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Tag: real-time

  • Dependability is Crucial for Real-Time Experiences

    Dependability is Crucial for Real-Time Experiences

    Millions of people around the world experienced a major disruption after an October 2021 outage saw Facebook, WhatsApp and Instagram go offline. A few days prior, the popular workplace collaboration platform, Slack, also went down for some users. And in the last few weeks of 2021, Amazon’s AWS caused considerable global chaos after significant networking issues in its busiest data center, US East 1, disrupting streaming services such as Disney+ and Netflix.

    Downtime can be costly, causing organizations to lose $5,600 per minute and up to $300,000 per hour, on average, according to Gartner. But it’s not only financial and reputational loss that businesses need to worry about. Outages also seriously downgrade—and in the case of real-time experiences, completely disrupt—the customer experience.

    At a time when consumers are demanding more live and interactive digital experiences, organizations can ill afford disruption or downtime, as customers quickly move to other services that ‘just work’.

    It’s not just the capacity within a real-time system that matters, but also globally distributed failover capabilities when something does go wrong. While organizations could try to build their own failover mechanisms, it’s extremely difficult to failover so services continue seamlessly, regardless of the status of its underlying infrastructure. Simple failover systems not only take longer to resume but typically suffer data loss during the time that a region is disrupted. Businesses need to know that even if, say, AWS suffers an outage, they won’t be affected.

    This is why it’s vital that organizations get it right when looking to develop their own real-time infrastructure. Managing tens of thousands if not hundreds of thousands of concurrent connections while synchronizing data in real-time means that if anything does go wrong it’s immediately obvious to users. If tech behemoths like Amazon and Facebook can’t get it right, what chance do organizations with far fewer resources have when building and managing their own real-time infrastructure?

    The Steps to Success With Real-Time Infrastructure

    Regardless of whether it’s for synchronized multi-user collaboration, audience engagement or instant updates, developers have a hard enough time developing even the most basic of real-time infrastructure, let alone making sure it’s dependable. There are four key elements to achieve dependability: Predictable performance, data integrity, reliability of service and high scalability.

    • Predictable performance: When we think of performance we usually imagine more computing power or speed. But when it comes to real-time, it’s not just about minimizing latency and bandwidth, it’s about having a predictable system. If developers have global latencies and bandwidth within certain operating boundaries, it provides certainty in uncertain operating conditions. This makes it easier to design, build and scale features around this certainty.
    • Data integrity: As we all know, the internet can be an unreliable network. Users abruptly disconnect and reconnect all the time, resulting in data that gets lost, is delivered in the wrong sequence or that is sent multiple times. As a result, organizations must ensure their infrastructure can guarantee high integrity without sacrificing anything else.
    • Reliability of service: The live nature of delivering updates in real-time requires total reliability. Outages can cause distrust and annoyance from users. Organizations could find their reputation taking a hit or customers quickly jumping ship if reliability proves to be a recurring issue. To prevent this, organizations should develop infrastructure that’s fault-tolerant and redundant at both a global and regional level so they can deliver a great experience even if there are multiple failures.
    • High scalability: More often than not, delivering an experience in real-time can result in unpredictable traffic; for example, a huge number of people wanting sports updates for a World Cup game. If thousands of devices connect over a short period of time but capacity can’t scale up quickly enough, then an outage will occur. To avoid this, developers must use infrastructure that can be elastic and meet changing levels of demand. Otherwise, the user experience is seriously affected and real-time capabilities crash when the network is swamped with connections it can’t cope with.

    While organizations often build their own infrastructure with the best of intentions, it’s easy for them to run into trouble. Most lack the internal expertise, resources and time; plus, going it alone often results in a huge technical debt. It’s also a massive undertaking, due to the amount of ongoing complexity and cost involved.

    Third-Party Partnerships Enable Dependability

    Unless organizations have the resources, finances and expertise of the likes of Amazon or Google, then building your own real-time infrastructure is just setting yourself up for failure. Instead, they should save on development cycles and focus on generating revenue more quickly by offloading their real-time infrastructure needs to a third party. This will mean organizations can design without limitations and focus on solving the challenges that really matter to them while putting in place real-time infrastructure that is as dependable and future-proof as possible.

  • Harmonizing Real-Time on Edge Platforms

    Harmonizing Real-Time on Edge Platforms

    Edge computing platforms sit at the boundary between the real-time world and the digital enterprise. Uninterrupted, uncorrupted data from the edge is a must if analytics in the cloud drive reliable business decisions. What’s the best approach: using Linux, an RTOS (real-time operating system), a hypervisor or something else for edge platforms?  Let’s talk about harmonizing real-time on edge platforms and introduce a new foundation project in the Linux Foundation’s LF Edge family.

