Commenting on Velocity, Zakas said there was “so much cross-conversation going on, people sharing ideas and experiences.” Identifying the main conversation points, he mentioned “a lot to do with the amount of JavaScript people are using and the JavaScript solutions they are using,” discussion about mobile performance, something that was still really new but being dealt with as a “fresh problem”, as well as the challenges of swithcing to 3E for mobile.

Everything starts with analytics

Asked about the perception of speed in user experience, Zakas pointed out that “perception is more important than reality, if you make people believe what they’re seeing is faster than it is, they’re happy.”

“Everything starts with analytics,” Zakas said “it’s hard to know if you’re slow or not unless you’re watching” the metrics. “Getting to a good definition of what is fast vs. what is slow is the first step,” then companies need to figure out the right analytics and metrics. If the time spend on a server rendering a page is of 2-3 seconds, “you should be unhappy.” After that, you have to test it on users and see their reactions and get feedback.

“There’s a lot of things to do with perception,” Zakas expalined. “If you have a large blank space on your page and people stare at that, it looks slow.” If frames or a loading bar are added, the perception changes.

Asked about the current starndard app and monitoring analytics, Zakas said that there were different tools but they all did the same things. In the case of web apps, what is usually measured is unload time – how long it takes till everything on the page is completely loaded so people can use the app. He mentioned Boomerang, a tool that measures unload time, but also other associated times: how long a DNS look up take, how long it takes to get data to the client, JavaScrip and images loading times, etc.

“The most interesting part is that you can write one language and build a complete stack out of it. Developers love JavaScript but were not enamored with the browser side of it,” Zakas explained. “On the server, you control that environment completely. Now, there’s actually opportunity to have a really awesome, fulfilling job by having NODE on the server. When you have node compiling JavaScript, it can run just as fast or faster than Java and PHP.”

“The most imp thing is to understand your users,” Zakas said. “Why are they coming to you and what are they trying to do,” and make sure you enable them to do it, provide the right experience. “After that, you’re free to do pretty much whatever you want. If there is some way to progressively load things, so that you don’t get large blank spaces,” the app will seem faster and it will improve customer experience.

The thing with Javascript…

Talking about his presentation at Velocity, Zakas stated “I love JavaScript, it’s my favorite language. The big issue is that people are using so much of it that they run into problems they wouldn’t otherwise run into.” Based on his experiences with clients, people have 1-2 MB of JavaScript loaded into the browser, which slows everything done. Upon analyzing the code, he noticed that on average, about 35-40 percent of that code would be used when the page is completely loaded. The mentality is “computers, browsers are faster, I’m going to load a lot of code.” Developers expect computers to catch up and tend to load a lot of code. “You can achieve a lot with less code if you actually think about what you want to do with it,” Zakas explained.

“One of the biggest things is to make sure you take advantage of the various layers of your applications,” Zakas advised, referring to JavaScript, CSS, HTML, browser, and server. “When you are able to delegate responsibilities efficiently, things always work better. You create a nice balanced web app where you don’t touch JavaScript every time you want to make a change.”

Consumer Perception, Great Metrics + Analytics Are Key to Assessing Web Performance | #velocityconf is a post from: DevOpsANGLE

Commenting on the conference, Lounibos pointed out that it’s mostly about developers, not marketing messages. There was “not a lot of hype, there is a lot of conversation about fixing problems,” Lounibos notes.

Talking about SOASTA’s experience with web performance testing, Lounibos said the company started looking at web and mobile performance in the early days, ten years ago when there was a big difference in web and mobile apps, mostly about scale, agility, and performance. “We’re known for Quality as a Service. Our approach was to find more automation, more scale, and more affordability associated with testing mobile and web apps.” The company has over 45o business customers, some of their most famous being the Curiosity Rover, the London Olympics apps,  and currently the Russian Olympics.

Commenting on automation in testing, Lounibos said that cloud computing delivers your apps around the word. “The no. 1 problem is fragmentation,” getting an app to work well on different browsers or operating systems, as customers want a seamless app experience.

Fragmentation still an issue in app development, distribution

Currently there is an estimate of a billion websites and apps, a million and a half mobile apps, but fragmentation is going to continue to be an issue.

“The trend lines we’re seeing,” Lounibos explained, ”many people are building apps that will only be used for 72 hours,” the so-called disposable apps. The London Olympics’ ticket selling app, or websites created to handle the sale of new smartphone models by large carriers.

“One of the things fundamentally changing, we’re talking about users,” Lounibos stated. There’s a difference between users and consumers.” If a site is slow, “users will stay on site and keep coming back.” Consumers, on the other hand, will just find another site. There is currently an evolution from users to consumers, and “the behavior of consumers is not as easy to deal with for the tech community right now.”

Retail is major market for the company, with an especially busy summertime season, Lounibos explained, as all major retailers are testing their apps for holidays (starting with Halloween).

• A new app cycle

For the past 20 years, the app life cycle has been dominated by the big players such as IBM or HP, he said. A life cycle includes development, testing, deployment, and management. “Right now, because of this new form of consumerism – you’re seeing a transition that has gone from bricks and mortars storefronts to ecommerce,” a shift driven by real revenue. “The battle will be who will provide the infrastructure for it,” as eCommerce is now a trillion dollar business and will increase to 10 trillion.

“There is a shift in the economy driven by mobile,” Lounibos said, adding that it has been caused major worries for CIOs eyes in the past 2 years. “The issue to make the switch is not the technology,” it’s a cultural one, especially when it comes to moving large sales teams that were used to do things a certain way.

“Quality matters more today than it’s ever mattered,” Lounibos ssaid. Consumers are always only three clicks away from a competitor. “If the site does not work, you’re done. By the time you see latency on a site, your customers are gone and they might not come back.”

Quality Matters Mores More then Ever as Competitors Are Only a Click Away | #velocityconf is a post from: DevOpsANGLE

“The web is a very technical, very complex stack,” McAnlis said. “Translating where the internal engineers are pushing the web forward and where the external developers push the web forward,” being a huge part of his role with Google.  ”We have to work with each of them and find where the medium value is.” That is why conferences as Velocity help, “we talk to the best and the brightest on performance, and set our course.”

“Everyone’s got their own perfect world,” McAnlis said, commenting on Google’s decision to move to Blink. ”We kind of looked at where we wanted Chrome to go and the web to go.” Talking about the making and communicating such decisions, he explained that “it’s a multi-tier process” that “starts with ‘is it the right decision?’” For each decision taken, there are thousands of man hours spent on debating it, testing it, and evaluating the benefits. “We make small changes that will affect how a product works live. Our small change can have a big effect on someone’s business.”

“I work on the web gaming side of things,” McAnlis said, mentioning the recent boom of technologies that allow web games to get very interactive, offer great graphics. As it all happening in the browser, there is no download, no installation, the games are very social, they run everywhere. “You click a link, you share it, it works.”

Addressing developer expectations for Google Chrome

Asked about his upcoming presentation at the Velocity conference, McAnlis said it would focus on GPU implementation in rendering web page, the pros and cons of using this approach in Chrome, on how to use CSS tags the right way, to make pages that are fast and user responsive.

Where the most common caveats for developers are concerned, McAnlis mentioned the aspect of performance, which is actually made up of network, render, and compute performance. “Each pillar requires to solve a problem a certain way.” Another issue for developers to focus is their use of memory with JavaScript operations.

Mobile “is one of the big competing points with developers,” McAnlis said. “Mobile performance hasn’t been where it needs to be, but it has to get better.” Right now, tons of websites ask you to install native apps when accessed via mobile, the reason being the better performance developers get with native. Technologies are however changing the landscape, one of them being Chrome getting into mobile. As performance is getting better, websites will get rid of native apps and come back to browsers.

