Tech News

Docker Enterprise Edition 2.0 was released yesterday. The major focus of this new release (and the platform as a whole) is speeding up multi-cloud initiatives and automating the application delivery model, that go hand-in hand with DevOps and Agile philosophy. Docker has become an important tool for businesses in a very short space of time. With Docker EE 2.0, it looks like Docker will consolidate its position as the go-to containerization tool for enterprise organizations. Key features of Docker Enterprise Edition 2.0 Let’s look at some of the key capabilities included in Docker EE 2.0 release. Docker EE 2.0 is incredibly flexible  Flexibility is one of the biggest assets of Docker Enterprise Edition as today’s software delivery ecosystem demands freedom of choice. Organizations that are building applications on different platforms, using varied set of tools, deploying on different infrastructures and running them on different set of platforms require a huge amount of flexibility. Docker EE has addressed this concern with the following capabilities: Multi-Linux, Multi-OS, Multi-Cloud Many organizations have adopted a Hybrid cloud or Multi-cloud strategy, and build applications on different operating systems. Docker EE is registered across all the popular set of operating systems such as Windows, all the popular Linux distributions, Windows Server, and also on popular public clouds, enabling the users to deploy applications flexibly, wherever required. Docker EE 2.0 is interoperable with Docker Swarm and Kubernetes Container orchestration forms the core of DevOps and the entire ecosystem of containers revolve around Swarm or Kubernetes. Docker EE allows flexibility is switching between both these tools for application deployment and orchestration. Applications deployed on Swarm today, can be easily migrated to Kubernetes using the same compose file, making the life of developers simpler. Accelerating agile with Docker Enterprise Edition 2.0 Docker EE focuses on monitoring and managing containers to much greater extent than the open source version of Docker. The Enterprise Edition has specialized management and monitoring platform for looking after Kubernetes cluster and also has access to Kubernetes API, CLI and interfaces. Cluster management made simple: Easy-to-use cluster management services: Basic single line commands for adding cluster High availability of management plane Access to consoles and logs Securing configurations Secure application zones: With swift integration with corporate LDAPs and Active Directory system, we can divide a single cluster logically and physically into different teams. This seems to be the most convenient way to assign new namespaces to Kubernetes clusters. Layer 7 routing for Swarm: The new interlock 2.0 architecture provides new and optimized enhancements for network routing in Swarm. For more information on interlock architecture, refer the official Docker blog. Kubernetes: All the core components of Kubernetes environment like APIs, CLIs are available for users in a CCNF- conformant Kubernetes stack. There were few more enhancements related to the supply chain and security domains. For the complete set of improvements to Docker, check out the official Docker EE documentation.

Welcome to this week's security news bulletin. This is where you'll find updates from around the web on what's happening in cybersecurity, from technology releases to changes in legislation. Security news from the Packt Hub Report warns of the growing threat of cryptojacking  YouTube gets hacked Security news from across the web Google Cloud Platform adds new security service to protect against DDoS attacks. Google wrote a blog post explaining the features making this possible: Cloud "Armor [the name of the feature] works with Cloud HTTP(S) Load Balancing, provides IPv4 and IPv6 whitelisting/blacklisting, defends against application-aware attacks such as cross-site scripting (XSS) and SQL injection (SQLi), and delivers geography-based access control." Google planning to build a 'walled garden' around Gmail. This decision is an obvious step for Google as it looks to push it's paid-for version of email much harder. However, it is notable that for all the security bells and whistles it has announced, it hasn't said anything about end to end encryption. Clearly, the need to keep the government happy remains high on the agenda for the company... Leonovus announces partnership with IT security experts SynerSolutions npm Acquires ^Lift Security and the Node Security Platform. The partnership shouldn't really come as a huge surprise, as the teams have history. They've been working together for number of years. npm wrote on Medium that "Adam Baldwin and his team have joined npm to work full time on keeping the npm Registry and npm applications safe, and to develop new products to help developers and their companies securely develop JavaScript." Humio Partners With Corelight To Bring Comprehensive Network Visibility And Fast, Affordable Log Management To Businesses. Humio, the log management software company, have teamed up with network monitoring tool Corelight to tackle today's biggest challenges in identifying and acting on security threats. Essentially, it should give greater visibility on potential attacks and points of vulnerability.

