Interesting thoughts on web3, distributed infrastructure / trust, blockchains, NFTs...
internet’s 90-9-1 rule, which is a simple rule of thumb to approximate the number of contributors in internet societies. It basically says that 90% of users in a system are passive consumers of content and don’t post or write almost at all, 9% are sporadic contributors, while 1% are power users and creators.
Bank Python implementations are effectively proprietary forks of the entire Python ecosystem which are in use at many (but not all) of the biggest investment banks. Bank Python differs considerably from the common, or garden-variety Python that most people know and love (or hate).
I've said so far that a lot of data is stored in Barbara. Time to drop a bit of a bombshell: the source code is in Barbara too, not on disk. Remain composed. It's kept in a special Barbara ring called sourcecode.
it's possible to sit down, write a script and get it running in prod within the hour, which is a big deal.
Using simple Python functions, in a source controlled system, is a better middle ground than the modern-day equivalent of J2EE.
One thing I regret about software as a field is how little time is spent learning from existing systems and judging what they did well, or badly. There are only a small number of books discussing, in detail, real systems that exist.
designed for microservices, cloud native and container-based (Docker, K8s, Mesos) architectures. Underlying technology is a distributed tracing system.
- Provide high performance Java agent, no need to CHANGE any application source code.
Only increase extra 10% cpu cost in 5000+ tps application, even when collect all traces. - Manual instrumentation
- As an OpenTracing supported tracer
- Use @Trace annotation for any methods you want to trace.
- Integrate traceId into logs for log4j, log4j2 and logback.
Instant messaging with many features: voice and/or video calls, screen sharing, file sharing, group chat
Encrypted, open-source
"Tox has no central servers that can be raided, shut down, or forced to turn over data — the network is made up of its users"
A Comprehensive study of Convergent and Commutative Replicated Data Types (CRDT) | the morning paper
A comprehensive study of Convergent and Commutative Replicated Data Types - Shapiro et al. 2011 This is the third of five Desert Island Paper choices from Jonas Bonér, and it continues the theme of avoiding coordination overhead in a principled manner whenever you can. As we saw yesterday, there are trade-offs between consistency, failure tolerance,…
Want to learn how to write faster and more efficient programs for Apache Spark? Two Spark experts from Databricks, Vida Ha and Holden Karau, provide some perf…
services-engineering - A reading list for services engineering, with a focus on cloud infrastructure services
conductor - A framework for testing distributed systems
Getting Started with Spark (in Python)
huginn - Build agents that monitor and act on your behalf. Your agents are standing by!
Tips for speed up your algorithm in the CUDA programming
Partie 1 - Introduction aux topologies, mécanismes et API Par principe les traitements par batchs sont trop lents et la vision qu’ils nous donnent de nos données est dépassée de la