McAnlis also said that, performance-wise, the community is not focusing on emerging markets. There are 5 billion people expected to come online soon, most from low connectivity areas. Developers have to “look at all of their regions and optimize differently,” it’s all about connectivity speed. “The web is forcing us to think like a global developer,” McAnlis said.

Diverse developer culture

Asked what he found most exciting about the Velocity conference, he mentioned the large number of people “taking their own twist on cloud. It is interesting to see so many different takes on the same architecture.” Such diversity shows “we’re not done yet.” With so much competition, different ideas, “man, that’s just fuel for awesome,” he said.

As far as future trends are concerned, McAnlis said that over the next 12 months there will be “a lot more discussion about client-side performance ramification,” while the current focus is on the network right now. As cloud issues get easier to deal with, the next big challenge for developers will be client side mobile web performance.

“The web is forcing us to think like a global developer,” says Google’s Colt McAnlis | #velocityconf is a post from: DevOpsANGLE

The aim is to enable “continuous delivery” of software solutions allowing companies to take advantage of market opportunities and better meet customer demands. Improving development processes for cloud applications is critical for companies. However, traditional approaches to software development can make the changes but innovations take weeks and to succeed in a changing marketplace, organizations can not afford to prolong the time.

That’s why IBM has created these solutions to improve and streamline these processes. And here’s how the mega-giant world corporation seeks to do that:

Cloud Solutions

The company continues to add analytical capabilities to its solutions in the cloud. Newest of these is the Log Analysis, part of IBM SmartCloud Analytics. Log Analysis can bring the power of automated analysis to records of IT assets from the terabytes of unstructured data produced from infrastructure and applications. IBM SmartCloud Monitoring Application Insight is a solution that helps companies monitor the performance and availability of applications hosted on a cloud in real time.

The other offering is the Expanded IBM SmartCloud Application Services. Developers can use SmartCloud Application Services to deploy and manage applications written in the PHP programming language using Zend Server 6. The support for this language makes it easier for developers to create native applications in the cloud.

“Software is the invisible thread driving transformations in businesses of all industries and sizes,” said Kristof Kloeckner, general manager IBM Rational Software.  “As organizations and the dynamic markets in which they conduct business become more complex, it is critical that they adopt a DevOps approach to continuously delivery software-driven innovations to their clients.”

Mobile Solutions

Enabling efficient development and management of mobile apps, IBM at the start of the year launched MobileFirst initiative. As part of the initiatives, IBM has launched new tools to help companies deliver better mobile applications faster and at lower cost.

Now extending the inventiveness, the company introduced IBM Rational Test Workbench. With this solution, developers can record, modify, reproduce and evaluate the test scenarios to automate hundreds (even thousands) of tests of a mobile device. They will also be able to virtualize and test parts of the application that have not been completed yet.

IBM Worklight & IBM SmartCloud Application Services is a free service that allows developers to create applications and deploy them in IBM SmartCloud with IBM Worklight technology. Companies can develop mobile applications quickly avoiding early costs in the project management using this service.

IBM Joins Hands with AT&T to Enhance MobileFirst Strategy

IBM and AT&T have announced a partnership to help companies to develop high performing mobile applications. The integration of both companies’ technologies will help improve the testing process and analysis of the applications and the battery life of mobile devices, giving organizations the time to make changes and improve performance.

As part of the IBM MobileFirst strategy, mobile developers can verify the performance of their corporate mobile applications on any wireless network and improve their performance.

The integration of AT&T’s Application Resource Optimizer (ARO) with IBM’s software development solution for Collaborative Lifecycle Management (CLM) tackles finding and fixing performance and power bottlenecks of apps. ARO can help developers create apps that conserve battery life, load pages faster and consume network resources in a smarter way, all of which improve the customer experience.

IBM DevOps Solutions to Accelerate Development of Mobile and Cloud Applications is a post from: DevOpsANGLE

Graphdat, the real-time application performance monitoring provider launched last year, introduces Smart Alarms–a system that provides real time and historical data in one interface. It offers developers a comprehensive, enterprise-wide solution for the central management of performance and availability of servers, hardware, operating systems and applications.