The rise of the video game industry over the last two decades has been staggering, to say the least. Considered to be an area with massive revenue potential, we have seen a revolution in the way games are designed, developed and played across various platforms.Unity, the most popular cross-platform game development platform, is now encouraging even the non-programmers to take up Unity game development by equipping them with state-of-the-art tools for designing interactive games. Unity game development simplified for non-developers These days, there are a lot of non-developers, game designers and even artists who wish to build their own games. Well, they are now in for a treat. Unity have come up with their 2D and 3D Game kits wherein the users develop 2D or 3D gameplays without the need to code. With the help of these game kits, beginners can utilize the elements, tools and systems within the kit to design their gameplay. The Unity 2D game kit currently supports versions Unity 2017.3 and higher, while the 3D game kit is supported by Unity 2018.1 or higher. Visual scripting with Bolt Unity  have also introduced a new visual scripting tool called Bolt, which allows non-programmers to create new gameplays from scratch and design interactive systems in Unity, without having to write a single line of code. With live editing, predictive debugging and a whole host of other features, Bolt ensures you can get started with designing your own game in no time at all. The idea of introducing these game kits and the Bolt scripting engine is to encourage more and more non-programmers to take up game development and let their creative juices flow. It will also serve as a starting point for absolute beginners to start their journey in game development. To know more about how to use these Unity game kits, check out the introduction to game kit by Unity.

Scrivito, a SaaS-based Content Management Service, launched a new breed of cloud-based serverless JavaScript CMS which is specifically targeted towards medium to large sized businesses. While the world is shifting to cutting-edge cloud technology, web CMS platforms are still stuck in the past. Thomas Witt, Co-Founder, and CTO of Scrivito said that “We’re at a tipping point. Agencies and dev teams that stick with Wordpress and the like are doomed to be overtaken by the inevitable shift to serverless computing and JavaScript development.” Scrivito checks the boxes for key trending tech innovations in the web development space. Serverless? Yes. Cloud native? Yes. So what’s unique about this cutting-edge content management interface and how exactly does it differentiate itself from the other traditional CMS? Scrivito requires zero maintenance thanks to the cloud This is the most unique feature of Scrivito. Since it is a cloud-based service, it allows developers to spin up a CMS instance without having to re-install anything or reconfigure databases, search engine indexing, backups or metadata. This leads to no downtime, no software patches, and minimal maintenance efforts. Component reusability powered by ReactJS Scrivito is powered by Facebook’s popular frontend framework-React. Thanks to its reusable UI components and its flexibility, developers can create complex and interactive functionalities such as configurators or multi-page forms with ease. Not only built for developers, it also makes it easier for agencies and marketing teams to build, edit and manage secure, reliable and cost-effective sites, microsites, and landing pages. Scrivito is extendable Scrivito is easily extendable because it doesn’t require any infrastructure. Developers and editors can create their own widgets and data structures on the fly. Due to its unique working copies technology, it brings version control technologies from software development to the CMS world, thus eliminating the need for a staging server and allowing parallel editing of content across teams. Plus, its API-driven approach provides the benefits of a serverless and a headless CMS together with WYSIWYG editing in a single solution. Scrivito has certainly ignited a revolution in the web development space by introducing serverless technologies to CMS applications. It is available at different price points for personal and enterprise users. To know more about other features and pricing options, check out the project's official webpage.

Splunk has announced Splunk Industrial Asset Intelligence (Splunk IAI). It's now available on limited release. It would be made open to general availability later this year, in the fall. What is Splunk Industrial Asset Intelligence? The Splunk IAI system makes it easy for customers to use Splunk’s data analytics capabilities for analyzing data from industrial systems and devices. Critical industrial systems lack real time visibility. This can lead to a reactive approach to managing industrial operations and problems are often solved via intuition instead of a data-driven approach. Splunk Industrial Asset Intelligence (SIAI) has been introduced to combat these challenges facing companies in manufacturing, energy, transportation, oil and gas and other industrial verticals. The SIAI would be built on top of Splunk Enterprise machine data platform. The benefits of Splunk Industrial Asset Intelligence Benefits of Splunk IAI include : It correlates data from Industrial Control Systems (ICS), sensors, SCADA systems and applications, making it easy to monitor and diagnose equipment and operational issues in real time. Enables customers to respond to issues faster without affecting production, where unplanned downtime can equate to millions of dollars in lost revenue. The packaged set of capabilities provided by Splunk Industrial Asset Intelligence easily integrates with the existing Splunk platform. The Splunk IAI offers a single solution that ensures industrial systems running at full capacity, enabling organisations to significantly save resources and money on unplanned downtime. To learn more about Splunk Industrial Asset Intelligence, visit Splunk’s website.

Welcome to this week's web development news bulletin. There's some interesting new releases, and also news of conflict between 4 of the planet's biggest tech companies and the W3C. Web development news from the Packt Hub Mozilla is building a bridge between Rust and JavaScript. Mozilla has a high level plan for Rust to become a web development language used for backend tasks within the stack. To do this, it has created something called wasm-bindgen, which makes Rust code interoperable with JavaScript via WebAssembly. Web development news from across the web You can now take a sneak peak at WebAssembly Studio. WebAssembly Studio is an online IDE that provides incredible support when using WebAssembly. It's also a neat place to learn how to use WebAssembly. Apple, Google, Mozilla and Microsoft push back against W3C. The 4 companies behind the world's most popular web browsers have expressed considerable dissatisfaction with W3C's new DOM 4.1 specification. Columbia University's engineering department launches web development bootcamp. Columbia Engineering has teamed up with Trilogy Education Services to create a 24 week course to teach aspiring developers full-stack skills. "Web development is one of the fastest growing careers in today's economy with a projected 15% percent growth by 2026" notes Professor Soulaymane Kachani, Vice Provost for Teaching and Learning at Columbia University. "We are proud to partner with Trilogy to expand access to the digital skills New Yorkers need." New software releases Vue Press, a 'Vue-powered' static site generator has been released. Designed to be incredibly simple and easy to use, Vue Press promises to be a useful new way to build single page web applications. Parcel V1.7.0 has been released, with lots of exciting new features and improvements. This release includes Vue support (which was a big request from users), and content hashed bundle names to provide support for long-term cacheable files. Ember 3.1 and 3.2 released. The release of version 3.1.0 of Ember.js, Ember CLI, and Ember Data has kicked off the beta cycle for Ember sub-projects. Devil Box v0.13 released. This is described as a 'major release which introduces various stabilization and performance fixes as well as ships a very detailed documentation about all customizable features" Rails 5.2.0 is out. Vulkan 1.1.73 released.

After the successful conference at Amsterdam, Vuejs recently conducted the first ever VueConf.US in New Orleans on March 26th-28th 2018. The conference congregated hundreds of Vuejs developers from around the world and the VueJS Core team and featured workshops and talks from members of the Vuejs community and Vue experts. It also witnessed new releases and project processes. The conference commenced with an inaugural keynote by Evan You, the creator of Vue. He talked about the growth of Vue since 2016, also highlighting new developments coming soon. In his keynote, You said that “Vue will be moving to a standardized release cycle with new minor releases every three months and a minimum six-month notice prior to major releases.” They will also be shifting from a single release channel to four separated release channels. The VueConf.US conference covered 4 major workshops by Vuejs experts. In the first workshop, Evan You talked about building simple versions of libraries for features such as routing, state management, form validation and i18n using basic Vue features. Chris Fritz, conducted a second workshop on the basics of building world-class Vue applications. Topics included configuring Webpack for single-file components, setting up the most advanced workflows currently possible, and more. Sarah Drasner organized a workshop on animation in Vue to creating complex effects in performant and visually stunning patterns. Rachel Nabors, presented a talk, "Vue In Motion", on implementing animations and transitions in Vue. In the fourth workshop, Blake Newman presented his views on Vuex, a state management pattern. The VueConf.US conference also featured multiple presentations by key Vue experts. Daniel Rosenwasser, Program Manager on TypeScript at Microsoft, presented his views on making TypeScript and Vue seamless to make sure that JavaScript users of all communities can use Typescript. In another interesting presentation, Jen Looper talked about creating an Engaging Native Mobile App with Vue and NativeScript all the while retaining shared code between the Vue created website and mobile app. Edd Yerburgh, Vue core team member and author of "vue-test-utils", spoke about testing Vue applications. He presented an adapted the testing pyramid for the front end, consisting of end-to-end tests, snapshot tests, and unit tests. In a talk, “Vue & SSR: The best practices”, Sebastien Chopin talks about common problems with server-side rendering and how to deal with them. He also shows Nuxt.js as a possible solution to most of these problems. Community support was the highlight of the VueConf.US conference with a large number of talks mentioning the importance of Vue community support. The attendees were extremely positive about the conference and stated how comfortable and welcoming the community was. Each attendee shared a similar level of excitement about the platform and its possibilities and was excited about meeting the wide variety of developers and to know their experiences. All talks were recorded and will be posted soon on VueMastery.

Say Robot to someone today, and Sophia the humanoid just flashes in front of the eye. This is where robotics has reached, at present; super charged by Artificial Intelligence.  Robotics and Artificial Intelligence are usually confused terms; where there is a thin line between the two. Traditional robots are pre-programmed humanoids or machines meant to do specific tasks irrespective of the environment they are placed in. Therefore, they do not show any intelligent behaviour. With a sprinkle of Artificial Intelligence, these robots have transformed into Artificially intelligent robots, which are now controlled by the AI programs making them capable of taking decisions when encountered by real world situations. How has AI helped Robotics You can look at Artificial intelligence loosely as General or narrow based on the level of task specificity. General AI could be the one from the movie Terminator or Matrix. It imparts wider knowledge and capabilities to machines that are almost similar to humans. However, general AI is way too far in the future and does not exist yet. Current robots are designed to assist humans in their day-to-day tasks in specific domains. For instance, the Roomba Vacuum cleaner is largely automated with very less human intervention. The cleaner can make decisions if it is confronted with choices such as, if the way ahead is blocked by a couch. The cleaner might decide to turn left because it has already vacuumed the carpet to the right. Let’s have a look at some basic capabilities that Artificial Intelligence has imparted into robotics with the example of a self-driving car: Adding power of perception and reasoning: Novel sensors including Sonar sensors, Infrared sensors, Kinect sensors, and so on and their functionalities give robots good perception skills, using which they can self-adapt to any situations. Our self-driving car, with the help of these sensors takes the input data from the environment (such as identifying roadblocks, signals, objects (people), others cars) and labels it, transforms it into knowledge, and interprets it. It then modifies its behaviour based on the result of this perception and takes necessary actions. Learning process: With newer experiences such as heavy traffic, detour, and so on, the self-driving car is required to perceive and reason, in order to obtain conclusions. Here, the AI creates a learning process when similar experiences are repeated in order to store knowledge and speed up intelligent responses. Making correct decisions: With AI the driverless car gets the ability to prioritize actions such as taking another route in case of an accident or detour, or applying sudden brakes when a pedestrian or an object appears suddenly, and so on, in order to be safe and effective in the decisions that they make. Effective Human interaction: This is the most prominent capability that is enabled by Natural Language Processing (NLP). Driverless car accepts and understands the passenger commands with the help of the In-car voice commands based on NLP. Thus, the AI in the car understands the meaning of natural human language and readily responds to the query thrown at it. For instance, based on the destination address given by the passenger, the AI will drive along the fastest route to get there. NLP also helps in understanding human emotions and sentiments. Real-world Applications of AI in Robotics Sophia the humanoid is by far the best real-world amalgamation of Robotics and Artificial Intelligence. However, there other real-world use cases of AI in robotics with practical applications include: Self - supervised learning : This allows robots to create their own training examples for performance improvement. For instance, if the robot has to interpret long-range ambiguous sensor data, it uses apriori training and data that it captured from close range. This knowledge is later incorporated within the robots and within the optical devices that can detect and reject objects (dust and snow, for example). The robot is now capable of detecting obstacles and objects in rough terrain and in 3D-scene analysis and modeling vehicle dynamics. An example of self- supervised learning algorithm is, a road detection algorithm. The front-view monocular camera in the car uses road probabilistic distribution model (RPDM) and fuzzy support vector machines (FSVMs). This algorithm was designed at MIT for autonomous vehicles and other mobile on-road robots. Medical field : In the medical sphere, a collaboration through the Cal-MR: Center for Automation and Learning for Medical Robotics, between researchers at multiple universities and a network of physicians created Smart Tissue Autonomous Robot (STAR). Using innovations in autonomous learning and 3D sensing, STAR is able to stitch together ‘pig intestines’ (used instead of human tissue) with better precision and reliability than the best human surgeons. STAR is not a replacement for surgeons, but in future could remain on standby to handle emergencies and assist surgeons in complex surgical procedures. It would offer major benefits in performing similar types of delicate surgeries. Assistive Robots : these are robots that sense, process sensory information, and perform actions that benefit not only the general public but also people with disabilities, or senior citizens. For instance, Bosch’s driving assistant systems are equipped with radar sensors and video cameras, allowing them to detect these road users even in complex traffic situations. Another example is, the  MICO robotic arm, which uses Kinect sensor. Challenges in adopting AI in Robotics Having an AI robot means lesser pre-programming, replacement of manpower, and so on. There is always a fear that robots may outperform humans in decision making and other intellect tasks. However, one has to take risks to explore what this partnership could lead to. It is obvious that casting an AI environment in robotics is not a cakewalk and there are challenges that experts might face. Some of them include, Legal aspects: After all robots are machines. What if something goes wrong? Who would be liable? One way to mitigate bad outcomes is by developing extensive testing protocols for the design of AI algorithms, improved cybersecurity protections, and input validation standards. This would require AI experts who not only have a deeper understanding of the technologies, but also experts from other disciplines such as law, social sciences, economics and more. Getting used to an automated environment: While it was necessary for traditional robots to be pre-programmed, with AI this will change to a certain extent and experts would just have to feed in the initial algorithms and further changes would be adapted by the robot by self-learning. AI is feared for having the capacity to take over jobs and automate many processes. Hence, broad acceptance of the new technology is required and a careful and managed transition of workers should be carried out. Quick learning with less samples: The AI systems within the robots should assist them in learning quickly even when the supply of data is limited, unlike deep learning which requires hoards of data to formulate an output. The AI-robotics fortune The future for this partnership is bright as robots become more self-dependant and might as well assist humans in their decision making. However, all of this seems like a work of fiction for now. At present, we mostly have semi-supervised learning which requires a certain human touch for essential functioning of AI systems. Unsupervised learning, one shot learning, meta-learning techniques are also creeping in, promising machines that would not require human intervention or guidance any more. Robotics manufacturers such as Silicon Valley Robotics, Mayfield robotics and so on together with auto-manufacturers such as Toyota, BMW are on a path to create autonomous vehicles, which implies that AI is becoming a priority investment for many.

The highly anticipated Unreal Engine 4.19 is now generally available. This release hosts a new Live Link plugin, improvements to Sequencer, new Dynamic Resolution feature, and multiple workflow and usability improvements. In addition to all of these major updates, this release also features a massive 128 improvements based on queries submitted by the Unreal Engine developers community on GitHub. Unreal Engine 4.19 allows game developers to know exactly what their finished game will look like at every step of the development process. This update comes with three major goals: Let developers step inside the creative process. Build gaming worlds that run faster than ever before. Give developers full control. Here's a list of all the major features and what they bring to the game development process: New Unreal Engine 4.19 features Live Link Plugin Improvements The Maya Live Link Plugin is now available and can be used to establish a connection between Maya and UE4 to preview changes in real-time. Virtual Subjects are added to the Live Link. It can also be used with Motion Controllers. Live Link Sources can now define their own custom settings. Virtual Initialization function and Update DeltaTime parameter are also added to Live Link Retargeter API. Source: Unreal Engine blog Unified Unreal AR framework The Unreal Augmented Reality Framework provides a unified framework for building Augmented Reality (AR) apps for both Apple and Google handheld platforms using a single code path. Features include functions supporting Alignment, Light Estimation, Pinning, Session State, Trace Results, and Tracking. Temporal upsampling The new upscaling method, Temporal Upsample performs two separate screen percentages used for upscaling: Primary screen percentage that by default will use the spatial upscale pass as before; Secondary screen percentage that is a static, spatial only upscale at the very end of post-processing, before the UI draws. Dynamic resolution Dynamic Resolution adjusts the resolution to achieve the desired frame rate, for games on PlayStation 4 and Xbox One. It uses a heuristic to set the primary screen percentage based on the previous frames GPU workload. Source: Unreal Engine blog Physical light units All light units are now defined using physically based units. The new light unit property can be edited per light, changing how the engine interprets the intensity property when doing lighting related computations. Source: Unreal Engine blog Landscape rendering optimization The Landscape level of detail (LOD) system now uses screen size to determine detail for a component, similar to how the Static Mesh LOD system works. Starting from this release, all existing UE4 content that supports SteamVR is now compatible with HTC's newly-announced Vive Pro. These are just a select few updates to the Unreal Engine. The full list of release notes is available on the Unreal Engine forums.

