Architectural Integrity Meets Primal Wellness: Engineering a Sauna for Optimal Health and Durability

As professionals in the building environment, we know that true quality emerges when design decisions are made with both aesthetic beauty and structural resilience in mind. I recently completed a project that perfectly illustrates this principle: a deeply integrated sauna structure designed to withstand extreme conditions while offering profound health benefits.

The Challenge of Placement and Access

Building on a difficult site demands meticulous planning and execution. The location of this sauna required significant manual site preparation. Due to the rugged terrain, moving all necessary building materials was a challenging logistical feat, emphasizing the premium placed on every element chosen for the final structure.

Constructing the Perfect Envelope: Defying the Dew Point

When designing a space defined by intense, fluctuating humidity - like a sauna - the issue of the dew point becomes paramount. Condensation forming within the wall cavities leads directly to rot and mold, compromising both the building's longevity and occupant health.

Our crucial design decision to combat this involved constructing robust, layered wall assemblies that deliberately encourage airflow between the building layers. This controlled ventilation system ensures a perpetually dry building by carrying away moisture vapor before it can condense within the envelope. This preventative measure is fundamental to promoting a durable and structurally sound building for decades. Visible elements of the construction include vertical stud framing and insulation materials integrated into the wall structure.

Performance Through Precision Materials

We selected materials not just for their looks, but for their commitment to performance:

Custom-Milled Rhombus Siding: The exterior features unique custom-milled rhombus siding. This deliberate profile enhances the building's aesthetic appeal while serving as an effective rain screen, supporting the ventilation strategy and rapid drainage.

Triple-Glazed Windows: Windows are often the weakest thermal link. To mitigate heat loss and maintain a high level of energy efficiency, we specified high-performance, triple-glazed windows. This choice minimizes thermal bridging and ensures internal glass surfaces remain warm, further preventing condensation risks inside the heated space.

The custom milled rhombus siding was not only aesthetic, it was also the least expensive.

The Heart of the Ritual: Heat, Cold, and Restoration

The interior is designed around the powerful, transformative experience of the heat and the stones. A moderately sized stove capable of holding a substantial volume of volcanic stones dominates the space, crucial for generating rich, intense löyly (steam). Heating the space is a manual process, requiring tending to the firebox to achieve the desired temperature. Three large spoonfuls of essential oil infused water poured over the hot stones brings the temperature up in 3 - 5 degree bursts.

Adding essential oils to the water before pouring over the hot stones provides additional wellbeing.

The sauna and the associated features are intended to work together as a holistic wellness facility. The structure is integrated with a separate, adjacent cold feature, built by converting the properties legacy surface well. The below-grade concrete structure and ladder is designed for a splash or cold plunge - that is situated a few steps from the sauna building. A deep breath and quickly lowering yourself into the 6'6" pool allows you to emerge into a different dimension.

The Thermal Cycle for Deep Wellness:

The full restorative experience involves cycling between the heat and the cold. Based on traditional practices, the cycle emphasizes a deep heating step followed immediately by a rapid cooling phase.

A suggested cycle involves:

1. Heating: Spending time in the intense heat of the sauna.

2. Cooling: Transitioning directly to the cold plunge or splash pool for up to three minutes.

3. Rest: Resting outside for another 5 to 10 minutes before returning to the sauna.

This cycle is typically repeated three times to maximize circulatory benefits and promote relaxation. Taking the opportunity the sit and relax in the cool air, or by an outdoor fire, and breathe deeply further enhances the experience.

It should be noted that while the existence of the heated sauna and the cold plunge structure is supported by the sources, the specific timing, duration (3 minutes in the pool, 5-10 minutes outside), and repetition count (3 times) for this wellness protocol are details that need to be considered by the user. Know your body and how it responds to heat and cold cycles. Good to consult with your physician before using a sauna and cold pool.

Sunset and views from the sauna are outstanding. And the deck provides enough space for laying about and completing a few yoga postures.

The colour of the wood burning firebox always adds to the ambience and provides enough light to choose a few more pieces of wood organized under the interior bench seats.

The dry summer months also provide an opportunity to maintain the lands around the sauna and splash pool.

This project demonstrates that successful architecture transcends mere shelter; it is about engineering environments that actively support health, durability, and a profound connection to beneficial natural rituals.

ODE Data Lab has its technology footing

This month has become more about standing up technology than it has been talking to people about their ocean data needs. That's ok... if you are building a technology company, you need to build technology. Ocean of Data Endeavours (ODE) is about building and utilizing software towards making it super easy to work with data, large amounts of data.

The last 10 days have been about refreshing a server infrastructure I stood up 12 years ago for a number of other projects. What was left was a couple of simple websites, some domain hosting, and all the related mail server infrastructure. All of this needed a complete refresh to be brought up to date;

1. Rebuild the server infrastructure to have more horsepower. - DONE
2. Upgrade the Ubuntu OS from 10.04 (Lucid Lynx) to 20.04 (Focal Fossa). - DONE
3. Rework all the domain aliases to remove dependency on a domain I no longer owned. - DONE
4. Do some basic security work to the server. Mostly SSH focused. - DONE
5. Create a new mail server, and do some mailbox maintenance. - DONE
6. Install Apache2 httpd host. - DONE
7. Configure Apache2 for a couple of web sites. - DONE
8. Code some basic HTML to confirm the sites are working. - DONE
9. Celebrate! http://endeavours.com/

So good to have all this done. The server will provide a strong foundation and is well prepared for the ELK stack and the first load of ocean data. So excited! 

