Posts Tagged :

Dev Ops

Opinions don’t matter, data does – A framework to collect measurable data for DevOps

DevOps started as part of the agile movement and making great strides since then. As we take stock of the progress from the time it started, we see organizations adopting it at a rapid pace. But companies are able to realize only a fraction of DevOps potential and benefits. Adapting to an era of always connected and Data-driven apps, organizations have to build solid muscles around executing Data-driven DevOps for multiplying DevOps benefits. More honestly, software deliveries are no longer guess estimates or instincts; they need a bolster from real-time data from machines, customers, tests and IT operations.

In our experience, with most of the organizations there’s a lack of understanding between traditional reporting and advanced analytics that involves Machine Learning. One of the leading financial advisory firm did heavy investments in the DevOps program, when we did a thorough examination, most of their processes were below average. Client sprints did not match the capacity of the teams and teams were not operating on the defined acceptance criteria basis. They regularly mentioned using DevOps tools, but when asked data, they presented manually extracted reports. The question is, how deeply your data is driving DevOps, and not DevOps experts’ opinions? In this article, we argue the next-phase in DevOps is real Data and not tools and technologies and no more opinions.

Build a framework to collect data for DevOps

All good in theory, but how? Moving from waterfall to agile and then introducing DevOps was itself not a simple proposition for organizations, now enabling Data in every software decision requires major changes towards organizational mindset–from room full of opinions to data-advocated opinions and IT infrastructure to capture data in real-time.

Even in DevOps Data Beats Opinions

Most of you remember chasing release timelines of features that’s not even get used by customers. Or for another instance, changing the environments without understanding the data flow and running into compliance issues. These were normal scenarios where people backed their decisions with opinions or human memories and ran into problems.

The profound shift in the development practices and customer demands need re-examination of DevOps practices. While the primary goals of agility, speed, efficiency and collaboration remains same, Data has to get intertwined in DevOps decisions. Building or maintaining Data-driven application with DevOps requires greater collaboration between different teams and data from different sources. Development, Operations, Security and Governance, Data Science, Marketing, Customer service, Product Management, and Leadership everyone has to get involved.

The three important data categories to mine insights to deliver strategically superior services to customers are–Data from Machines, Data from Customers and Data from Tests. Data from these three areas can bring in quick improvements in the release cycles. Qentelli has worked directly with C-suite to identify which data to capture and how to use them to optimize applications. We have done it without pausing their development efforts, keeping regular deliveries unaffected.

Automate your Delivery Pipeline

It’s no coincidence that organizations are automating more than ever. Organizations have seen how their counterparts are scoring big with Data-driven approach, instead flipping monthly reports or referring to outdated knowledge bases. Automation is essential to support data democratization. Automation creates a continuous stream of data to feed into applications for learning and improving and even produce self-learning and self-healing systems. Radically balanced and future-ready automation initiatives need to integrate with Analytics engine, a core of deriving insights from the infused data.

Consider Infrastructure Managers working on building network infrastructure using manual tools like excel sheets, tedious to manage and prone to human error. The rise in application and network complexity is compounding this challenge. Through automation-assisted “replicated build” which mimics required configuration for developers, testers, pre-production, the same manager can cycle through countless configurations and this can be the base for infusing AI to learn, improve, suggest and predict with every iteration.

Build or Buy – Analytics Engine

Organizations realized data troves created in the DevOps pipeline holds the real worth for the businesses to improve their Delivery Operations. But is it possible for Development or IT or QA teams to understand what they stand for and how they can be mined to derive real business intelligence? Mostly, No! AI can be of help here.

With AI taking concrete shape in businesses, building or buying an Analytics engine for DevOps pipeline gives endless benefits to businesses. The potential use cases of applying Analytics to DevOps data are many, measuring customer engagement after a feature release to real-time visibility of usage, performance, build pass/fail percentage, reliability, measuring errors percentage, etc.

DevOps Dashboard

After applying analytics to the DevOps data, organizations should see results in a comprehensive Dashboard. This dashboard summarizes the view of day-to-day operations and development activities. With up-to-the-minute insights about how applications are performing, and development activities are progressing, it becomes easy to drive delivery decisions with data rather gut feelings or intuitions or human-decided priorities.

For DevOps Dashboard, there are a lot of options mushrooming in the concentrated DevOps tool chain market. Most of them claim to provide full visibility of DevOps data but selecting them requires a targeted approach towards what businesses are expecting from DevOps–be a development philosophy or a strategic differentiator.

Building dashboard can be an intensive exercise and lies outside the expertise area of organizations. It is always advisable to opt for a tool that can be integrated with the existing and diverse DevOps Tool Chain and/or can be customized completely. Qentelli has worked with clients having a plethora of DevOps tools and struggling to get a complete view of multiple projects and teams.

We developed The Engineering Dashboard (TED), our proprietary tool to solve these challenges of distributed tool chain, projects and teams and remove the complexities of aggregating data, stopping organizations from driving their DevOps with data. TED, our Engineering Dashboard is a one-stop unified cognitive dashboard to aggregate, analyse and alert based on data produced within DevOps pipeline.

Reworking on DevOps with Data

Business leaders can look beyond the rear-view mirror of faster deliveries, as DevOps move on from opinions to data. Instead, they can harness the power of Data and Artificial Intelligence to drive application and business decisions based on real-time and predictive insights. They can use Data-driven DevOps to up their game: effortlessly for new feature releases, assuring IT alignment for new initiatives, block security threats and improving application performance. The end results? DevOps is no longer a battle to release faster in the face of growing data complexity. It becomes an opportunity to build Data-driven culture within an organization to benefit customers with more innovation and faster deliveries. Talk to us in more detail about TED and how it can complement your current development tool chain at info@qentelli.com.

Your DevOps loop is broken – Solving the continuous feedback puzzle – Part 2

In the first article, of this 2-blog series we talked about signs to identify missing DevOps feedback loop and its characteristics. In case, you have missed it–Give it a read here!

The second part of the blog uncovers how to set up a feedback loop for DevOps and how the future of DevOps with feedback looks like.

DevOps feedback loop–Delivers quality application at light-speed

DevOps grabbed a lot of attention as it provides agility to businesses powered by software. Still DevOps teams run into a bottleneck when feedback is not timely at the right stage, pulling the whole release timeline backwards. The formalized feedback loop can bring in required Agility, Quality and Customer-centricity.

The concept of monitoring has already been injected into the phases with a wide variety of tools, but these tools do not provide an end to end insights about pipeline health. The extension of this monitoring is broader DevOps feedback loop that drills down to the overall pipeline health. DevOps feedback spans across all the phases such as Planning, Development, Integration, Testing, Deployment, Monitoring.

