4 Strategies to Create a DevOps Culture
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The document discusses strategies for creating a DevOps culture and system that fosters innovation and customer obsession. It recommends forming a cross-functional reliability team to gather user experience data, perform correlational analysis, and devise plans for building and maintaining resiliency. The document also advocates investing in continuous delivery, agile methodology, and intelligent analytics to achieve optimized software quality, velocity, and costs while driving business value.
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4 Strategies to Create a DevOps Culture
- 1. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Vivek Santhana, DevOps Advisor Asia Pacific & Japan May 3rd , 2017 4 Strategies to Create a DevOps Culture & System that favors Innovation & Customer Obsession.
- 2. 1.http://www.forbes.com/forbesinsights/synchrony/index.html 2.https://www.accenture.com/us-en/insight-state-b2b-procurement-study-uncovering-shifting-landscape BORN DIGITAL TRANSFORMING 82% 94% Of B2B buyers research online1 Of consumers research online 2 Digital Revolution Is Happening Every Company Must Become a Software Company
- 3. However, when organizations want to develop a new software idea, only eight percent of them are able to approve it, build it and deploy it to users in fewer than three months. Building Competitive Advantage With Software Through A Continuous Delivery Process, Forrester Consulting 1 Continuous Delivery: A Maturity Assessment Model: Building Competitive Advantage With Software Through A Continuous Delivery Process, Forrester Consulting, March, 2013.
- 4. And AWS Cloud Is A Key Enabler COST EFFICIENCY AGILITY INNOVATION
- 5. Running Resilient Cloud Based App & Infrastructure Is critical but can be challenging CHANGING BUSINESS CONDITIONS DYNAMIC INFRASTRUCTURES HYBRID INFRASTRUCTURES
- 6. Apps Demand Speed, Quality & Amazing Experience USER EXPERIENCE 79% of users will abandon a site if they don’t quickly find what they need3 QUALITY 2/3 of business leaders say the future of their business depends on the quality of their software2 VELOCITY 94% of executives face increased pressure to release apps more quickly1 1. 2014 Vanson Bourne study commissioned by CA 2. “Surviving Disruption, Leading Change: Winning in the Application Economy,” 2015 3. voke Market Snapshot TM Report: Service Virtualization – January 2015 WHILE DRIVING COSTS LOWER!
- 7. Invest in DevOps Culture and A “Software Factory” 1
- 9. 9 © 2015 CA. ALL RIGHTS RESERVED. Digital Transformation SDLC / DevOps Methodology / Continuous Delivery / Agile Products / Tools Omni/Digital Channel Enabled Business Rewritten By Software
- 10. 10 © 2016 CA. ALL RIGHTS RESERVED. Companies Are Evolving to a Modern Software Factory Based on 3 Core Principles SoftwareQuality Number of Releases Accelerates software development with iterative, incremental work cadences. Agile Invest Heavily in All Three Areas Increases collaborating between developers and operations. DevOps Fully automated, modern software factory that constantly churns out applications. Continuous Delivery Waterfall 10
- 11. 11 © 2016 CA. ALL RIGHTS RESERVED. CONTINUOUSDELIVERYMATURITY Manual Scripting Automated Continuous Optimized BUSINESS VALUE LEVEL 1 LEVEL 2 LEVEL 3 LEVEL 4 LEVEL 5 ? Organization depth and breadth of agile practice *Application release automation view Continuous Improvement End-to-End Connection Consistency & Collaboration Heroes & Heavy Lifting DevOps/Continuous Delivery is a Journey Maturing of Culture, Processes and Tools AGILEMATURITY Silos, manual handovers, waterfall, one release/year, monolithic apps, long term project/resource planning, error prone release processes DevOps, end-to-end delivery, incremental agile/sprint release cadence, multi- component micro apps, “on the fly” scrum planning, reliable and continuous releases Where are you? Software Factory
- 12. 12 © 2016 CA. ALL RIGHTS RESERVED. Point of View on the “Software Factory” Software Factory Support the pace and scale of Agile Fully Automated & Repeatable Model based Continuous Delivery supporting highly heterogeneous SDLC tool ecosystems Remove ambiguity from requirements & testing Abstraction of dependent services/APIs radically accelerate speed and quality “Pre instrumented” app releases Flexibility/portability across modern infrastructure & cloud platforms
- 13. Modernize Your Operations for AWS and Migrations 2
- 14. USER EXPERIENCE is the measure of IT and business success ANALYTICS to augment humans with data & machine intelligence UNIFIED VIEW of app, infra and edge optimizes experience Vision for Agile Operations
- 15. 15 © 2016 CA. ALL RIGHTS RESERVED. PERFORMANCE METRICSUSAGE REPORTS MACHINE LOGS Application Experience Machine Logs BUSINESS INSIGHTS OPERATIONAL INTELLIGENCE Store Search Correlate Open Elastic Platform Predict PrescribeDiagnose Predictive Analytics
- 16. 16 © 2016 CA. ALL RIGHTS RESERVED. 1 Slide Overview of PM and Highlights on Upcoming release SD-WAN vCPE vEPC NaaS Network Virtualization Legacy SDN/Cloud-Ready Network Performance Management Next-generation big data collection and analytics solution that helps the worlds largest networks successfully monetize service offerings while lowering the cost and complexity of service delivery.
- 18. 18 © 2016 CA. ALL RIGHTS RESERVED. Cross-Stack Correlations for Fastest Time to Resolution Correlation engine for analytical apps Leverages production- proven monitoring tech Unlimited data SaaS-enabled, Multi-tenant Open APIs for integration Fast time to value App Performance Agents Infrastructure Probes SDN/N Monitoring AppExperienceAnalytics ApptoInfraCorrelation LogAnalytics AssistedTriage CloudCapacityAnalytics SD-WANServiceChain INFRASTRUCTUREAPPLICATIONS NETWORKSINFRASTRUCTUREAPPLICATIONS NETWORKSApplication Experience Machine Data Open Analytics Platform Predict PrescribeDiagnose Anomalies TrendsPatterns
- 19. From Reactive To Predictive Safe Zone 360 DEGREE VISIBILITY SPEEDRPM REAL-TIME EFFICIENCY No Danger Ahead OPERATIONAL DATA CAPACITY MANAGEMENT PREVENTIVE ALERTS EVENT & LOG RECORDER PREDICTIVE PERFORMANCE METRICS Unified, App Centric Analytics Infrastructure to log/App correlation Predictive Analytics Predictive Capacity Analytics Machine learning-based prediction TRADITIONAL MONITORING MODERN HEAD UP MONITORING
- 20. CORRELATED ROOT CAUSEAPPLICATION HEALTH PREDICT PROBLEMS APPTOINFRASTRUCTURE CORRELATION
- 21. RAPID ROOT CAUSEENRICH DATA IN-CONTEXT ALERTS INFRASTRUCTURETO LOGCORRELATION
- 22. OPTIMIZED RESOURCESPREDICTIVE ALERTS WHAT-IF ANALYSIS PREDICTIVECAPACITY ANALYTICS
- 23. Form A Reliability Team and Process 4
- 24. Service Reliability Team and Process Form a cross functional team - application developers, network and cloud administrators, and support personnel Conduct regular meetings to share insights and devise new plans for building and maintain resiliency Gather user experience and infrastructure utilization of applications in test and go live environments Perform correlational analysis on IT and non-IT data (e.g. satisfaction, sentiment, sales etc.)
- 25. CA Solutions @ AWS Summit
- 26. Thank You Visit Us Booth # G7
- 27. For Informational Purposes Only Terms of this Presentation © 2016 CA. All rights reserved. All trademarks referenced herein belong to their respective companies. The presentation provided is intended for information purposes only and does not form any type of warranty. Some of the specific slides with customer references relate to customer's specific use and experience of CA products and solutions so actual results may vary. Certain information in this presentation may outline CA’s general product direction. This presentation shall not serve to (i) affect the rights and/or obligations of CA or its licensees under any existing or future license agreement or services agreement relating to any CA software product; or (ii) amend any product documentation or specifications for any CA software product. This presentation is based on current information and resource allocations as of December 2016, and is subject to change or withdrawal by CA at any time without notice. The development, release and timing of any features or functionality described in this presentation remain at CA’s sole discretion. Notwithstanding anything in this presentation to the contrary, upon the general availability of any future CA product release referenced in this presentation, CA may make such release available to new licensees in the form of a regularly scheduled major product release. Such release may be made available to licensees of the product who are active subscribers to CA maintenance and support, on a when and if-available basis. The information in this presentation is not deemed to be incorporated into any contract.
Editor's Notes
- Image ID : 47334020 Nearly every interaction that a company has with customers today has some digital component. Software is at the center of everything, and the common thread to achieving the innovation necessary to succeed is a hyper focus on digital customer experience. Customers expect a trusted experience, one that is explicitly secure, but also easy, simple and intuitive to use. They expect it to be personal, to be connected to what’s important to them. Digital disruptors are getting these things right.
- We always knew that the market was coming to us. Those of us that were on board 3-4 years ago will remember that we spend most of our time talking about tools removing constraints, or about how we got a quicker release. We didn’t have a higher narrative. This year the SDLC and Continuous Delivery enabled us to have a better narrative, and now Digital Transformation has enabled us to have an even more powerful narrative. If you enrich your conversation you’ll be much closer aligned to the execs who are driving these strategies. The CEO and CIOs who are engaging with us are doing so because we’re enabling them to reach their strategic business objectives. If you customer really wants to rewrite their software in business, they need to do that with Omni/ Digitally Connected multichannel and will have a strategic Digital Transformation initiative to drive it. That will be building a world class Software Development using DevOps methodologies like Agile development and implementing Continuous Delivery. And this will be underpinned by the right products and tools. All of us need to be comfortable elevating our conversation up this pyramid. We can also use this to help qualify our accounts: Does my customer have a DT initiative Are they chaning their SDLC as a result Are they moving to agile
- So how does a modern transforming organization deliver innovation faster with greater quality and amazing user experience so they can be more competitive and win in the app economy– they are investing in 3 core areas… 1st is the transformation and move to Agile (SAFE methodology) – move the SW development process to smaller chunks so you can be more nimble and responsive to changing market demand, but what organizations typically find after that is that while the dev teams are innovating faster, test, release and operations are still operation in a waterfall manner……which exasperates the release cycles..so once they have recitifies and adopted agile across all of the silos…. 2nd transformational change is the move to a devops context – while devops means so many different things to so many different people, it’s a cultural change and something is never stops, the organziations that do this well continue to evolved culture between dev and ops and adjust their roles in a working manner to focus on business outcomes – deliver omni-channel experience for an application to a new market and not operations and IT metrics 3rd transformation change is technology centric – need for continuous deliver tool chain that allows the context of devops and agile to flow (similar to the manufacturing analogy with robotics, build on open source adoption and industrialize agile and devops to benefit end consumer and ultimately improve competitiveness…so we can automated and end to end tool chain from dev to build to testing (unit to system to performance to acceptance) to release to production
- The Continuous Delivery Journey is not prescriptive, and companies may have teams at different stages of maturity. It’s also a journey of scale, where many companies are starting small (single project or team) and then scaling bigger (multiple, composite apps and many teams). The goal over the course of the journey is to become more automated, more standardized, more efficient and more agile across the enterprise—while improving quality of the release processes and applications. Teams also become more productive along the way, focusing on project work versus firefighting and maintenance tasks. Continuous delivery adoption involves the maturation of culture, application content/frequency (make up of the application, as well as cadence), release management processes, and tooling. Release culture: From “silo based & manual handovers” with strong hierarchical approach single DevOps teams in charge for end to end delivery Release content: from full application centric monolithic releases incremental, high-volume, multi component micro releases Release frequency: From waterfall and 1 release/year multi releases towards agile and sprint based release management Release management: from long term project resourcing and planning agile and scrum based / “on the fly” requirements prioritization and delivery Release tooling: from manual & error prone consistent & automated reliable & continuous release deployment Note that companies typically move up the continuous delivery maturity curve as they increase the depth and breadth of their agile development practices. CONTINUOUS DELIVERY MATURITY MODEL LEVEL DETAILS Level 1: (Manual) Success depends on the competence and heroics of the people doing the delivery. There are no repeatable release or deployment processes. Teams are very much operating in silos. No sign of DevOps in this organization. May not be ready for release automation yet if not using some form of version control system, repository management or automated builds. Level 2: (Scripting) Deployment processes are planned per release, and status is managed and tracked. Teams may think that they are achieving sufficient automation at this stage. Automation may exist for some deployment capabilities (e.g. using scripts). They may be using version control and repositories (e.g., Nexus) and doing automated builds with tools