gefyra VS tuna

Gefyra attempts to provide the same value as mirrord, but in a different way (via VPN).

Please find the draft here: https://github.com/gefyrahq/gefyra/issues/353

- https://gefyra.dev/

We recently presented our open-source tool Gefyra (https://gefyra.dev) at a "Kubernetes Community Days" event.

My team and I created the open-source tool Gefyra: https://github.com/gefyrahq/gefyra

Gefyra - a tool that creates local infrastructure to write code directly in a Kubernetes cluster while using conventional development tools (including debugger): https://gefyra.dev

As an example: for another project (https://gefyra.dev) I create a Deckfile which contains: - a Keycloak, with initial data (realm, clients, user, etc.) - a service with a sidecar pattern (oauth2-proxy for handling OIDC) - the K8s dashboard for developer experience Have a look: https://github.com/gefyrahq/gefyra-demos/blob/main/deck.yaml And all it takes to run this locally is deck get https://github.com/gefyrahq/gefyra-demos.git Epinio can effectively become part of the Deckfile (so the platform is installed locally already), and the developer can run epinio push immediately after deck get... to bring in new apps. Sounds good.

Mhh. Interesting. With Gefyra (https://gefyra.dev) I automated just that process and it seems to work. I tested it successfully with GKE. However, I decided to use a NodePort service. Is your GCP firewall rule UDP based (TCP is default and does not work)?

If a local Docker container instance supports GPU access on M1 Mac (and I really don't know) you could use Gefyra (https://gefyra.dev) to run the container with the special hardware requirements on you local Docker host and the rest within Minikube. The container running with Gefyra should behave as it would run within a Kubernetes namespace.

Every minor detail matters and adds to the total import time as part of the cold start. We need to optimize our code and imports. If you use Python, you can analyze your code with a tool like Tuna and optimize your libraries (perhaps replace slower ones) and your imports.

I started to examine the output of python -X importtime -m gefyra 2> import.log just to check the imports. There is an awesome tool to analyze the Python imports: tuna (see: https://github.com/nschloe/tuna). tuna allows analyzing the import times from the log. Run it like so tuna import.log. It opens a browser window and visualizes the import times. With that I was able to manually move all imports to the functions in which they are needed (and bring in some other optimizations). This greatly violates PEP 8 (https://peps.python.org/pep-0008/#imports) but leads to very fast startup times.