  • Continuous Planning–Post-deployment application usage, customer reviews, incomplete user stories, user-behavior.
  • Continuous Development–New user stories, new compliance and security requirements, build tests.
  • Continuous Integration–Build fail/pass, test environment, latest code version, artifacts.
  • Continuous Testing–Root cause analysis of tests failure. Result of mini regression suite.
  • Continuous Deployment–Application feature and usage, end-user interaction and the areas of improvement.

Constructing feedback loop

The proactive monitoring across stages like application health, log monitoring, code quality monitoring, etc is a thing of the past. The modern DevOps team requires platform/solution to have a panoramic view from planning to post-deployment. The basic premise of DevOps feedback loop is simple–Collect real-time information based on the code movement in the pipeline, provide this information to the teams responsible for it, establish processes to fix issues and improve continuously. This should be introduced focusing strongly on customer journey. On a broader level, DevOps feedback loop requires–1. Setting up Quality Check Gates 2. Requires an End-to-End Intelligent Engineering Dashboard tools such as The Engineering Dashboard (TED) 3. Establishing and adopting processes to ensure immediate remediation of issues.

1. Setting up Quality Check Gates

Building DevOps feedback loop requires setting up quality check-gates at each level with specified threshold at each stage for code acceptance. This requires brainstorming from the various teams such as customer service, product managers, business analysts, QAs, Infra teams, Developers. Customer experience metrics and industry statistics can also be helpful in determining these threshold numbers for the first time. Quality gates ensure–

  • Code shipped into production have the highest quality standards including security, compliance and governance
  • Code is halted if a certain threshold is reached and respective teams are notified to fix the issues
  • Better release confidence to developers
  • Better collaboration between teams
  • Quick roll-back strategies to the previous stage

For organizations starting to build their feedback mechanisms, it is a work-in-progress to get the specific threshold at each phase correctly in one shot. The key is to remain progressive and observant in recording and iterating them.

2. Requires an End-to-End Intelligent Engineering Dashboard tools such as The Engineering Dashboard (TED)

There are many tools already available in the market such as NewRelic, HP LoadRunner that are great tools but are focused on the particular segment of the DevOps pipeline like application performance monitoring, load testing.

DevOps adoption has increased but still IT leaders have low visibility into the quality and health of DevOps pipeline. The acceptance of DevOps has created an over-importance of metrics and how to collect them instead of interpreting them for wowing customers. They can’t look beyond the defined metrics to measure the efficiency of processes, tools, projects and teams. This makes it hard to identify the gaps and provide proper feedback to realign the deviated processes. CIOs are seeking products/solutions to examine and improve efficiency and quality of the software.

DevOps feedback loop requires tools like TED that provide complete insights around the health and quality of the DevOps process. This gathers information right from planning phase to code commit till production and end-user monitoring.

TED collects near real-time data from different quality check gates and integrates with existing tool stack. Teams can configure alerts and notifications for different teams to act upon them. TED creates transparency by showing the required information (depending on your team structure and rules for accessibility of information) to the right people. It shows the relevant information to developers so they can fix the code, or infra team so they can see the downtime, or business analysts about the requirements gathering for the upcoming sprint.

TED D1TED dashboard that gives comprehensive view of the DevOps program

3. Adopting processes to ensure immediate remediation of issues

DevOps feedback loop ensures identifying errors earlier and if they slipped to the production responding faster to resolve them without customers getting a hint. This also involves understanding the root and cause of issues and proactively avoiding them. The third aspect of DevOps feedback involved major changes around culture. Amplifying DevOps feedback loops require creating a dynamic and agile culture to have comfort of changing the course whenever required.

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DevOps Beyond Metrics

Feedback is valuable whether for people or processes. Metrics don’t uncover the gaps, but feedbacks are well-detailed to reveal the gaps and how to remove them and create a knowledge base for organizations to act upon them. Organizations like CapitalOne has witnessed how DevOps feedback loop drives quality with unmatched speed. Organizations can catapult their digital journey in a heated battle for market share with a properly administered feedback loop.

Feedback maximizes DevOps returns

Feedback at any level (personal or project) works as a catalyst for organizational change. With a feedback mechanism in place to pinpoint the issues and bottlenecks. The DevOps feedback loop will revolutionize complete app lifecycle from planning to deployment all integrated to see problems before they go live. Or sometimes rolling back them from the hands of end-users before they experience major hiccup.

Born-digital decacorns are leading the ‘releases per day’ game but there are a lot of opportunities for organizations to realize the true benefits of DevOps with the feedback loop. Intelligent DevOps feedback solutions help businesses address their persistent quality loopholes, helping them use relevant feedback to build effective processes that will enable old systems into dynamic solutions.

With so much of data generated, feedback multiplies continuously at the receiving end, it requires a lot of human judgement and detailed exploration to act upon them. Qentelli’s approach of establishing DevOps feedback loop using tools like TED benefits organizations to improve DevOps processes using data captured across DevOps pipeline. Are you ready to maximize your DevOps efforts? Start the conversation with Qentelli at info@qentelli.com to deliver value to your customers faster.

Your DevOps loop is broken; Solving the continuous feedback puzzle – Part 1

With DevOps, we have come a long way from it’s the code or it’s the environment puzzles. As the concept became familiar, thought leaders like Qentelli are giving emphasis on democratizing feedback loop (listening and responding) across the entire DevOps. Further course of CI/CD requires near real-time detailed feedback for each phase to make finer improvements in the application delivery. Properly administered feedback loop results in offering new dimensions to act upon such as new events, feedback, data, customer demands or variables for businesses.

In this 2-blog series of the DevOps Feedback loop we will talk about signs for identifying missing feedback loop and how-to plug-in feedback at all stages of DevOps. The first article in the series talks about signs of missing feedback and characteristics of the feedback loop. Let’s get started –

Observe the obvious

Organizations assume few things are obvious, but the assumptions bust when things go wrong. Observing the smallest of changes and communicating at the right moment completes the feedback to foster proper improvements in DevOps. For instance, a top game development company assessed that industry will witness the mobile revolution in second decade of 2000s, but it came early. Though they were the market leaders, they witnessed a major fall as none of their games were ready for mobiles. There was a gap to identify market forces and how it would impact internal business plans. The application development space is changing so rapidly that what holds relevance a year ago or even five minutes before is irrelevant now. Teams not evolving rapidly are leaving behind in the race.

Organizations should look for such obvious gaps to identify their broken feedback loop. These signs can serve as a beacon to navigate the path of DevOps and establish a feedback loop to avoid mediocre software deliveries.

#1 – Treating DevOps and Business separately

The meaning of DevOps doesn’t convey properly because of its formation. It says Dev and Ops–combining development and operations, but in reality, it expands to integrate business into engineering. If your business teams are not part of your next feature release or prioritizing tickets, it is a red flag for DevOps program. Business teams can translate Developed versus Released features, Automation, Security, Compliance & Governance integration into costs resulting into right rankings for development.