like Jenkins/CloudBees (baseline of readiness for release automation). May also be using provisioning or config management tools like Chef, Puppet for environments to help with delivery. But no end-to-end process or standard in place. Efforts at scripted automation are not scalable (and require significant maintenance effort). Cultural shift to DevOps likely happening in parts of the organization. Level 3: (Automated) There are standard, reusable, automated application delivery processes across environments and releases. Release processes, release meta data and release artifacts are monitored and tracked under full life cycle control. Delivery automation exists at the environment release level, which may include leveraging existing provisioning and deployment automation capabilities (which may not be scalable). Companies may see adoption of application release automation solution as a catalyst to spur DevOps adoption in the company. Level 4: (Continuous) Agile development through end-to-end application delivery combines automation and people by loosely coupling the release ecosystem (ALM through change mgmt.). Release operations integrate and orchestrate application release promotion enabling predictable, monitored and measurable continuous delivery from development to production. Can deploy applications consistently across different types of environments. Could be managing multiple applications (multi-services) / multiple teams. Feedback loops are efficient—helping to close the gap between the business and the customer. Releasing software is a routine and relatively low-risk event. Continuous Delivery as a Service may be practiced. The continuous delivery pipeline is becoming the single point of control that’s too important to fail. Level 5: (Optimized) Continuous optimization of end-to-end application delivery processes through feed back loops, in-product evaluation, deployment patterns, scenario simulation, and analysis of operational release data to continuously improve cost-performance of application delivery; focus on improving team and app delivery performance. Effectively managing multiple applications (multi-services)/multiple teams through continuous delivery pipeline. The continuous delivery pipeline runs at maximum efficiency and with clear focus on resiliency and continuous availability.
- Our solutions for IT Operations are within our Agile Operations business unit, named so because we see that DevOps and the overall pace of business has made IT teams become more agile and our solutions need to match that pace. The industry’s approaches to monitoring are changing and evolving rapidly. Why? Quality of experience is the new measure of IT effectiveness; this is true across all businesses. It is now a success metric for many IT initiatives; managing experience is a key requirement. You can’t manage what you can’t measure. You need insight into every aspect of the apps, infrastructure and network supporting user experience. To gain this insight you need a new approach to analytics. One that correlates across these elements and delivers predictive insights to improve experience. The current crop of tools don’t enable correlation; in fact it can be very challenging to combine app, infrastructure and network monitoring into one.
- You will learn how CA is uniquely positioned to deliver OPERATIONAL ANALYTICS This approach supports the 3 key pillars – design, code, infrastructure. And we don’t just collect more data, we add CONTEXT to the data- we figure out behavior, pattern, and anamolies we deliver an open platform that uses analytics to give insights and provides advanced capabilities like assisted workflows and machine learning to optimize ROOT CAUSE Dashboards that all ‘digital experience engineers’ (business and IT) can view – and get consistent perspective on BUSINESS INSIGHTS and IT OPERATIONAL EXCELLENCE
- In this short discussion I’ve outlined our vision and strategy and some of the advanced capabilities we’re delivering with correlated analytics. Our open, scalable correlation engine is the foundation for many new transformational apps, including app experience analytics. It’s also the basis for continually enriching our proven monitoring technology with new capabilities such as log analytics and assisted triage. This strategy doesn’t impose limits or constraints on the amount of data or method in which it’s collected. That will only grow and change, so our goal is to enrich it with monitoring depth. We also recognize that you’ve made significant investments in many good monitoring toolsets, so we deliver open APIs that help integrate and transform massive amounts of monitoring data – across apps, systems and networks. And we understand that your needs are changing, with many adopting new microservice architectures and containerized services to support increased deployment rates. This is why our solution agile operations extends into supporting the platforms specific to your own businesses models
- Traditional Monitoring is Similar to Traditional Car Dashboards: its is Reactive and only provides immediate Operational data, instant Capacity Management, and in some cases Event Recording. This results in Limited monitoring, with multiple “blind spots” and After-the-fact response to issues CLICK Now when you add Preventive Alerting (looking ahead) 360 degree visibility for more context Real-time efficiency And more importantly Predictive Performance Metrics CLICK You now get Modern Predictive Monitoring Similar to Modern Head Up Displays: CA UIM provides, Unified Analytics, Contextual Log analytics & Predictive Analytics whereas other analytics like Predictive Capacity Analytics are planned for the future. <<Segue to next slide>> Let’s see how this is materialized in real IT life CLICK