Tech News - Cloud Computing

Yesterday, the Kubernetes team announced the availability of Kubernetes 1.16, which consists of 31 enhancements: 8 moving to stable, 8 is beta, and 15 in alpha. This release contains a new feature called Endpoint Slices in alpha to be used as a scalable alternative to Endpoint resources. Kubernetes 1.16 also contains major enhancements like custom resources, overhauled metrics and volume extension. It also brings additional improvements like the general availability of custom resources and more. Extensions like extensions/v1beta1, apps/v1beta1, and apps/v1beta2 APIs are deprecated in this version. This is Kubernetes' third release this year. The previous version Kubernetes 1.15 released three months ago. It accorded features like extensibility around core Kubernetes APIs and cluster lifecycle stability and usability improvements. Introducing Endpoint Slices in Kubernetes 1.16 The main goal of Endpoint Slices is to increase the scalability for Kubernetes Services. With the existing Endpoints, a single resource had to include all the network endpoints making the corresponding Endpoints resources large and costly. Also, when an Endpoints resource is updated, all the pieces of code watching the Endpoints required a full copy of the resource. This became a tedious process when dealing with a big cluster. With Endpoint Slices, the network endpoints for a Service are split into multiple resources by decreasing the amount of data required for updates. The Endpoint Slices are restricted to 100 endpoints each, by default. The other goal of Endpoint Slices is to provide extensible and useful resources for a variety of implementations. Endpoint Slices will also provide flexibility for address types. The blog post states, “An initial use case for multiple addresses would be to support dual stack endpoints with both IPv4 and IPv6 addresses.”  As the feature is available in alpha only, it is not enabled by default in Kubernetes 1.16. Major enhancements in Kubernetes 1.16 General availability of Custom Resources With Kubernetes 1.16, CustomResourceDefinition (CRDs) is generally available, with apiextensions.k8s.io/v1, as it contains the integration of API evolution in Kubernetes. CRDs were previously available in beta. It is widely used as a Kubernetes extensibility mechanism. In the CRD.v1, the API evolution has a ‘defaulting’ support by default. When defaulting is  combined with the CRD conversion mechanism, it will be possible to build stable APIs over time. The blog post adds, “Updates to the CRD API won’t end here. We have ideas for features like arbitrary subresources, API group migration, and maybe a more efficient serialization protocol, but the changes from here are expected to be optional and complementary in nature to what’s already here in the GA API.” Overhauled metrics In the earlier versions, the global metrics registry was extensively used by the Kubernetes to register exposed metrics. In this latest version, the metrics registry has been implemented, thus making the Kubernetes metrics more stable and transparent. Volume Extension This release contains many enhancements to volumes and volume modifications. The volume resizing support in (Container Storage Interface) CSI specs has moved to beta, allowing the CSI spec volume plugin to be resizable. Additional Windows Enhancements in Kubernetes 1.16 Workload identity option for Windows containers has moved to beta. It can now gain exclusive access to external resources. New alpha support is added for kubeadm which can be used to prepare and add a Windows node to cluster. New plugin support is introduced for CSI in alpha. Interested users can download Kubernetes 1.16 on GitHub. Check out the Kubernetes blog page for more information. Other interesting news in Kubernetes The Continuous Intelligence report by Sumo Logic highlights the rise of Multi-Cloud adoption and open source technologies like Kubernetes Kubernetes releases etcd v3.4 with better backend storage, improved raft voting process, new raft non-voting member and more CNCF-led open source Kubernetes security audit reveals 37 flaws in Kubernetes cluster; recommendations proposed

AWS already has solutions for machine learning, edge computing, and IoT. But a recent update to AWS Greengrass has combined all of these facets so you can deploy machine learning models to the edge of networks. That's an important step forward in the IoT space for AWS. With Microsoft also recently announcing a $5 billion investment in IoT projects over the next 4 years, by extending the capability of AWS Greengrass, the AWS team are making sure they set the pace in the industry. Jeff Barr, AWS evangelist, explained the idea in a post on the AWS blog: "...You can now perform Machine Learning inference at the edge using AWS Greengrass. This allows you to use the power of the AWS cloud (including fast, powerful instances equipped with GPUs) to build, train, and test your ML models before deploying them to small, low-powered, intermittently-connected IoT devices running in those factories, vehicles, mines, fields..." Industrial applications of machine learning inference Machine learning inference is bringing lots of advantages to industry and agriculture. For example: In farming, edge-enabled machine learning systems will be able to monitor crops using image recognition  - in turn this will enable corrective action to be taken, allowing farmers to optimize yields. In manufacturing, machine learning inference at the edge should improve operational efficiency by making it easier to spot faults before they occur. For example, by monitoring vibrations or noise levels, Barr explains, you'll be able to identify faulty or failing machines before they actually break. Running this on AWS greengrass offers a number of advantages over running machine learning models and processing data locally - it means you can run complex models without draining your computing resources. Read more in detail on the AWS Greengrass Developer Guide. AWS Greengrass should simplify machine learning inference One of the fundamental benefits of using AWS Greengrass should be that it simplifies machine learning inference at every single stage of the typical machine learning workflow. From building and deploying machine learning models, to developing inference applications that can be launched locally within an IoT network, it should, in theory, make the advantages of machine learning inference more accessible to more people. It will be interesting to see how this new feature is applied by IoT engineers over the next year or so. But it will also be interesting to see if this has any impact on the wider battle for the future of Industrial IoT. Further reading: What is edge computing? AWS IoT Analytics: The easiest way to run analytics on IoT data, Amazon says What you need to know about IoT product development

Last week, Fastly Inc., a provider of an edge cloud platform announced that it has filed its proposed initial public offering (ipo) with the US Securities and Exchange Commission. Last year in July, in its last round of financing before a public offering,  the company raised $40 million investment. The book-running managers for the proposed offering are BofA Merrill Lynch, Citigroup, and Credit Suisse. William Blair, Raymond James, Baird, Oppenheimer & Co., Stifel, Craig-Hallum Capital Group and D.A. Davidson & Co. are co-managers for the proposed offering. Founded by Artur Bergman in 2011, Fastly is an American cloud computing services provider. Its edge cloud platform provides a content delivery network, Internet security services, load balancing, and video & streaming services. The edge cloud platform is designed from the ground up to be programmable and to support agile software development. This programmable edge cloud platform gives developers real-time visibility and control by stream logging data. So, developers are able to instantly see the impact of new code in production, troubleshoot issues as they occur, and rapidly identify suspicious traffic. Fastly boasts of catering to customers like The New York Times, Reddit, GitHub, Stripe, Ticketmaster and Pinterest. The company, in the unfinished prospectus shared how it has grown over the years, the risks of investing in the company, what are its plans for the future, and more. The company shows a steady growth in its revenue, while in December 2017 it was $104.9 million, it increased to $144.6 million, by the end of 2018. Its loss has also shown some decline from $32.5 million in December 2017 to $30.9 million in December 2018. Predicting its future market value, the prospectus says, “When incorporating these additional offerings, we estimate a total market opportunity of approximately $18.0 billion in 2019, based on expected growth from 2017, to $35.8 billion in 2022, growing with an expected CAGR of 25.6%.“ Fastly has not yet determined the number of shares to offered and the price range for the proposed offering. Currently, the company’s public filing has a placeholder amount of $100 million. However, looking at the amount of funding the company has received, TechCrunch predicts that it is more likely to get closer to $1 billion when it finally prices its shares. Fastly has two classes of authorized common stock: Class A and Class B. The rights of both the common stockholders are identical, except with respect to voting and conversion. Each Class A share is entitled to one vote per share and each Class B share is entitled to 10 votes per share. Class B shares are convertible into one shares of Class A common stock. The Class A common stock will be listed on The New York Stock Exchange under the symbol “FSLY.” To read more in detail, check out the ipo filing by Fastly. Fastly open sources Lucet, a native WebAssembly compiler and runtime Cloudflare raises $150M with Franklin Templeton leading the latest round of funding Dark Web Phishing Kits: Cheap, plentiful and ready to trick you  