It’s the software economy and application releases decide how the balance sheet and P&L statements of organizations look like. Early feedback from management helps in tailoring application delivery as per the business goals.

#2 – Unidentified communication barriers

Communication and collaboration are the true enablers of DevOps. In DevOps, prescriptive rules do not drive communication, instead it is a philosophy for cross-functional teams to work together for software deployment, support and maintenance in production and beyond that. Organizations constantly reinforce different modes of communication such as stand up meetings, smiley boards, chat rooms and open spaces. But does it create transparent and open communication culture? The answer is No! As per the Pulse of Profession Report 2018, inadequate or poor communication accounts for the top 5 reasons for the project failure in any organization.

The goal of DevOps is to have development and operations work together collaboratively for better application releases. But if your developers still throw surprises to Operations about the releases, this is a sign of unidentified communication barriers. If there are many instances like this, it is an alarm to fix DevOps feedback loop around communication.

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The only way of removing these communication barriers is to learn, educate and promote DevOps. Teams questioning about “What is DevOps?”… “Why we keep on changing priorities in every sprint”… “We are doing well, why we need it?” are not mindset challenges, they are just poor communication about the benefits of DevOps. Management and other technology leaders must proactively act to establish communication rhythm and sell DevOps across the organization.

#3 – Late identification of issues 

Organizations are trying hard to identify and resolve errors in the early stage of development lifecycle but are achieving limited success. Teams identifying bugs at later stages of development is a sign of missing DevOps feedback loop.

It is unavoidable to commit mistakes but spotting, preventing or resolving them in lower environments is possible using feedback. Teams need to stop looking at defects as an unaccepted practice, rather look for better and stronger feedback loops and quicker processes to fix them. DevOps teams should align testing with the development to catch errors in an early stage and avoid any mismatches downstream.

The formal feedback loop should reflect customer perception of poor quality. Say, for example, customers perceive hundred defects that doesn’t impact user-experience as great rather ten issues impacting usage of important features as poor quality. Tracking customer perception of quality and duly developed testing strategies exploits the feedback around perceived quality. This helps in resolving bugs as per the customer perception of quality. Above all customer experience is Emotion, Convenience & Outcomes and not underlying application technology or infrastructure performance.

#4 – Lack of automation

For most of the organizations, starting automation initiative is a fine mess. If your most of the development processes are still manual, this is a sign of missing DevOps loop.

Automation is heavily associated with DevOps. DevOps stresses on creating a highly automated environment from planning to production and post-production monitoring. Lack of automation in DevOps breaks the feedback loop as–

  • Errors are detected in later stages
  • Increased risk of a deployment causing downtime affecting application
  • Delayed roll-back in case of issues

Non-automated processes cannot be put under a continuous frame of capturing feedback from delivery pipelines and set up notification triggers. Based on the processes, applications and architectures, organizations need to identify critical steps from where important and timely feedback distributes to the team.

#5 – Faster releases but no insights about critical KPIs

DevOps adoption is increasing, but DevOps improvement has reached a plateau stage. If the only improvement area in your releases is deployment speed, then this is a sign of missing DevOps feedback. Faster releases with compromised quality are giving sub-optimal benefits to teams. Improvements in Customer centric and quality metrics such as Number of production defects, Mean time between failures, Mean time to recover and Cycle time show about the efficient processes and time taken to provide actionable feedback to developers about their codes.

The more, the time taken for feedback, the more time is wasted in delivering value to customers. The feedback can be faster if developers are running unit tests early in the pipeline saving time for them.

The feedback should include customer experience metrics tied to improve overall DevOps metrics. Customer experience metrics need to be shared across the organization, reviewed by a set of identified cross-functional team members to discuss how organizations can work on them to meet most of the end-user expectations. Cross-functional teams should create a product roadmap to break user stories small enough to release them fast and provide value to users. Feedback and involvement from business teams avoid backlogs of non-value-added features later in the development.

#6 – Monitoring should extend to feedback loops

In DevOps, just monitoring without taking relevant actions is a sign of missing feedback loop. Feedback is the extension of Monitoring. Monitoring infrastructure, applications and logs do not give a clear and comprehensive picture of DevOps as a whole.

In current times, DevOps teams are monitoring different areas of DevOps pipeline resulting into a siloed picture of the DevOps pipeline. The way to DevOps feedback starts with alerts and monitoring extending into feedback for all the areas of DevOps pipeline and recommended improvement areas. Some areas to track for creating feedback in a simple delivery pipeline are–

Commit Stage–Commit notifications, build fail/pass results, unit test results and code metrics

Testing Stage–Performance testing results, having threshold criteria for performance and comparing them

Deploy Stage–Production performance monitoring and deployment reports.

Qentelli’s tool like TED covers the entire DevOps lifecycle and provides feedback on how each of the process are doing and actionable insights for potential flaws. TED is technology and tool agnostic and can be integrated with lots of DevOps tools used by organizations.

The nature of DevOps feedback loop

The right feedback loop must bear these characteristics–Faster, Relevant, Actionable and Accessible. Engineering teams need to set rules for acting on different feedback and own the complete code quality checked in by engineering teams.

We all remember the classic example of SlideShare DevOps failure where one small reorganization in database brought whole site down for over 60,000 users. Had it been a timely and properly targeted feedback at the developer level they would have avoided the whole situation?

Another example comes from IBM in early 2000s. IBM started their DevOps journey to speed up their software releases. But unable to achieve so, they assumed that the problem is with code deployment and automated it. Still, didn’t achieve results. Later with the help of experts they discovered that the problem was with operational and development environment. Again, a relevant feedback would have given the expected results.

This is the early 2000s scenario, companies failed, changed strategies and now, they are maturing in DevOps. But still things that seem obvious go wrong with the broken feedback loop. Some scenarios we still encounter are failed smoke tests in production, insufficient test code coverage, etc. The feedback loop places a set of rules to roll back to the original state or not to introduce any new changes without reaching the threshold of the test code coverage.

Feedback is fundamental not only to DevOps practice but throughout the SDLC process. A customized feedback loop and process is necessary for every organization to act as a control center to alter the course early when things go wrong.

In the next blog of this 2-blog series we will talk about the integrating feedback at each stage and how the future of DevOps with feedback looks like. Stay tuned!

DevOps – why should the Business fund you?

Once left out of business conversations, the role of CIOs or IT leaders is shifting from delivery executives to business executives. Why? Technology is used as a commercial advantage; organizations allocate significant budgets for technology initiatives and CIOs are the best person to justify investments and advantages. While delivery is still at the core of CIO responsibilities, but they need to put a bigger picture of technological and delivery trends to leverage them for business goals. DevOps is one such practice that requires immediate focus from C-suite.

