and knowledge heart units. It targets a spread of kit together with IOS-XR and NX-OS units, Meraki switches, UCS servers, ACI APIC nodes, and third-party PDUs from Eaton and Raritan. This instrument 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 knowledge processing, InfluxDB for knowledge storage, and Grafana for visualization. This setup facilitates real-time monitoring and historic evaluation, empowering customers with actionable knowledge to boost their infrastructure’s power effectivity. The answer’s intensive use of open-source applied sciences lowers obstacles to entry and helps Cisco’s developer group 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 function 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 downside. You’ll be able to watch the recordings of our webinar and workshop to realize 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 develop your community. Be a part of the DevNet Webex group, 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 look ahead to future challenges.
Share: