Industrial insight and articles from Winder.AI, focusing on the topic Cloud Native
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Fri May 4, 2018, by Phil Winder, in Data Science, Cloud Native
Following the Cloud Native best practices of immutability, automation and provenance will serve you well in a CNDS project. But working with data brings its own subtle challenges around these themes.
Thu May 3, 2018, by Phil Winder, in Data Science, Cloud Native
Technology choices in data-driven products are, as you would expect, largely directed by the type and amount of data. The first and most crucial decision to make is whether the data will be processed in a batch or streaming fashion.
Wed May 2, 2018, by Phil Winder, in Data Science, Cloud Native, Strategy
Data Science has become an important part of any business because it provides a competitive advantage. Very early on, Amazon’s data on book purchases allowed them to deliver personalised recommendations whilst customers were browsing their site. Their main competitor in the US at the time was Borders, who mainly operated in physical stores. This physicality prevented them from seamlessly providing customers with personalised recommendations [1]. This example highlights how strategic business decisions and data science are inextricably linked.
Tue Apr 3, 2018, by Phil Winder, in Cloud Native
A current project required a list of Amazon Machine Images (AMIs) for all regions for use in terraform. I couldn’t find a script to do this for me, so here you will find one that uses the aws cli, jq and a bit of Bash.
Mon Dec 4, 2017, by Phil Winder, in Cloud Native
https://prometheus.io is an open source time series database that focuses on capturing measurements and exposing them via an API. I love Prometheus because it it so simple; it’s minimalism is its greatest feature. It achieves this by pulling metrics from instrumented applications, not pulling like many of its competitors. In other words Prometheus “scrapes” the metrics from the application.
This means that it works very well in a distributed, cloud-native environment. All of the services are unburdened by load on the monitoring system. This has knock on effects meaning that HA is supported through simple duplication and scaling is supported through segmentation.
Thu Nov 30, 2017, by Phil Winder, in Cloud Native
What do you mean by monitoring? Why do you need it? What are the real needs and are you monitoring them? Ask yourself these questions. Can you answer them? If not, you’re probably doing monitoring wrong.
This post asks the basic question. What is monitoring? How does it compare to logging and tracing? Let’s find out.
Thu Jul 6, 2017, in Cloud Native, Talk
Abstract In this talk, you will discover a reference microservices architecture – the sock shop – which we will abuse in order to investigate microservice security on the Kubernetes orchestrator and Weave Net, a software-defined network. Despite covering a range of topics, it will focus on the demonstration of two key areas: network policy and secure containers. Objective: You will learn how to secure containers and improve network security through the use of a software defined network.
Wed Jun 21, 2017, by phil-winder, in Cloud Native
Cloud-Native, a collection of tools and best practices, disrupts the ideas behind traditional software development. I am a firm believer of the core concepts, which include visibility, repeatability, resiliency and robustness.
The idea begins in 2015 when the Linux Foundation formed the Cloud-Native Computing Foundation. The idea was to collect the tools and processes that are often employed to develop cloud-based software.
However, the result was a collection of best practices which extend well beyond the realms of the cloud. This post introduces the essential components: DevOps, continuous delivery, microservices and containers.
Mon Jun 12, 2017, in Cloud Native, Data Science, Talk
Abstract The proliferation of Data Science is largely due to: ubiquitous data, increasing computational power and industry acceptance that solutions are an asset. Data Science applications are no longer a simple dataset on a single laptop. In a recent project, we help develop a novel cloud-native machine learning service. It is unique in that problems are packaged as containers and submitted to the cloud for processing. This enables users to distribute and scale their models easily.
Wed May 17, 2017, in Cloud Native, Talk
Abstract In this talk, you will discover a reference microservices architecture – the sock shop – which we will abuse in order to investigate microservice security on the Kubernetes orchestrator and Weave Net, a software-defined network. Despite covering a range of topics, it will focus on the demonstration of two key areas: network policy and secure containers. Objective: You will learn how to secure containers and improve network security through the use of a software defined network.