CEOs seek answers on how technology investments will retain the existing customer base, how sales will increase by X% for online channels, how our competitor increased market share in XYZ geography as compared to last year. DevOps gives an answer for CEOs questions like:

  • How we are planning to retain the customer base and engage them? –Introducing loyalty rewards and programs in our application. DevOps can help us in building and releasing these features fast.
  • How sales will increase by X% for online channels? –DevOps will help to introduce frequent application features with no downtime.
  • How our competitor increased market share in XYZ geography? –They are adopting DevOps that helps in continuous monitoring and incorporate feedback to release new features for customers every month.

There are scenarios where being agile is at the topmost priority and CIOs don’t know how to translate DevOps benefits into agility metrics. Sometimes we have seen that teams are already practicing DevOps but unable to quantify the benefits to convince the management about the success. In some other cases, management was happy about the success of DevOps pilots, but they didn’t have confidence to implement it across geographically dispersed teams or other reasons. These scenarios are common and bring up the need to convince funding for an enterprise scale initiative. CIOs should approach business leaders proactively with a business case that talks beyond application delivery and releases.

Organizations are at different stages of exploring DevOps practices, but are confused about the full-fledged implementation. At Qentelli, we have consulted organizations to advance their application delivery using DevOps, the pilot DevOps projects were successful and all reacted positively, but for funding a full-fledged implementation, organizations lack confidence.

Building a business case for DevOps

In current times, applications with limited agility are frail for competing with digital native applications. Technology leaders experience pain points like non-compliance, unsupported hardware and software components, integrations problems, lack of finding technical skills to maintain outdated technologies and difficulty in adding or updating new features with the old development practices. Businesses are caught up in deciding for the technical capital investment, with the less idea how competitors are using DevOps for commercial advantage. CIOs have to approach CEOs by building a winning business case to fund DevOps implementation.

Must-haves in the DevOps business case

Apart from your business case format of executive briefing, financial ask and support, DevOps business case should convey the message of being a business enabler using technology.

Businesses are less worried about the tool and technology stack used for the DevOps implementation. The implementation methods, phases and processes are also of less consideration for them. While preparing DevOps business case, the most coveted section is how DevOps translates into business bottom-line. Thus, DevOps business case should talk about numbers relevant to business bottom line, cost savings, optimizing operations, efficient cash flows and tech debt reduction translated to operating flows. Some of the ways to do it are –

  • Translate the recent downtime you experienced in dollars and how we are losing customers. Show how DevOps reduces friction between Dev and Ops team.
  • Present numbers to management on how your teams are spending times on fixing non-relevant issues of fixing and finding things. Talk about DevOps continuous loop that finds relevant issues early in the development and provide insights to fix them.
  • Time wasted in finding irrelevant issues and fixing them because of lack of prioritization. This time can be used to increase test coverage and creating unique tests increasing software quality.
  • Highlight how DevOps stresses on automation and this can save a lot of time by automating manual tasks.
  • Educate them about the rising costs each year with the maintenance and inflexible systems architecture.
  • Present success stories of how DevOps helped in advancing the application development life cycle. If you can present competitor case studies, chances are high that business leaders can relate to it easily.
  • Highlight the competitive risk of losing market share to competitors who are already using DevOps.

DevOps Vision for business

If implemented right, DevOps brings immediate and measurable business benefits. But DevOps is a continuous exercise and may require C-suite to become brand ambassadors in promoting DevOps. As a forward-thinking business executive CIO should present the vision of DevOps to business.

CIOs should envision and present to the management how time and cost saved can be put to the best use in the company’s interest. For instance, customers are looking for a new solution/product, 10% of the engineering time saved will be used for it. These details assure management about DevOps as not a quick fix; usually demanded by Dev or IT but a business strategy for numerous benefits.

Need more reasons to convince your management

Qualitative

Conclusion

Unlike other technology initiatives, DevOps is a joint venture between business and technology teams. This requires management buy-in and budget for implementation. The pointers highlighted above will help CIOs to present the business case backed by relevant numbers, case studies and vision of the DevOps exercise. A winning business case for DevOps is crucial to the overall success of DevOps initiatives.

As digital future approaches, CEOs are looking to build deep digital businesses. More than ever, CIOs are tasked to guide CEOs to build these businesses. The CIO-CEO relationship has improved significantly but still CIOs are looked at as cost centres for getting rid of legacy systems, moving to cloud or rather multi-cloud, get new firewall, etc.

Qentelli’s DevOps assessment provides a complete overview of business costs, risks and impacts of adopting DevOps. This information is valuable for building a business case for DevOps and communication the benefits to executives and other stakeholders. Start the conversation with us at info@qentelli.com to help in building your DevOps business case.

Why and How AI and Machine Learning Make App Development and DevOps More Efficient

AI is one such technology that can be applied to every business process, as it runs on data. With the advent of internet and computing power, humans have created troves of data in past few decades. The rapid adoption of DevOps practices has created similar amounts of data within the companies to be utilized for creating intelligent AI systems particularly using Machine Learning (ML) accentuating their DevOps practices.

Is it worth investing in Machine Learning and Artificial Intelligence for DevOps efficiency?

Machine Learning has been one field getting a lot of traction after technology giants like Google made frameworks like Tensorflow open-source. It is very clear that the future of application development is about intelligent systems, utilizing data being created and letting the systems learn by their own. This is a new paradigm shift and whether companies are ready or not, it is going to take over.

There have been, over the past 5 years, companies have invested a lot of resources to collect data to build Machine learning algorithms for their specific use cases. So, does Machine learning or AI make sense in the DevOps world? How does it help improve efficiency? What use cases have been explored successfully in this space already? And for answers to many more questions, read on!

Data is the King

Anyone who has explored ML/AI knows that Data is the King. Without a huge dataset, it is difficult to derive feature sets and achieve high levels of accuracy for any Machine learning algorithm. If you look around, your DevOps toolchain is already producing a huge stream of data, as your developers work through bug fixes and releases. The stream of data related to your git commits, milestones and releases, infrastructure deployments, test execution, build logs, application log files, the list just goes on and on. Many companies have been successful in leveraging this data stream and build algorithms that resulted in improved efficiency.

Invest in data

DevOps data not only helps technical teams but also helps business teams in understanding how DevOps is improving their bottom lines. This helps businesses in achieving their goals, schedule releases and predict customer satisfaction and take immediate corrective actions. DevOps with data helps in providing end to end visibility on the software development lifecycle keeping everyone informed in the loop. DevOps data is the first point to create automated and intelligent systems that helps in developing advanced tests for complex and distributed applications.

Companies are now utilizing DevOps data to create automate and intelligent systems that helps in creating tests and executing them. They produce data that are utilized to create automated for complex and distributed applications that are being developed.