The company has run the tagline “every dev deserves a heartrate monitor for their apps” to explain the product and from our examination, that’s exactly what Graphdat supplies.

As important as development of software, is the maintenance and awareness of how that software is operating on hardware. Companies like Graphdat provide these sorts of solutions so it’s worth looking into what exists on the market. So, what made Graphdat catch our eye? The monitoring concept of “smart alarms” is a good place to start.

How it Works?

The Smart Alarms system automates the seamless monitoring of critical servers, for all Windows systems and non-Windows systems such as Mac, Ubuntu, Debian, Redhat and CentOS. First you need to create an account with Graphdat and then install the agent on your server. The agent gives access to real time server performance for CPU, memory, disk and network metrics.

The next step is to install the plugin on the server. The web server plugin contributes access to real time application request counts and response time. The add Graphdat into the application code base and Keep a close eye on system with Smart Alarms.

Smart Alarms can be customized to get metrics data from CPU usage, memory, disk bytes read and write, network bytes read and write, application request count and application response time. What sets apart Graphdat alarms is that you can not only alarm basic aggregates like min, max, count but you can also alarm for an average.

The time period to set alarm can range from 1 second up to 12 hours. For example as per Graphdat documentation, if you set a CPU threshold of, say, avg > 80% and a period of 1 minute then this translate to: “Tell me when my CPU average is above 80% for at least 1 minute.”

By default, the alarm is set for all servers, but you can choose which servers you wish to alarm. The smart alarm then provides dynamic and intelligent graphs and reports summarize a lot of information of your systems and applications. You can click on the graph to see a legend, drag around to see historical data, zoom out to see larger sections of time with the mouse wheel, and do much more.

SDK for Developers

As with all DevOps, developers themselves become an important organ for understanding the software product and producing the scripts and automation necessary to make monitoring function. As a result, Graphdat does not shirk their responsibility to provide a powerful way for Dev to grasp and extend their platform.

To make integration as easy as possible, Graphdat is compatible with all major operating systems; web servers including Apache, IIS, and Linux NGiNX; software stack (node.js, Microsoft .NET, php, python and ruby); and database (SQL server and MySQL).

The company provides an SDK that when installed will talk to the agent, who then sends everything to your graphs as a single package such as server metrics and code metrics. The SDK lets developers set alarms, alerts, adding meta data to graphs, plus Python, Ruby and Java support as well as mobile application performance management.

Graphdat: Real time Performance Monitoring and Alerting Tool is a post from: DevOpsANGLE

The reason for this is that many industry sectors have high-value assets that create a majority of this data. To illustrate his point he presents three scenarios, one each in healthcare, energy, and transportation, based on Wikibon research.

Healthcare spending in the United States topped $2.75 trillion in 2012, 17.5% of GDP, the highest spend on healthcare in the world. Analysts estimated that as much as 43% of that spend went for unnecessary procedures and administrative waste. This creates huge opportunities for analysis of Big Data from sources ranging from high-value medical equipment such as MRI or CT scanners to patients, themselves, to create major improvements. By predicting part failures on high value assets, for instance, it can maximize both availability and useful life of the asset. By monitoring low-value assets such as hand washing stations, it can ensure that basic procedures such as washing hands between patients are followed rigorously, decreasing the spread of hospital infections such as MRSA, which costs hospitals approximately $30,000 per case. And by monitoring patients themselves it can measure their compliance with home treatment plans and minimize the times they need hospitalization.

In the energy industry a study by the University of Minnesota found that power outages and “power quality disturbances” cost the United States as much as $188 bill per year. Analysis of Industrial Internet data from sensors mounted at critical points in the generating equipment and power grid can minimize those outages by moving maintenance from a break/fix to a preemptive strategy that fixes the problem before it becomes acute.

