The world keeps spinning, I keep reading...
- On the various ways of creating large files in NTFS
Another option is to make the file sparse. I refer you to the remarks I made some time ago on the pros and cons of this technique. One thing to note is that when a file is sparse, the virtual-zero parts do not have physical disk space assigned to them. Consequently, it's possible for a WriteFile into a previously virtual-zero section of the file may fail with an ERROR_DISK_QUOTA_EXCEEDED error.
- Trash Day: Coordinating Garbage Collection in Distributed Systems
In this paper, we show that distributed applications suffer from each node’s language runtime system making GC-related decisions independently. We first demonstrate this problem on two widely-used systems (Apache Spark and Apache Cassandra). We then propose solving this problem using a Holistic Runtime System, a distributed language runtime that collectively manages runtime services across multiple nodes.
- Inside NGINX: How We Designed for Performance & Scale
NGINX scales very well to support hundreds of thousands of connections per worker process. Each new connection creates another file descriptor and consumes a small amount of additional memory in the worker process. There is very little additional overhead per connection. NGINX processes can remain pinned to CPUs. Context switches are relatively infrequent and occur when there is no work to be done.
In the blocking, connection-per-process approach, each connection requires a large amount of additional resources and overhead, and context switches (swapping from one process to another) are very frequent.
- The WTF economy is transforming how we do business
What is the future when more and more work can be done by intelligent machines instead of people, or only done by people in partnership with those machines? What happens to workers, and what happens to the companies that depend on their purchasing power? What’s the future of business when technology-enabled networks and marketplaces are better at deploying talent than traditional companies? What’s the future of education when on-demand learning outperforms traditional universities in keeping skills up to date?
- Monitoring 101: Collecting the right data
For each resource in your system, try to collect metrics that cover four key areas:
- utilization is the percentage of time that the resource is busy, or the percentage of the resource’s capacity that is in use.
- saturation is a measure of the amount of requested work that the resource cannot yet service, often queued.
- errors represent internal errors that may not be observable in the work the resource produces.
- availability represents the percentage of time that the resource responded to requests. This metric is only well-defined for resources that can be actively and regularly checked for availability.
- Defining a High Performance Team: It’s not just about Structure
Flattened structure doesn’t mean no managers, or no hierarchy of responsibility. It more means that the leaders with more responsibility share openly and include people. This is what flattens the structure.