Leveraging the power of Data in DevOps

Machine learning has found the right fit in anomaly detection and prevention for a long time now. Companies have successfully blocked attempts to hack a network by identifying patterns and detecting anomalies. Going by the same principles many of the real-time application and infrastructure monitoring tools, which provided analytics and dashboards have integrated Machine learning as one of the key capabilities, to help predict application or infrastructure failures, and notifying appropriate stakeholders to take corrective action. Splunk, Elasticsearch are few examples in this space. Similarly, many companies are now beginning to look at patterns in their planning tools such as Jira, to improve their planning efficiency. Many other use cases related to code commits, build failures are being explored to increase the overall DevOps efficiency.

Going beyond Descriptive and Predictive analytics

As we have seen, many of the use cases have been more around Descriptive Analytics, i.e., providing inferences automatically based on what has occurred, and Predictive analytics, i.e., identifying an error or event before it occurs. These two approaches themselves provide huge efficiency improvements for Operations and Business teams, but the real power of AI is when issues can be predicted and can either be remediated automatically or solutions prescribed which point to Knowledgebase articles, for a quick fix. This approach also is known as Prescriptive analytics, has the power to drive DevOps in a much more efficient and effective way.

Continuous feedback as an outcome of Prescriptive analytics

Companies have discussed it, some have even claimed their systems provide continuous feedback from customers, but the true continuous feedback loop involves not just getting feedback from end users but being able to provide faster feedback at each stage of CI/CD pipeline. Prescriptive analytics is already being applied by companies like Atlassian in one of their most popular support tools, Freshdesk. Their machine learning algorithms drive huge business efficiency, due to its ability to quickly understand and respond to end users with prescriptions to their problems. Being able to prescribe a solution across stakeholders in DevOps lifecycle, and analyzing the usage patterns will enable true continuous feedback across the lifecycle.

Driving efficiency true DevOps way

As discussed above, and with details of how some companies are already driving business and operational efficiency, it will only get better with time. The automated process of identifying patterns and suggesting corrective measures will bring out the true power of DevOps. The future businesses that are trying to drive efficient DevOps practices using AI, we will see more faster deliveries, less failure rates, improved customer satisfaction ratio and seamless experience on trillions of connected devices.

Is it for me?

It depends on how efficient you would want your processes to be. If you are just getting started on the journey, why not leverage tools that have the intelligence built in? If you have achieved a good level of maturity and efficiency in your DevOps implementation, it is time your data did the work for you, and for those who are in midst of their implementation, or have some level of DevOps maturity, pick your use cases.

Companies starting to put efforts in utilizing data for DevOps efficiency, should look to invest in capturing engineering life cycle data. DevOps data helps in aligning technological initiatives with business goals. Now is the right time to get started!

Why cloud and DevOps succeed together

Businesses are in the continuous flux of providing perpetual application performance, zero downtimes to trillions of connected devices and redesign customer interaction on digital assets. Moving to the cloud is one way to achieve mentioned parameters. Moving to the cloud is not the ultimate survival strategy. They still need agility, cost-savings, and better performance for millions of connected devices. The development and cloud operations must go hand in hand to make the most of cloud platforms. Organizations still using traditional development models miss out on the benefits of cloud such as – automation, self-provisioning, infinite computing and flexibility.

Cloud and DevOps are successful together

DevOps bring two teams together and cloud facilitates their smooth relationship by automated provisioning and scaling of hosting resources. Developers can quickly set up new environments without help of IT operations. Meanwhile, IT can investigate other functions related to infrastructure costs, enabling security and dynamics. Cloud is the common language here and thus, connects two different teams.

Cloud and DevOps both have the same purpose of providing speed, agility and automation to businesses. DevOps stresses on automation and practicing everything continuously. Cloud enables automated provisioning of computing resources, scaling up and down, and usage-based cost. Both solve the automation problems for organizations.

They have an ability to bring in a dramatic shift by providing a centralized platform to test, automate and deploy apps. In traditional setups, there are dependencies on the operations team. Legacy systems pull downscaling of new applications because of incompatibility with new age technologiesDevOps on cloud gives better application availability and faster deliveries. But it is easier said than done.

The article highlights how teams starting DevOps on cloud should approach it to keep software delivery, quality, performance and security intact –

Security in the cloud – DevSecOps is already taking the centre stage for organizations moving ahead in DevOps journey. Organizations are concerned about security while doing DevOps in cloud because of increase in releases, frequent application changes and data breaches, DDoS attacks etc. Organizations using DevOps in the cloud with new technologies like micro-services, containers etc. have new security challenges into the overall product architecture.

It becomes very critical to integrate security from into the build and test pipelines. Cloud security best practices like identity and access management, security architecture drawing in the application development and robust compliant practices are few points to consider.

Taking care of automated performance engineering – Cloud architectures can be complex and can cause unpredictable issues in the workload, every time a new code is being deployed in the environment. Performance tests with continuous integration, build and deployment provide a stable performance of cloud applications.

Platform agnostic DevOps tools – Organizations are aware about disadvantages of getting into vendor lock in. The quickest solution for organizational buyers is to seek help from same cloud vendors for DevOps tools, but not an ideal thing to do. The right set of DevOps tools should be platform agnostic and must be able to scale as per the requirements. 

Achieving CloudOps – Cloud has gained popularity because of its high availability and load balancing features that keep the applications running continuously. Continuous Operations can help companies to achieve zero downtime with the ability to run software into cloud using right Cloud Management Platform, Monitoring tools that help in achieving continuous everything in the CloudOps.

The Qentelli Way

Qentelli has worked with some of the world’s largest companies to implement DevOps practices and CI/CD in the cloud. We have pioneered usage of DevSecOps, Performance Engineering, CloudOps in these engagements.

Qentelli has a suite of accelerators such as MoBe (Mobile and Beyond) for all the device access and automation, FAST (Framework for Automated Software Testing), AiR (Artificial Intelligence for remediation across the DevOps value chain), TED (Test Engineering Dashboard) and others that provide advantage to CloudOps initiatives by collecting data from various data sources and derive actionable insights to improve processes, provide predictions for incidents and auto-healing broken processes and get a complete view of functional and non-functional test results. Facebook Twitter LinkedIn

About Qentelli

Headquartered in Dallas, TX with global delivery teams in India, Qentelli is an Industry Thought Leader in Quality Engineering, Automated Testing, and Continuous Delivery. With high performing engineering teams working in the dedicated Innovation Group, Qentelli brings design thinking to address complex business problems and enables Continuous Delivery across Enterprise IT through automation for its global customers – www.qentelli.com

Getting Started with DevSecOps

If you ask CIOs or even CEOs what keeps them up at night, chances are that most of them will respond with ‘Security Breaches”.