    Real-Time and Deterministic

    Real-time only means events are captured, tagged and processed as they unfold in the real world. That cadence can be seconds, milliseconds or microseconds depending on how many events and how often they occur and how tasks and algorithms stay in control. Three operating system characteristics determine how well real-time execution keeps pace: prioritization, interrupt response time and context switch time.

    Prioritization ensures that tasks receive resources when needed. Tasks at a lower priority should pre-empt when a higher priority task requests service. A task refusing to yield to pre-emption can throw off the prioritization scheme, causing missed deadlines.

    Interrupt response time measures the latency from the time an event requests service via a hardware interrupt to when the handler task executes. Real-time hardware platforms often place high-priority events on hardware interrupts for fastest pre-emption.

    Context switch time is softer scheduling at work. It measures the time for a change in processing control from one execution entity to another, swapping out resources including registers, cache and memory as needed.

    Deterministic means there are no surprises in behavior. The faster real-time events happen, and the harder a system works, the more likely non-determinism surfaces. One venture into virtual memory paging or a burst of networking activity can show up at an inopportune time, even though under most conditions real-time performance is adequate.

    ‘Hard’ vs. ‘Soft’ Real-Time

    That’s why most people think of real-time as “hard” with a fast, deterministic operating system. RTOS platforms optimize the kernel and only build things in around it that are necessary, providing rigorous and sometimes mathematically proven scheduling for many tasks.

    “Soft” real-time is more forgiving. On a fast processor, interrupt response time is tiny compared to the execution window. A system that isn’t deterministic can, if there is enough margin in context switch time, keep up with real-time events on a slower scale. Linux, while not deterministic, can handle some real-time needs through minimizing packages and tuning the kernel for better prioritization.

    Linux also benefits from lighter context switching. Originally, execution entities in Linux were resource-heavy processes. Now, threads can handle tasks with far less switching overhead. POSIX threads standardized the approach with portability between Linux and RTOS environments.

    How fast are threads? According to a recent synthetic thread benchmark by Eli Bendersky, switching on server-class platforms with enough memory, cache and storage can be in the range of 2 microseconds with 10,000 threads under ideal conditions. Eli pointed out his test environment has more RAM than many edge hardware platforms provide, but most edge applications won’t need that many threads, either.

    So, the line for soft real-time has moved down into new territory, making the trade-off between hard and soft a bit blurrier.

    Hypervisors and Orchestration

    If your DevOps team commits to an RTOS, you may give up some familiar functionality and have a learning curve to deal with, but you get assured hard real-time performance. If you go with Linux, you get the tools and coding practices you’re used to, but soft real-time performance can be an issue as code piles up.

    The leaders in RTOS platforms with enterprise networking noticed this, too. Recently they’ve turned to hypervisors in a bare-metal approach. A hypervisor can capture the benefits of environments working together, so teams are not forced into an either/or operating system choice. This is especially important if the edge application requires some form of certification, such as in medical, industrial or defense applications. Certified code can be compartmentalized on an RTOS, while Linux runs alongside.

    Linux providers are turning more toward orchestration layers and containers. It’s an application focus speeding up deployment, with more scalability and less hardware dependence. It also brings the edge into the enterprise faster with the same application deployment strategy anywhere. More code means more determinism risk.

    Convergence is a faint hope on this landscape with competing objectives, but a new approach offers a path for software reuse and rapid deployment.

    Harmonizing the Edge

    The Linux Foundation is active across the spectrum of IoT development, from the Zephyr open source RTOS to various embedded Linux projects. One of the newest projects in the LF Edge initiative is a foundation targeting a blend of deployment models in a consistent, open approach.

    Project EVE (short for Edge Virtualization Engine) supports containers, clusters, virtual machines and unikernels simultaneously. It’s a slim bare-metal runtime offering hardware root of trust, device resource management and software update and patch functions. EVE can host any combination of apps in virtual machines or containers, including running an RTOS with its application in a virtual machine. It can even assign CPU and GPU cores to specific applications for enhanced determinism.

    On the EVE road map is support for the ACRN hypervisor (another LF Edge project) and shrinking the EVE runtime for smaller embedded-class edge platforms. These efforts are essential where real-time requirements become harder and a hypervisor plus an RTOS makes sense. For softer real-time environments, EVE is adding support for Kubernetes K3S, Docker Compose, VPNs for public clouds and mesh networking for data flow between edge platforms.

