This article is a step by step guide of how I deployed a Prefect Server with a Fargate ECS Cluster using Docker Storage on a private registry. A few articles covered deployment with Prefect Cloud and different combinations of runners and storage. As I ran through a few issues when deploying this specific architecture, I decided to detail the steps in this article. You can choose to use different Agents and Storage options, this article is only a base guideline to the many options of Prefect. Although I will not detail Prefect and AWS concepts, you will find references to relevant documentation to help you.

Analysis of large observational data sets generated by a reactive system is a common challenge in debugging system failures and determining their root cause. One of the major problems is that these observational data suffer from survivorship bias. Examples include analyzing traffic logs from networks, and simulation logs from circuit design. In such applications, users want to detect non-spurious correlations from observational data and obtain actionable insights about them. In this paper, we introduce log to Neuro-symbolic (Log2NS), a framework that combines probabilistic analysis from machine learning (ML) techniques on observational data with certainties derived from symbolic reasoning on an underlying formal model. We apply the proposed framework to network traffic debugging by employing the following steps. To detect patterns in network logs, we first generate global embedding vector representations of entities such as IP addresses, ports, and applications. Next, we represent large log flow entries as clusters that make it easier for the user to visualize and detect interesting scenarios that will be further analyzed. To generalize these patterns, Log2NS provides an ability to query from static logs and correlation engines for positive instances, as well as formal reasoning for negative and unseen instances. By combining the strengths of deep learning and symbolic methods, Log2NS provides a very powerful reasoning and debugging tool for log-based data. Empirical evaluations on a real internal data set demonstrate the capabilities of Log2NS.

Increasing the penetration of variable generation has a substantial effect on the operational reliability of power systems. The higher level of uncertainty that stems from this variability makes it more difficult to determine whether a given operating condition will be secure or insecure. Data-driven techniques provide a promising way to identify security rules that can be embedded in economic dispatch model to keep power system operating states secure. This paper proposes using a sparse weighted oblique decision tree to learn accurate, understandable, and embeddable security rules that are linear and can be extracted as sparse matrices using a recursive algorithm. These matrices can then be easily embedded as security constraints in power system economic dispatch calculations using the Big-M method. Tests on several large datasets with high renewable energy penetration demonstrate the effectiveness of the proposed method. In particular, the sparse weighted oblique decision tree outperforms the state-of-art weighted oblique decision tree while keeping the security rules simple. When embedded in the economic dispatch, these rules significantly increase the percentage of secure states and reduce the average solution time.

DataSunrise, in their own words: DataSunrise is a database security software company that offers a breadth of security solutions, including data masking (dynamic and static masking), activity monitoring, database firewalls, and sensitive data discovery for various databases. The goal is to protect databases against external and internal threats and vulnerabilities. Customers often choose DataSunrise Database Security because it gives them unified control and a single-user experience when protecting different database engines that run on AWS, including Amazon Redshift, Amazon Aurora, all Amazon RDS database engines, Amazon DynamoDB, and Amazon Athena, among others. DataSunrise Security Suite is a set of tools that can protect and audit PII data in Amazon Redshift. DataSunrise offers passive security with data auditing in addition to active data and database security.

WASHINGTON/TAIPEI – New security measures including stricter passenger screening take effect on Thursday on all U.S.-bound flights to comply with government requirements designed to avoid an in-cabin ban on laptops, airlines said. Airlines contacted by Reuters said the new measures could include short security interviews with passengers at check-in or the boarding gate, sparking concerns over flight delays and extended processing time. They will affect 325,000 airline passengers on about 2,000 commercial flights arriving daily in the United States, on 180 airlines from 280 airports in 105 countries. The United States announced the new rules in June to end its restrictions on carry-on electronic devices on planes coming from 10 airports in eight countries in the Middle East and North Africa in response to unspecified security threats. Those restrictions were lifted in July, but the Trump administration said it could reimpose measures on a case by case basis if airlines and airports did not boost security.

WASHINGTON – The U.S. Transportation Security Administration (TSA) said Wednesday it will impose new stricter security rules requiring airline travelers to remove all electronic items larger than mobile phones, including tablets, e-readers and video game consoles, from carry-on baggage for screening. Prior rules required only laptops to be removed for separate screening. The new rules significantly expand the number of electronic devices that will need to be removed for screening and help government employees get a clearer view during X-ray screening. TSA said the new rules have been in place in a pilot project at 10 U.S. airports, including Detroit, Los Angeles, Boston and Phoenix, and will expand to all U.S. airports in the months ahead. The new enhanced security rules at U.S. airports only apply at standard security lanes -- not at lanes for travelers who are in "pre-check" programs.