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How LogicMonitor Buying Airbrake Unleashes DevOps To Do What They Do Best

Bottom Line:  LogicMonitor knows first-hand how much pressure DevOps teams are under to produce high-quality code in record time during the pandemic. Acquiring Airbrake proves they get it: DevOps has a high need for speed right now.

LogicMonitor Aims To Solve Today’s DevOps Paradox

The pandemic is forcing every business to make DevOps a core part of their DNA faster than any of them expected. The competitive strengths many banked on in a pre-pandemic world aren’t as relevant as having a steady pipeline of new apps, platforms, and digital channels are. It’s creating a paradox for DevOps: on the one hand, they’re expected to deliver perfect code, and on the other, it needs to be delivered in record time. Pre-pandemic, a typical DevOps team in a $500M+ enterprise has over 200 concurrent projects in progress, with over 70% dedicated to safeguarding and improving customer experiences according to IDC. Today, there are up to 2X more projects, and up to 80% are focused on cybersecurity.

No organization is perfect at DevOps today. Everyone is at various stages of maturity and growth. The pandemic puts a lot of pressure on DevOps teams to get their code right quickly and into a released app in record time. LogicMonitor must see it in their customer base every day. The trade-offs DevOps teams have to make for speed versus quality – and even security – when pushing out a release are real and often tend to overlook diagnostics. That’s why the Airbrake acquisition makes so much sense today. LogicMonitor bought Airbrake to help DevOps teams do what they do best.

The often-quoted Boston Consulting Group (BCG) article, Going All In With DevOps, illustrates the typical pressure DevOps is under to perform, including catching bugs early, solving them, and getting code into test and deployment. According to Airbrake, 73% of their DevOps customers are pushing code multiple times per week – and many said they were deploying code “multiple times per day.”  What makes Airbrake a perfect fit for LogicMonitor is how their developer-centric application error and performance monitoring service provides detailed diagnostics beyond the first layer of a bug or problem. In the context of the BCG graphic below, LogicMonitor buying Airbrake gives DevOps teams the diagnostics they need to move faster through error detection and into the test, deploy and release phases.

How LogicMonitor Buying Airbrake Unleashes DevOps To Do What They Do Best

Competing In Real-Time Is DevOps’ New Reality

  • 46% of DevOps teams are expected to build and deploy software faster now than before the pandemic, according to a recent survey by Checkmarx.
  • 36% of DevOps team members are struggling to keep up with increased dev speeds and demands, according to Checkmarx’s survey.
  • 55% of DevOps team members have taken on more security responsibility during the pandemic, according to Checkmark’s survey.

DevOps teams are struggling to keep up with their workloads today. LogicMonitor believes that by automating more monitoring processes and providing deeper contextual data and insight, DevOps teams can improve their response times and quality.

Automation pays off with more efficient continuous integration and deployment (CI/CD) cycles across DevOps teams, speeding up time-to-market and improving software quality in the process. Buying Airbrake extends LogicMonitor into developer environments and enables their shared customers to gain visibility into CI/CD workflows while reducing risk and ensuring every code release meets customer expectations. The following graphic illustrates how the CI/CD pipelines support DevOps. The more efficient continuous integration, testing, delivery, and operations, the more code releases DevOps can deliver at a higher quality, on time, and to customers’ expectations.

How LogicMonitor Buying Airbrake Unleashes DevOps To Do What They Do Best

Source: Deloitte, DevOps Point of View, An Enterprise Architecture perspective, Amsterdam, 2020

Conclusion

The best aspect of LogicMonitor acquiring Airbrake is how practical, pragmatic, and immediately useful their vision of providing unified observability is in supporting DevOps teams under pressure to perform today. Airbrake is LogicMonitor’s second acquisition in just over a year, having also acquired Stockholm-based log analytics company Unomaly in January 2020. LogicMonitor’s Airbrake page provides additional information.

Machine Learning’s Greatest Potential Is Driving Revenue In The Enterprise

  • Enterprise investments in machine learning will nearly double over the next three years, reaching 64% adoption by 2020.
  • International Data Corporation (IDC) is forecasting spending on artificial intelligence (AI) and machine learning will grow from $8B in 2016 to $47B by 2020.
  • 89% of CIOs are either planning to use or are using machine learning in their organizations today.
  • 53% of CIOs say machine learning is one of their core priorities as their role expands from traditional IT operations management to business strategists.
  • CIOs are struggling to find the skills they need to build their machine learning models today, especially in financial services.

