Machine Learning capabilities analyze vast volumes of financial data, including transactions and check images to detect unusual customer behavior and suspicious activity with high accuracy and fewer false positives.

Transaction boundaries are a critical aspect of a system.

I've often noticed that these boundaries are not considered when carving out microservices.

Subsequently, workarounds are put in place that tend to be complicated as they attempt to implement two phase commits.

K8S is not easy.

  It helps standardize:
    - deployments of containers
    - health checks
    - cron jobs
    - load balancing

What is the "old way" of doing things?

Is it same/similar across teams within and outside your organization.

If not, what would it cost to build consensus and shared understanding?

How would you build this consensus outside your organization?

For small organizations, one should do whatever makes them productive.

However, as soon as you need to standardize across teams and projects, you can either build your own standards and tooling or use something like K8S.

  Once you have K8S, the extensibility feature kicks in to address issues such as:
   - Encrypted comms between pods
   - Rotating short lived certificates

I don't love K8S.

However, if not K8S then, what alternative should we consider to build consensus and a shared understanding?

I love Cloudflare & their products.

From a moat perspective, I wonder if the TAM of this business in the context of the three cloud providers is substantial.

Their stock price is back down to reasonable levels.

Perhaps they'll remain a niche player in the market?