Signadot is a Kubernetes-native platform that accelerates the development of microservices. It provides a fast feedback loop, allowing developers to test their changes alongside dependencies, data and 3rd party APIs as they write code.
Thanks to @mwseibel and @ycombinator for the hunt!
👋 Hey Hunters, we're excited to share a major new update with you.
In September last year, we launched Signadot as a platform that enables test & preview environments for microservices in Kubernetes. Working with our customers, something we heard from developers overwhelmingly was that while preview environments were great for testing changes once they’re pushed to a branch, the feedback loop wasn’t quite as fast as it could be - because it still involved waiting for docker images to build and the CI (Continuous Integration) pipeline to kick in, which could take many minutes for each commit before it updated a sandboxed microservice and made it available to test.
🔥 What’s new
With our latest release, we’re adding the following new capabilities to Signadot:
• Developers can now run the dev version of a microservice on their laptop and seamlessly connect it to a shared Kubernetes cluster and start testing as though the whole application were running locally. They get 10x faster feedback by testing their changes in a live Kubernetes environment during active development.
• Multiple such dev environments can be combined together to test different microservices with each other as they're being developed. This means developers can collaborate and get a feature spanning different microservices working end-to-end long before their code gets merged or hits a staging/production environment.
Just as before, we use request routing (using a Service Mesh like Istio to isolate environments in the shared Kubernetes cluster, an approach similar to systems like Uber’s SLATE). This approach is highly scalable - enabling developer environments that work well across hundreds of developers and microservices without incurring large infrastructure costs or maintenance burdens.
🤓 How this helps development teams
• Developers test in a real environment with dependencies, data, 3rd party APIs.
• Highly scalable with minimal infrastructure cost - spins up in seconds.
• Easy Collaboration across teams developing different microservices.
• Ship features fast with fewer rollbacks.
✨ Want to go further?
If you’re interested, you can try this out by going to app.signadot.com, using the quickstart guide. We can’t wait to see what you do and look forward to all the feedback!
This is such a neat use case for Istio/sidecars/service mesh. If you can get in control of networking between services, you can really do amazing stuff. Is anyone trying this in their production cluster or is it all dev/staging for now?
@nocnica The approach itself works exactly the same, whether in dev / staging / prod. While most commonly, it's used in pre-production currently, there are some companies using this approach in production. It's relatively less common because it requires a higher degree of maturity to be able to enforce controls for data isolation and compliance between test and prod traffic.
Great tool for easily bringing "shift left" practice in the dev cycle.
What I've seen so far in different organizations are devs making a code change, merging the change, and a new tag/artefact creation. Then a long cycle of feature testing and performance testing happens. Sometimes, a few iterations are required to reach the desired level, making the whole feature development process slow and monotonous.
It would be a good tool for us, as we always face the problem...
Kudos to the Signadot team!!
@shivanshu1333 Thanks for your positive feedback! Couldn't agree more :-) It's about giving developers a fast and high fidelity feedback loop earlier in the dev workflow.
@shantanu_apex that's a great question. Typically, companies adopt this kind of approach when they hit a certain scale of microservices - say 30 or more, where bringing up the entire stack for isolated environments becomes both cost prohibitive and not as effective, so, it's sector agnostic.
Some of the early adopters of this approach that we've seen include internet companies (e-commerce, social, app-based logistics, etc) where they have large numbers of microservices, and a second category is companies that have the need for high-fidelity data during development and testing - so, several companies in the FinTech & ML domains. In the mid to long term, as this approach becomes more well understood and easier to do, I believe that most companies that are doing microservices at any reasonable scale will move towards using request-based isolation for developer and test environments.
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