IT Security has become a game of continuous one-upmanship on both sides of the fence – attackers are finding new ways to get into systems, while defenders are innovating to stop them before they do.

How can developers and testers help to improve the security posture to at least some extent? The answer is “baking” security into the application development process.

Web applications have a much lower risk profile with improved firewalls and access controls being deployed, but they continue to be a large attack vector – large enough to dedicate time and money to reduce risk.

An alarming fact published by Veracode is that about 75% of all applications have some security vulnerability that could be exploited!Source: State of Software security – A Developer’s Guide 2017 by CA Veracode


Kaspersky Labs found that 90% of Enterprises had a security breach in a quarter, with the potential financial impact on an average of $550KSource: Damage Control: The Cost of Security Breaches by Kaspersky Labs 2018

Comparing OWASP Top 10 from 2013 to the 2017 version (latest version), it is surprising that the Top 2 vulnerabilities are persisting. The next 3 are also issues that point to lack of security coding practices and automated security testing.Source: OWASP Top 10

With so much data available on the vulnerable areas and business impacts, are companies doing more frequent security testing for their apps? Apparently not.Source: https://www.sans.org/reading-room/whitepapers/analyst/survey-application-security-programs-practices-34765


The Solution: DevSecOps

DevSecOps is not a new concept, but for companies that have started or just starting with DevOps initiatives, it makes good sense to include Security testing within their build and test pipelines from the start.

With Dev teams using open-source and proprietary libraries, cloud, micro-services, containers etc. joining the product technology landscape, each of these components bring along their own set of security challenges into the overall product architecture.

How can Engineering teams start with integrating security tests within DevOps?

Teams can start using the 3 layers of application security integration in the Development process:

  • Secure coding standards
  • Integrating Static Application Security Testing (SAST) tools in Developer Builds
  • Integrating Dynamic Application Security Testing (DAST) tools in QA Builds

Let’s take a closer look at these layers and how you can integrate them into your Development process for overall security around your application stack –

Secure Coding Standards

It all starts with the code – Unsafe coding practices can result in vulnerabilities in application software that can be difficult to detect and expensive to fix later in the lifecycle. OWASP, SEI, NIST and several other Standards organizations and private companies publish secure coding guidelines covering all major programming languages.

These practices cover all development areas, for example:

  • Input Validation
  • Authentication and Authorization Management
  • Credentials Management
  • Session Management
  • Access Control
  • Encryption of Data at rest and in Transit
  • Resource Management

Integrated Development Environments (IDEs) are used by almost every developer, so plug-ins have been developed for these IDEs that can assist Developers in identifying and fixing errors when writing source code. Some of these tools include SecureAssist, GreenLight, ASIDE, FxCop, FindBugs.

Static Application Security Testing (SAST)

There are multiple tools available that can automate static code analysis rules during the build process and prevent developer branch from merging with the baseline repository. Some of the validations that can be performed at this stage include:

  • Software Component Analysis for identifying issues in third-party libraries and packages
  • Secure coding guidelines for the specific language
  • Unpatched libraries – when more recent versions of libraries are available, but not included in the source code calls
  • Injection – although more well-known for SQL calls, Injection vulnerabilities can occur in API calls or even Javascript
  • Unreleased Resources – DB connections, object references, data collections etc., may not have been released in the code, potentially leading to Denial-of-Service (DoS) attacks
  • Improper Error-handling – Developers may insert messages during development for easier debugging and may miss removing them when promoting code to higher environments. Another common mistake is not having a catch-all Error handling mechanism, that can provide a useful error message without revealing the technical details of the OS, Servers, language etc)

Some common SAST tools that integrate with CI Pipelines are:

TOOL LANGUAGES SUPPORTED SUPPORTED CI/CD PLATFORMS
SonarQube Java, .NET, Python, Ruby and many other languages Jenkins, TeamCity, Microsoft TFS, Bamboo, Azure Pipelines
Checkmarx Multiple Languages including Java and .NET Jenkins, TeamCity, Microsoft TFS, Bamboo
Fortify Multiple Languages including Java and .NET Jenkins, Bamboo and some other tools through CLI
RIPS PHP is the primary language supported Jenkins, Bamboo
IBM Appscan Multiple Languages including Java and .NET Jenkins, TeamCity
Brakeman Ruby on Rails Jenkins
OWASP Dependency Check Java and .NET fully supported. Other languages have some limited support Jenkins
Dynamic Application Security Testing (DAST)

As the name implies, DAST tools find security issues when the application interacts with other system components like web services, DB and third-party components. In short, these tools run checks that simulate an external attacker trying to gain entry through the application.

Due to the dynamic nature of the applications, DAST tools are not 100% effective in uncovering security issues, but they can provide a very effective line of defense. Most common vulnerabilities have already been identified and included in these tools, so only very smart hackers can find issues after these tests are run.

Some of the core validations that DAST tools can perform include:

  • Application Penetration Tests
  • Production Deployment Configuration Tests
  • Injection tests
  • Session Management
  • Cross-Site forgery
  • Data at Transit issues

Common DAST Tools that integrate within the CI-CD Pipeline include

TOOL APPLICATIONS SUPPORTED SUPPORTED CI/CD PLATFORMS
OWASP ZAP Web Jenkins
Gauntlt Web Gauntlt can be set up within Docker containers and then integrated with Jenkins
BDD-Security Web Jenkins can trigger the BDD-Security Framework and analyze results
IBM AppScan Web, Web services/API, Mobile Jenkins
HP WebInspect Web, Web services/API, Mobile Jenkins

We can construct a pipeline integrating these tools as shown below:

Note: The Tools shown are for illustration only – the actual toolset will depend on your environments, platforms, budget, Risk profile etc.

Key Point: To increase the security Test footprint, you may have to write custom tests (using selenium or similar tools). These could cover areas such as:

  • Duplicate session validation
  • User Authorization tests
  • HTTP Header spoofing

Key Point: The results generated by all of the tools are NOT uniform, with the result that you may have to review multiple reports, logs etc to get an overall picture. For example, Jenkins can call HP Fortify, but the tool results are not reported back to Jenkins.

To summarize:

  • Your applications and data are under constant attack. A breach can cause a very serious financial and reputational loss for your business and, increasingly, for you personally (due to US & European Regulations)
  • There is no magic fix for security. Instead, a defense-in-depth strategy starting from the application level and comprised of multiple tools, processes, and practices is much more resilient and effective
  • Leverage automation where you can, particularly for software testing
  • Integrating Automated security tests into your DevOps pipeline is becoming easier with modern tools
How can Qentelli help:

Qentelli works with some of the world’s largest companies to implement Automation across the lifecycle and has pioneered use of DevSecOps in these Engagements. Qentelli also has a custom-built Engineering Dashboard, TED, that can pull results from any software product which exposes such data through an API.

