In the previous three parts of our OpenTracing series, we provided an Overview of OpenTracing, explaining what OpenTracing is and does, how it works and what it aims to achieve, we looked at Zipkin – a popular open-source distributed tracer and then at Jaeger – a newer open-source distributed tracer developed under the CNCF umbrella. In this blog post – the last part of the OpenTracing series – we will compare Jaeger vs. Zipkin side by side!
Whenever you run a Honeycomb query, you’re directed to the permalink for the results. Returning to this URL always supplies the same data without re-running the query, which is important when sharing links to make sure that everybody is looking at the same thing. However, there may be cases where you want a link not to a specific set of results, but to a set of query parameters which are re-run automatically. Further, you may want to generate these links without relying on the Honeycomb UI.
Let me preface this article with a quick customer story. I was recently talking with the director of operations of a G2000 company and he asked in a nice, but pointed way: “All I want is a SaaS software solution to manage my applications. Why does the architecture of the software matter?”. At Sumo Logic, we couldn’t agree and disagree more.
Azure has an offering for Kubernetes: Azure Kubernetes Service (AKS). In this post, Learn more about AKS and show you two methods you can use it to create a cluster.
While Logz.io provides Kibana — the ELK Stack’s visualization tool — as part of its service, a lot of users have asked us to support Grafana. One of the leading open source visualization tools today, Grafana has some added value when compared to Kibana, especially around visualizing time-series data.
Errors. We all cause them all the time, which can make it difficult to figure out the person or team who should be responsible for fixing individual issues. Time that could be spent resolving an issue is instead spent tracking down who should be handling it and what it’s even about. This is a waste. It balloons time to resolution, often from minutes to hours or sometimes even days.
When we announced support for ingesting AWS Elastic Load Balancer access logs to Honeycomb, one of the first follow-up requests was for us to add support for AWS Application Load Balancer as well (which, alongside the Network Load Balancer, represents ELBv2). Given the list of features that ALB supports, it’s not difficult to see why. Who doesn’t want microservice-friendly path routing, native HTTP/2 support, tight integration with Amazon’s container-related services, and more?