How the depth and breadth of the Microsoft Azure partner ecosystem enables thousands of organizations to bring their mission-critical applications to Azure. In the past few years, IT organizations have been realizing compelling benefits when they transitioned their business-critical applications to the cloud, enabling them to address the top challenges they face with running the same applications on-premises. As even more companies embark on their digital transformation journey, the range of mission and business-critical applications has continued to expand, even more so because technology drives innovation and growth. This has further accelerated in the past months, spurred in part by our rapidly changing global economy. As a result, the definition of mission-critical applications is evolving and goes well beyond systems of record for many businesses. It’s part of why we never stopped investing across the platform to enable you to increase the availability, security, scalability, and performance of your core applications running on Azure. The expansion of mission-critical apps will only accelerate as AI, IoT, analytics, and new capabilities become more pervasive. We’re seeing the broadening scope of mission-critical scenarios both within Microsoft and in many of our customers’ industry sectors. For example, Eric Boyd, in his blog, outlined how companies in healthcare, insurance, sustainable farming, and other fields have chosen Microsoft Azure AI to transform their businesses. Applications like Microsoft Teams have now become mission-critical, especially this year, as many organizations had to enable remote workforces. This is also reflected by the sheer number of meetings happening in Teams. Going beyond Azure services and capabilities Many organizations we work with are eager to realize myriad benefits for their own business-critical applications, but first need to address questions around their cloud journey, such as: Are the core applications I use on-premises certified and supported on Azure? As I move to Azure, can I retain the same level of application customization that I have built over the years on-premises? Will my users experience any impact in the performance of my applications? In essence, they want to make sure that they can continue to capitalize on the strategic collaboration they’ve forged with their partners and ISVs as they transition their core business processes to the cloud. They want to continue to use the very same applications that they spent years customizing and optimizing on-premises. Microsoft understands that running your business on Azure goes beyond the services and capabilities that any platform can provide. You need a comprehensive ecosystem. Azure has always been partner-oriented, and we continue to strengthen our collaboration with a large number of ISVs and technology partners, so you can run the applications that are critical to the success of your business operations on Azure. A deeper look at the growing spectrum of mission-critical applications Today, you can run thousands of third-party ISV applications on Azure. Many of these ISVs in turn depend on Azure to deliver their software solutions and services. Azure has become a mission-critical platform for our partner community as well as our customers. When most people think of mission-critical applications, enterprise resource planning systems (ERP), supply chain management (SCM), product lifecycle management (PLM), and customer relationship management (CRM) applications are often the first examples that come to mind. However, to illustrate the depth and breadth of our mission-critical ecosystem, consider these distinct and very different categories of applications that are critical for thousands of businesses around the world: Enterprise resource planning (ERP) systems. Data management and analytics applications. Backup, and business continuity solutions. High-performance computing (HPC) scenarios that exemplify the broadening of business-critical applications that rely on public cloud infrastructure. Azure’s deep ecosystem addresses the needs of customers in all of these categories and more. ERP systems When most people think of mission-critical applications ERP, SCM, PLM, and CRM applications are often the first examples that come to mind. Some examples on Azure include: SAP—We have been empowering our enterprise customers to run their most mission-critical SAP workloads on Azure, bringing the intelligence, security, and reliability of Azure to their SAP applications and data. Viewpoint, a Trimble company—Viewpoint has been helping the construction industry transform through integrated construction management software and solutions for more than 40 years. To meet the scalability and flexibility needs of both Viewpoint and their customers, a significant portion of their clients are now running their software suite on Azure and experiencing tangible benefits. Data management and analytics Data is the lifeblood of the enterprise. Our customers are experiencing an explosion of mission-critical data sources, from the cloud to the edge, and analytics are key to unlocking the value of data in the cloud. AI is a key ingredient, and yet another compelling reason to modernize your core apps on Azure. DataStax—DataStax Enterprise, a scale out, hybrid, cloud-native NoSQL database built on Apache Cassandra™, in conjunction with Azure, can provide a foundation for personalized, real-time scalable applications. Learn how this combination can enable enterprises to run mission critical workloads to increase business agility, without compromising compliance and data governance. Informatica—Informatica has been working with Microsoft to help businesses ensure that the data that is driving your customer and business decisions is trusted, authenticated, and secure. Specifically, Informatica is focused on the quality of the data that is powering your mission-critical applications and can help you derive the maximum value from your existing investments. SAS®—Microsoft and SAS are enabling customers to easily run their SAS workloads in the cloud, helping them unlock critical value from their digital transformation initiatives. As part of our collaboration, SAS is migrating its analytical products and industry solutions onto Azure as the preferred cloud provider for the SAS Cloud. Discover how mission-critical analytics is finding a home in the cloud. Backup and disaster recovery solutions Uptime and disaster recovery plans that minimize recovery time objective (RTO) and recovery point objective (RPO) are the top metrics senior IT decision-makers pay close attention to when it comes to mission-critical environments. Backing up critical data is a key element of putting in place robust business continuity plans. Azure provides built-in backup and disaster recovery features, and we also partner with industry leaders like Commvault, Rubrik, Veeam, Veritas, Zerto, and others so you can keep using your existing applications no matter where your data resides. Commvault—We continue to work with Commvault to deliver data management solutions that enable higher resiliency, visibility, and agility for business-critical workloads and data in our customers’ hybrid environments. Learn about Commvault’s latest offerings—including support for Azure VMware Solution and why their Metallic SaaS suite relies exclusively on Azure. Rubrik—Learn how Rubrik helps enterprises achieve low RTOs, self-service automation at scale, and accelerated cloud adoption. Veeam—Read how you can use Veeam’s solution portfolio to backup, recover, and migrate mission-critical workloads to Azure. Veritas—Find out how Veritas InfoScale has advanced integration with Azure that simplifies the deployment and management of your mission-critical applications in the cloud. Zerto—Discover how the extensive capabilities of Zerto’s platform help you protect mission critical applications on Azure. Teradici—Finally, Teradici underscores how the lines between mission-critical and business-critical are blurring. Read how business continuity plans are being adjusted to include longer term scenarios. HPC scenarios HPC applications are often the most intensive and highest-value workloads in a company, and are business-critical in many industries, including financial services, life sciences, energy, manufacturing and more. The biggest and most audacious innovations from supporting the fight against COVID-19, to 5G semiconductor design; from aerospace engineering design processes to the development of autonomous vehicles, and so much more are being driven by HPC. Ansys—Explore how Ansys Cloud on Azure has proven to be vital for business continuity during unprecedented times. Rescale—Read how Rescale can provide a turnkey platform for engineers and researchers to quickly access Azure HPC resources, easing the transition of business-critical applications to the cloud. You can rely on the expertise of our partner community Many organizations continue to accelerate the migration of their core applications to the cloud, realizing tangible and measurable value in collaboration with our broad partner community, which includes global system integrators like Accenture, Avanade, Capgemini, Wipro, and many others. For example, UnifyCloud recently helped a large organization in the financial sector modernize their data estate on Azure while achieving 69 percent reduction in IT costs. We are excited about the opportunities ahead of us, fueled by the power of our collective imagination. Learn more about how you can run business-critical applications on Azure and increase business resiliency. Watch our Microsoft Ignite session for a deeper diver and demo.   “The construction industry relies on Viewpoint to build and host the mission-critical technology used to run their businesses, so we have the highest possible standards when it comes to the solutions we provide. Working with Microsoft has allowed us to meet those standards in the Azure cloud by increasing scalability, flexibility and reliability – all of which enable our customers to accelerate their own digital transformations and run their businesses with greater confidence.” —Dan Farner, Senior Vice President of Product Development, Viewpoint (a Trimble Company) Read the Gaining Reliability, Scalability, and Customer Satisfaction with Viewpoint on Microsoft Azure blog.     “Business critical applications require a transformational data architecture built on scale-out data and microservices to enable dramatically improved operations, developer productivity, and time-to-market. With Azure and DataStax, enterprises can now run mission critical workloads with zero downtime at global scale to achieve business agility, compliance, data sovereignty, and data governance.”—Ed Anuff, Chief Product Officer, DataStax Read the Application Modernization for Data-Driven Transformation with DataStax Enterprise on Microsoft Azure blog.     “As Microsoft’s 2020 Data Analytics Partner of Year, Informatica works hand-in-hand with Azure to solve mission critical challenges for our joint customers around the world and across every sector.  The combination of Azure’s scale, resilience and flexibility, along with Informatica’s industry-leading Cloud-Native Data Management platform on Azure, provides customers with a platform they can trust with their most complex, sensitive and valuable business critical workloads.”—Rik Tamm-Daniels, Vice President of strategic ecosystems and technology, Informatica Read the Ensuring Business-Critical Data Is Trusted, Available, and Secure with Informatica on Microsoft Azure blog.       “SAS and Microsoft share a vision of helping organizations make better decisions as they strive to serve customers, manage risks and improve operations. Organizations are moving to the cloud at an accelerated pace. Digital transformation projects that were scheduled for the future now have a 2020 delivery date. Customers realize analytics and cloud are critical to drive their digital growth strategies. This partnership helps them quickly move to Microsoft Azure, so they can build, deploy, and manage analytic workloads in a reliable, high-performant and cost-effective manner.”—Oliver Schabenberger, Executive Vice President, Chief Operating Officer and Chief Technology Officer, SAS Read the Mission-critical analytics finds a home in the cloud blog.   “Microsoft is our Foundation partner and selecting Microsoft Azure as our platform to host and deliver Metallic was an easy decision. This decision sparks customer confidence due to Azure’s performance, scale, reliability, security and offers unique Best Practice guidance for customers and partners. Our customers rely on Microsoft and Azure-centric Commvault solutions every day to manage, migrate and protect critical applications and the data required to support their digital transformation strategies.”—Randy De Meno, Vice President/Chief Technology Officer, Microsoft Practice & Solutions Read the Commvault extends collaboration with Microsoft to enhance support for mission-critical workloads blog.     “Enterprises depend on Rubrik and Azure to protect mission-critical applications in SAP, Oracle, SQL and VMware environments. Rubrik helps enterprises move to Azure securely, faster, and with a low TCO using Rubrik’s automated tiering to Azure Archive Storage. Security minded customers appreciate that with Rubrik and Microsoft, business critical data is immutable, preventing ransomware threats from accessing backups, so businesses can quickly search and restore their information on-premises and in Azure.”—Arvind Nithrakashyap, Chief Technology Officer and Co-Founder, Rubrik Learn how enterprises use Rubrik on Azure.     “Veeam continues to see increased adoption of Microsoft Azure for business-critical applications and data across our 375,000 plus global customers. While migration of applications and data remains the primary barrier to the public cloud, we are committed to helping eliminate these challenges through a unified Cloud Data Management platform that delivers simplicity, flexibility and reliability at its core, while providing unrivaled data portability for greater cost controls and savings. Backed by the unique Veeam Universal License – a portable license that moves with workloads to ensure they're always protected – our customers are able to take control of their data by easily migrating workloads to Azure, and then continue protecting and managing them in the cloud.”—Danny Allan, Chief Technology Officer and Senior Vice President for Product Strategy, Veeam Read the Backup, recovery, and migration of mission-critical workloads on Azure blog.     “Thousands of customers rely on Veritas to protect their data both on-premises and in Azure. Our partnership with Microsoft helps us drive the data protection solutions that our enterprise customers rely on to keep their business-critical applications optimized and immediately available.”—Phil Brace, Chief Revenue Officer, Veritas Read the Migrate and optimize your mission-critical applications in Microsoft Azure with Veritas InfoScale blog.     “Microsoft has always leveraged the expertise of its partners to deliver the most innovative technology to customers. Because of Zerto’s long-standing collaboration with Microsoft, Zetro's IT Resilience platform is fully integrated with Azure and provides a robust, fully orchestrated solution that reduces data loss to seconds and downtime to minutes. Utilizing Zerto’s end-to-end, converged backup, DR, and cloud mobility platform, customers have proven time and time again they can protect mission-critical applications during planned or unplanned disruptions that include ransomware, hardware failure, and numerous other scenarios using the Azure cloud – the best cloud platform for IT resilience in the hybrid cloud environment.”—Gil Levonai, CMO and SVP of Product, Zerto Read the Protecting Critical Applications in the Cloud with the Zerto Platform blog.     “The longer business continues to be disrupted, the more the lines blur and business critical functions begin to shift to mission critical, making virtual desktops and workstations on Microsoft Azure an attractive option for IT managers supporting remote workforces in any function or industry. Teradici Cloud Access Software offers a flexible and secure solution that supports demanding business critical and mission critical workloads on Microsoft Azure and Azure Stack with exceptional performance and fidelity, helping businesses gain efficiency and resilience within their business continuity strategy.”—John McVay, Director of Strategic Alliances, Teradici Read the Longer IT timelines shift business critical priorities to mission critical blog.         "It is imperative for Ansys to support our customers' accelerating needs for on-demand high performance computing to drive their increasingly complex engineering requirements. Microsoft Azure, with its purpose-built HPC and robust go-to market capabilities, was a natural choice for us, and together we are enabling our joint customers to keep designing innovative products even as they work from home.”—Navin Budhiraja, Vice President and General Manager, Cloud and Platform, Ansys Read the Ansys Cloud on Microsoft Azure: A vital resource for business continuity during the pandemic blog.     “Robust and stable business critical systems are paramount for success. Rescale customers leveraging Azure HPC resources are taking advantage of the scalability, flexibility and intelligence to improve R&D, accelerate development and reduce costs not possible with a fixed infrastructure.”—Edward Hsu, Vice President of Product, Rescale Read the Business Critical Systems that Drive Innovation blog.     “Customers are transitioning business-critical workloads to Azure and realizing significant cost benefits while modernizing their applications. Our solutions help customers develop cloud strategy, modernize quickly, and optimize cloud environments while minimizing risk and downtime.”—Vivek Bhatnagar, Co-Founder and Chief Technology Officer, UnifyCloud Read the Moving mission-critical applications to the cloud: More important than ever blog.

