Imagine a world in which there are only mainframes, and all individuals have are mainframe terminals. Then imagine that personal rights (e.g. to privacy) are violated in many ways by the mainframes…
Dropped packets are a fact of life in networking; there can be any number
of reasons why a packet may not survive the journey to its destination.
Indeed, there are so many ways that a packet can meet its demise that it
can be hard for an administrator to tell why packets are being dropped.
That, in turn, can make life difficult in times when users are complaining
about high packet-loss rates. Starting with 5.17, the kernel is getting
some improved instrumentation that should shed some light on why the kernel
decides route packets into the bit bucket.
With the latest release of Cerbos, we introduced a new experimental query planner API to help address this problem efficiently in a language-agnostic way. This article describes how we designed and developed that API.
At my university, one of our internal software systems allows a professor to submit a revision to a course. The professor might change the content or the objectives of the course. In a university, professors have extensive freedom regarding course content. As long as you reasonably meet the course objectives, you can do whatever you … Continue reading Enforcement by software
Assessing data infrastructure: the Digital Public Goods standard and registry
This is the second in a short series of posts in which I’m sharing my notes and thoughts on a variety of different approaches for assessing data infrastructure and data institutions. The firs…
Goodbye SDLC, Hello SSDF! What is the Secure Software Development Framework?
This is the first article in a five-part series on the recently published NIST 800-218 ‘The Secure Software Development Framework (SSDF): Recommendations for Mitigating the Risk of Software Vulnerabilities’ Although the software development lifecycle (SDLC) has been around for a while, few SDLC models explicitly address software security in detail.
How Machine Learning Can Save You from Observability Overload
#DevOps teams are drowning in metrics, and it’s gotten harder for teams to interpret and take action on them. Machine learning can help sort out the data. #machinelearning #ML #observability
Assessing data infrastructure: the Principles of Open Scholarly Infrastructure
How do we create well-designed, trustworthy, sustainable data infrastructure and institutions? This is a question that I remain deeply interested in. Much of the freelance work I’ve been doin…
Markdown in all its flavors, interpretations, and forks won’t go away. However, it’s important to look at emerging content formats that try to encompass modern needs. In this article, Knut shares his advice against Markdown by looking back on why it was introduced in the first place, and by going through some of the major developments of content on the web.
Under the Lid: How AtomicJar is Reshaping Testcontainers - DevInterrupted
Sergei Egorov, co-founder & CEO of AtomicJar, wanted a way to make integrated testing simpler and easier. Today, Testcontainers powers over a million builds per month.
Managing Time-Series Data in Industrial IoT - The New Stack
Time- series data provides a shared context for sensor readings and becomes the critical fulcrum for processing and understanding Industry 4.0 IoT data.