THE FUTURE OF CLOUD PROVIDERS IN KUBERNETES
Approximately 9 months ago, the Kubernetes community agreed to form the Cloud Provider Special Interest Group (SIG). The justification was to have a single governing SIG to own and shape the integration points between Kubernetes and the many cloud providers it supported. A lot has been in motion since then and we’re here to share with you what has been accomplished so far and what we hope to see in the future.
Read moreDETECTING MALARIA WITH DEEP LEARNING
Artificial intelligence (AI) and open source tools, technologies, and frameworks are a powerful combination for improving society. ‘Health is wealth’ is perhaps a cliche, yet it’s very accurate! In this article, we will examine how AI can be leveraged for detecting the deadly disease malaria with a low-cost, effective, and accurate open source deep learning solution. While I am neither a doctor nor a healthcare researcher and I’m nowhere near as qualified as they are, I am interested in applying AI to healthcare research. My intent in this article is to showcase how AI and open source solutions can help malaria detection and reduce manual labor. Thanks to the power of Python and deep learning frameworks like TensorFlow, we can build robust, scalable, and effective deep learning solutions.
Read morePOD PRIORITY AND PREEMPTION IN KUBERNETES
Kubernetes is well-known for running scalable workloads. It scales your workloads based on their resource usage. When a workload is scaled up, more instances of the application get created. When the application is critical for your product, you want to make sure that these new instances are scheduled even when your cluster is under resource pressure. One obvious solution to this problem is to over-provision your cluster resources to have some amount of slack resources available for scale-up situations. This approach often works, but costs more as you would have to pay for the resources that are idle most of the time.
Read moreKUBERNETES INGRESS PAST, PRESENT, AND FUTURE
This post was inspired by listening to the February 19, 2019, Kubernetes Podcast, “Ingress, with Tim Hockin.” The Kubernetes Podcast is turning out to be a very well done podcast overall, and well worth the listen. In the Ingress episode, the podcasters interview Tim Hockin who’s one of the original Kubernetes co-founders, a team lead on the Kubernetes predecessor Borg/Omega, and is still very active within the Kubernetes community such as chairing the Kubernetes Network Special Interest Group that currently own the Ingress resource specification.
Read moreCLOUD NATIVE COMPUTING FOUNDATION ANNOUNCES FLUENTD GRADUATION
SAN FRANCISCO, Calif. – April 11, 2019 – The Cloud Native Computing Foundation® (CNCF®), which sustains open source technologies like Kubernetes® and Prometheus™, today announced that Fluentd is its sixth project to graduate, following Kubernetes, Prometheus, Envoy, CoreDNS and containerd. To move from the maturity level of incubation to graduation, projects must demonstrate thriving adoption, a documented, structured governance process, and a strong commitment to community sustainability and inclusivity. Fluentd was created in 2011 by Sadayuki “Sada” Furuhashi, co-founder of Treasure Data, Inc., as an open source data collector for building a Unified Logging Layer, which unifies the data collection and consumption for a better use and understanding of data.
Read moreSECRETS OF A NRQL WIZARD
New Relic’s Kevin Scaldeferri shares insider tips and tricks on how to use New Relic Query Language (NRQL) to understand and use your application data in powerful new ways. Source: newrelic.com
UNTOLD HISTORY OF AI: WHEN CHARLES BABBAGE PLAYED CHESS WITH THE ORIGINAL MECHANICAL TURK
The famed 19th-century engineer may have been inspired by an early example of AI chicanery and hype In this six-part series, we explore that human history of AI—how innovators, thinkers, workers, and sometimes hucksters have created algorithms that can replicate human thought and behavior (or at least appear to). While itcan be exciting to be swept up by the ideaof superintelligent computers that have no need for human input, the true history of smart machines shows that our AI is only as good as we are. In the year 1770, at the court of the Austrian empress Maria Theresa, an inventor named Wolfgang von Kempelen presented a chess-playing machine.
Read moreSONIC, THE LIGHTWEIGHT SEARCH ENGINE BACKEND IS AN ALTERNATIVE TO ELASTICSEARCH
Looking for a lightweight alternative search backend to Elasticsearch? Sonic is a search backend written in Rust. It aims for a low CPU footprint and uses around 30 MB of RAM. See its speed benchmarks and its search query features. Find out how to get started. According to the DB-Engines Ranking, Elasticsearch is currently in the top ten database management systems.
Read moreANATOMY OF CVE-2019-5736: A RUNC CONTAINER ESCAPE!
On Monday, February 11, CVE-2019-5736 was disclosed. This vulnerability is a flaw in runc, which can be exploited to escape Linux containers launched with Docker, containerd, CRI-O, or any other user of runc. But how does it work? Dive in! Processes interact with the operating system to perform a variety of operations (for example, reading and writing files, taking input, communicating on the network, etc.) via system calls, or syscalls. Syscalls can perform a variety of actions.
Read moreAN ML SHOWDOWN IN SEARCH OF THE BEST TOOL
Ever burgeoning digital data combined with impressive research has lead to a rising interest in Machine Learning or ML, which has further powered a vibrant ecosystem of technologies, frameworks, and libraries in the space. Scikit-learn sees high adoption from the tech community. The most probable reason is a powerful Python interface that allows tweaking of models across multiple parameters. MLlib and H2O should be considered when working with Spark. Spark does come with MLlib and has a higher level wrapper called SparkML that supports the same.
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