What a year we have had! Hypergrowth, a huge community, and lots of recognition. But what we are most proud of is how Kong’s technology has impacted the world, thanks to our users. We can’t thank these users and the community enough for making Kong the most adopted open source API gateway out there. In fact, our technology just crossed 30,000+ stars on Github . And with over 2M instances and more than 257M downloads our OSS community has more than doubled over the last year.
If you’ve done any reading about service meshes, you’ve probably come across mentions of an open source project named Envoy. And if you’ve done any reading about Envoy, you’ve probably seen references to service meshes. How are these two technologies related? How are they different? Do they work together? I’ll attempt to answer all those questions in this blog post’s first and second parts, plus possibly a few more.
We are happy to announce a new major release of Kuma, and a new major release of Kong Mesh built on Kuma! Kuma 1.3 ships with 10+ new features and countless improvements. Kong Mesh ships we enterprise capabilities for large scale service mesh deployments. We strongly suggest to upgrade, in order to take advantage of the latest and greatest when it comes to service mesh.
Here at Kong, we’re advocates for architecting your application as a group of microservices . In this design style, individual services are responsible for handling one aspect of your application, and they communicate with other services within your network to share data. Systems like Kubernetes or the Kuma service mesh help orchestrate traffic and manage network policies so that your microservices can function together as a unified whole.
Today’s software testing trends show the growing demand for more efficient and automation-oriented API testing. Many of the current test automation solutions focus on the UI, while most API-level testing is still done manually. As a result, testers are in need of easy-to-use, intelligent automation tools for testing APIs — improving their productivity and efficiency, while also reducing time-to-market.