OPTIMIZING STRAGGLERS IN GOOGLE CLOUD DATAFLOW

I’m currently bench-marking Flink against Google Cloud Dataflow using the same Apache Beam pipeline for quantitative analytics. One observation I’ve seen with Flink is the tail latency associated with some shards. 

WHY CRYPTOCURRENCY MATTERS

The point of cryptocurrency is to provide a decentralized, secure, and efficient way to transfer value. Cryptocurrencies are not issued by any central authority, such as a government or bank, and they are not backed by any physical asset. Instead, they are created and maintained by a network of computers that are running a special software program. This software program is designed to verify and record cryptocurrency transactions, and to prevent fraud.

OPTIMIZING LATENCY IN MICROSERVICES

Great talk by by Peter Lawrey regarding latency in micro-services.  https://www.infoq.com/presentations/latency-sensitive-microservices/

APACHE BEAM VS FLINK: CHOOSING THE RIGHT FRAMEWORK

Apache Beam and Apache Flink are both powerful open-source frameworks for distributed data processing, enabling efficient handling of massive datasets. While they share the common goal of parallel data processing, they differ significantly in their architecture, programming model, and execution strategies. Understanding these differences is crucial for choosing the right tool for your specific needs. This article will help you navigate the decision-making process.

SCALING RISK ANALYTICS ON GOOGLE CLOUD

This one is better explained with the presentation below. If you want to learn how to run quantitative analytics at scale, it’s well worth a watch.

DEVSECOPS VS SRE: KEY DIFFERENCES EXPLAINED

DevSecOps and SRE are two complementary approaches to ensuring the reliability and security of software systems.

BUILDING HIGH-PERFORMANCE TEAMS

Here are some tips on how to build high-performance teams:

CASH EQUITIES: ORDER MANAGEMENT SYSTEM

Built and maintained a client and market side booking service, off order book trade reporting engine and trade manager/repository

JAMES MICKENS: LEGENDARY DATABASE SYSTEMS TALK

Still one of the best talks I’ve ever seen https://vimeo.com/95066828

WHEN TECHNICAL DEBT COSTS $440 MILLION

I’ve always hated the phrase “technical debt” as it can lead to items being banished to a backlog that are never addressed. For example, Knight Capital recently blamed a “technology issue” for a $440 million trading loss.