In transportation, a new Boeing 787 creates up to a Tbyte of data per round-trip.  That data can be used for everything from increasing operational efficiencies and driving preventive maintenance to keep the plane in the air to identifying weak points in engine and airframe design and designing them out of the next generation of the plane.

All the potential upside should drive fast adoption of Industrial Internet. However, Kelly writes, it isn’t quite that easy. Several challenges need to be overcome, starting with the writing of standards for the various kinds of data involved and the creation of an open platform that provides scalability, high availability, high security, flexibility, and orchestration. Regulatory requirements also need to be worked around. For instance in healthcare, HIPAA sets fairly high standards for the security and privacy of personally identifiable medical data.

However, he concludes, “the opportunities to improve efficiencies and create valuable new business models associated with the Industrial Internet are vast.” This gives all the players involved strong impetus to work together to overcome the challenges. As with all major technology advances, the successful early adopters reap the majority of the rewards, while the laggards often face shrinking market share and competitive disadvantage.

Industrial Internet Promises High Value Business Data is a post from: DevOpsANGLE

Sqrrl, the Cambridge, Mass.-based company commercializing Apache Accumulo, has added a number of enhancements to version 1.1 of its security-focused Big Data analytic platform specifically aimed at simplifying the application development process. These include the ability to convert Accumulo key/value pairs into hierarchical JSON documents to streamline data models and structures, according to Sqrrl. The company also added better installation tools and command-line shells, new configurable indexing capabilities, and the ability to ingest streaming data.

There are also security enhancements, such as better integration with Active Directory, Kerberos and LDAP, as well as new analytics capabilities including full-text search, SQL support and graph analysis functions. Sqrrl is aiming its platform at developers in financial services firms and government agencies looking to build security-focused Big Data applications, as well as to application developers in healthcare and other highly regulated industries that demand fine-grained security and access control capabilities.

Wikibon Chief Analyst Dave Vellante said Big Data application development is still largely a complex, manual process, but new platforms like Sqrrl Enterprise are poised to change that.

“Developing Big Data applications is complicated and Sqrrl Enterprise substantially simplifies application development for emerging large scale apps,” Vellante said. “Wikibon practitioners are excited about Sqrrl toolsets because they enable organizations to co-mingle sensitive datasets on a single Big Data platform through fine-grained cell-level security controls. Scale, performance, security and flexibility will define the next wave of Big Data application development, and companies like Sqrrl are leading the way.”

Sqrrl CTO and Co-Founder Adam Fuschs recently recorded a series of whiteboard videos on theCUBE demonstrating how Sqrrl Enterprise addresses cell-level security and enables Big Data application development.  See our initial coverage here, and catch Fuschs’ demonstration in the video below.

Sqrrl Enterprise Simplifies Big Data App Development in GA Release is a post from: DevOpsANGLE

In order to understand the Industrial Internet, Wikibon’s David Floyer looked into what industry segments the technology has penetrated. Already we’re seeing GE looking into hooking up aviation equipment to Amazon’s cloud to get better metrics on how aircraft engines and parts are doing and that should be a signal to the developer community at large its time to start thinking about the problems associated with generating and collecting information.

API Frameworks: Sensors and server will have to be “smart” about their habits

As the number of sensors expands, each of those devices will have to connect back for its data to be collected. For this, I feel developers might find their best benefit by looking at the mobile industry because it already does this: mobile devices load apps (across thousands of devices), apps connect to the Internet, they connect back to their servers, and viola, that’s how they provides their services and make their money. The Industrial Internet will be extremely similar—just with the alternative that most of the time they’ll be inside of a private network rather than reaching out over the open network.

However, this still means that scalability and reliability will come into play when thinking about all those sensors. API frameworks will need to exist to allow devices that collect data from sensors to connect back to the storage system, to authenticate themselves, and then to deliver the data—and in probably a lot of cases, receive instructions back on how to handle future incoming data.