TED can be used to review metrics from the entire DevSecOps toolchain to get a complete view of functional and non-functional test results.

To learn and explore more in detail about Qentelli’s AI-driven automated testing solutions and DevSecOps implementations, please write to us at info@qentelli.com. Our experts will be delighted to engage with you. Also, you can visit Qentelli’s social links for more details– Facebook Twitter LinkedIn

About Qentelli

Headquartered in Dallas, TX with global delivery teams in India, Qentelli is an Industry Thought Leader in Quality Engineering, Automated Testing and Continuous Delivery. With high performing engineering teams working in the dedicated Innovation Group, Qentelli brings design thinking to address complex business problems and enables Continuous Delivery across Enterprise IT through automation for its global customers.

Is your “Ops” truly integrated into your “DevOps” lifecycle? The significance of Ops intelligence

Companies are adopting DevOps at lightning speed, but they are faced with the challenges of adopting it successfully. The difference between successful and unsuccessful DevOps adoption is impact in measurable metrics of faster feedback and recovery times, quality code, less downtime, high availability and better communication between Development and Operations teams.

The changing meme has brought in a radical shift in the responsibilities of development team from just writing code, and doing hand-offs to configure virtual and cloud servers, deploy applications, monitor application health and respond faster in terms of fixing bugs. But is it solving the problem for businesses to release faster, lesser downtime, less production failures? In one word, No, the operations team is still having night mares as software releases have become more frequent when compared to the past releases that occur once in a quarter or half yearly.

Thus, the IT operations is more relevant and need to be better placed in DevOps stack to get the desired business outcomes. As the article is titled, “Is your Ops truly integrated into your DevOps lifecycle”, we want to emphasize on how adoption of DevOps requires operations to be tied well with automation and real-time monitoring and intelligence initiatives. The role of Operations from classical operations (starting with the servers, keep them running and doing the deployment) to new operations where they are managing infrastructure, configuring and monitoring systems and networking, enforcing policies around security and compliances, and other non-production application related tasks that are crucial for better application quality and less production defects.

Companies believe they are on the right journey when the developers are equipped with continuous integration, build, deploying and managing all environment from development to production. We interact with many companies while helping them with their DevOps initiatives where developers are doing steps mentioned above, probing further they revealed that they still don’t have a measurable impact on speed and quality. This is because since their operations team have moved from managing manual tasks they have not been aligned with the task of continuous and real-time monitoring and feedback required to test effectiveness and defect traceability before it got slipped into production. The reason can be DevOps washing leading to just DevOps tools, processes and technologies and fail to look beyond it to measure that impact of DevOps over desired KPIs.

There’s so much of operations data and how does this impact “DevOps” lifecycle

At Qentelli we believe, in DevOps, Ops is not just about the operations team but also about operations data. Companies are holding so much of operations data and development teams are working in separation with these datasets. Companies are collaborating on processes, but data needs special attention to achieve business outcomes with DevOps. The first step of getting Ops in DevOps is to decide on the measurable metrics businesses want to achieve. Look for the past data that can be measured to derive insights and actionable items to achieve them.
In the DevOps environment, most of the environment assume transparency and does not realize the lack of intelligent dashboards and have manual dashboards (prone to error and time taking) to know about the real-time intelligence. The manual dashboards do not suffice the aggressive business outcomes of achieving agility and digital transformation. Operations data must be looped in the DevOps process to identify patterns and anomalies automatically.

Operations team can use this data to identify inconsistencies early in the testing stage itself and improving them can impact the overall quality of the application or software being released. Automating test runs for speed, quality and accuracy can help in saving time and detecting problems that might take too much of time or in haste, can go unidentified in the end-user environment. With Artificial Intelligence (AI) and Machine Learning (ML), tools available in the market, companies need to put operational data together and, analyse them, define KPIs, measure KPIs from them and create actionable steps for improvement of DevOps practices. The next action after deriving insights is to keep your operations team in continuous monitoring mode to predict incidents even before they happen and integrate ‘Ops’ truly in DevOps.

The future of Ops is to help developers in just self-serving them with the maximum automation and least intervention and monitoring real-time data to ensure the quality is not compromised with more frequent releases.

Qentelli’s TED as Quality Intelligence Platform:

Qentelli created TED, an Engineering dashboard with capabilities to collect data from various data sources, create metrics and define KPIs and derive insights for improvement. What makes TED a true Quality Intelligence platform and unique, is its ability to derive actionable insights for most key DevOps KPIs out of the box and artificial intelligence (AI) to improve processes, provide predictions for incidents and auto-healing for broken processes. Qentelli helped some of Fortune 1000 companies get better with their Quality and Speed using TED. This can help operations team to have end to end visibility of where companies are leading on their DevOps journey and get it on the right track if it goes here and there.

To learn and explore more in detail about Qentelli’s AI-driven automated testing solutions and DevOps implementations, please write to us at info@qentelli.com. Our experts will be delighted to engage with you. Also, you can visit Qentelli’s social links for more details–

Facebook Twitter LinkedIn

About Qentelli

Headquartered in Dallas, TX with global delivery teams in India, Qentelli is an Industry Thought Leader in Quality Engineering, Automated Testing and Continuous Delivery. With high performing engineering teams working in the dedicated Innovation Group, Qentelli brings design thinking to address complex business problems and enables Continuous Delivery across Enterprise IT through automation for its global customers.

Security and Compliance in the Continuous Delivery (CD) World: things to make your CD Journey right

Security and Compliance in the world of everything “Continuous” can be frightening to most of the engineering and IT heads. External regulations like HIPAA and SOX applies to every organization. Few industries like healthcare, digital payment service providers, financial services, and listed companies have stronger compliance needs.

DevOps, the enabler of Continuous Delivery, has enabled businesses to innovate fast, frequent product upgrades and releases. But some businesses are finding their IT teams pressed with challenges to manage stable IT infrastructure for scheduled development work while taking care of the stringent compliance requirements. This limits the role of IT teams in innovation and put them back in the firefighting mode of traditional IT teams.
Futuristic technologies and applications cannot withstand trade-off between innovation and adhering to security and compliance, as most of the customer-facing applications hold personal data of customers making it high risk for exposing it to potential security threats. The middle path is to adopt CD in such a way that it aids IT, teams, to reduce the challenges of infrastructure management and do more innovation and ensuring security and compliance. Here are a few things to ensure security and compliance in the CD journey –

Assess compliance requirements in the beginning

Before beginning your CD journey, ensure you have well-documented compliance requirements that help in building the complete CD pipeline to take care of your security and compliance practices in the form of a code with a continuous build, test, security tests, performance tests, and deployment. Security and compliance must be viewed as the part of automating infrastructure and continuous testing before applications get deployed.

