A lot of enterprises are evolving their monolithic applications into microservices architectures. In this pattern, applications are composed of fine-grained services that communicate via APIs. Microservices promise, faster development, innovation, cloud scaling, better infrastructure optimization—and happier developers. No wonder this architecture gets so much attention.
In the current microservices DevOps environment, there are tough new and evolving challenges for developers and teams to consider on top of the more traditional ones. From worsening versions of already common threats to new-generation evolving threats, new perspectives are required on securing microservices. These new perspectives may not be intuitive for many otherwise sophisticated DevOps and data teams.
As we continue to expand across new industries and regions, we’re excited to share Cargill’s digital transformation story and how it turned to Kong Enterprise to create a unified API platform across existing legacy and newer cloud native systems. We talked to Jason Walker, senior enterprise architect at Cargill, about their journey to microservices. What was the driver for Cargill’s move to microservices?
Microservices are a type of architectural style for building software that has been gaining popularity. The concept was first introduced at a tech conference in 2011 and has been adopted by many Agile enterprises such as Netflix, Amazon, Uber, SoundCloud, Groupon, eBay, to name a few. So, what are microservices? What are the benefits of microservices? And why are so many large enterprises have been implementing this method into their DevOps and continuous testing strategies?
The cloud native paradigm for application development has come to consist of microservices architecture, containerized services, orchestration, and distributed management. Many companies are already on this journey, with varying degrees of success. To be successful in developing cloud native applications, it’s important to craft and implement the right strategy. Let’s examine a number of important elements that must be part of a viable cloud native development strategy.
Today, we have some exciting news! We’re announcing our $43 million Series C round, led by Index Ventures and our board member Mike Volpi, with participation from existing investors Andreessen Horowitz (Martin Casado) and Charles Rivers Ventures (Devdutt Yellurkar), as well as new strategic investors GGV Capital and World Innovation Lab (WiL).
Today, we’re thrilled to announce the release of Kong 1.1! Building on the release of support for service mesh in Kong 1.0 last September, our engineering teams and community have been hard at work on this latest iteration of our open source offering. With new Declarative Config and DB-less deployment capabilities, as well as numerous small improvements and fixes, Kong 1.1 is one of our most exciting releases to date!
This post is the last in a three-part series about deploying Kong as a service mesh. The first post discussed how we define the term “service mesh” here at Kong, and the second post explained the architectural pattern used to deploy Kong as a mesh. In this post, we will talk about the new features and configuration options we added to give Kong its mesh capabilities.
In the modern SaaS world, observability is key to running software reliability, managing risks and deriving business value out of the code that you’re shipping. To measure how your service is performing, you record Service Level Indicators (SLIs) or metrics, and alert whenever performance, correctness or availability is affected.
API Fortress is a continuous testing platform for APIs. We’ve been a friend to Kong since the beginning. In this guest blog post, we explain how our company uses Kong to facilitate the process of virtualizing APIs.
