In my last blog I described how to achieve continuous integration, delivery and deployment of Talend Jobs into Docker containers with Maven and Jenkins. This is a good start for reliably building your containerized jobs, but the journey doesn't end there. The next step to go further with containerized jobs is scheduling, orchestrating and monitoring them.
From personalizing your initial prompt to asking the right questions, here are some proven ways for improving the response rate from your live chat efforts.
In a previous post, we explained how the team at Kong thinks of the term “service mesh.” In this post, we’ll start digging into the workings of Kong deployed as a mesh. We’ll talk about a hypothetical example of the smallest possible deployment of a mesh, with two services talking to each other via two Kong instances – one local to each service.
A 5-step, systematic approach to engaging and influencing your audience.
The service mesh deployment architecture is quickly gaining popularity in the industry. In the strategy, remote procedure calls (RPCs) from one service to another inside of your infrastructure pass through two proxies, one co-located with the originating service, and one at the destination. The local proxy is able to perform a load-balancing role and make decisions about which remote service instance to communicate with, while the remote proxy is able to vet incoming traffic.
As we've taken Yellowfin 8 to market, we've been overwhelmed by the response we've had from media and analysts across the industry. We actually shocked the industry a bit because people didn’t expect an established dashboard vendor to be willing to disrupt themselves with two radical new products.
Where do you start? Our experience based on working with hundreds of clients worldwide, both rapidly growing companies and enterprises, is that the one place to start with any digital transition and data innovation is (drumroll) - Managerial reports.
Jason Walker shares how Cargill is using Kong to transform legacy architecture with a “Cloud first, but not always” approach. Hear why Cargill chose Kong for their API gateway as part of their internal API platform, Capricorn, allowing Jason’s small team to stay nimble while they administer decentralized deployments. In this talk from Kong Summit 2018, Jason shares how Kong routes traffic in Cargill’s Kubernetes cluster.
From augmented intelligence to multi-cloud deployment, here's a look back at our path to innovation in 2018.
In our last blog post in this series, we discussed our journey designing a metrics pipeline for Kong Cloud to ensure the reliability of our SaaS offering. We discussed how we re-architected our production data pipeline using OpenResty to send metrics to Prometheus and saw huge performance gains. We are now able to monitor high traffic volumes in our system using much less compute power, lowering our costs.
