Ever since the dawn of the Internet, people have struggled with how to get one computer to talk to another. Early business systems had no provision for such interactions. They were entirely closed— worlds unto themselves. As enterprises set up early networks, the question of how to get applications to interact with each other became a pressing business concern, and led to the introduction of Remote Procedure Calls (RPCs). A client computer might directly interact with the program running on a server or host by calling procedures (or subroutines, methods, etc.) over the network.
The IoT's basic concept of collecting data from as many sources possible to drive better decision making, create process innovation and realize additional revenue has been in use at large enterprises with deep pockets for decades. So what has changed? In his session at @ThingsExpo, Prasanna Sivaramakrishnan, Solutions Architect at Red Hat, will discuss the impact commodity hardware, ubiquitous connectivity, and innovations in open source software are having on the connected universe of people, things and information in the IoT.
The IoT's basic concept of collecting data from as many sources possible to drive better decision making, create process innovation and realize additional revenue has been in use at large enterprises with deep pockets for decades. So what has changed? In his session at @ThingsExpo, Prasanna Sivaramakrishnan, Solutions Architect at Red Hat, will discuss the impact commodity hardware, ubiquitous connectivity, and innovations in open source software are having on the connected universe of people, things and information in the IoT.
If the calibration engineer does the calibration incorrectly – or a malefactor intentionally introduces a miscalibration – then the end result would be off. Every time. Even though there was nothing wrong with the sensor data, no security breach between the sensor and emissions device, and furthermore, every line of code in the device was completely correct. In fact, the only way to detect a calibration attack is by running an independent analog test. In other words, someone would have to get their own exhaust particulate measuring device and run tests on real vehicles to see if the emissions device was properly calibrated.
A business process is any sequence of events or tasks that must be performed for a business to operate. For example, a customer’s purchase resulting in a delivery is a key business process that exists in all for-profit organizations. BPM is neither task management or project management (although it can occur within a project context). BPM is focused more on repetitive ongoing processes that follow a predictable pattern.
Container technology is shaping the future of DevOps and it’s also changing the way organizations think about application development. With the rise of mobile applications in the enterprise, businesses are abandoning year-long development cycles and embracing technologies that enable rapid development and continuous deployment of apps. In his session at DevOps Summit, Kurt Collins, Developer Evangelist at Built.io, examines how Docker has evolved into a highly effective tool for application delivery by allowing increasingly popular Mobile Backend-as-a-Service (mBaaS) platforms to quickly create and scale enterprise apps across mobile, web and IoT.
Over the past few years, there has been an explosion in the volume of data. To tackle this big data explosion, there has been a rise in the number of successful Hadoop projects in enterprises. Due to the large volumes of data, the emergence of Hadoop technology, and the need to store all soloed data in one place, has prompted a phenomenon among enterprises called: Data Lake.
To let other TypeScript libraries use your library, you need to create a .d.ts file to declare all your public APIs of your library with the typing information. The enforce to clearly list all your public APIs for each libraries you are developing. We found it serves as a quick and accurate reference for all your APIs. Refer to https://github.com/borisyankov/DefinitelyTyped for TypeScript definition files created for large amounts of JavaScript libraries.
Martin Fowler describes how infrastructure automation is a key enabler of microservices: “Many of the products or systems being build with microservices are being built by teams with extensive experience of Continuous Delivery and it’s precursor, Continuous Integration. Teams building software this way make extensive use of infrastructure automation techniques. This is illustrated in the build pipeline shown below.”
In their session at DevOps Summit, Asaf Yigal, co-founder and the VP of Product at Logz.io, and Tomer Levy, co-founder and CEO of Logz.io, will explore the entire process that they have undergone – through research, benchmarking, implementation, optimization, and customer success – in developing a processing engine that can handle petabytes of data. They will also discuss the requirements of such an engine in terms of scalability, resilience, security, and availability along with how the architecture accomplishes these requirements. Lastly, they will review the gory details of the technologies they have chosen, which are based mostly on open source platforms including Kafka, Elasticsearch, and Docker as well as other proprietary technologies.
SYS-CON Events announced today that Vitria will exhibit, conduct a demo theater presentation, and CTO Dale Skeen will deliver a technical session at @ThingsExpo, which will take place on November 3–5, 2015, at the Santa Clara Convention Center in Santa Clara, CA. Vitria is a leading provider of advanced analytics platforms that enable businesses to transform their operations and boost revenue growth through Faster Analytics, Smarter Actions, and Better Outcomes Faster.
Test-Driven Development is a great tool for functional testing, but can you apply the same technique to performance testing? Why not? The purpose of TDD is to build out small unit tests, or scenarios, under which you control your initial coding. Your tests will fail the first time you run them because you haven’t actually developed any code. But once you do start coding, you’ll end up with just enough code to pass the test. There’s no reason the same philosophy can’t be applied to performance testing.
