 Cloud Security and AWS Special Report |
| Sponsored by |  |
|
|
| |
| |
| In this special newsletter we bring you up to date on all the new content and news related to Cloud Security and AWS on InfoQ. We are also maintaining a portal page for this content on InfoQ at: https://www.infoq.com/security. |
|
| |
| |
| Here are the top 10 risks that show up in AWS. Are you making those same mistakes? We bet you are. Download now. Sponsored content |
| |
|
| Top Viewed Content on InfoQ |
|
| Meltdown and Spectre: What They Are and How to Deal with Them (news, Jan 05, 2018) | | A Deeper Dive into Spectre and Meltdown (news, Jan 07, 2018) | | Beyond OAuth2: End to End Microservice Security (presentations, Oct 28, 2017) | | Confusion in the Land of the Serverless (presentations, Nov 12, 2017) | | A 4-Step Guide to Building Continuous Security into Container Deployment (articles, Sep 30, 2017) |
|
| |
| Version 7.0.0 of the seL4 high-assurance microkernel has been released, bringing with it an alternate CMake-based build system with support for out-of-tree builds and interactive configuration. | | The latest version of the container orchestration framework Kubernetes supports GA version of Workloads API, container storage enhancements and Windows support (beta). The Kubernetes team announced the release of version 1.9 last week. This is the fourth and final release this year, and also supports the Custom Resource Definition (CRD) validation. |
|
| Enterprises are innovating and delivering digital services quicker than ever before. To achieve success, security must be in place. Learn how to maintain agility and security with "The Six Essentials for DevOps Team Excellence". Sponsored content |
| |
|
| Gremlin Inc has released Gremlin, a “resilience as a service” SaaS-based platform, which allows organisations to “break things on purpose” and conduct chaos experiments in order to help prevent application downtime before it happens. Gremlin allows the controlled injection of resource, network and state failure to managed infrastructure so that engineers can observe the behaviour of the system. | | At the recent re:Invent conference, Amazon announced a preview release of AWS IoT Analytics. The solution was presented during a few sessions at the event. |
|
| |
| We know what "cloud-native apps" are, but what about the data services they depend on? In this article, we look at ten characteristics of cloud-native data and the implications of each. |
| |
|
| How do you take all very different kinds of applications and make them ready for cloud? This article by Pete Johnson looks at cloud-ready criteria and strategies. |
| |
|
| Mikael Hakansson looks at five critical areas that require focus to ensure IoT success: business ownership, team skillsets, device onboarding, ability to handle change, and comprehensive testing. |
| |
|
| InfoQ recently sat down with Mike Julian, author of Practical Monitoring , and discussed the role and implementation of effective monitoring within software development and the business. |
| |
|
| The bad guys are continuously looking for your cloud’s weaknesses, so don’t delay in getting your cloud security into shape. The “AWS Security Fitness Guide” will coach you through the necessary exercises to strengthen your cloud infrastructure. Download Now. Sponsored content |
| |
|
| |
| Edward Wible and Rafael Ferreira discuss the key elements that make Nubank tick for millions of customers every day, and some key security decisions they made along the way. |
| |
|
| Richard Zhao talks about TI and AI in real practices, and crowd defense - a way to integrate defense measures against both targeted and untargeted attacks. |
| |
|
| Rafal Gancarz introduces the core concepts around Serverless/FaaS and describes architectural and operational aspects of distributed systems built on top the serverless stack with application on AWS. |
| |
|
| Steve Poole discusses actions one can take (and some behaviors one must change) to create a more secure Java application for the cloud. |
| |
|
| Jacob Burnim discusses Sift’s approach to building a ML system to detect fraud and abuse, including training models, handling imbalanced classes, sharing learning, measuring performance, etc. |
| |
|
| |