The Cloud Native Computing Foundation (CNCF), which builds sustainable ecosystems for cloud native software, yesterday announced the stable release of Helm 3. Helm is a package manager for Kubernetes and a tool for managing charts of pre-configured Kubernetes resources. “Helm is one of our fastest-growing projects in contributors and users contributing back to the project,” said Chris Aniszczyk, CTO, CNCF. “Helm is a powerful tool for all Kubernetes users to streamline deployments, and we’re impressed by the progress the community has made with this release in growing their community.” As per the team the internal implementation of Helm 3 has changed considerably from Helm 2. The most important change is the removal of Tiller, a service that communicates with the Kubernetes API to manage Helm packages. Then there are improvements to chart repositories, release management, security, and library charts. Helm uses a packaging format called charts, which are collections of files describing a related set of Kubernetes resources. These charts can then be packaged into versioned archives to be deployed. Helm 2 defined a workflow for creating, installing, and managing these charts. Helm 3 builds upon that workflow, changing the underlying infrastructure to reflect the needs of the community as they change and evolve. In this release, the Helm maintainers incorporated feedback and requests from the community to better address the needs of Kubernetes users and the broad cloud native ecosystem. Helm 3 is ready for public deployment Last week, third party security firm Cure53 completed their open source security audit of Helm 3, mentioning Helm’s mature focus on security, and concluded that Helm 3 is “recommended for public deployment.” According to the report, “in light of the findings stemming from this CNCF-funded project, Cure53 can only state that the Helm projects the impression of being highly mature. This verdict is driven by a number of different factors… and essentially means that Helm can be recommended for public deployment, particularly when properly configured and secured in accordance to recommendations specified by the development team.” “When we built Helm, we set out to create a tool to serve as an ‘on-ramp’ to Kubernetes. With Helm 3, we have really accomplished that,” said Matt Fisher, the Helm 3 release manager. “Our goal has always been to make it easier for the Kubernetes user to create, share, and run production-grade workloads. The core maintainers are really excited to hit this major milestone, and we look forward to hearing how the community is using Helm 3.” Helm 3 is a joint community effort, with core maintainers from organizations including Microsoft, Samsung SDS, IBM, and Blood Orange. As per the team the next phase of Helm’s development will see new features targeted toward stability and enhancements to existing features. Features on the roadmap include enhanced functionality for helm test, improvements to Helm’s OCI integration, and enhanced functionality for the Go client libraries. To know more about this news, read the official announcement from the Cloud Native Computing Foundation. StackRox Kubernetes Security Platform 3.0 releases with advanced configuration and vulnerability management capabilities Microsoft launches Open Application Model (OAM) and Dapr to ease developments in Kubernetes and microservices An unpatched security issue in the Kubernetes API is vulnerable to a “billion laughs” attack Kubernetes 1.16 releases with Endpoint Slices, general availability of Custom Resources, and other enhancements StackRox App integrates into the Sumo Logic Dashboard for improved Kubernetes security  

