<feed xmlns="http://www.w3.org/2005/Atom"> <id>/</id><title>Malike St</title><subtitle>tech stuff</subtitle> <updated>2025-04-12T18:30:25+02:00</updated> <author> <name>Malike St</name> <uri>/</uri> </author><link rel="self" type="application/atom+xml" href="/feed.xml"/><link rel="alternate" type="text/html" hreflang="en" href="/"/> <generator uri="https://jekyllrb.com/" version="4.2.2">Jekyll</generator> <rights> © 2025 Malike St </rights> <icon>/assets/img/favicons/favicon.ico</icon> <logo>/assets/img/favicons/favicon-96x96.png</logo> <entry><title>Predicting Customer Purchases: A Beginner's Guide to E-Commerce Data Science</title><link href="/posts/Predicting-Customer-Purchases-Beginners-Guide/" rel="alternate" type="text/html" title="Predicting Customer Purchases: A Beginner's Guide to E-Commerce Data Science" /><published>2025-04-02T00:00:00+02:00</published> <updated>2025-04-12T18:29:57+02:00</updated> <id>/posts/Predicting-Customer-Purchases-Beginners-Guide/</id> <content src="/posts/Predicting-Customer-Purchases-Beginners-Guide/" /> <author> <name>malike</name> </author> <category term="python" /> <category term="data-science" /> <category term="ai" /> <category term="machine-learning" /> <summary> Have you ever wondered how online stores seem to know exactly what you want to buy? Or how they manage to show you products you’re likely interested in? The secret lies in a field called predictive analytics, which is basically using past data to make educated guesses about the future. In this blog post, I’ll walk you through a real-world example of how data science helps an online store under... </summary> </entry> <entry><title>Custom Kubernetes Operators in Golang with OperatorSDK and Kubebuilder</title><link href="/posts/Custom-Operator-With-Operator-SDK/" rel="alternate" type="text/html" title="Custom Kubernetes Operators in Golang with OperatorSDK and Kubebuilder" /><published>2023-01-06T00:00:00+01:00</published> <updated>2023-01-06T00:00:00+01:00</updated> <id>/posts/Custom-Operator-With-Operator-SDK/</id> <content src="/posts/Custom-Operator-With-Operator-SDK/" /> <author> <name>malike</name> </author> <category term="devops" /> <category term="sre" /> <category term="dev" /> <summary> Kubernetes Operators Kubernetes Operators are patterns that help us extend the behavior of the cluster. Operators enable us to view an application deployed on Kubernetes as one item. That is your application can composed of a Pod, a Service, a ConfigMap a Deployement etc but you get to manage it as one item and have a much better control of their lifecycle. The lifecycle includes but not limit... </summary> </entry> <entry><title>Observability Stack with Grafana Loki Tempo and Prometheus</title><link href="/posts/Obersevability-Stack-with-Grafana-Loki-And-Tempo/" rel="alternate" type="text/html" title="Observability Stack with Grafana Loki Tempo and Prometheus" /><published>2022-04-20T00:00:00+02:00</published> <updated>2024-02-17T16:30:52+01:00</updated> <id>/posts/Obersevability-Stack-with-Grafana-Loki-And-Tempo/</id> <content src="/posts/Obersevability-Stack-with-Grafana-Loki-And-Tempo/" /> <author> <name>malike</name> </author> <category term="devops" /> <category term="sre" /> <category term="distributed" /> <category term="observability" /> <category term="monitoring" /> <summary> Observability Observability is tooling or a technical solution that allows teams to actively debug their system. Observability is based on exploring properties and patterns not defined in advance. This definitaion somewhat summarizes what Observability means. For your software system to be observable, the telemetry collected and how its process helps diagnose and investigate better. Observab... </summary> </entry> <entry><title>Apache Kafka on Kubernetes with Strimzi Operator</title><link href="/posts/Apache-Kafka-On-Kubernetes-Strimzi-Operator/" rel="alternate" type="text/html" title="Apache Kafka on Kubernetes with Strimzi Operator" /><published>2022-03-05T00:00:00+01:00</published> <updated>2023-02-16T13:15:41+01:00</updated> <id>/posts/Apache-Kafka-On-Kubernetes-Strimzi-Operator/</id> <content src="/posts/Apache-Kafka-On-Kubernetes-Strimzi-Operator/" /> <author> <name>malike</name> </author> <category term="distributed" /> <category term="devops" /> <category term="sre" /> <summary> Strimzi is a kubernetes operator that enables a way to run an Apache Kafka cluster on Kubernetes in various deployment configurations with simple configurations. Meaning, we easily manage the lifecycle of our kafka deployment. The details on how this is done can be found here but to summarize: There are 4 main operators: 1. Cluster Operator: Deploys and manages Apache Kafka clusters, Kafka C... </summary> </entry> <entry><title>Taking DataStax Enterprise for a Spin on Kubernetes</title><link href="/posts/Cassandra-DSE-On-Kubernetes-With-Cass-Operator/" rel="alternate" type="text/html" title="Taking DataStax Enterprise for a Spin on Kubernetes" /><published>2022-02-09T00:00:00+01:00</published> <updated>2022-02-09T00:00:00+01:00</updated> <id>/posts/Cassandra-DSE-On-Kubernetes-With-Cass-Operator/</id> <content src="/posts/Cassandra-DSE-On-Kubernetes-With-Cass-Operator/" /> <author> <name>malike</name> </author> <category term="distributed" /> <category term="devops" /> <category term="sre" /> <summary> 1. Introduction DataStax Enterprise (DSE) version 6.8 a hybrid cloud, that is can run on-premises or across regions on the cloud to give all the capabilities of Apache Cassandra with enterprise tooling and expert support. In this particular concept it will be deployed on AWS. Specifically EKS. 2. Setting Up DSE Cluster on EKS To set up a simple DSE cluster. DSE version : DSE 6.8.4 EKS... </summary> </entry> </feed>
