This started as a conversation between James A Rosen & Gerhard in August 2023. Several months later, it evolved into a few epic pairing sessions captured in these GitHub threads:

1. thechangelog#480 (reply in thread)
2. thechangelog#486

The last pairing session eventually lead to 🎧 Kaizen! Should we build a CDN? This is the follow-up to that. How far did we get in 1 hour?

LINKS

• The 5-hour CDN
• varnish - Docker Official Image
• Introduction to Varnish
• Magento2 Varnish config
• Magento Internals: Cache Purging and Cache Tags
• Varnish modules

EPISODE CHAPTERS

• (00:00) - Intro

For our 4th episode, we have four conversations from KubeCon EU 2024.

We talk to Jesse Suen about Argo CD & Kargo, Solomon Hykes shares the next evolution of Dagger, and Justin Cormack dives into Docker & AI. We also catch up with Frederic Branczyk & Thor Hansen on the latest Parca & Polar Signals Cloud updates since our last conversation.

Each conversation has a video version too:

1. Jesse Suen: 🎬 GitOps & ClickOps beyond Kubernetes
2. Solomon Hykes: 🎬 Pipelines as Functions
3. Justin Cormack: 🎬 Works on my Computer
4. Frederic Branczyk & Thor Hansen: 🎬 always BPF

LINKS

1. Jesse Suen

- What's New in Kargo v0.5.0

- 🎬 Navigating Multi-stage Deployment Pipelines via the GitOps Approach 

2. Solomon Hykes

- Introducing Dagger Functions

- A Keynote heard around the world - KubeCon EU 2024 Recap

- 🎬 Local & open-source AI Developer Meetup

3. Justin Cormack

- AI Trends Report 2024: AI’s Growing Role in Software Development

- Building a Video Analysis and Transcription Chatbot with the GenAI Stack

4. Frederic Branczyk & Thor Hansen

- Correlating Tracing with Profiling using eBPF

LET'S MAKE IT BETTER

If you enjoyed this episode, I will appreciate your feedback on Apple Podcasts or Spotify.

If there is something that would have made it better for you, let me know: [email protected]

• (00:00) - Intro

Alex Sims, Solutions Architect & Sr. Software Engineer at James and James Fulfilment, talks about their journey to 80ms response SLO with PHP & React.

Alex shares how they optimised API performance, specifically highlighting improvements made by altering interactions with Amazon S3 and Redis. Key points include the transition from synchronous to asynchronous S3 processes, the impact of Amazon's SLO on write speed, and the significant runtime reduction achieved through JIT compilation in PHP 8. 

We conclude with insights into decision-making in technology architecture, emphasising the balance between choosing cutting-edge technology and the existing skill set of the team.

🎬 View the video part of this episode at 80ms response SLO with PHP & React

🎁 Access the audio & video as a single conversation at makeitwork.gerhard.io

EPISODE CHAPTERS

• (00:00) - Introduction

Today we delve into BuildKit and Dagger, focusing on their significance in the development and deployment of containerized applications, as well as Kubernetes integration.

• BuildKit's Role: Essential for anyone using Docker Build, facilitating efficient, dependency-aware container builds with advanced caching mechanisms. It's not just for Docker but serves as a versatile execution engine across various projects, including Dagger.
• Eric's Attraction to BuildKit: The power of BuildKit's DAG (Directed Acyclic Graph) execution model and its parallelization and deduplication capabilities drew Eric to maintain and contribute to the project.
• First BuildKit Project: Eric's initial project, bincastle, aimed to build a development environment from source, highlighting BuildKit's ability to handle complex builds.
• Introduction of Dagger: Dagger builds on top of BuildKit, enhances automation by allowing developers to use familiar programming languages without being confined to a specific domain-specific language (DSL). It aims to simplify and optimize automation tasks, particularly in CI/CD environments.
• Dagger's Enhancements over BuildKit: Dagger introduces a language-agnostic layer, making automation more accessible and scalable. It incorporates features like remote caching and a services layer, potentially positioning it as a simpler alternative to Kubernetes for certain use cases.
• Future Directions: The podcast touches on ongoing developments, such as modules for sharing automation code within Dagger, aiming to foster an ecosystem where developers can easily reuse and contribute to collective automation solutions.

The conversation highlights the evolving landscape of development tools, where BuildKit and Dagger play pivotal roles in making containerized development and deployment more efficient and user-friendly. Eric and Gerhard discuss the potential for these tools to simplify and enhance automation, reflecting on past projects and future possibilities.

🎬 View the video part of this episode: Deploying and Experimenting with Dagger 0.9 on Kubernetes 1.28

🎁 Access the audio & video as a single conversation at makeitwork.gerhard.io

LINKS

• sipsma/bincastle
• moby/buildkit
• dagger/dagger

dagger --mod github.com/sipsma/daggerverse/yamlinvaders@8071646e5831d7c93ebcd8cca46444250bf25b8c shell play

EPISODE CHAPTERS

• (00:00) - Intro

This episode looks into the observability tool Parca & Polar Signals Cloud with Frederic Branczyk and Thor Hansen. We discuss experiences and discoveries using Parca for detailed system-wide performance analysis, which transcends programming languages.

We highlight a significant discovery related to kube-prometheus and the unnecessary CPU usage caused by Prometheus exporter's attempts to access BTRFS stats, leading to a beneficial configuration change for Kubernetes users globally.

We also explore Parca Agent's installation on Kubernetes 1.28 running on Talos 1.5, the process of capturing memory profiles with Parca, and the efficiency of the Parca Agent in terms of memory and CPU usage.

We  touch upon the continuous operation of the Parca Agent, the importance of profiling for debugging and optimization, and the potential of profile-guided optimizations in Go 1.22 for enhancing software efficiency.

🎬 Screensharing videos that go with this episode:

1. First impressions: Parca Agent on K8s 1.28 running as Talos 1.5
2. See where your Go code allocates memory
3. How to debug a memory issue with Parca?
4. See which line of your Go code allocates the most memory

🎁 Access the audio & all videos as a single conversation at makeitwork.gerhard.io

LINKS

• Go Profile-guided optimization
• View Profiling Data within Code
• Announcing Continuous Memory Profiling for Rust

EPISODE CHAPTERS

• (00:00) - Intro