Archives (2008 - 2023)

"KubeSquash is a tool for live debugging of microservices running on Kubernetes. By attaching modern debuggers to your microservices application, KubeSquash gives you the full strength of live debugging : getting/setting the value of variables, adding pauses and sleeps in certain portions of the code, forcing the execution of specific code paths, etc.

KubeSquash is extremely easy to launch, and requires No server. Its user interface is dead simple: invoke with a single command ksquash, target the desired pod, and the debugging session is initiated automatically with zero configuration or effort."

"This tutorial walks you through setting up Kubernetes the hard way. This guide is not for people looking for a fully automated command to bring up a Kubernetes cluster. If that's you then check out Google Kubernetes Engine, or the Getting Started Guides.

Kubernetes The Hard Way is optimized for learning, which means taking the long route to ensure you understand each task required to bootstrap a Kubernetes cluster."

"Vitess is a database solution for deploying, scaling and managing large clusters of MySQL instances. It's architected to run as effectively in a public or private cloud architecture as it does on dedicated hardware. It combines and extends many important MySQL features with the scalability of a NoSQL database. Vitess can help you with the following problems:

Scaling a MySQL database by allowing you to shard it, while keeping application changes to a minimum.
Migrating from baremetal to a private or public cloud.
Deploying and managing a large number of MySQL instances.

Vitess includes compliant JDBC and Go database drivers using a native query protocol. Additionally, it implements the MySQL server protocol which is compatible with virtually any other language.

Vitess has been serving all YouTube database traffic since 2011, and has now been adopted by many enterprises for their production needs."

"Docker Inc. express a preference that container labels should be namespaced. Label Schema is a community project to provide a shared namespace for use by multiple tools, specifically org.label-schema.

By providing a shared and community owned namespace we aim to:

Avoid duplication in cases where the same information is needed in multiple labels

Encourage the use of labels, both by image creators and by tool builders which might consume them

Codify good community practice in a way that is easy to consume and keep up-to-date with"

"The BFG is a simpler, faster alternative to git-filter-branch for cleansing bad data out of your Git repository history:

Removing Crazy Big Files Removing Passwords, Credentials & other Private data"

"The original intent of the CNCF Serverless Working Group was to explore the intersection of cloud native and serverless technology. As a result of that work the following artifacts were produced:

A Whitepaper Landscape"

"PORTAINER IS AN OPEN-SOURCE LIGHTWEIGHT MANAGEMENT UI WHICH ALLOWS YOU TO EASILY MANAGE YOUR DOCKER HOSTS OR SWARM CLUSTERS

AVAILABLE ON LINUX, WINDOWS & OSX"

"Nowadays, Microservices is one of the most popular buzz-word in the field of software architecture. There are quite a lot of learning materials on the fundamentals and the benefits of microservices, but there are very few resources on how you can use microservices in the real world enterprise scenarios.

In this post, I’m planning to cover the key architectural concepts of the Microservices Architecture(MSA) and how you can use those architectural principles in practice.

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"Jaeger, inspired by Dapper and OpenZipkin, is a distributed tracing system released as open source by Uber Technologies. It can be used for monitoring microservice-based architectures:

Distributed context propagation Distributed transaction monitoring Root cause analysis Service dependency analysis Performance / latency optimization"

"Zipkin is a distributed tracing system. It helps gather timing data needed to troubleshoot latency problems in microservice architectures. It manages both the collection and lookup of this data. Zipkin’s design is based on the Google Dapper paper.

Applications are instrumented to report timing data to Zipkin. The Zipkin UI also presents a Dependency diagram showing how many traced requests went through each application. If you are troubleshooting latency problems or errors, you can filter or sort all traces based on the application, length of trace, annotation, or timestamp. Once you select a trace, you can see the percentage of the total trace time each span takes which allows you to identify the problem application."