Automate Compliance Management

CD is practiced in its truest form when businesses will have automated every process in the CD pipeline. Automating infrastructure management with DevOps tools such as terraform, chef, puppet etc. helps in ensuring consistency in environments. Secured and compliant environments can be accessed by developers using infrastructure as code tools while replicating the enforced security measures and compliance practices. Replicating secured and compliant environment can be created as a repeatable and consistent process without getting IT teams involved and act as watchers if there’s any inconsistency in the environment. This also ensures a continuous feedback loop incomplete CD cycle for compliance requirements to ensure fast remediation of any bugs.

Just like infrastructure as code, compliance as code is very much doable. Compliance requirements can be coded that ensures that every change request or bug fixes are adhering to the compliance and security practices leaving a trail of changes done by the developers. Stating clear requirements in form of code makes it easy for developers to understand what is expected out of compliance adhered application. Compliance tests can be run to ensure that there are no deviations in the application before it reaches the deployment phase. The automation capabilities of CD can be extended to security and compliant practices so that even compliance standards are consistent and repetitive.

During audits, it becomes companies to show auditors about every code or change made and thus, ensuring transparency and visibility in the organization as well as with regulatory authorities.

The Qentelli Way

Qentelli has setup DevOps Operations Centre for many enterprise customers in Banking and Financial sector, to ensure that Security and Compliance are met for both applications and infrastructure, and continuous monitoring is provided on the various environments with real time alerts and notifications sent to appropriate stakeholders. Qentelli’s AI-driven DevOps solutions provide predictive analytics to help identify issues before they occur and provide prescriptions to resolve the issues.

To learn and explore more in detail about Qentelli’s AI-driven DevOps implementations and DevOps Operations Centre, please write to us at info@qentelli.com. Our experts will be delighted to engage with you. Also, you can visit Qentelli’s social links for more details – Facebook Twitter LinkedIn

About Qentelli

Headquartered in Dallas, TX with global delivery teams in India, Qentelli is an Industry Thought Leader in Quality Engineering, Automated Testing and Continuous Delivery. With high performing engineering teams working in the dedicated Innovation Group, Qentelli brings design thinking to address complex business problems and enables Continuous Delivery across Enterprise IT through automation for its global customers.

How to Create a Successful DevOps Team in a Global Enterprise.

“In the past, business success was all about size: The large eat the small. Today, business success is all about speed: The fast eat the slow.” Daniel Burrus, Futurist.

DevOps is not the new black anymore and has become quite prevalent in all types of organizations from early-stage startups to multinationals to become dynamic and agile. Those who have adopted DevOps or are in the process of adopting it knows well that it is beyond a set of tools and technologies. Culture becomes successful when organizational teams/members adopt it to propel towards common business goal enabled with technologies.

A lot has been said and written about the benefits of adopting DevOps environment; organizations struggle to find their ground when it comes to creating successful DevOps teams in global enterprises. If you are reading, we presumed that you are looking to or are in the process of building a successful DevOps team. From our experience of working with organizations across the world trying to build their DevOps practice, Qentelli has identified a few things that can be of help for your DevOps initiative –

1. Collaboration is the key – The first and foremost requirement for building a successful DevOps team is to lay a proper change management process. People are resistant to change and thus, laying complete guidelines to undergo change with DevOps is considered very useful. In traditional organizations, Development and Operations team are working in siloed environment, but to sustain in multi-modal IT environment, development and operations team work together and are equally responsible for release cycles, production environments, software maintenance, versioning controls, and providing high-quality codes to operations for deployment.

Tip – A successful DevOps team should work on breaking the notion of Developer – who only code and Operations – who only support production to Developer – Who code and help operations to support the application in production and operations – who works parallel with developers to support production need and environment. There are a lot of tools in DevOps that can help both the team for Configuration Management, Test-and Build systems, Application Deployment, Collaboration, and Communication and Monitoring.

2. Top-down approach with Continual Improvement – DevOps comes with the benefit of business innovation, reducing time to market, more release cycles or updates in the product development lifecycle. The DevOps culture of Continuous Development with continual improvement will trickle down once there’s an optimal workflow process, team restructuring and reorganizing and have right set of infrastructure and automation tools to move ahead with the agreed development framework by the management or engineering heads.

Tip – DevOps requires CIOs, CTOs, and other C-suite to champion the cause of adoption of DevOps and scaling it up to the enterprise level. Business people need to understand first the challenges of Development and Operations working in seclusion with little whereabouts of each other to develop a culture of communication and collaboration to take collective accountability of success and failures.

3. Embracing Continuous Integration and Continuous Delivery (CI/CD) – With a change in culture, a successful DevOps team also needs essential changes to be made around technology like an automation of pre-production, testing, deployment, and integration. CI/CD lies at the heart of DevOps as they promote working in collaborative and shared manner. Global enterprises embracing DevOps knows the transitional shift they have experienced with developers working in isolation and waiting for months to integrate code, fix bugs, solve code conflicts and wasted time in duplicated efforts. Similarly, software release cycles were slow due to the manual provisioning of production environment leading to delays and errors.

Tip – A successful DevOps team is well-equipped and well trained with the ability to quickly respond to failures, errors and fixing them quickly. Enterprises looking for building a successful DevOps team with the ability to embrace CI/CD and continually tweaking processes to scale it to enterprise level need to know right toolkit for their teams, business environment, and business goals.

DevOps is a work in progress

As per a study by RightScale, cloud-management provider, the percentage of enterprises that have adopted DevOps principles reached 84% in 2017 but the same study shows that just 30% of these enterprises have been able to scale it to company-wide adoption. Enterprises looking for company-wide adoption must learn that DevOps is a work in progress and requires the strategic view of sustaining its usability, objectives, and effectiveness. DevOps is neither best of the industry’s toolkit nor team nor process; it is a shift in how IT teams work where people come first then the technology.

At Qentelli, we work with businesses as a partner to drive their DevOps initiatives after having a firm understanding of their business processes, teams and where DevOps fit best for them and their people. We work as an “enablement” team and empower the existing stakeholders to adapt to enhanced roles and responsibilities to drive a successful DevOps implementation. Qentelli has helped setup DevOps Operation Center for many enterprises to continuously evolve their implementations.

To learn and explore more in detail about Qentelli’s AI-driven automated testing solutions and DevOps implementations, please write to us at info@qentelli.com. Our experts will be delighted to engage with you. Also, you can visit Qentelli’s social links for more details– Facebook Twitter LinkedIn

About Qentelli

Headquartered in Dallas, TX with global delivery teams in India, Qentelli is an Industry Thought Leader in Quality Engineering, Automated Testing and Continuous Delivery. With high performing engineering teams working in the dedicated Innovation Group, Qentelli brings design thinking to address complex business problems and enables Continuous Delivery across Enterprise IT through automation for its global customers – www.qentelli.com

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