For financial services organizations, onboarding institutional clients is challenging. The process is complex and made even more so by increasingly distributed and decentralized work, which compromises visibility and transparency and makes connectedness difficult. It also introduces a high degree of risk, as manual processes expose organizations to errors and inconsistencies.

Over the past few months, I’ve been redesigning and writing StatusCake’s SSL monitoring feature from Node to Go. This blog post describes one of the more subtle challenges we came across to help you master it if you find yourself with it too! Writing a Go client that fetches an SSL certificate isn’t a new problem. A common approach is to use a http.Client. This limits you to just certificates served over HTTPS, when technically anything running TLS can have a certificate.

Customers today expect feature-reach and user-friendly access to technology that makes their lives easier. They expect to use this technology to engage with companies anywhere, anytime, and with any device. Organizations must be able to not just meet, but exceed, these expectations. Failing to do so could result in lost revenue as customers move on to competitors.

Unlike a traditional monolithic approach, in which all components form an inseparable entity, microservices work in synergy to accomplish the same tasks while being separate. Each of these components or processes is a microservice. Granular and lightweight, this type of software development allows a similar process to be used in multiple applications. This is a key element in optimizing application development for a cloud-native model.

If your organization is using multi-tenant big data clusters (and everyone should be), do you know the usage and cost efficiency of resources in the cluster by tenants? A chargeback or showback model allows IT to determine costs and resource usage by the actual analytic users in the multi-tenant cluster, instead of attributing those to the platform (“overhead’) or IT department. This allows you to know the individual costs per tenant and set limits in order to control overall costs.

Cloudera Data Platform (CDP) supports access controls on tables and columns, as well as on files and directories via Apache Ranger since its first release. It is common to have different workloads using the same data – some require authorizations at the table level (Apache Hive queries) and others at the underlying files (Apache Spark jobs). Unfortunately, in such instances you would have to create and maintain separate Ranger policies for both Hive and HDFS, that correspond to each other.

The #descendants method is part of Rails. It returns all subclasses that inherit from a given class. In this article, Jonathan Miles shows us how to use this method and how it's implemented. It's a great lesson in the ins and outs of Ruby's object model.

One of the things that’s quite interesting about service mesh is that it has not been a very well-defined category for a very long time. Service mesh is not a means to an end. By looking at its adoption, we’ve been seeing a refocus on the end use case that service mesh allows us to enable. Some are around observability while others are around security and trust – being able to provide that identity to all of our services.

In our first episode of Kongcast, I had the pleasure of speaking with Liz Fong-Jones, principal developer advocate at Honeycomb, about the concept of error budgets for service level objectives (SLOs) and how to accelerate software delivery with observability. Check out the transcript and video from our conversation below, and be sure to subscribe to get email alerts for the latest new episodes.

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