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.

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.

RapidSpike Connect Anything (RCA) is my favourite least used product. We use it for loads of stuff internally, but it often gets overlooked by our customers. But as a developer, whenever I see a slightly obscure API, I can’t resist having a play with it to get the data into RCA, just to prove we can monitor anything.

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!

I come from a world where strategy is best kept secret. Whether it be from a company who has a codename for literally everything, or the competitive culture of playing and coaching D1 athletics, confidentiality became a required skill. Meetings, trainings, code reviews, scouting reports… anything of significance happened behind closed doors. In other words, definitely not open source.

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.

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?

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.

In order to successfully implement continuous testing, DevOps teams need the right mix of tools, people, and processes. Most importantly, they need fast and frequent feedback loops to guide their testing efforts. Learn how this can be implemented.

We’ve all been there — you’re on-call, fast asleep at 3 AM when suddenly, in comes the alerts–in overdrive. Your system is notifying you of some sort of abnormal behavior, but with all the alerts and data coming through, its difficult to figure out what your system is trying to tell you. Is there potential malicious behavior? Did someone write faulty code? Is it an important issue or can it wait? Is it nothing at all?