Welcome to the new week! Here is the data science news you need to know. There's a theme emerging this week with machine learning popping up in new areas such as IoT and security. This is something we're probably going to see more of in the weeks and months to come... Data science news from the Packt Hub MongoDB goes relational with 4.0 release TensorFlow 1.8.0 has just been released in beta Amazon Sagemaker is going to make machine learning on the cloud easier Data science news from across the web UK's House of Lords report on AI raises concerns around ethics and monopolization Symantec has opened its machine learning tools - "Targeted Attacks Analytics" to the public. The cyber security company has been using machine learning in its research into state-sponsored cybercrime, and believes it to be incredibly effective in identifying and tackling threats. Algorithms capable of processing a huge range of behaviors are used to identify suspect activity. One of the researchers behind the project claimed that it helped them to identify threats they had never seen before - clearly, this could be big news for many companies battling cybercrime. NeoPulse Framework 2.0 launched in a bid to make artificial intelligence more accessible. Created by AI startup Dimensional Mechanics, NeoPulse Framework 2.0 is a toolkit that allows developers - and others - to solve business problems using artificial intelligence and machine learning with relative ease. Even for those with AI experience and knowledge, the company suggests that NeoPulse Framework 2.0 will "reduce the amount of code required to build AI models by up to an amazing 85%." Splunk gets on board with Industrial IoT. The big data analytics company has announced Splunk Industrial Asset Intelligence, a tool that will allow businesses to better process and analyze IoT. It will be formally announced on April 23 at the Hannover Messe conference, and made available as a limited release. It's expected to be opened up later this year. Nvidia and Arm partner to enter IoT marketplace. Nvidia's Deep Learning Accelerator (NVDLA) is going to be integrated within Arm's Project Trillium platform. This will make it easier to embed deep learning within IoT systems. PGAdmin 4 v.3.0 released.  EdgeDB is slated for release very soon. "In the next few weeks we will release the first public technology preview of EdgeDB say the team behind it on their blog. EdgeDB describes itself as a 'new generation of database' that aims to solve the "inconsistency between relational databases and modern programming." OmniDB 2.7 has been released. 2nd Quadrant, the PostgreSQL organization, has released an update to its broswer based database management tool. It offers improved debugging and security features.

With just 15 days from TensorFlow’s major release of 1.7.0, the TensorFlow Community is highly energetic and enthusiast to distribute its 1.8.0 in coming days. The team has announced the beta release 1.8.0-rc0 with numerous exciting features and bug fixes. This newer version has paid more attention towards supporting GPU memory, running on multiple GPUs and cloud performance. Major features and improvements in TensorFlow 1.8.0-rc0: Adds Gradient Boosted Trees for pre-made Estimators with BoostedTreesClassifier and BoostedTreesRegressor. Adds 3rd generation pipeline config for Cloud TPUs for performance improvement and usability. Support for running Estimator model on multiple GPUs by passing tf.contrib.distribute.MirroredStrategy() to tf.estimator.RunConfig(). Support for prefetching GPU memory using tf.contrib.data.prefetch_to_device(). Moving Bayesian computation tf.contrib.bayesflow to its own dedicated repository. Allows generic proto parsing and RPC communication with tf.contrib.{proto,rpc}. Bug Fixes in TensorFlow 1.8.0-rc0: Enabled support for prefetching of dataset elements to GPU memory with tf.contrib.data.prefetch_to_device. Allows automatic tuning of prefetch buffer sizes with tf.contrib.data.AUTOTUNE. Added support for building datasets of CSV files with tf.contrib.data.make_csv_dataset. Provision of creating iterators with Both Dataset.__iter__() and Dataset.make_one_shot_iterator() in eager execution mode. Enabled automatic device placement. tf.GradientTape voluntarily moved out of future contributions to the library. Added new data preprocessing functions and fashion mnist dataset to tf.keras. Accelerated Linear Algebra (XLA) with lexicographical feature. Allows exclusion of nodes in tensor-filter operations. Fixed spurious background colors in text terminals. Fixed batch dimensions reshaping with BatchReshape. Support for explicit gradient checkpointing on TPU with tf.contrib.layers.recompute_grad works. For the complete list of bug fixes and improvements, you can read TensorFlow’s Github page. Miscellaneous changes: Easy calling to TensorFlow C API. Description of shapes and pointer noted in tf.distributions.Distribution tutorial notebook. Scatter operations extended and updated with tf.scatter_min and tf.scatter_max cuDNN RNN operations moved to TensorFlow codebase. Added float64 support for Conv2d, Conv2dBackpropInput, Conv2dBackpropFilter and AvgPool/AvgPoolGrad. Localised graph name scope thread for multi-threaded environments. Updated nsync synchronization library for avoiding slow primitives on Linux. Non-uniformity of orthogonal matrices fixed. Multi-image Estimator eval summaries displays correctly. You can download the source code to access all the exciting features of TensorFlow 1.8.0-rc0.

