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Book Review: Developer, Advocate!
Developer, Advocate! is a set of interviews with prominent technologists, covering what drives their interest and enthusiasm in the industry. The brevity of each interview provides direct information and insight that can be read separately at any time, in any order, enabling those with busy schedules to read, put down, and repeat.
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Preparing Entity Framework Core for Static Analysis and Nullable Reference Types
In this article we walk through the process of updating an EF Core 3.1 based DAL to adhere to modern best practices such as TreatWarningsAsErrors, FxCopAnalyzers, and C# 8’s nullable reference types.
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How to Use Redis TimeSeries with Grafana for Real-Time Analytics
In this article, author Roshan Kumar discusses how a purpose-built database like RedisTimeSeries can be used to manage time-series data. He also shows how to visualize this data in a Grafana dashboard.
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Q&A on the Book Real-World Bug Hunting
The book Real-World Bug Hunting by Peter Yaworski is a field guide to finding software vulnerabilities. It explains what ethical hacking is, explores common vulnerability types, explains how to find them, and provides suggestions for reporting bugs while getting paid for doing so.
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Postgres Handles More Than You Think
Thinking about scaling beyond Postgres with a data store like Redis or Elasticsearch? Think again before adopting a complex infrastructure. Postgres can scale for heavy loads and offers powerful features which are not obvious at first sight. For example, it's possible to enable in-memory caching, text search, specialized indexing, and key-value storage. Article
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Azure Data Lake Analytics and U-SQL
In this article, the author shows how to use big data query and processing language U-SQL on Azure Data Lake Analytics platform. U-SQL combines the concepts and constructs both of SQL and C#. It combines the simplicity and declarative nature of SQL with the programmatic power of C# including rich types and expressions.
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Data Analytics in the World of Agility
Is it all about customer-centric business, or is there any data left? Can we integrate data analytics and customer empathy? This article explores how we can move towards a more customer-centric business and what information we require in order to understand the most valuable thing we have: our customer.
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Stream Processing Anomaly Detection Using Yurita Framework
In this article, author Guy Gerson discusses the stream processing anomaly detection framework they developed by PayPal, called Yurita. The framework is based on Spark Structured Streaming.
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Understanding Serverless: Tips and Resources for Building Servicefull Applications
There are still many misconceptions and concerns regarding serverless solutions. Vendor lock-in, tooling, cost management, cold starts, monitoring and the development lifecycle are all hot topics where serverless technologies are concerned. This article shares tips and resources to guide serverless newcomers towards building powerful, flexible and cost-effective serverless applications.
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How to Use Open Source Prometheus to Monitor Applications at Scale
In this article, the author discusses how to collect metrics and achieve anomaly detection from streaming data using Prometheus, Apache Kafka and Apache Cassandra technologies.
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How Do We Think about Transactions in (Cloud) Messaging Systems? An Interview with Udi Dahan.
Do today's cloud-based messaging services have different transactional support than those that preceded it? If so, what are the implications? In this interview with distributed systems expert Udi Dahan, we explores the question.
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Real-Time Data Processing Using Redis Streams and Apache Spark Structured Streaming
Structured Streaming, introduced with Apache Spark 2.0, delivers a SQL-like interface for streaming data. Redis Streams enables Redis to consume, hold and distribute streaming data between multiple producers and consumers. In this article, author Roshan Kumar walks us through how to process streaming data in real time using Redis and Apache Spark Streaming technologies.
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