We can take the GE example where a sensor connected to a wind-farm turbine could collect data about the speed of the turbine (power output, temperature, resistance, etc.) every minute or 10 seconds. All that data would either have to be stored on the device to be transmitted later, or transmitted instantly. Depending on the bandwidth available it might not be possible (or even desirable) for every sensor on an entire turbine to collect data every second so its set to ping every 60s. However, if something is starting to go wrong, a faster collection rate might be triggered.

Not only do the sensors on the “thing” need to be instructed properly by their own internal resources, but the receiving server needs to be prepared to see more or less data flowing from them.

Thinking along these lines will be just as important as developing authentication methods from the sensor devices to the servers (probably public-private key trades to encrypt the transmissions or at least identify individual sensors) and producing API frameworks that can open up space for new sensors being added on the fly in environments where more sensors will come and go. The sense of scale of the Industrial Internet could be just as daunting as a few hundred thousand customers with smartphones—and a little bit more critical to make sure each sensor knows how to operate in its niche.

Cloud-thinking across time and “thing”

With the Internet of Things (on the consumer side) Expertmaker CTO and founder Lars Hard mentioned to me that it was “all about the sensors,” and there’s no reason to believe this isn’t as true for the Industrial Internet. Those sensors are just connected to many more things than they are directly to people and the end product is designed to go to an operator than a consumer.

This means that after the challenge of detecting and connecting all those sensors and then collecting all their data is done (or, more accurately, is ongoing) there’s going to be an analysis phase. This is where big data and technology like Hadoop are going to come into play. For an extensive list of examples and challenges, you can see a report by Jeffy Kelley from Wikibon on the subject.

As with most big data analysis, there’s a spectrum of modes that operators are interested in and those are split between real-time analysis and historical analysis. For the most part, big data will be thinking about historical analysis to try to detect and identify faults or enable engineers to optimize equipment based on how it acted and reacted in the past. For more potential catastrophic problems, sensors will want to compare that historical data to current incoming data and warn a human (or trigger a programmed response) to whatever is currently going on.

In the wind-turbine example there might be a case where greatly increased wind speed might need the system to react by reducing the total electrical load on the generator to prevent it from providing too much wind resistance. Sensors talking from the turbine to the analytical servers could have that trigger automatically or ask a human operator to judge from the visualized data in front of her to make the decision.

However, I see a whole other problem cropping up and that’s one of occasionally connected sensors. All this data may provide a better landscape to understand an industrial application; but with real time big data analysis not all the data is coming in a continuous stream in the order it was sent. As a result, the Hadoop system underneath needs to not just handle a lot of differentiated data from numerous sources, but it needs to be prepared and developed to respond to fluctuating historical data.

After all, some of those sensors might have had to wait minutes or hours before offloading if network congestion became too high and decision making would need to take into account what sensors had checked in and when they were expected to check in.

Food for thought in the Industrial Internet.

The Industrial Internet Will Open Up a Whole New Horizon for Developers is a post from: DevOpsANGLE

I don’t know of any company that has transitioned to DevOps without a struggle. But I also don’t know of any company that doesn’t consider the results of DevOps well worth it. What worries me is that, just as with Agile, too many people are fooling themselves with half-measures and blaming DevOps. They are putting a little bit of pretty red DevOps lipstick on ill-defined processes that oink, squeal, and don’t really deliver value.

Why DevOps is Hard

Nobody finds it easy to get DevOps going because it challenges organizational mores and requires discipline, new skills, and for people to work in new ways.

The first reaction to DevOps is often pushback. Traditionalists argue that specialization is not a barrier to progress but a way of keeping order. If you breakdown silos and allow just anyone to make operational changes, chaos will ensue. If the entire operational environment is “ours” and not owned by an expert, nothing will work.

Making DevOps work means beating back the naysayers. There are a thousand reasons you can’t do DevOps, and many involve “musts.” Storage must be controlled by storage admins, networking must be controlled by network admins, systems must be managed by system admins, and developers must write code but not deploy it to production. If you build a typical cross-functional team to embrace DevOps, you put people with organizational blinders on in the room, people who think they have good reasons not to do DevOps, which can kill the initiative.