MongoDB is, without a doubt, the most popular NoSQL database today. Per the Stack Overflow Developer Survey, more developers have been wanting to work with MongoDB than any other database over the last two years. With the upcoming MongoDB 4.0 release, it plans to up the ante by adding support for multi-document transactions and ACID-based features (Atomicity Consistency Integrity and Durability). Poised to be released this summer, MongoDB 4.0 will combine the speed, flexibility and the efficiency of document models - features which make MongoDB such a great database to use - with the assurance of transactional integrity. This new addition should give the database a more relational feel, and would suit large applications with high data integrity needs regardless of how the data is modeled. It has also ensured that the support for multi-document transactions will not affect the overall speed and performance of the unrelated workloads running concurrently. MongoDB have been working on this transactional integrity feature for over 3 years now, ever since they incorporated the WiredTiger storage engine. The MongoDB 4.0 release should also see the introduction of some other important features such as snapshot isolation, a consistent view of data, ability to roll-back transactions and other ACID features. Per the 4.0 product roadmap, 85% of the work is already done, and the release seems to be on time to hit the market. You can read more about the announcement on MongoDB’s official page.You can also join the beta program to test out the newly added features in 4.0.  

In the era of cloud deployment and DevOps, cloud adoption has seen a steady rise since 2017. Forbes report state that global public cloud market will rise up to $178B in 2018, as compared to $146B in 2017, and it will continue to grow at a staggering rate of 22% compound annual growth rate (CAGR). Though all major cloud service providers offer a wide range of efficient services related to Security, it still remains a looming concern when it comes to cloud adoption. Service providers definitely try to address the major concerns with respect to security, but it is always advisable to have a tab on all the major cloud security threats that can haunt you. Following are the top 5 trending cloud security threats for 2018: Data breaches and losses As the name suggests, breach of any confidential data pertaining to personal information, health or financial information is termed as a data breach. US reported the highest number of security breaches (1579) in 2017, with the business sector accounting for 55% of it. Data breaches can be a primary objective of any malicious attack, or a result of poor security best practices. Data loss can be a result of any cyber-attack, natural disaster, or just an accidental deletion. The best way to avoid a data loss is to keep strong back-ups at different geographical locations. Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks This is one of the most popular forms of attack and very simple to execute for any cyber hacker. DoS is also trending in the Dark Web ecosystem, so it becomes even simpler for the attackers as a Dark Web service and can be availed easily by trading few cryptocurrencies. Some security countermeasures like implementing intrusion prevention system, or setting clear expectations with the ISP for clean bandwidth can help you to prevent DoS attacks to a limited extent. Also, DDoS as-a-Service, which has been popular since decades, remains trending even in 2018. GitHub experienced the biggest-ever DDoS attack with an intensity as big as 1.35Tbps via 126.9 million packets per second. Insecurity in APIs Application Programming Interface (APIs) is a set of software user interfaces that is provided by cloud service providers, so that user can interact with the cloud environment. Exploiting an API vulnerability attack is the best way to gain access to all the confidential information, hence it needs to be secure thoroughly. A critical vulnerability discovered in a popular browser extension i.e grammarly is a perfect example of threat posed by insecure APIs.  API testing methodology is considered an effective way to secure cloud APIs before they go live. We can also perform API change reporting on a regular basis to ensure API security. Lack of secure Identity and Access management Attackers masquerading as developers, users, and operators can read, modify or miss-use the data on cloud. Hence lack of secure credentials, or access management can lead to a breach of information through unauthorized access to data and potentially leading to a big loss to the organization. A critical flaw was discovered CYBERARK Enterprise Password Vault application which allowed the attacker to gain unauthorized access to the system and data. Malware attacks 2017 was the year for malware attacks with popular malwares like Ransomware, Petya, Meltdown and Spectre disrupting the entire security mechanism of many organizations. This has affected everything, right from smartphones to servers and continues to be a looming threat for cloud as well. There are minor patch works that can be implemented to prevent these attacks, but they seem to degrade the performance of cloud servers to a great extent. Having a close eye on these security vulnerabilities will help you secure your cloud solutions and ecosystems. With machine learning based cyber attacks and hacking becoming bolder and more common, it is not enough to stay current in your knowledge of these threats and cyber security solutions available in the market. To learn how to secure your cloud environments, you can get your hands on a few of our books;  Mastering AWS Security, Cloud Security Automation, and Enterprise Cloud Security and Governance. Check out other latest news: Vevo’s YouTube account Hacked: Popular videos deleted Cryptojacking is a growing cybersecurity threat, report warns    