If you missed the Azure announcements made at Microsoft Ignite 2018, don’t worry, we’ve got you covered. Here are some of the biggest changes and improvements the Microsoft Azure team have made to their cloud offering. Infrastructure Improvements Azure’s new capabilities to deliver the best infrastructure for every workload include: 1. GPU enable and High-Performance VM To deliver the best infrastructure for every workload, Azure has announced the Preview of GPU-enabled and High-Performance Computing Virtual Machines. The two new N-series Virtual Machines have NVIDIA GPU capabilities. The first one is the NVv2 VMs and the second virtual machine is the NDv2 VMs. The two new H-series VMs are optimized for performance and cost and are aimed at HPC workloads like fluid dynamics, structural mechanics, energy exploration, weather forecasting, risk analysis, and more. The first VM is the HB VMs and the second VM is the HC VMs. 2. Networking Azure has announced the general availability of Azure Firewall and Virtual WAN. They have also announced the preview of Azure Front Door Service, ExpressRoute Global Reach, and ExpressRoute Direct. Azure Firewall has a built-in high availability and cloud scalability. The Virtual WAN will provide a simple, unified, global connectivity, and security platform to deploy large-scale branch connectivity. 3. Improved Disk storage Microsoft has expanded the portfolio of Azure Disk offerings to deploy any app in Azure, including those that are the most IO intensive. The new previews include the Ultra SSDs, Standard SSDs, Larger managed disk sizes - to help deal with data-intensive workloads. This will also ensure better availability, reliability, and latency as compared to standard SSDs 4. Hybrid Microsoft has announced new hybrid capabilities to manage data, create even more consistency, and secure hybrid environment. They have introduced the Azure Data Box edge, Windows Server 2019 and Azure stack. With AI enable edge computing capabilities, and OS that supports hybrid management and flexibility for deploying applications, Azure is causing waves in the developer community Built-in security & management For improved Security, Azure has announced new services for preview, like Confidential Computing DC VM series, Secure score, improved threat protection, and network map (preview). These will expand Azure security controls and services to protect network, applications, data, and identities. These services are enhanced by the unique intelligence that comes from the trillions of signals we collect in running first party services like Office 365 and Xbox. For better Management, Azure has announced the preview of Azure Blueprints. These blueprints make it easy to deploy and update Azure environments in a repeatable manner using composable artifacts such as policies, role-based access controls, and resource templates. Azure cost management in the Azure portal (preview) will help to access cost management from PowerBI or directly from your own custom applications. Migration To make the migration to the cloud less challenging, Azure has announced the support for Hyper-V assessments in Azure Migrate, Azure SQL Database Managed Instance, which enables users to migrate SQL Servers to a fully managed Azure service. To help improve your migration experience, we are announcing that if you migrate Windows Server or SQL Server 2008/R2 to Azure, you will get three years of free extended security updates on those systems. This could save you some money when Windows Server and SQL Server 2008/ R2 end of support (EOS). Automated ML capability in Azure Machine Learning The problem of finding the best machine learning pipeline for a given dataset scales faster than the time available for data science projects.  Azure’s Automated machine learning enables developers to access an automated service that identifies the best machine learning pipelines for their labelled data. Data scientists are empowered with a powerful productivity tool that also takes uncertainty into account, incorporating a probabilistic model to determine the best pipeline to try next. To follow more of the Azure buzz, head to  Microsoft’s official Blog   Microsoft’s Immutable storage for Azure Storage Blobs, now generally available Azure Functions 2.0 launches with better workload support for serverless Microsoft announces Azure DevOps, makes Azure pipelines available on GitHub Marketplace  