These and many other insights are from the recently published study, Global CIO Point of View. The entire report is downloadable here (PDF, 24 pp., no opt-in). ServiceNow and Oxford Economics collaborated on this survey of 500 CIOs in 11 countries on three continents, spanning 25 industries. In addition to the CIO interviews, leading experts in machine learning and its impact on enterprise performance contributed to the study. For additional details on the methodology, please see page 4 of the study and an online description of the CIO Survey Methodology here.

Digital transformation is a cornerstone of machine learning adoption. 72% of CIOs have responsibility for digital transformation initiatives that drive machine learning adoption. The survey found that the greater the level of digital transformation success, the more likely machine learning-based programs and strategies would succeed. IDC predicts that 40% of digital transformation initiatives will be supported by machine learning and artificial intelligence by 2019.

Key takeaways from the study include the following:

  • 90% of CIOs championing machine learning in their organizations today expect improved decision support that drives greater topline revenue growth. CIOs who are early adopters are most likely to pilot, evaluate and integrate machine learning into their enterprises when there is a clear connection to driving business results. Many CIO compensation plans now include business growth and revenue goals, making the revenue potential of new technologies a high priority.
  • 89% of CIOs are either planning to use or using machine learning in their organizations today. The majority, 40%, are in the research and planning phases of deployment, with an additional 26% piloting machine learning. 20% are using machine learning in some areas of their business, and 3% have successfully deployed enterprise-wide. The following graphic shows the percentage of respondents by stage of their machine learning journey.

  • Machine learning is a key supporting technology leading the majority Finance, Sales & Marketing, and Operations Management decisions today. Human intervention is still required across the spectrum of decision-making areas including Security Operations, Customer Management, Call Center Management, Operations Management, Finance and Sales & Marketing. The study predicts that by 2020, machine learning apps will have automated 70% of Security Operations queries and 30% of Customer Management ones.

  • Automation of repetitive tasks (68%), making complex decisions (54%) and recognizing data patterns (40%) are the top three most important capabilities CIOs of machine learning CIOs are most interested in.  Establishing links between events and supervised learning (both 32%), making predictions (31%) and assisting in making basic decisions (18%) are additional capabilities CIOs are looking for machine learning to accelerate. In financial services, machine learning apps are reviewing loan documents, sorting applications to broad parameters, and approving loans faster than had been possible before.

  • Machine learning adoption and confidence by CIOs varies by region, with North America in the lead (72%) followed by Asia-Pacific (61%). Just over half of European CIOs (58%) expect value from machine learning and decision automation to their company’s overall strategy. North American CIOs are more likely than others to expect value from machine learning and decision automation across a range of business areas, including overall strategy (72%, vs. 61% in Asia Pacific and 58% in Europe). North American CIOs also expect greater results from sales and marketing (63%, vs. 47% Asia-Pacific and 38% in Europe); procurement (50%, vs. 34% in Asia-Pacific and 34% in Europe); and product development (48%, vs. 29% in Asia-Pacific and 29% in Europe).
  • CIOs challenging the status quo of their organization’s analytics direction are more likely to rely on roadmaps for defining and selling their vision of machine learning’s revenue contributions. More than 70% of early adopter CIOs have developed a roadmap for future business process changes compared with just 33% of average CIOs. Of the CIOs and senior management teams in financial services, the majority are looking at how machine learning can increase customer satisfaction, lifetime customer value, improving revenue growth. 53% of CIOs from our survey say machine learning is one of their core priorities as their role expands from traditional IT operations to business-wide strategy.

Sources: CIOs Cutting Through the Hype and Delivering Real Value from Machine Learning, Survey Shows

Roundup Of Analytics, Big Data & Business Intelligence Forecasts And Market Estimates, 2014

NYC SkylineFrom manufacturers looking to gain greater insights into streamlining production, reducing time-to-market and increasing product quality to financial services firms seeking to upsell clients, analytics is now essential for any business looking to stay competitive.  Marketing is going through its own transformation, away from traditional tactics to analytics- and data-driven strategies that deliver measurable results.

Analytics and the insights they deliver are changing competitive dynamics daily by delivering greater acuity and focus.  The high level of interest and hype surrounding analytics, Big Data and business intelligence (BI) is leading to a proliferation of market projections and forecasts, each providing a different perspective of these markets.

