Imagine a world where product owners, Development, QA, IT Operations, and Infosec work together, not only to help each other, but also to ensure that the overall organization succeeds. By working toward a common goal, they enable the fast flow of planned work into production (e.g., performing tens, hundreds, or even thousands of code deploys per day), while achieving world-class stability, reliability, availability, and security.
The goal of Continuous Testing is to shift testing left to find defects earlier and release software faster. This can be achieved by integrating a set of open source functional and performance testing tools in the early stages of your software delivery lifecycle. There is one process that binds all application delivery stages together into one well-orchestrated machine: Continuous Testing. Continuous Testing is the conveyor belt between the Software Factory and production stages. Artifacts are moved from one stage to the next only after they have been tested and approved to continue. New code submitted to the repository is tested upon commit. When tests fail, the code is rejected. Subsystems are approved as part of periodic builds on their way to the delivery stage, where the system is being tested as production ready. The release process stops when tests fail. The key is to shift test creation and execution to the left, rather than creating tests after development is complete. As code is committed and promoted, all tests run in the background near instantaneously, as there is no longer time for human intervention in a continuous deployment cycle.
SYS-CON Events announced today that Grape Up will exhibit at SYS-CON's 21st International Cloud Expo®, which will take place on Oct. 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Grape Up is a software company specializing in cloud native application development and professional services related to Cloud Foundry PaaS. With five expert teams that operate in various sectors of the market across the U.S. and Europe, Grape Up works with a variety of customers from emerging startups to Fortune 1000 companies.
[Opening Scene]: Billy Dean is pacing the office. He’s struggling to keep his delivery trucks at full capacity and on the road. Random breakdowns, unexpected employee absences, and unscheduled truck maintenance are impacting bookings, revenues and ultimately customer satisfaction. He keeps hearing from his business customers how they are leveraging data science to improve their business operations. Billy Dean starts to wonder if data science can help him. As he contemplates what data science can do for him, he slowly drifts off to sleep, and visions of Data Science starts dancing in his head…
Monitoring of Docker environments is challenging. Why? Because each container typically runs a single process, has its own environment, utilizes virtual networks, or has various methods of managing storage. Traditional monitoring solutions take metrics from each server and applications they run. These servers and applications running on them are typically very static, with very long uptimes. Docker deployments are different: a set of containers may run many applications, all sharing the resources of one or more underlying hosts. It's not uncommon for Docker servers to run thousands of short-term containers (e.g., for batch jobs) while a set of permanent services runs in parallel. Traditional monitoring tools not used to such dynamic environments are not suited for such deployments. On the other hand, some modern monitoring solutions (e.g. SPM from Sematext) were built with such dynamic systems in mind and even have out of the box reporting for docker monitoring. Moreover, container resource sharing calls for stricter enforcement of resource usage limits, an additional issue you must watch carefully. To make appropriate adjustments for resource quotas you need good visibility into any limits containers have reached or errors they have caused. We recommend using alerts according to defined limits; this way you can adjust limits or resource usage even before errors start happening.
First there was the Stone Age. Then we learned how to manipulate and smelt metals, which led to an Agrarian age. From there, machines helped bring about the Industrial age, then the Space Age. So where are we now? Shall we call it the Network Age? Metcalfe’s Law holds that the value of a connected network, telecommunications in the parlance of his day, is proportional to the square of the number of connected users. Or stated more simply, the utility of a connected ‘thing’ increases as more and more ‘things’ are connected. The telephone acts as an easy example. One phone by itself is a paperweight, but one million connected to the same network is immeasurably powerful.
It has been an amazing year for Docker and the container industry. We had 3 major releases of Docker engine this year , and tremendous increase in usage. The community has been following along and contributing amazing Docker resources to help you learn and get hands-on experience. Here’s some of the top read and viewed content for the year. Of course releases are always really popular, particularly when they fit requests we had from the community.
Grape Up is a software company, specialized in cloud native application development and professional services related to Cloud Foundry PaaS. With five expert teams that operate in various sectors of the market across the USA and Europe, we work with a variety of customers from emerging startups to Fortune 1000 companies.
Automation is enabling enterprises to design, deploy, and manage more complex, hybrid cloud environments. Yet the people who manage these environments must be trained in and understanding these environments better than ever before. A new era of analytics and cognitive computing is adding intelligence, but also more complexity, to these cloud environments. How smart is your cloud? How smart should it be? In this power panel at 20th Cloud Expo, moderated by Conference Chair Roger Strukhoff, panelists will look at the evolving nature of hybrid cloud, how it affects enterprise IT staffing requirements, and what skills are needed to be successful.
Translating agile methodology into real-world best practices within the modern software factory has driven widespread DevOps adoption, yet much work remains to expand workflows and tooling across the enterprise. As models evolve from pockets of experimentation into wholescale organizational reinvention, practitioners find themselves challenged to incorporate the culture and architecture necessary to support DevOps at scale. In his session at @DevOpsSummit at 20th Cloud Expo, Anand Akela, Senior Director of DevOps Solutions at CA Technologies, will discuss how existing adopters are employing unified agile and DevOps techniques to engage functional processes and toolchains that deliver increased software quality, faster time-to-market and measurably improved customer experience.
All clouds are not equal. To succeed in a DevOps context, organizations should plan to develop/deploy apps across a choice of on-premise and public clouds simultaneously depending on the business needs. This is where the concept of the Lean Cloud comes in - resting on the idea that you often need to relocate your app modules over their life cycles for both innovation and operational efficiency in the cloud. In his session at @DevOpsSummit at19th Cloud Expo, Valentin (Val) Bercovici, CTO of SolidFire, discussed how to leverage this concept to seize on the creativity and business agility to make it real.
