We are thrilled to announce the release of Kong Ingress Controller 0.6! This release builds on the previous releases and unlocks integrations and features, including the Admission Controller, integration with Kuma and Istio, and support for Kustomize native configuration management.
As outlined in a previous article on security challenges for microservices, DevOps are getting more widely distributed, spread thin, and forced to plan for higher levels of interactivity as well as evolving national security “backdoor” measures. Microservices, born from a still-emerging DevOps laboratory environment, can be deployed anywhere: on-prem, in the public cloud, or a hybrid implementation.
We are excited to announce the release of a new open source project, Kuma – a modern, universal control plane for service mesh! Kuma is based on Envoy, a powerful proxy designed for cloud native applications. Envoy has become the de-facto industry sidecar proxy, with service mesh becoming an important implementation in the cloud native ecosystem as monitoring, security and reliability become increasingly important for microservice applications at scale.
With the 1.3 release, Kong is now able to natively manage and proxy gRPC services. In this blog post, we’ll explain what gRPC is and how to manage your gRPC services with Kong.
Service mesh is redefining the way we think about security, reliability, and observability when it comes to service-to-service communication. In a previous blog post about service mesh, we took a deep dive into our definition of this new pattern for inter-service communication. Today, we’re going to take you through how to use Istio, an open source cloud native service mesh for connecting and securing east-west traffic.
Today, we are excited to announce the release of Kong 1.3! Our engineering team and awesome community has contributed numerous features and improvements to this release. Based on the success of the 1.2 release, Kong 1.3 is the first version of Kong that natively supports gRPC proxying, upstream mutual TLS authentication, along with a bunch of new features and performance improvements.
This is part three in a series discussing the metrics pipeline powering Kong Cloud. In previous posts in this series, we’ve discussed how Kong Cloud collects, ships, and stores high volumes of metrics and time-series data. We’ve described the difference between push and pull models of collecting metrics data, and looked at the benefits and drawbacks of each from a manageability and performance perspective.
When a data breach occurs involving a cloud service, the impulsive reaction is to denounce using the cloud (at least for sensitive information). Since cloud security is not widely understood, it may be difficult to delineate it in the context of more general information security.