Yesterday, at the Microsoft Ignite 2019 in Orlando, the company released the preview of its first full-stack, scalable, general open cloud ecosystem, ‘Azure Quantum’. For developers, Microsoft has specifically created the open-source Quantum Development Kit, which includes all of the tools and resources you need to start learning and building quantum solutions. Azure Quantum is a set of quantum services including pre-built solutions to software and quantum hardware, providing developers and customers access to some of the most competitive quantum offerings in the market. For this offering, Microsoft has partnered with 1QBit, Honeywell, IonQ, and QCI. With Azure Quantum service, anyone gains deeper insights about quantum computing through a series of tools and learning tutorials such as the quantum katas. It also allows developers to write programs with Q# and QDK and experiment running the code against simulators and a variety of quantum hardware. Customers can also solve complex business challenges with pre-built solutions and algorithms running in Azure. According to Wired, “Azure Quantum has similarities to a service from IBM, which has offered free and paid access to prototype quantum computers since 2016. Google, which said last week that one of its quantum processors had achieved a milestone known as “quantum supremacy” by outperforming a top supercomputer, has said it will soon offer remote access to quantum hardware to select companies.” Microsoft’s Azure Quantum model is more like the existing computing industry, where cloud providers allow customers to choose processors from companies such as Intel and AMD, says William Hurley, CEO of startup Strangeworks. This startup offers services for programmers to build and collaborate with quantum computing tools from IBM, Google, and others. With just a single program, users will be able to target a variety of hardware through Azure Quantum – Azure classical computing, quantum simulators, and resource estimators, and quantum hardware from our partners, as well as our future quantum system being built on revolutionary topological qubit. Microsoft, on its official website, announced that the Azure Quantum will be launched in private preview in the coming months. Many users are excited to try the Quantum service by Azure. https://twitter.com/Daniel_Rubino/status/1191364279339036673 To know more about Azure Quantum in detail, visit Microsoft’s official page. Are we entering the quantum computing era? Google’s Sycamore achieves ‘quantum supremacy’ while IBM refutes the claim Using Qiskit with IBM QX to generate quantum circuits [Tutorial] How to translate OpenQASM programs in IBX QX into quantum scores [Tutorial]

Last week on Tuesday Amazon announced that Amazon S3 will no longer support path-style API requests. Currently Amazon S3 supports two request URI styles in all regions: path-style (also known as V1) that includes bucket name in the path of the URI (example: //s3.amazonaws.com/<bucketname>/key) and virtual-hosted style (also known as V2) which uses the bucket name as part of the domain name (example: //<bucketname>.s3.amazonaws.com/key). Amazon team mentions in the announcement that, “In our effort to continuously improve customer experience, the path-style naming convention is being retired in favor of virtual-hosted style request format.” They have also asked customers to update their applications to use the virtual-hosted style request format when making S3 API requests. And this should be done before September 30th, 2020 to avoid any service disruptions. Customers using the AWS SDK can upgrade to the most recent version of the SDK to ensure their applications are using the virtual-hosted style request format. They have further mentioned that, “Virtual-hosted style requests are supported for all S3 endpoints in all AWS regions. S3 will stop accepting requests made using the path-style request format in all regions starting September 30th, 2020. Any requests using the path-style request format made after this time will fail.” Users on Hackernews see this as a poor development by Amazon and have noted its implications that collateral freedom techniques using Amazon S3 will no longer work. One of them has commented strongly on this, “One important implication is that collateral freedom techniques [1] using Amazon S3 will no longer work. To put it simply, right now I could put some stuff not liked by Russian or Chinese government (maybe entire website) and give a direct s3 link to https:// s3 .amazonaws.com/mywebsite/index.html. Because it's https — there is no way man in the middle knows what people read on s3.amazonaws.com. With this change — dictators see my domain name and block requests to it right away. I don't know if they did it on purpose or just forgot about those who are less fortunate in regards to access to information, but this is a sad development. This censorship circumvention technique is actively used in the wild and loosing Amazon is no good.” Amazon team suggests that if your application is not able to utilize the virtual-hosted style request format, or if you have any questions or concerns, you may reach out to AWS Support. To know more about this news check out the official announcement page from Amazon. Update from Amazon team on 8th May Amazon’s Chief Evangelist for AWS, Jeff Barr sat with the S3 team to understand this change in detail. After getting a better understanding he posted an update on why the team plans to deprecate the path based model. Here’s his comparison on old vs the new: S3 currently supports two different addressing models: path-style and virtual-hosted style. Take a quick look at each one. The path-style model looks either like this (the global S3 endpoint): https://s3.amazonaws.com/jbarr-public/images/ritchie_and_thompson_pdp11.jpeg https://s3.amazonaws.com/jeffbarr-public/classic_amazon_door_desk.png Or this (one of the regional S3 endpoints): https://s3-useast2.amazonaws.com/jbarrpublic/images/ritchie_and_thompson_pdp11.jpeg https://s3-us-east-2.amazonaws.com/jeffbarr-public/classic_amazon_door_desk.png For example, jbarr-public and jeffbarr-public are bucket names; /images/ritchie_and_thompson_pdp11.jpeg and /jeffbarr-public/classic_amazon_door_desk.png are object keys. Even though the objects are owned by distinct AWS accounts and are in different S3 buckets and possibly in distinct AWS regions, both of them are in the DNS subdomain s3.amazonaws.com. Hold that thought while we look at the equivalent virtual-hosted style references: https://jbarr-public.s3.amazonaws.com/images/ritchie_and_thompson_pdp11.jpeg https://jeffbarr-public.s3.amazonaws.com/classic_amazon_door_desk.png These URLs reference the same objects, but the objects are now in distinct DNS subdomains (jbarr-public.s3.amazonaws.com and jeffbarr-public.s3.amazonaws.com, respectively). The difference is subtle, but very important. When you use a URL to reference an object, DNS resolution is used to map the subdomain name to an IP address. With the path-style model, the subdomain is always s3.amazonaws.com or one of the regional endpoints; with the virtual-hosted style, the subdomain is specific to the bucket. This additional degree of endpoint specificity is the key that opens the door to many important improvements to S3. The select few in the community are in favor of this as per one of the user comment on Hacker News which says, “Thank you for listening! The original plan was insane. The new one is sane. As I pointed out here https://twitter.com/dvassallo/status/1125549694778691584 thousands of printed books had references to V1 S3 URLs. Breaking them would have been a huge loss. Thank you!” But for the other few Amazon team has failed to address the domain censorship issue as per another user which says, “Still doesn't help with domain censorship. This was discussed in-depth in the other thread from yesterday, but TLDR, it's a lot harder to block https://s3.amazonaws.com/tiananmen-square-facts than https://tiananmen-square-facts.s3.amazonaws.com because DNS lookups are made before HTTPS kicks in.” Read about this update in detail here. Amazon S3 Security access and policies 3 announcements about Amazon S3 from re:Invent 2018: Intelligent-Tiering, Object Lock, and Batch Operations Amazon introduces S3 batch operations to process millions of S3 objects