In their session at @ThingsExpo, Shyam Varan Nath, Principal Architect at GE, and Ibrahim Gokcen, who leads GE's advanced IoT analytics, focused on the Internet of Things / Industrial Internet and how to make it operational for business end-users. Learn about the challenges posed by machine and sensor data and how to marry it with enterprise data. They also discussed the tips and tricks to provide the Industrial Internet as an end-user consumable service using Big Data Analytics and Industrial Cloud.
In a recent research, Analyst firm IDC found that the average cost of a critical application failure is $500,000 to $1 million per hour and the average total cost of unplanned application downtime is $1.25 billion to $2.5 billion per year for Fortune 1000 companies. In addition to the findings on the cost of the downtime, the research also highlighted best practices for development, testing, application support, infrastructure, and operations teams.
Electric power utilities face relentless pressure on their financial performance, and reducing distribution grid losses is one of the last untapped opportunities to meet their business goals. Combining IoT-enabled sensors and cloud-based data analytics, utilities now are able to find, quantify and reduce losses faster – and with a smaller IT footprint. Solutions exist using Internet-enabled sensors deployed temporarily at strategic locations within the distribution grid to measure actual line loads.
If the calibration engineer does the calibration incorrectly – or a malefactor intentionally introduces a miscalibration – then the end result would be off. Every time. Even though there was nothing wrong with the sensor data, no security breach between the sensor and emissions device, and furthermore, every line of code in the device was completely correct. In fact, the only way to detect a calibration attack is by running an independent analog test. In other words, someone would have to get their own exhaust particulate measuring device and run tests on real vehicles to see if the emissions device was properly calibrated.
The Internet of Things is clearly many things: data collection and analytics, wearables, Smart Grids and Smart Cities, the Industrial Internet, and more. Cool platforms like Arduino, Raspberry Pi, Intel's Galileo and Edison, and a diverse world of sensors are making the IoT a great toy box for developers in all these areas. In this Power Panel at @ThingsExpo, moderated by Conference Chair Roger Strukhoff, panelists will discuss what things are the most important, which will have the most profound effect on the world, and what should we expect to see over the next couple of years.
Still here? Okay then, let me explain further. This whole thing started because I was reading the Internet the other day and happened upon a claim that stated: “the attack surface for cloud applications is dramatically different than for highly controlled data centers”. And that made me frustrated because it isn’t true at all.
What it means to build quality software has taken a beating over the years. We’re no longer content to strive for defect-free code. We must also make sure the software meets both its functional and nonfunctional requirements. Only now with the rise of more Agile ways of thinking, we’ve placed the notion of a software requirement under the microscope, as building flexible, resilient software often trumps checking items off our requirements list.
Riak TS is focused to handle time series application needs. It can do fast read/write to IOT devices, there in is its strength. It also targets financial and economics data as well as in scientific research applications. This is straight from Riak TS: "Riak TS automatically co-locates, replicates, and distributes data across the cluster to achieve fast performance and high availability. The unique master-less architecture enables near-linear scale using commodity hardware so you can easily add capacity as your time series data grows."
As with most modernized economies, the United States economy utilizes capitalist principles. It is only fitting that we invented a technological solution that will help companies engage in c-api-talism using APIs in a more efficient manner. If we look back into the history of mankind, we progressed towards more civilized, mature, monetary-based economies on a steady basis. The progression from the Stone Age, to the Bronze Age, to the Iron Age, to the Industrial Age and to the current Digital Age all made strides towards the current digital economy.
Microservices architecture compartmentalize the application by function allowing for greater application flexibility, portability and an increase in update/changes. This architecture introduces new layer of monitoring challenges to an already complex application environment. The strides and enhancements we made in CA APM 10 with APM Team Center Perspectives, Timeline views and Differential Analysis has helped us to make strides in solving these challenges of monitoring microservices that include:
No one should need to be convinced the value of good data. It gives you the confidence to make decisions quickly and with less risk, it allows you to measure your success, and it lets you know when you need to adjust your course. But there’s a difference between knowing the value of data, and creating a culture around it. A data-driven culture is a culture where everyone quantifies their actions as much as possible, and asks themselves how their teams are having a tangible impact on the business. It turns your entire organization into a squad of analysts. But creating a data-driven culture isn’t always easy. Here are five steps that will help you get there.
The move to DevOps also introduces additional constraints to our burgeoning Iron Polygon, as individual projects become less distinct. In an environment focused on continuous automated testing as well as continuous integration and deployment, individual iterations become the project unit as organizations establish regular cadences of repeated iterations (link is external) instead of the discrete, monolithic project releases that characterize traditional waterfall-oriented development.
To let other TypeScript libraries use your library, you need to create a .d.ts file to declare all your public APIs of your library with the typing information. The enforce to clearly list all your public APIs for each libraries you are developing. We found it serves as a quick and accurate reference for all your APIs. Refer to https://github.com/borisyankov/DefinitelyTyped for TypeScript definition files created for large amounts of JavaScript libraries.