Building the Data Lab Technology Stack

The idea of building a data lab is emerging from my ocean data conversations and how to best utilize my knowledge and skillset within this opportunity. In my mind, the service offering would be twofold;

1.  Data Engineering / Software Development consulting and services with focus on ocean data. We will do the heavy lifting of extracting, cleansing, transforming, and loading your data. And then we will help with analysis and visualizing the data. We are comfortable working in both the open source and Microsoft technology stacks.
2. Standing up (and data loading) the technology stack for the data lab. You are going to need to host all this compute power and storage somewhere. It could be on-premise. Most likely, it will be in the cloud. We can help with this also. We could build it in Azure, using the Microsoft technology stack. Or we could build it using an Open Source stack on top of Linux in any of the hosted environments of Azure, AWS, or Rackspace.

https://stock.adobe.com/

How do you build a low priced, large compute, technology stack to support data engineering efforts, implement a data lab, and showcase these new services capabilities. The low price is the key factor given the current startup state of this ocean data endeavour. Particularly, when you think of the cost of compute for processing and storing large amounts of data. I believe the the best way forward is as follows;

1. Use open source where you can. Fortunately, many of the infrastructures, tools, frameworks, and programming languages for the data lab are open source.
2. Automate the build so it can be built and torn down with ease. This would eliminate the need for the stack to always be running.
3. Store the data at it's source, if possible. Fetch, and load, the data when you automatically rebuild the stack. Keep in mind this limits the amount of big data you can store locally, and loading large amounts of data can cumulatively take days. Be mindful of this. 

Note: this stack is to showcase the services capabilities. A full data lab would also need the ability to both persist and fetch data. It's going to take some time to build the data lab!

The Data Lab Technology Stack

The deployment of this technology stack will use open source wherever possible running on a Linux (Ubuntu) Server hosted at Rackspace. The rational for these decisions are;

• Little to No licensing costs 
• Strong familiarity with Rackspace as hosting company
• Existing domain name (endeavours.com) hosted with Rackspace
• Extensive experience with Ubuntu Linux in a hosted environment
• Familiarity with deploying data intensive solutions using the ELK stack
• Experience programming in Python

Note: The deployment of this technology stack will happen in phases, where each phase will complete with some basic tests to ensure the stack behaves as desired.

Phase 0

Phase 0 will be a basic ELK stack running on an Ubuntu Linux server hosted at Rackspace with access via the endeavours.com web domain. The use case for where the data comes from, how we transform it, the analysis, and visualization is still to be determined. This use case will be used for testing this first iteration of the newly stood up data lab. Exciting times!

Phase 1

During phase 1 we will add the Python programming language to the technology stack and use it for two purposes;

• Apply a model to the data using Python.
• Present the processed data to a web page for display.

Phase 2

During phase 2 we will add Kafka as an infrastructure resource, identify some additional data sources, and pre-process the data before it gets loaded into ElasticSearch.

Phase 3 and beyond

Investigate the Apache Data lab stack, add Spark to our lab, add a data workbench...

Digital by Design, Agility and Data Architecture

For 12 months, starting the summer of 2018, I was very fortunate to fill the data architect role for the Government of Newfoundland and Labrador's digital by design citizen facing web portal. An amazing team was brought together and we accomplished an amazing amount of work given the complexity of the environment we were all working. Kudos to the leadership team for seeding the ground and pulling together a diverse and effective group of people.

Being the oldest team member, with 35 years as a technology professional, I noticed a number of items and approaches that I consider the highlights of the project. I call out my 35 years experience because I know success doesn't always happen in a large group of people (with a team larger than 35). A group of strangers doesn't always come together when tasked to ship software on schedule and on budget. The cool part of this project is that the highlights were both technical and project management. In a nutshell, we came together using a scrum model of project management (hosted within JIRA) and architected a microservices technology stack using predominantly Microsoft technologies. The user experience design was exemplary and the software approach stayed aligned with the best of agile practices. We also used a scrum of scrums approach to manage the three distinct scrum teams.

What made this first year of a new project so effective?

The Agile Practices
The team was encouraged to use Agile approaches to successfully ship software. Thankfully, the commitment came from the most senior level and agile workshops were used to align the teams understanding and approach to agile. I consider these three agile practices what kept us all well aligned;

1. We rigorously stayed with 3 week sprints. This was facilitated by the scrum of scrums group and kept us all focused on shipping working software.
2. We embraced jira and stayed true to moving cards. It took a few sprints, as a whole we ended up having all the team members updating and moving cards. This, combined with morning standups, kept the team transparency high and important issues in the open.
3. We always had demo days and retrospectives. This went a long way to keeping us focused and successful. All team members were encouraged to attend the other scrums demo days, this built excitement and kept us focused and moving.

Software Engineering Discipline
Developing software is as much art as it is science. Our team included many accomplished software engineers and this helped us implement features quickly and completely. Kudos are deserved by many on this project team, in particular, one of our technical leads (this is you, Phil) was hellbent and lead through example with two attributes of software engineering that are super important and sometimes missed;

1. We refactored always, no excuses. As a group we were always learning, as implementing features is a relentless teacher. Improving upon our code base through refactoring kept the quality improving, and the bugs low. Even from a data architecture perspective, at the beginning of each sprint we refactored the data tier with the required data changes from the previous sprint. Data tiers often have different heart beats that the middle and user tiers as they are dependent on the legacy systems, which often have legacy heart beats. This is a blog post in itself...
2. Automated testing. We automated whenever we could, we aspired to have automated tests with coverage to all our code. We got close by using frameworks and having a test first mind set. And don't underestimate how effective existing testing frameworks can be applied to the data tier.

Architecture was collaborative 
All architects were encouraged to contribute and discuss, we were always white-boarding and soliciting feedback. This kept the architecture strong and well understood throughout the team. And because we had a shared understanding of architecture the refactoring was reduced. All good...