Cloudflare users will very soon be able to deploy Workers without having a Cloudflare domain. They will be able to deploy their Cloudflare Workers to a subdomain of their choice, with an extension of .workers.dev. According to the Cloudflare blog, this is a step towards making it easy for users to get started with Workers and build a new serverless project from scratch. Cloudflare Workers’ serverless execution environment allows users to create new applications or improve existing ones without configuring or maintaining infrastructure. Cloudflare Workers run on Cloudflare servers, and not in a user’s browser, meaning that a user’s code will run in a trusted environment where it cannot be bypassed by malicious clients. workers. dev was obtained through Google’s TLD launch program. Customers can head over to workers.dev where they will be able to claim a subdomain (one per user). workers.dev is fully served using Cloudflare Workers. Zack Bloom, the Director of Product for Product Strategy at Cloudflare, says that workers.dev will especially be useful for Serverless apps. Without cold-starts users will obtain instant scaling to almost any volume of traffic, making this type of serverless seem faster and cheaper. Cloudflare workers have received an amazing response from users all over the internet: Source:HackerNews This news has also been received with much enthusiasm: https://twitter.com/MrAhmadAwais/status/1097919710249783297 You can head over to the Cloudflare blog for more information on this news. Cloudflare’s 1.1.1.1 DNS service is now available as a mobile app for iOS and Android Cloudflare’s Workers enable containerless cloud computing powered by V8 Isolates and WebAssembly Cloudflare Workers KV, a distributed native key-value store for Cloudflare Workers

With the GDPR deadline looming closer everyday, Microsoft has started to apply General Data Protection Regulation (GDPR) to its cloud services. Microsoft recently announced that they are providing some enhancements to help organizations using Azure and Office 365 services meet GDPR requirements. With these improvements they aim at ensuring that both Microsoft's services and the organizations benefiting from them will be GDPR-compliant by the law's enforcement date. Microsoft tools supporting GDPR compliance are as follows: Service Trust Portal, provides GDPR information resources Security and Compliance Center in the Office 365 Admin Center Office 365 Advanced Data Governance for classifying data Azure Information Protection for tracking and revoking documents Compliance Manager for keeping track of regulatory compliance Azure Active Directory Terms of Use for obtaining user informed consent Microsoft recently released a preview of a new Data Subject Access Request interface in the Security and Compliance Center and the Azure Portal via a new tab. According to Microsoft 365 team, this interface is also available in the Service Trust Portal. Microsoft Tech Community post also claims that the portal will be getting a "Data Protection Impacts Assessments" section in the coming weeks. Organizations can now perform a search for "relevant data across Office 365 locations" with the new Data Subject Access Request interface preview. This helps organizations search across Exchange, SharePoint, OneDrive, Groups and Microsoft Teams. As explained by Microsoft, once searched the data is exported for review prior to being transferred to the requestor. According to Microsoft, the Data Subject Access Request capabilities will be out of preview before the GDPR deadline of May 25th. It also claims that IT professionals will be able to execute DSRs (Data Subject Requests) against system-generated logs. To know more in detail you can visit Microsoft’s blog post.

Update: On 25th November, the Quarkus team announced the release of Quarkus 1.0.0.Final bits. Head over to the Quarkus blog for more details on the official announcement. Last week, RedHat’s Quarkus, the Kubernetes native Java framework for GraalVM & OpenJDK HotSpot announced the availability of its first release candidate. It also notified users that its first stable version will be released by the end of this month. Launched in March this year, Quarkus framework uses Java libraries and standards to provide an effective solution for running Java on new deployment environments like serverless, microservices, containers, Kubernetes, and more. Java developers can employ this framework to build apps with faster startup time and less memory than traditional Java-based microservices frameworks. It also provides flexible and easy to use APIs that can help developers to build cloud-native apps, and best-of-breed frameworks. “The community has worked really hard to up the quality of Quarkus in the last few weeks: bug fixes, documentation improvements, new extensions and above all upping the standards for developer experience,” states the Quarkus team. Latest updates added in Quarkus 1.0 A new reactive core based on Vert.x with support for reactive and imperative programming models. This feature aims to make reactive programming a first-class feature of Quarkus. A new non-blocking security layer that allows reactive authentications and authorization. It also enables reactive security operations to integrate with Vert.x. Improved Spring API compatibility, including Spring Web and Spring Data JPA, as well as Spring DI. A Quarkus ecosystem also called as “universe”, is a set of extensions that fully supports native compilation via GraalVM native image. It supports Java 8, 11 and 13 when using Quarkus on the JVM. It will also support Java 11 native compilation in the near future. RedHat says, “Looking ahead, the community is focused on adding additional extensions like enhanced Spring API compatibility, improved observability, and support for long-running transactions.” Many users are excited about Quarkus and are looking forward to trying the stable version. https://twitter.com/zemiak/status/1192125163472637952 https://twitter.com/loicrouchon/status/1192206531045085186 https://twitter.com/lasombra_br/status/1192114234349563905 How Quarkus brings Java into the modern world of enterprise tech Apple shares tentative goals for WebKit 2020 Apple introduces Swift Numerics to support numerical computing in Swift Rust 1.39 releases with stable version of async-await syntax, better ergonomics for match guards, attributes on function parameters, and more Fastly announces the next-gen edge computing services available in private beta

Today, at the ongoing KubeCon 2019, Grafana Labs, an open source analytics and monitoring solution provider, announced that Loki version 1.0 is generally available for production use. Loki is an open source logging platform that provides developers with an easy-to-use, highly efficient and cost-effective approach to log aggregation. The Loki project was first introduced at KubeCon Seattle in 2018. Before the official launch, this project was started inside of Grafana Labs and was internally used to monitor all of Grafana Labs’ infrastructure. It helped ingest around 1.5TB/10 billion log lines a day. Released under the Apache 2.0 license, the Loki tool is optimized for Grafana, Kubernetes, and Prometheus. Just within a year, the project has more than 1,000 contributions from 137 contributors and also has nearly 8,000 stars on GitHub. With Loki 1.0, users can instantaneously switch between metrics and logs, preserving context and reducing MTTR. By storing compressed, unstructured logs and only indexing metadata, Loki is cost-effective and simple to operate by design. It includes a set of components that can be composed into a fully-featured logging stack. Grafana Cloud offers a high-performance, hosted Loki service that allows users to store all logs together in a single place with usage-based pricing. Loki’s design is inspired by Prometheus, the open source monitoring solution for the cloud-native ecosystem, as it offers a Prometheus-like query language called LogQL to further integrate with the cloud-native ecosystem. Tom Wilkie, VP of Product at Grafana Labs, said, “Grafana Labs is proud to have created Loki and fostered the development of the project, building first-class support for Loki into Grafana and ensuring customers receive the support and features they need.” He further added, “We are committed to delivering an open and composable observability platform, of which Loki is a key component, and continue to rely on the power of open source and our community to enhance observability into application and infrastructure.” Grafana Labs also offers enterprise services and support for Loki, which includes: Support and training from Loki maintainers and experts 24 x 7 x 365 coverage from the geographically distributed Grafana team Per-node pricing that scales with deployment Read more about Grafana Loki in detail on GitHub. “Don’t break your users and create a community culture”, says Linus Torvalds, Creator of Linux, at KubeCon + CloudNativeCon + Open Source Summit China 2019 KubeCon + CloudNativeCon EU 2019 highlights: Microsoft’s Service Mesh Interface, Enhancements to GKE, Virtual Kubelet 1.0, and much more! Grafana 6.2 released with improved security, enhanced provisioning, Bar Gauge panel, lazy loading and more