Automation and DevOps

Remember a key ingredient of Agile that people often forget: test-driven development (TDD). TDD is the heart and soul of Agile. If you’re going to move fast, the only way to move fast is to build a test for a desired behavior, code against that test and move forward. When you change your code, you need those tests as a safety net to tell you whether you’ve broken something. Without TDD, it’s not Agile.

For DevOps the equivalent of TDD is configuration tools and automation. The reason that a developer can add capacity to a application or create a new test environment on his own is that as much as possible has been automated. In addition, DevOps usually involves an ever-expanding collection of tests that are constantly being run so that if anything does go awry, the cause can be found quickly and any offending changes rolled back.

Growing Your Own

What skills and resources do you need on a DevOps team? DevOps requires what I call “system engineers,” which is a totally different kind of skill set, one that is almost impossible to hire.

My experience at NASA illustrates the difficulty of creating a DevOps team. At NASA when we tried to bring in ops people to run our DevOps process, the first thing they wanted to do was lock all of the developers out of the infrastructure. It was a colossal failure. We tried hiring system administrators and having them work with configuration management tools and automation. That didn’t work either.

To staff a DevOps team, you have to grow and nurture people. You need someone who has an interest and a drive to get to know others and learn what they do. Sure, on rare occasions you’ll find somebody who has grown up as a system administrator, or on the operations side of the house, who actually understands computer science beyond a couple of bash scripts or a little bit of Perl. They can start to understand test-driven development.

How DevOps Makes Things Faster

I’ll close with a fundamental idea from systems thinking: The effectiveness of a system is related to the connections between the components, not the efficiency of individual components. Let’s apply that to DevOps. If you can provision a virtual machine in five minutes but it takes a week to get an IP address, you didn’t get a virtual machine (VM) in five minutes; it took a week. If you can’t get storage configured for a month, it’s really a month before the VM is useful. It’s the relationships between systems that really matter, not the individual components. In essence DevOps means working together toward a single goal. We need to deploy as fast as possible. The only way that we can do that is by working in synergy, not in silos.

When you successfully produce a DevOps team, everybody in the building knows that the most important activity is pushing code to production; there is a common objective. In a DevOps world there is still specialization, but there is a common goal. The sense of “your” apps running on “my” servers disappears. Everything is “ours.”

Once this happens, you’ve got a real shift toward DevOps culture. You can add more tests and automation; there will still be kinks to work out, but you’ll have a real DevOps team, not an entry to the state fair.

Joshua McKenty’s bio:

Prior to co-founding Piston Cloud Computing, Joshua McKenty was the Technical Architect of NASA’s Nebula Cloud Computing Platform and the OpenStack compute components. As a board member of the OpenStack Foundation, Joshua plays an instrumental role in the OpenStack community. Joshua has over two decades of experience in entrepreneurship, management and software engineering and architecture. He was the team lead for the development of the Netscape Browser (vs. 8) as well as AOL’s IE AIM toolbar, and a senior engineer at Flock.com. He also led the successful first release of OpenQuake, an open source software application allowing users to compute seismic hazard, seismic risk and the socio-economic impact of earthquakes.

Real DevOps Is Harder Than Putting Lipstick on a Pig is a post from: DevOpsANGLE

O’Reilly Fluent is the key event for web and mobile developers, software engineers, and others to gather and learn from each other. It also attracts the best coders, as well as offer the best and most innovative thinkers in the industry!

Developers today are going beyond javascript and moving on how to develop for the web and for the web platform. They even showcased demos of developing games without using classic programming techniques because the speed and the flexibility of the application is there.

To watch SiliconAngle’s recorded interviews at O’Reilly, they’re up on our YouTube channel in a playlist specific to Fluent.

O’Reilly Fluent Conference 2013 Wrap-Up is a post from: DevOpsANGLE