Presented below is a roundup of recent forecasts and market estimates:

  • The Advanced and Predictive Analytics (APA) software market is projected from grow from $2.2B in 2013 to $3.4B in 2018, attaining a 9.9% CAGR in the forecast period.  The top 3 vendors in 2013 based on worldwide revenue were SAS ($768.3M, 35.4% market share), IBM ($370.3M, 17.1% market share) and Microsoft ($64.9M, 3% market share).  IDC commented that simplified APA tools that provide less flexibility than standalone statistical models tools yet have more intuitive graphical user interfaces and easier-to-use features are fueling business analysts’ adoption.  Source: http://www.idc.com/getdoc.jsp?containerId=249054
  • A.T. Kearney forecasts global spending on Big Data hardware, software and services will grow at a CAGR of 30% through 2018, reaching a total market size of $114B.  The average business expects to spend $8M on big data-related initiatives this year. Source: Beyond Big: The Analytically Powered Organization.
  • Cloud-based Business Intelligence (BI) is projected to grow from $.75B in 2013 to $2.94B in 2018, attaining a CAGR of 31%.  Redwood Capital’s recent Sector Report on Business Intelligence  (free, no opt in) provides a thorough analysis of the current and future direction of BI.  Redwood Capital segments the BI market into traditional, mobile, cloud and social business intelligence.   The following two charts from the Sector Report on Business Intelligence  illustrate how Redwood Capital sees the progression of the BI market through 2018.

redwood capital global intelligence market size

  • Enterprises getting the most value out of analytics and BI have leaders that concentrate more on collaboration, instilling confidence in their teams, and creating an active analytics community, while laggards focus on technology alone.  A.T. Kearney and Carnegie Mellon University recently surveyed 430 companies around the world, representing a wide range of geographies and industries, for the inaugural Leadership Excellence in Analytic Practices (LEAP) study.  You can find the study here.  The following is a graphic from the study comparing the characteristics of leaders and laggards’ strategies for building a culture of analytics excellence.

leaders and laggards2

  • The worldwide market for Big Data related hardware, software and professional services is projected to reach $30B in 2014.  Signals and System Telecom forecasts the market will attain a Compound Annual Growth Rate (CAGR) of 17% over the next 6 years.  Signals and Systems Telecom’s report forecasts Big Data will be a $76B market by 2020.  Source: http://www.researchandmarkets.com/research/s2t239/the_big_data
  • Big Data is projected to be a $28.5B market in 2014, growing to $50.1B in 2015 according to Wikkbon.  Their report, Big Data Vendor Revenue and Market Forecast 2013-2017 is outstanding in its accuracy and depth of analysis.  The following is a graphic from the study, illustrating Wikibon’s Big Data market forecast broken down by market component through 2017.

Big Data Wikibon

  • SAPIBMSASMicrosoftOracle, Information Builders, MicroStrategy, and Actuate are market leaders in BI according to Forrester’s latest Wave analysis of BI platforms.  Their report, The Forrester Wave™: Enterprise Business Intelligence Platforms, Q4 2013 (free PDF, no opt in, courtesy of SAS) provides a thorough analysis of 11 different BI software providers using the research firm’s 72-criteria evaluation methodology.
  • Amazon Web Services, Cloudera, Hortonworks, IBM, MapR Technologies, Pivotal Software, and Teradata are Big Data Hadoop market leaders according to Forrester’s latest Wave analysis of Hadoop Solutions.  Their report, The Forrester Wave™: Big Data Hadoop Solutions, Q1 2014 (free PDF, no opt in, courtesy of MapR Technologies) provides a thorough analysis of nine different Big Data Hadoop software providers using the research firm’s 32-criteria evaluation methodology.
  • IDC forecasts the server market for high performance data analysis (HPDA) will grow at a 23.5% compound annual growth rate (CAGR) reaching $2.7B by 2018.  In the same series of studies IDC forecasts the related storage market will expand to $1.6B also in 2018. HPDA is the term IDC created to describe the formative market for big data workloads using HPC. Source: http://www.idc.com/getdoc.jsp?containerId=prUS24938714
  • Global Big Data technology and services revenue will grow from $14.26B in 2014 to $23.76B in 2016, attaining a compound annual growth rate of 18.55%.  These figures and a complete market analysis are available in IDC’s Worldwide Big Data Technology and Services 2012 – 2016 Forecast.  You can download the full report here (free, no opt-in): Worldwide Big Data Technology and Services 2012 – 2016 Forecast.

big data analytics by market size

  • Financial Services firms are projected to spend $6.4B in Big Data-related hardware, software and services in 2015, growing at a CAGR of 22% through 2020.  Software and internet-related companies are projected to spend $2.8B in 2015, growing at a CAGR of 26% through 2020.  These and other market forecasts and projections can be found in Bain & Company’s Insights Analysis, Big Data: The Organizational Challenge.  An infographic of their research results are shown below.

Big-Data-infographic-Bain & Company

potential payback of big data initiatives

Sizing the Cloud Computing Market

The pace of cloud computing market forecasts produced and announced is quickening, with several new projections announced this month. In every one of these forecasts, the benefits of operating expense (OPEX) versus capital expense (CAPEX) financing play a role, as does the emerging trust in cloud computing as a viable platform.

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