With the wrong architecture, APIs can be a bottleneck to not only your applications but to your entire business. Bottlenecks such as downtime, low performance, or high application complexity, can result in exaggerated infrastructure and organizational costs and lost revenue. Serverless APIs mitigate these bottlenecks with autoscaling capabilities and consumption-based pricing models. Once you start thinking of serverless as not only a remover-of-bottlenecks but also as an enabler-of-business, layers of your application infrastructure become a source of new opportunities. This is especially true of the API layer, as APIs can be productized to scale your business, attract new customers, or offer new services to existing customers, in addition to its traditional role as the communicator between software services. Given the increasing dominance of APIs and API-first architectures, companies and developers are gravitating towards serverless platforms to host APIs and API-first applications to realize these benefits. One serverless compute option to host API’s is Azure Functions, event-triggered code that can scale on-demand, and you only pay for what you use. Gartner predicts that 50 percent of global enterprises will have deployed a serverless functions platform by 2025, up from only 20 percent today. You can publish Azure Functions through API Management to secure, transform, maintain, and monitor your serverless APIs. Faster time to market Modernizing your application stack to run microservices on a serverless platform decreases internal complexity and reduces the time it takes to develop new features or products. Each serverless function implements a microservice. By adding many functions to a single API Management product, you can build those microservices into an integrated distributed application. Once the application is built, you can use API Management policies to implement caching or ensure security requirements. Quest Software uses Azure App Service to host microservices in Azure Functions. These support user capabilities such as registering new tenants and application functionality like communicating with other microservices or other Azure platform resources such as the Azure Cosmos DB managed NoSQL database service. “We’re taking advantage of technology built by Microsoft and released within Azure in order to go to market faster than we could on our own. On average, over the last three years of consuming Azure services, we’ve been able to get new capabilities to market 66 percent faster than we could in the past.” - Michael Tweddle, President and General Manager of Platform Management, Quest Quest also uses Azure API Management as an serverless API gateway for the Quest On Demand microservices that implement business logic with Azure Functions and to apply policies that control access, traffic, and security across microservices. Modernize your infrastructure Developers should be focusing on developing applications, not provisioning and managing infrastructure. API management provides a serverless API gateway that delivers a centralized, fully managed entry point for serverless backend services. It enables developers to publish, manage, secure, and analyze APIs on at global scale. Using serverless functions and API gateways together allows organizations to better optimize resources and stay focused on innovation. For example, a serverless function provides an API through which restaurants can adjust their local menus if they run out of an item. Chipotle turned to Azure to create a unified web experience from scratch, leveraging both Azure API Management and Azure Functions for critical parts of their infrastructure. Calls to back-end services (such as ordering, delivery, and account management and preferences) hit Azure API Management, which gives Chipotle a single, easily managed endpoint and API gateway into its various back-end services and systems. With such functionality, other development teams at Chipotle are able to work on modernizing the back-end services behind the gateway in a way that remains transparent to Smith’s front-end app. “API Management is great for ensuring consistency with our API interactions, enabling us to always know what exists where, behind a single URL,” says Smith. “There are lots of changes going on behind the API gateway, but we don’t need to worry about them.”- Mike Smith, Lead Software Developer, Chipotle Innovate with APIs Serverless APIs are used to either increase revenue, decrease cost, or improve business agility. As a result, technology becomes a key driver of business growth. Businesses can leverage artificial intelligence to analyze API calls to recognize patterns and predict future purchase behavior, thus optimizing the entire sales cycle. PwC AI turned to Azure Functions to create a scalable API for its regulatory obligation knowledge mining solution. It also uses Azure Cognitive Search to quickly surface predictions found by the solution, embedding years of experience into an AI model that easily identifies regulatory obligations within the text. “As we’re about to launch our ROI POC, I can see that Azure Functions is a value-add that saves us two to four weeks of work. It takes care of handling prediction requests for me. I also use it to extend the model to other PwC teams and clients. That’s how we can productionize our work with relative ease.”- Todd Morrill, PwC Machine Learning Scientist-Manager, PwC Quest Software, Chipotle, and PwC are just a few Microsoft Azure customers who are leveraging tools such as Azure Functions and Azure API Management to create an API architecture that ensures your API’s are monitored, managed, and secure. Rethinking your API approach to use serverless technologies will unlock new capabilities within your organization that are not limited by scale, cost, or operational resources. Get started immediately Learn about common serverless API architecture patterns at the Azure Architecture Center, where we provide high-level overviews and reference architectures for common patterns that leverage Azure Functions and Azure API Management, in addition to other Azure services. Reference architecture for a web application with a serverless API. 

