---

Takeaways:

• Observability in Tech: Understand how tech giants leverage eBPF to enhance observability metrics.

• Kubernetes Testing: Explore the application of Testcontainers with Python for effective end-to-end testing within Kubernetes environments.

• KEDA Implementation: Learn about scaling applications to zero on Google Kubernetes Engine using KEDA.

• Kubernetes Updates: Familiarize yourself with Kubernetes v1.32’s new CPU Manager static policy for strict CPU reservation.

• Data Engineer Strategies: Delve into best practices for testing, monitoring, and observability in data engineering.

• Telemetry Management: Gain insights on sending telemetry data to AWS S3 and the role of the OTel Collector.

• OpenTelemetry Standards: Engage with the discussion surrounding OpenTelemetry and its significance in establishing formal standards.

• EKS Auto Mode: Clarify what EKS Auto Mode is and its implications for managing Kubernetes clusters.

Links:

• eBPF and How Tech Giants Use It to Uplevel Observability

• Kubernetes End-to-End Testing Using Testcontainers and Python

• Scaling to Zero on Google Kubernetes Engine with KEDA

• Kubernetes v1.32 Adds A New CPU Manager Static Policy Option For Strict CPU Reservation

• The Data Engineer’s Guide to Testing, Monitoring, and Observability

• When Game Days Go Wrong

• Sending Telemetry to AWS S3 with the OTel Collector

• OpenTelemetry and the Value of Standards

• What Is EKS Auto Mode and Will It Fully Manage My Kubernetes?

---

Takeaways:

• New updates on Open Policy Agent usage in Skipper Ingress.

• Insights on mapping reliability to accountability in systems.

• Exploration of tools and strategies for optimizing observability in Kubernetes and carbon footprint management.

• Best practices for keeping User Journey SLOs up-to-date with end-to-end testing in microservices architectures.

• Key highlights from AWS re:Invent2024 related to Amazon CloudWatch and Kubernetes v1.32.

Links:

• Open Policy Agent in Skipper Ingress

• Mapping reliability to accountability

• Kubernetes, Kepler, and carbon footprints

• Keeping User Journey SLOs up-to-date

• What’s new with Amazon CloudWatch at AWS re:Invent2024

• Kubernetes v1.32: QueueingHint for pod scheduling

• Importance of Kubernetes Operators for Platform Engineers

---

Takeaways:

• Microservices can lead to technical debt, increasing complexity in system management.

• Amazon EKS is adapting with new features such as hybrid nodes and auto mode for streamlined Kubernetes management.

• Data-driven incident management is crucial; leveraging SLOs can significantly enhance performance during incidents.

• Keeping systems updated and understanding timing issues in distributed systems can prevent operational problems.

• The latest DORA Accelerate State of DevOps report is available for insights into current trends in DevOps.

Links:

• Microservices as Technical Debt

• Amazon EKS Hybrid Nodes

• Understanding Timings in Distributed Systems

• DORA State of DevOps Report

• Leveraging SLOs in Incident Management

---

Takeaways:

• Kubernetes RBAC improvements can enhance security posture in K8s environments.

• Recognize challenges and limitations when moving away from Kubernetes.

• Building an AI agent can optimize Site Reliability Engineering (SRE) practices.

• Celebrating Go’s15th anniversary highlights its evolution and community impact.

• Utilizing metrics from the OpenTelemetry collector aids in effective scaling solutions.

• SQL-based observability is evolving to address complex data insights and management.

• Understanding IT engineers’ mental models can improve team dynamics and workflows.

• Cautionary tales highlight the importance of following cloud service guidelines (e.g., AWS Amplify).

Links:

• Kubernetes RBAC: Improve the K8s Security Posture

• We’re leaving Kubernetes

• How to build an AI Agent for SRE

• Go Turns15

• Using metrics from OTEL collector for scaling

• The evolution of SQL-based observability

• Inside Argo: Automating the Future

---

Takeaways:

• Kubernetes Operations Redefined: The Karpenter Effect reveals advancements in Kubernetes management and operational efficiency.

• Observability Enhancement: eBPF technology strengthens observability in cloud-native environments, improving performance monitoring.

• OpenTelemetry Expansion: OpenTelemetry is enhancing its capabilities into CI/CD observability, streamlining monitoring and feedback loops in development.

Links:

• The Karpenter Effect: Redefining Our Kubernetes Operations

• How eBPF makes observability awesome

• OpenTelemetry Is expanding into CI/CD observability