On December 9th 2021, a high severity vulnerability in Log4j 2 was published as CVE-2021-44228, AKA Log4Shell. Any JVM-based project using log4j-core with a version <= 2.14.1 is affected. See this Cloudflare blog post for a detailed explanation.
Aerospike Developer Blog
Curated articles about application development and operations using Aerospike
Serverless compute architectural pattern allows you to run code without provisioning or managing servers, creating workload-aware cluster scaling logic, maintaining event integrations, or managing runtimes. AWS Lambda and Google Cloud Functions in GCP are important services that are based on this pattern and can be extended to support event streaming pipelines. AWS Lambda is integrated with the majority of the services of the AWS big data ecosystem. Likewise for the integration of Google Cloud Functions with Google Cloud Platform. This presents an opportunity for you to integrate the Aerospike database with the broader cloud ecosystem, in order to build efficient cloud-native streaming pipelines.
While working with databases or data replication solutions, you must have come across the term Change Data Capture, popularly abbreviated as CDC. It is a data pattern that informs external systems when records are inserted, modified, or deleted in a database. It is extensively used for building event stream processing systems (ESP).
The soon-to-be-released Aerospike 5.7 includes the first milestone of a rewrite of Secondary Indexes. Among these new features are indexes which are 60% more memory efficient, faster queries, and a superior new garbage collection system. You can get a more comprehensive launch overview by reading the blog post Aerospike Database 5.7: Operational, Query, and Security Enhancements.
Rack awareness — in the literal sense
The following article describes running a 3 nodes Aerospike cluster in Docker. After configuration and running the cluster we will then review the distribution of secondary partitions across the cluster. To acheive all of this we use a feature of Aerospike known as rack aware.
credit: Joseph Barrientos( Unsplash)
In this article we’ll cover the basics of Aerospike’s Kubernetes operator and how we went about several engineering challenges we faced. We’ll then discuss the capabilities of the Aerospike Kubernetes Operator, and go over 3 engineering challenges we faced when developing it.
Aerospike is a high performance, distributed, scalable, key value database. Aerospike leverages SSD technology to achieve levels of throughput and low latency exceeding even those obtained with in memory products. This allows hardware costs to be reduced 10x or more and data density to be increased 10x or more versus any other high performance solution.