Couchbase has just released Couchbase Mobile 2.0. And the organization is pretty excited; it claims that it's going to revolutionize the way businesses process and handle edge analytics. In many ways, Couchbase Mobile 2.0 extends many of the features of the main Couchbase server to its mobile version. Ultimately, it demonstrates Couchbase responding to some of the core demands of business - minimizing the friction between cloud solutions and mobile devices at the edge of networks. The challenges Couchbase Mobile 2.0 is trying to solve According to the Couchbase website, Couchbase Mobile 2.0 is being marketed as solving 3 key challenges: Deployment flexibility Performance at scale Security The combination of these 3 is really the holy grail for many software solutions companies. It's an attempt to resolve that tension between the need for security and stability while remaining adaptable and responsive to change. Learn more about Couchbase Mobile 2.0 here. Ravi Mayuram, Senior VP of Engineering and CTO of Couchbase said said: "With Couchbase Mobile 2.0, we are bringing some very exciting new capabilities to the edge that parallels what we have on Couchbase Server. For the first time, SQL queries and Full-Text Search are available on a NoSQL database running on the edge. Additionally, we’ve made programming much easier through thread and type safe database APIs, as well as automatic conflict resolution." Key features of Couchbase Mobile 2.0 Here are some of the key features of the Couchbase Mobile 2.0: Full text query and SQL search. Data change events will allow developers to build applications that respond more quickly. That's only going to be good for user experience. Using WebSocket for replication will make replication more efficient. That's because "it eliminates continuously polling servers". Data conflicts can now be resolved much more quickly. This new release will help to cement Couchbase's position as a data platform. And with an impressive list of customers, including Wells Fargo, Tommy Hilfiger, eBay and DreamWorks, it will be interesting to see to what extent it can grow that list. Source: Globe Newswire

Leap Motion, famous for building hand tracking hardware and software announced its move into the Augmented reality space with the project ‘North Star’- an augmented reality platform. They are planning to open source this project which includes a design for a headset that Leap Motion claims costs less than $100 at large-scale production. Image Credits: Leap Motion Official Blog Founded in 2010, Leap Motion first ventured into hand tracking technology by announcing their own set of motion controllers. This allowed users to interact with a computer by waving their hands, fingers, or other digits around to control games, maps, or other apps. While the technology was cool at that time, it was unimpressive to certain users because of the sensitivity of their controllers and the lack of apps available to play with. But the company’s still around, and now Leap Motion is unveiling something that could be revolutionary, or it could just be another cool idea that fails to catch on. Here’s a closer look: Design Project North Star isn’t a new consumer headset, the company is also releasing the necessary hardware specifications, designs, and software under an open source license. The headset design uses two fast-refreshing 3.5-inch LCD displays with a resolution of 1600x1440 per eye with 120fps and a 100-degree field in view. It also features Leap Motion’s 180-degree hand tracking sensor. The company claims that it offers a wider range of view than most AR systems that exist today, specifically comparing it with Microsoft Hololens which offers a 70-degree field of view. Most of the existing virtual reality and augmented reality headsets require handled controllers for input but with the Leap Motion sensor, users don’t need to hold anything in their hands at all. Pricing Leap Motion doesn’t plan to sell the headset, but it’ll make the hardware and software open source. They hope that someone else will build and sell the headsets, which the company says could cost less than $100 to produce. David Holz, the chief technology officer at Leap Motion mentioned in a blog post that “Although this is an experimental platform right now, we expect that the design itself will spawn further endeavors that will become available for the rest of the world”. This suggests that with relatively low cost and open source hardware third parties can experiment with the technology. While all these features sound promising, there are still plenty of details which are yet to be revealed. A thorough comparison with other prominent AR devices like Magic Leap and Hololens is necessary to identify Leap Motion’s true potential. Till then you can visit their Official Webpage to see some cool demos. Check out other latest news: Windows launches progressive web apps… that don’t yet work on mobile Verizon launches AR Designer, a new tool for developers