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Q&A: HP Talks About App Development and DevOps - Part 3

Pete Goldin
Editor and Publisher
APMdigest

In Part 3 of APMdigest's exclusive interview, John Jeremiah, Technology Evangelist for HP's Software Research Group, outlines the future of application development.

Start with Part 1 of the interview

Start with Part 2 of the interview

APM: Tell me about HP Software's portfolio of app development and ops tools.

JJ: HP delivers a comprehensive suite of products and services to facilitate the entire application lifecycle, including products for developers, testers and IT ops teams. Going back to HP's Four Transformative Areas, in addition to empowering the data-driven organization, these areas include protecting the digital enterprise; enabling workplace productivity; and transforming the hybrid infrastructure. Each of these areas can be incorporated into application development for added benefit.

For example, HP's Application Lifecycle suite of tools provides agile/DevOps teams a collaborative platform in Agile Manager; and automated and continuous testing with HP LeanFT and HP LoadRunner. Integrating HP's security solutions, namely Fortify, properly incorporates security in the DevOps delivery process.

Since speed and velocity are vital in a DevOps team, being able to virtualize infrastructure and services can greatly accelerate delivery and this is where both Service Virtualization and Network Virtualization are indispensable.

Regarding the data-driven organization, HP's Haven platform offers advanced data analytics in a SaaS model, enabling DevOps teams to analyze and derive actionable insights from development and production data.

Transforming the hybrid infrastructure entails creating a responsive, dynamic environment — comprising on-premise as well as cloud platforms — that can adapt quickly to changing application needs. Using HP's Helion Cloud, in concert with (or without) one's own platforms, gives DevOps teams maximum flexibility to run various jobs and apps where they need to be run, depending on factors like time-sensitivity and the level of required computing power.

Additionally, numerous testing tools like load testing are available in HP StormRunner Load, and they allow DevOps teams to test using load generated from other clouds as well. This allows DevOps teams to test application performance under load for various geographies and end-user segments.

Finally, DevOps teams need to have their finger on the pulse of what users are experiencing. Only with insightful feedback are they able to react, respond and deliver world class apps. HP's AppPulse family of products gives developers exactly this kind of insight, leveraging big data analytics to provide actionable insight.

APM: Can you give an example of HP's value proposition in action?

JJ: Consider the case of SpeechTrans, a leading speech translation company. SpeechTrans uses HP AppPulse mobile to apply Big Data analytics to end-user experience data — for example, what screens are end-users getting stuck on the most; where are end users exiting the app — so developers can focus specifically on improving these app areas.

Previously, it took SpeechTrans up to three weeks to fix an app issue; now, they can address most problems in less than two days. This approach has enabled SpeechTrans to achieve consistent 5-star ratings in mobile app stores, a key driver of new customers and revenues.

APM: Where do you see application development headed next?

JJ: We don't foresee the relentless focus on app velocity and quality abating anytime soon. Consider mobile apps in particular. According to Rubin Research, in 2004, the average mobile user executed one mobile transaction per day. Today, that number is 37, and by 2025, the number of mobile transactions conducted around the world will increase 5x. In addition, the number of smartphone users around the world is exploding. It's a land-grab right now, and whoever rolls out the best applications the fastest, will win. We expect organizations will get creative, using technologies like Big Data analytics to glean critical insights for identifying development roadblocks, enhancing processes and fine-tuning apps in production.

APM: Are there new upcoming challenges on the horizon that developers must look out for?

JJ: Competition will not only increase, but it will do so on a global scale, as regions like China and India explode for consumer e-commerce and smartphone use. DevOps teams will need to be able to test and roll-out applications quickly, across more geographies and device types.

In addition, security is growing as a development challenge. The pace of DevOps means that developers are often using pre-existing code, which may have security vulnerabilities. In reality, security is a fourth component of application quality, and it must become a fourth leg of the DevOps stool. Security audits and validating security requirements must keep up with the speed of DevOps. For this reason, like testing, basic security audits could benefit from automation as part of the DevOps process.

APM: How do you see big data and analytics playing a bigger role in application development going forward?

JJ: Moving forward, Big Data and analytics will play an increasingly important role in application development – both in terms of refining and improving development processes, as well as improving application functionality, end-user performance and resource-efficiency.

Consider this example – a DevOps team may analyze social sentiment as a means of determining what new functionality end users want most. Or, an IT Ops team may identify usage patterns for an app – for example, when during the day does an application come under heavy load, and when does this load taper off. This enables development teams to code applications accordingly – for example, architecting applications to accommodate longer or shorter queues (depending on time of day) which can free up CPU resources.

Finally, a testing team may detect that problem with a certain app function only occurs on a specific browser type. By correlating this with an information breakdown on end-user profiles, they may determine if users of this browser type are prevalent enough to warrant the time and effort required for a fix. With Big Data, the possibilities are truly endless, and we've only just started.

ABOUT John Jeremiah

John Jeremiah is a Technology Evangelist for HP’s Software Research Group. His background as a software developer and IT leader with over 20 years of experience includes roles in IT consulting, at Fortune 500 IT organizations, and with the US Navy. His previous positions span from application developer, project, and program manager, Director of Testing Services, and Delivery Process and Methodology Director.