Enterprises and governments rely upon the timely transfer of mission-critical information to keep their projects and operations flowing smoothly. To do so requires a complex chain of communications hubs working efficiently, and even when they are working optimally, there can still be seconds of lag time between communications. That may not seem like much, but being able to get information a second faster than the competition (or the enemy) can make a huge difference.
Everyone wants to use containers, but monitoring containers is hard. New ephemeral architecture introduces new challenges in how monitoring tools need to monitor and visualize containers, so your team can make sense of everything. In his session at @DevOpsSummit, David Gildeh, co-founder and CEO of Outlyer, will go through the challenges and show there is light at the end of the tunnel if you use the right tools and understand what you need to be monitoring to successfully use containers in your environments.
Is your application too difficult to manage? Do changes take dozens of developers hundreds of hours to execute, and frequently result in downtime across all your site’s functions? It sounds like you have a monolith! A monolith is one of the three main software architectures that define most applications. Whether you’ve intentionally set out to create a monolith or not, it’s worth at least weighing the pros and cons of the different architectural approaches and deciding which one makes the most sense for your applications. The proper design pattern can save your organization time and money, and can make your engineers a whole lot happier. But how will you know which is right for you? Read on to figure out if a monolith, microservices, or self-contained system makes the most sense for your development team.
Software as a service (SaaS), one of the earliest and most successful cloud services, has reached mainstream status. According to Cisco, by 2019 more than four-fifths (83 percent) of all data center traffic will be based in the cloud, up from 65 percent today. The majority of this traffic will be applications. Businesses of all sizes are adopting a variety of SaaS-based services – everything from collaboration tools to mission-critical commerce-oriented applications. The rise in SaaS usage has many positive benefits, but one drawback is that as demand grows, SaaS providers are having a harder time ensuring a high-performing (fast, reliable) end-user experience – at the same time performance expectations are growing higher than ever.
Since the term "DevOps" was coined in Belgium back in 2009, it has been impossible to avoid the debate raging around it. While we have watched it gain hype and momentum, many articles have been written to describe what elements of a DevOps strategy are required for it to be successful. In spite of this, not many organizations feel there is a need for DevOps. In a Gartner report entitled DevOps Adoption Survey Results (published in September 2015), 40% of respondents said they had no plans to implement DevOps and 31% of respondents said they hadn't implemented it but planned to start in the 12 months after the survey was conducted.
Back in February of 2017, Andrew Clay Schafer of Pivotal tweeted the following: “seriously tho, the whole software industry is stuck on deployment when we desperately need architecture and telemetry.” Intrigue in a 140 characters. For me, I hear Andrew saying, “we’re jumping to step 5 before we’ve successfully completed steps 1-4.”
@DevOpsSummit at Cloud taking place June 6-8, 2017, at Javits Center, New York City, is co-located with the 20th International Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. The widespread success of cloud computing is driving the DevOps revolution in enterprise IT. Now as never before, development teams must communicate and collaborate in a dynamic, 24/7/365 environment. There is no time to wait for long development cycles that produce software that is obsolete at launch. DevOps may be disruptive, but it is essential.
This term Data Unification is new in the Big Data lexicon, pushed by varieties of companies such as Talend, 1010Data, and TamR. Data unification deals with the domain known as ETL (Extraction, Transformation, Loading), initiated during the 1990s when Data Warehousing was gaining relevance. ETL refers to the process of extracting data from inside or outside sources (multiple applications typically developed and supported by different vendors or hosted on separate hardware), transform it to fit operational needs (based on business rules), and load it into end target databases, more specifically, an operational data store, data mart, or a data warehouse. These are read-only databases for analytics. Initially the analytics was mostly retroactive (e.g. how many shoppers between age 25-35 bought this item between May and July?). This was like driving a car looking at the rear-view mirror. Then forward-looking analysis (called data mining) started to appear. Now business also demands "predictive analytics" and "streaming analytics".
@DevOpsSummit has been named the ‘Top DevOps Influencer' by iTrend. iTred processes millions of conversations, tweets, interactions, news articles, press releases, blog posts - and extract meaning form them and analyzes mobile and desktop software platforms used to communicate, various metadata (such as geo location), and automation tools. In overall placement, @DevOpsSummit ranked as the number one ‘DevOps Influencer' followed by @CloudExpo at third, and @MicroservicesE at 24th.
DevOps is being widely accepted (if not fully adopted) as essential in enterprise IT. But as Enterprise DevOps gains maturity, expands scope, and increases velocity, the need for data-driven decisions across teams becomes more acute. DevOps teams in any modern business must wrangle the ‘digital exhaust’ from the delivery toolchain, "pervasive" and "cognitive" computing, APIs and services, mobile devices and applications, the Internet of Things, and now even blockchain.
Financial Technology has become a topic of intense interest throughout the cloud developer and enterprise IT communities. Accordingly, attendees at the upcoming 20th Cloud Expo at the Javits Center in New York, June 6-8, 2017, will find fresh new content in a new track called FinTech.
When executing an effective digital transformation strategy, management is tasked with placing the right workload into the most appropriate IT environment. This represents a shift from buying parts for self-assembly to composing services through self-serve consumption and pay-per-use models. Quite often this transition also leads to the adoption of software defined environments across the enterprise infrastructure.
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 discussed 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.
20th Cloud Expo, taking place June 6-8, 2017, at the Javits Center in New York City, NY, will feature technical sessions from a rock star conference faculty and the leading industry players in the world. Cloud computing is now being embraced by a majority of enterprises of all sizes. Yesterday's debate about public vs. private has transformed into the reality of hybrid cloud: a recent survey shows that 74% of enterprises have a hybrid cloud strategy.