MarketStudyReport.com adds Global Docker Monitoring Market research focusing on the major drivers and restraints for the key players. It also provides analysis of the market share, segmentation, revenue forecasts and geographic regions of the market.

Constituting a detailed study of the Docker Monitoring market, this research report basically entails an intrinsic breakdown of this business space in tandem with valuable forecasts pertaining to the market size and share. As per the report, the Docker Monitoring market is anticipated to accrue substantial returns by the end of the forecast period, while depicting a modest CAGR over the projected duration. Details subject to revenue predictions, sales volume, etc., have been overviewed in the article, while also covering the basic industry segmentation alongside the driving parameters impacting the commercialization portfolio of this business sphere.

Unveiling the Docker Monitoring market trends with respect to the geographical frame of reference:

The study is inclusive of a highly intrinsic study of the regional frame of reference of the Docker Monitoring market. The segment has been deeply analyzed, keeping in mind the vital aspects, and has been segmented into North America, Europe, Asia-Pacific, South America & Middle East and Africa.
Pivotal insights subject to the sales accrued by each region and the procured market share have been enlisted in the report.
The growth rate to be registered as well as the remuneration accrued by each region over the forecast period have been included within the report.

Some of the other important pointers highlighted in the study have been listed underneath:

The report comprises a detailed analysis of the competitive spectrum of the Docker Monitoring market, that basically is inclusive of companies such as The major players covered in Docker Monitoring are:,Broadcom,Signalfx,Dynatrace,Appdynamics,Sysdig,Splunk,Coscale,BMC Software,Datadog,Wavefront (VMware) andElastic.
It encompasses a generic overview of all the vendors, manufactured products, as well as the product application scope.
The study provides information about the present scenario, status of the companies in the industry, the sales procured by the firms, as well as their market share in the industry.
The firm’s profit margins and the price models have also been explained.
The product spectrum of Docker Monitoring market, that is subdivided amongst Linux and Windows, has been elaborated on, in the report. It also mentions the market share that each product segment holds in the industry.
The report elaborates on details pertaining to the sales accrued by the products as well as the share they will account for by the end of the estimation period.
The application spectrum of the industry has been mentioned in the report. It includes the applications such as Large Enterprises and Small and Medium-sized Enterprises (SMEs, as well as the market share obtained by every application.
The sales estimate and the revenue these applications will hold during the anticipated period are also contained within the report.
The report provides information on vital parameters such as market concentration rate and competition trends.
Detailed information pertaining to the direct and indirect sales marketing channels chosen by producers to market their products have been highlighted in the report.
The report on the Docker Monitoring market, that is projected to accumulate quite some returns by the end of the estimated duration, is also inclusive of other vital parameters such as the market dynamics. These include information about the challenges prevailing in this industry, main factors driving the industry outlook, and the numerous growth opportunities in this vertical.

The Solder Paste Inspection (SPI) System Market has witnessed continuous growth in the past few years and is projected to grow even further during the forecast period (2020-2026). The assessment provides a 360 view and insights, outlining the key outcomes of the industry. These insights help the business decision-makers to formulate better business plans and make informed decisions for improved profitability. In addition, the study helps venture or private players in understanding the companies more precisely to make better-informed decisions. Some of the prominent key players covered in the Solder Paste Inspection (SPI) System market are Koh Young (Korea), CyberOptics Corporation, Test Research,(TRI) (Taiwan), MirTec (Korea), PARMI Corp (Korea), Viscom AG (Germany), ViTrox (Malaysia), Vi TECHNOLOGY (France), Mek (Marantz Electronics) (Japan), CKD Corporation (Japan), Pemtron (Korea), SAKI Corporation (Japan), Machine Vision Products (MVP) (US), Caltex Scientific (US), ASC International (US), Sinic-Tek Vision Technology (China), Shenzhen JT Automation Equipment (China), Jet Technology (Taiwan)

What’s keeping Koh Young (Korea), CyberOptics Corporation, Test Research,(TRI) (Taiwan), MirTec (Korea), PARMI Corp (Korea), Viscom AG (Germany), ViTrox (Malaysia), Vi TECHNOLOGY (France), Mek (Marantz Electronics) (Japan), CKD Corporation (Japan), Pemtron (Korea), SAKI Corporation (Japan), Machine Vision Products (MVP) (US), Caltex Scientific (US), ASC International (US), Sinic-Tek Vision Technology (China), Shenzhen JT Automation Equipment (China), Jet Technology (Taiwan) Ahead in the Market? Benchmark yourself with strategic steps and conclusions recently published by Ample Market Research

The report also presents the market competitive landscape and a corresponding detailed analysis of the major vendor/key players in the market: Koh Young (Korea), CyberOptics Corporation, Test Research,(TRI) (Taiwan), MirTec (Korea), PARMI Corp (Korea), Viscom AG (Germany), ViTrox (Malaysia), Vi TECHNOLOGY (France), Mek (Marantz Electronics) (Japan), CKD Corporation (Japan), Pemtron (Korea), SAKI Corporation (Japan), Machine Vision Products (MVP) (US), Caltex Scientific (US), ASC International (US), Sinic-Tek Vision Technology (China), Shenzhen JT Automation Equipment (China), Jet Technology (Taiwan)