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Q&A: HP Talks About App Development and DevOps - Part 3

Pete Goldin
Editor and Publisher
APMdigest

In Part 3 of APMdigest's exclusive interview, John Jeremiah, Technology Evangelist for HP's Software Research Group, outlines the future of application development.

Start with Part 1 of the interview

Start with Part 2 of the interview

APM: Tell me about HP Software's portfolio of app development and ops tools.

JJ: HP delivers a comprehensive suite of products and services to facilitate the entire application lifecycle, including products for developers, testers and IT ops teams. Going back to HP's Four Transformative Areas, in addition to empowering the data-driven organization, these areas include protecting the digital enterprise; enabling workplace productivity; and transforming the hybrid infrastructure. Each of these areas can be incorporated into application development for added benefit.

For example, HP's Application Lifecycle suite of tools provides agile/DevOps teams a collaborative platform in Agile Manager; and automated and continuous testing with HP LeanFT and HP LoadRunner. Integrating HP's security solutions, namely Fortify, properly incorporates security in the DevOps delivery process.

Since speed and velocity are vital in a DevOps team, being able to virtualize infrastructure and services can greatly accelerate delivery and this is where both Service Virtualization and Network Virtualization are indispensable.

Regarding the data-driven organization, HP's Haven platform offers advanced data analytics in a SaaS model, enabling DevOps teams to analyze and derive actionable insights from development and production data.

Transforming the hybrid infrastructure entails creating a responsive, dynamic environment — comprising on-premise as well as cloud platforms — that can adapt quickly to changing application needs. Using HP's Helion Cloud, in concert with (or without) one's own platforms, gives DevOps teams maximum flexibility to run various jobs and apps where they need to be run, depending on factors like time-sensitivity and the level of required computing power.

Additionally, numerous testing tools like load testing are available in HP StormRunner Load, and they allow DevOps teams to test using load generated from other clouds as well. This allows DevOps teams to test application performance under load for various geographies and end-user segments.

Finally, DevOps teams need to have their finger on the pulse of what users are experiencing. Only with insightful feedback are they able to react, respond and deliver world class apps. HP's AppPulse family of products gives developers exactly this kind of insight, leveraging big data analytics to provide actionable insight.

APM: Can you give an example of HP's value proposition in action?

JJ: Consider the case of SpeechTrans, a leading speech translation company. SpeechTrans uses HP AppPulse mobile to apply Big Data analytics to end-user experience data — for example, what screens are end-users getting stuck on the most; where are end users exiting the app — so developers can focus specifically on improving these app areas.

Previously, it took SpeechTrans up to three weeks to fix an app issue; now, they can address most problems in less than two days. This approach has enabled SpeechTrans to achieve consistent 5-star ratings in mobile app stores, a key driver of new customers and revenues.

APM: Where do you see application development headed next?

JJ: We don't foresee the relentless focus on app velocity and quality abating anytime soon. Consider mobile apps in particular. According to Rubin Research, in 2004, the average mobile user executed one mobile transaction per day. Today, that number is 37, and by 2025, the number of mobile transactions conducted around the world will increase 5x. In addition, the number of smartphone users around the world is exploding. It's a land-grab right now, and whoever rolls out the best applications the fastest, will win. We expect organizations will get creative, using technologies like Big Data analytics to glean critical insights for identifying development roadblocks, enhancing processes and fine-tuning apps in production.

APM: Are there new upcoming challenges on the horizon that developers must look out for?

JJ: Competition will not only increase, but it will do so on a global scale, as regions like China and India explode for consumer e-commerce and smartphone use. DevOps teams will need to be able to test and roll-out applications quickly, across more geographies and device types.

In addition, security is growing as a development challenge. The pace of DevOps means that developers are often using pre-existing code, which may have security vulnerabilities. In reality, security is a fourth component of application quality, and it must become a fourth leg of the DevOps stool. Security audits and validating security requirements must keep up with the speed of DevOps. For this reason, like testing, basic security audits could benefit from automation as part of the DevOps process.

APM: How do you see big data and analytics playing a bigger role in application development going forward?

JJ: Moving forward, Big Data and analytics will play an increasingly important role in application development – both in terms of refining and improving development processes, as well as improving application functionality, end-user performance and resource-efficiency.

Consider this example – a DevOps team may analyze social sentiment as a means of determining what new functionality end users want most. Or, an IT Ops team may identify usage patterns for an app – for example, when during the day does an application come under heavy load, and when does this load taper off. This enables development teams to code applications accordingly – for example, architecting applications to accommodate longer or shorter queues (depending on time of day) which can free up CPU resources.

Finally, a testing team may detect that problem with a certain app function only occurs on a specific browser type. By correlating this with an information breakdown on end-user profiles, they may determine if users of this browser type are prevalent enough to warrant the time and effort required for a fix. With Big Data, the possibilities are truly endless, and we've only just started.

ABOUT John Jeremiah

John Jeremiah is a Technology Evangelist for HP’s Software Research Group. His background as a software developer and IT leader with over 20 years of experience includes roles in IT consulting, at Fortune 500 IT organizations, and with the US Navy. His previous positions span from application developer, project, and program manager, Director of Testing Services, and Delivery Process and Methodology Director.

The Latest
The Latest 10

The Latest

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...