GC - #30 One Year of Giant Conversations

Show notes

Giant Conversations Episode #30

Episode Date: March 12 2025

Hosted by:

Contributors:

### Swarmalicious News

We'll be at KubeCon in London Drop by booth N450

Date: 1-4 April 2025 in London

Giant Swarm Lineup - KubeCon:

Marco Ebert: How To Gateway With Ingress - 140 Days InGate

Giant Swarm Lineup at Rejekts:

Marcus Noble: Pod Deep Dive: Everything You Didn't Know You Needed to Know
Joe Salisbury: The Cluster API Migration Retrospective: Live migrating hundreds of clusters to Cluster API

Oliver's Take: You don't often go to conferences. I've heard there are three kinds of people who go:

Heavy learners who can't miss a session, take notes, and bring back boatloads of informatio
Those who just kind of hang around and network a bit
Those who party till the daytime and go to the conference slightly drunk
…. there's proibably a fourth.

The Evolution of IT Operations and Opsgenie:

Opsgenie end of support – effective April 5th, 2027: On this date, access to Opsgenie will be shut off, and the product will no longer accessible. Any unmigrated data in Opsgenie will also be deleted at this point.

This a reasonable amount of time to do something about it - right?

Undocumented commands found in Bluetooth chip used by a billion devices

Researchers have identified undocumented vendor-specific commands in the ESP32 microcontroller, a widely used chip enabling Wi-Fi and Bluetooth connectivity in over a billion IoT devices as of 2023.

The security issues include:

Spoof Trusted Devices: Impersonate legitimate devices to gain unauthorized access.
Access Data Illegally: Retrieve sensitive information without permission.
Network Pivoting: Move laterally within a network to compromise additional devices.
Establish Persistence: Maintain long-term unauthorized access to devices.

On May 5, Microsoft’s Skype will shut down for good:

Moving to Teams…

Why is Microsoft doing this? Integration Challenges: After acquiring Skype in 2011, Microsoft faced difficulties integrating it into its ecosystem, leading to technical issues and user dissatisfaction.

Rise of Competitors: The emergence of platforms like Zoom and WhatsApp, offering user-friendly interfaces and reliable services, diminished Skype's market share.

Strategic Shift to Teams: Microsoft's focus shifted to Teams, a platform that seamlessly integrates with its suite of productivity tools, aligning better with modern communication needs.

Cast AI 2025 Kubernetes Cost Benchmark Report

Key findings:

Only 10% of provisioned CPUs are utilized
Memory utilization averages just 23%
The gap between provisioned and requested resources is massive— 40% for CPU, 57% for memory

The data for our 106 clusters shows

CPU Utalization Mean between 9.6% and 13.7%, Max 19.6%
Memory Utalization Mean between 20.3% and 40.9%, Max 46.7%

How data centres can chase renewable energy across Europe

In Ireland, data centers' share of electricity consumption was 21% in 2023 and is projected to reach 32% by 2026. This article covers

Geographical Flexibility: Locating data centers in regions abundant in renewable resources—such as wind-rich northern Europe or sun-rich southern Europe—allows for optimal utilization of local renewable energy capacities.

Operational Flexibility: Scheduling non-time-sensitive computational tasks during periods of high renewable energy availability can reduce reliance on non-renewable power sources.

Dynamic Load Shifting: By distributing computing tasks across various locations based on real-time renewable energy availability, data centers can minimize energy costs and emissions. For instance, when wind generation is low in one area, tasks can be shifted to another region with higher wind output.

The European Centre for Medium-Range Weather Forecasts (ECMWF) has introduced the Artificial Intelligence Forecasting System (AIFS), an AI-based weather model that significantly enhances forecasting accuracy while reducing energy consumption by approximately 1,000 times compared to traditional methods.

Key Features of AIFS:

Enhanced Accuracy: AIFS leverages machine learning techniques to provide more precise weather predictions, improving the reliability of forecasts.

Energy Efficiency: The system's AI-driven approach drastically reduces the computational resources required, leading to substantial energy savings.

Operational Integration: As the first operational forecasting model extensively utilizing machine learning across various parameters, AIFS represents a significant advancement in meteorological practices.