    While the project is still young, EVE holds great promise for DevOps teams working the edge. We’d look forward to seeing some benchmarking on a real-time scale; it likely handles soft real-time needs as well as Linux today. By harmonizing a range of diverse approaches into one foundation, EVE is creating a space for real-time on edge platforms no matter which development perspective teams come from.

  • Panaya Offers Best-In-Class Integrations to Better Support Modern Software Development and Delivery

    Support for over 150 leading industry tools and services adds essential visibility and reporting capabilities to its Enterprise Agile Delivery Platform

    Hackensack, NJ – October 16, 2018 – Panaya, the leader in SaaS-based testing and continuous delivery, today announced the integration of over 150 leading application development and delivery tools and services into Panaya Release Dynamix (RDx), its Enterprise Agile Delivery (EAD) platform. Users can now take advantage of the tools they already employ every day to increase visibility, collaboration and communication among all stakeholders – the business, development, operations and test teams. With these new RDx integrations, organizations can now deliver application changes from ideation to realization in one unified platform.

    Digital transformation requires enterprises to adopt a continuous delivery model where release cadences are measured in days, not quarters, and quality is guaranteed. To get there, organizations need to apply agile methodologies, but are often limited by existing tools and technologies that create siloed work environments. These best-in-class integrations now offered by Panaya include many of the leading applications for software delivery, such as Jira, ServiceNow, Tricentis Tosca, CA Rally, Bugzilla, Salesforce and more, allowing Panaya’s RDx and Panaya’s test acceleration platform, Panaya Test Dynamix, to fully support continuous integration and continuous delivery.

    The new RDx integrations offer end-to-end visibility and connect the fragmented delivery tool chain to better address the risks associated with business-critical application delivery. From initial business change requests to testing and production, these RDx integrations ensure application development and delivery, project management and business teams can continue to leverage the tools they choose with greater visibility into where items are on the delivery pipeline, while delivering on time and without sacrificing quality. Additionally, open channels and better alignment with business objectives and requirements allows application development and delivery teams to gain a better understanding of the value of each delivery.

    “The pace of delivery in today’s development ecosystems is daunting, and delivering quality releases is hampered by a truly fragmented toolchain ecosystem. There is a plethora of solutions and tools in use today, and rather than force users into yet another solution and cause even more multiplicity, we opened the door to allow customers to use what they already have, seamlessly with Panaya Release Dynamix,” said Jake Klein, CEO of Panaya. “This is what Panaya’s Enterprise Agile Delivery is all about, ensuring all stakeholders involved in the business process have the tools they need in a single, holistic platform that proves the business value faster by managing changing priorities, all while juggling shorter release cycles to meet the continuously evolving needs of the business.”

    These new integrations also cover the gaps left from one tool to another, such as development teams needing to manually provide dev execution and backlog data since there is no visibility between the disparate tools. With extended visibility, IT teams and business managers can make more informed decisions and achieve greater business agility through collaboration.

    Panaya RDx provides a holistic and integrated environment that enables collaboration with all stakeholders involved in the business process, and the visualization, management and risk assessment of application delivery and value streams, while monitoring investment buckets to ensure strategic alignment. By providing real-time insight into risk and quality, corrective actions can be automatically generated, allowing for safe allocation relief and the continual flow of value. Panaya RDx also offers complete visibility of the entire delivery pipeline, so users can save time without having to sacrifice quality.

    Since 2008, over 2,000 companies in 62 countries, including a third of the Fortune 500, have used Panaya to delivery quick quality change to enterprise applications. Customers are from a variety of sectors including automotive, pharmaceutical, retail, manufacturing and more.

    For more information on available integration within the Panaya Enterprise Agile Delivery platform, visit www.panaya.com/agile-delivery/integrations.

    About Panaya

    Panaya, an Infosys company, enables organizations to accelerate application change and continuously deliver innovation with its Enterprise Agile Delivery Platform. Panaya provides cloud-based application delivery, and testing solutions that ensure collaboration between Business and IT. Enabling enterprise agility with faster release velocity and uncompromising quality, Panaya delivers an optimized user experience with end-to-end visibility of the application lifecycle. Since 2008, 2,000 companies in 62 countries, including a third of the Fortune 500, have been using Panaya to deliver quick quality change to enterprise applications.