For the past several years, Microsoft and Red Hat have worked together to co-develop hybrid cloud solutions intended to enable greater customer innovation. In 2019, we launched Azure Red Hat OpenShift as a fully managed, jointly engineered implementation of Red Hat OpenShift running on Red Hat OpenShift 3.11 that is deeply integrated into the Azure control plane. With the release of Red Hat OpenShift 4, we announced the general availability of Azure Red Hat OpenShift on OpenShift 4 in April 2020. Today we’re sharing that in collaboration with Red Hat, we are dropping the price of Red Hat OpenShift licenses on Azure Red Hat OpenShift worker nodes by up to 77 percent. We’re also adding the choice of a three-year term for Reserved Instances (RIs) on top of the existing one year RI and pay as you go options, with a reduction in the minimum number of virtual machines required. The new pricing is effective immediately. Finally, as part of the ongoing improvements, we are increasing the Service Level Agreement (SLA) to be 99.95 percent. With these new price reductions, Azure Red Hat OpenShift provides even more value with a fully managed, highly-available enterprise Kubernetes offering that manages the upgrades, patches, and integration for the components that are required to make a platform. This allows your teams to focus on building business value, not operating technology platforms. How can Red Hat OpenShift help you? As a developer Kubernetes was built for the needs of IT Operations, not developers. Red Hat OpenShift is designed so developers can deploy apps on Kubernetes without needing to learn Kubernetes. With built-in Continuous Integration (CI) and Continuous Delivery (CD) pipelines, you can code and push to a repository and have your application up and running in minutes. Azure Red Hat OpenShift includes everything you need to manage your development lifecycle; standardized workflows, support for multiple environments, continuous integration, release management, and more. Also included is the provision self-service, on-demand application stacks, and deploy solutions from the Developer Catalog such as OpenShift Service Mesh, OpenShift Serverless, Knative, and more. Red Hat OpenShift provides commercial support for the languages, databases, and tooling you already use, while providing easy access to Azure services such as Azure Database for PostgreSQL and Azure Cosmos DB, to enable you create resilient and scalable cloud native applications. As an IT operator Adopting a container platform lets you keep up with application scale and complexity requirements. Azure Red Hat OpenShift is designed to make deploying and managing the container platform easier, with automated maintenance operations and upgrades built right in, integrated platform monitoring—including Azure Monitor for Containers, and a support experience directly from the Azure support portal. With Azure Red Hat OpenShift, your developers can be up and running in minutes. You can scale on your terms, from ten containers to thousands, and only pay for what you need. With one-click updates for platform, services, and applications, Azure Red Hat OpenShift monitors security throughout the software supply chain to make applications more stable without reducing developer productivity. You can also leverage built-in vulnerability assessment and management tools in Azure Security Center to scan images that are pushed to, imported, or pulled from an Azure Container Registry. Discover Operators from the Kubernetes community and Red Hat partners, curated by Red Hat. You can install Operators on your clusters to provide optional add-ons and shared services to your developers, such as AI and machine learning, application runtimes, data, document stores, monitoring logging and insights, security, and messaging services. Regional availability Azure Red Hat OpenShift is available in 27 regions worldwide, and we’re continuing to expand that list. Over the past few months, we have added support for Azure Red Hat OpenShift in a number of regions, including West US, Central US, North Central US, Canada Central, Canada East, Brazil South, UK West, Norway East, France Central, Germany West Central, Central India, UAE North, Korea Central, East Asia, and Japan East. Industry compliance certifications To help you meet your compliance obligations across regulated industries and markets worldwide, Azure Red Hat OpenShift is PCI DSS, FedRAMP High, SOC 1/2/3, ISO 27001 and HITRUST certified. Azure maintains the largest compliance portfolio in the industry, both in terms of the total number of offerings and also the number of customer-facing services in assessment scope. For more details, check the Microsoft Azure Compliance Offerings, as well as the number of customer-facing services in the assessment scope. Next steps Try Azure Red Hat OpenShift now. We are excited about these new lower prices and how this helps our customers build their business on a platform that enables IT operations and developers to collaborate effectively, develop, and deploy containerized applications rapidly with strong security capabilities.

Serverless applications began gaining popularity when Amazon launched AWS Lambda back in the year 2014. Since then, we are becoming more familiar with Serverless Computing as it is exponentially growing in use and reference among the vendors who are entering the markets with their own solutions. The reason behind the hype of serverless computing is it requires no infrastructure management which is a modern approach for the enterprise to lessen up the workload. What is Serverless Computing? It is a special kind of software architecture which executes the application logic in an environment without visible processes, operating systems, servers, and virtual machines. Serverless Computing is also responsible for provisioning and managing the infrastructure entirely by the service provider. Serverless defines a cloud service that abstracts the details of the cloud-based processor from its user; this does not mean servers are no longer needed, but they are not user-specified or controlled. Serverless computing refers to serverless architecture which relates to the applications that depend on a third-party service (BaaS) and container (FaaS). Image Source: Tatvasoft The top serverless computing providers like Amazon, Microsoft, Google and IBM provide serverless computing like FaaS to companies like NetFlix, Coca-cola, Codepen and many more. FaaS Function as a Service is a mode of cloud computing architecture where developers write business logic functions or java development code which are executed by the cloud providers. In this, the developers can upload loads of functionality into the cloud that can be independently executed. The cloud service provider manages everything from execution to scaling it automatically. Key components of FaaS: Events - Something that triggers the execution of the function is regarded as an event. For instance: Uploading a file or publishing a message. Functions - It is regarded as an independent unit of deployment. For instance: Processing a file or performing a scheduled task. Resources - Components used by the function is defined as resources. For instance: File system services or database services. BaaS Backend as a Service allows developers to write and maintain only the frontend of the application and enable them by using the backend service without building and maintaining them. The BaaS service providers offer in-built pre-written software activities like user authentication, database management, remote updating, cloud storage and much more. The developers do not have to manage servers or virtual machines to keep their applications running which helps them to build and launch applications more quickly. Image courtesy - Gallantra Use-Cases of Serverless Computing Batch jobs scheduled tasks: Schedules the jobs that require intense parallel computation, IO or network access. Business logic: The orchestration of microservice workloads that execute a series of steps for applying your ideas. Chatbots: Helps to scale at peak demand times automatically. Continuous Integration pipeline: It has the ability to remove the need for pre-provisioned hosts. Captures Database change: Auditing or ensuring modifications in order to meet quality standards. HTTP REST APIs and Web apps: Sends traditional request and gives a response to the workloads. Mobile Backends: Can build on the REST API backend workload above the BaaS APIs. Multimedia processing: To execute a transformational process in response to a file upload by implementing the functions. IoT sensor input messages: Receives signals and scale in response. Stream processing at scale: To process data within a potentially infinite stream of messages. Should you use Serverless Computing? Merits Fully managed services - you do not have to worry about the execution process. Supports event triggered approach - sets the priorities as per the requirements. Offers Scalability - automatically handles load balancing. Only pay for Execution time - you need to pay just for what you used. Quick development and deployment - helps to run infinite test cases without worrying about other components. Cut-down time-to-market - you can look at your refined product in hours after creating it. Demerits Third-party dependency - developers have to depend on cloud service providers completely. Lacking Operational tools - need to depend on providers for debugging and monitoring devices. High Complexity - takes more time and it is difficult to manage more functions. Functions cannot stay for a longer period - only suitable for applications having shorter processes. Limited mapping to database indexes - challenging to configure nodes and indexes. Stateless Functions - resources cannot exist within a function after the function stops to exit. Serverless computing can be seen as the future for the next generation of cloud-native and is a new approach to write and deploy applications that allow developers to focus only on the code. This approach helps to reduce the time to market along with the operational costs and system complexity. Third-party services like AWS Lambda has eliminated the requirement to set up and configure physical servers or virtual machines. It is always best to take an expert's advice that holds years of experience in software development with modern technologies. Author Bio: Working as a manager in a Software outsourcing company Tatvasoft.com, Vikash Kumar has a keen interest in blogging and likes to share useful articles on Computing. Vikash has also published his bylines on major publication like Kd nuggets, Entrepreneur, SAP and many more. Google Cloud Firestore, the serverless, NoSQL document database, is now generally available Kelsey Hightower on Serverless and Security on Kubernetes at KubeCon + CloudNativeCon Introducing GitLab Serverless to deploy cloud-agnostic serverless functions and applications