On the basis of product, this report displays the production, revenue, price, market share, and growth rate of each type, primarily split into: In-line SPI System, Off-line SPI System

On the basis of the end users/applications, this report focuses on the status and outlook for major applications/end users, consumption (sales), market share and growth rate for each application, including :Automotive Electronics, Consumer Electronics, Industrials

Geographically, the following regions together with the listed national markets are fully investigated: North America Country (United States, Canada), South America, Asia Country (China, Japan, India, Korea), Europe Country (Germany, UK, France, Italy), Other Country (Middle East, Africa, GCC)

For Consumer-Centric Market, Survey Analysis can be included as part of customization which considers demographic factors such as Age, Gender, Occupation, Income Level or Education while gathering data. (if applicable)

Consumer Traits (If Applicable)

Ø Buying patterns (e.g. comfort & convenience, economical, pride)

Ø Buying behavior (e.g. seasonal, usage rate)

Ø Lifestyle (e.g. health-conscious, family orientated, community active)

Ø Expectations (e.g. service, quality, risk, influence)

The Solder Paste Inspection (SPI) System Market study covers current status, % share, future patterns, development rate, SWOT examination, sales channels, to anticipate growth scenarios for years 2020-2026. It aims to recommend analysis of the market with regards to growth trends, prospects, and player’s contribution to market development. The report size market by 5 major regions, known as, North America, Europe, Asia Pacific (includes Asia & Oceania separately), Middle East and Africa (MEA), and Latin America.

The Solder Paste Inspection (SPI) System market factors described in this report are:-Key Strategic Developments in Solder Paste Inspection (SPI) System Market: The research includes the key strategic activities such as R&D plans, M&A completed, agreements, new launches, collaborations, partnerships & (JV) Joint ventures, and regional growth of the key competitors operating in the market at a global and regional scale.

Key Market Features in Solder Paste Inspection (SPI) System Market: The report highlights Solder Paste Inspection (SPI) System market features, including revenue, weighted average regional price, capacity utilization rate, production rate, gross margins, consumption, import & export, supply & demand, cost bench-marking, market share, CAGR, and gross margin.

Analytical Market Highlights & Approach The Solder Paste Inspection (SPI) System Market report provides the rigorously studied and evaluated data of the top industry players and their scope in the market by means of several analytical tools. The analytical tools such as Porter’s five forces analysis, feasibility study, SWOT analysis, and ROI analysis have been practiced reviewing the growth of the key players operating in the market.

Table of Contents :Solder Paste Inspection (SPI) System Market Study Coverage: It includes major manufacturers, emerging players growth story, major business segments of Solder Paste Inspection (SPI) System market, years considered, and research objectives. Additionally, segmentation on the basis of the type of product, application, and technology.

Solder Paste Inspection (SPI) System Market Executive Summary: It gives a summary of overall studies, growth rate, available market, competitive landscape, market drivers, trends, and issues, and macroscopic indicators. Solder Paste Inspection (SPI) System Market Production by Region Solder Paste Inspection (SPI) System Market Profile of Manufacturers-players are studied on the basis of SWOT, their products, production, value, financials, and other vital factors.

Key Points Covered in Solder Paste Inspection (SPI) System Market Report: Solder Paste Inspection (SPI) System Overview, Definition and Classification Market drivers and barriers

Solder Paste Inspection (SPI) System Market Competition by Manufacturers

Impact Analysis of COVID-19 on Solder Paste Inspection (SPI) System Market

Solder Paste Inspection (SPI) System Capacity, Production, Revenue (Value) by Region (2019-2026)

Solder Paste Inspection (SPI) System Supply (Production), Consumption, Export, Import by Region (2019-2026)

Solder Paste Inspection (SPI) System Production, Revenue (Value), Price Trend by Type {In-line SPI System, Off-line SPI System}

Solder Paste Inspection (SPI) System Market Analysis by Application {Automotive Electronics, Consumer Electronics, Industrials}

Solder Paste Inspection (SPI) System Manufacturers Profiles/Analysis Solder Paste Inspection (SPI) System Manufacturing Cost Analysis, Industrial/Supply Chain Analysis, Sourcing Strategy and Downstream Buyers, Marketing Strategy by Key Manufacturers/Players, Connected Distributors/Traders Standardization, Regulatory and collaborative initiatives, Industry road map and value chain Market Effect Factors Analysis

Ample Market Research provides comprehensive market research services and solutions across various industry verticals and helps businesses perform exceptionally well. Our end goal is to provide quality market research and consulting services to customers and add maximum value to businesses worldwide. We desire to deliver reports that have the perfect concoction of useful data. Our mission is to capture every aspect of the market and offer businesses a document that makes solid grounds for crucial decision making.

The latest research report on Agile and DevOps Services market delivers reliable and informative insights pertaining to the growth trajectory of this business space over the forecast period 2020 TO 2026. It expounds the current as well as past growth dynamics to help industry partakers invest their resources in areas with strong profit potential. Moreover, the report identifies the prevailing challenges and chalks out methodologies to counter their impact.

Proceeding further, the research literature encompasses in-depth segmentation studies to comprehend the overall scope and size of the market. Further, it sheds light on the competitive arena and the companies that govern it. Additionally, the study is equipped with tactics and actions plans to deal with the spurring challenges in the Covid-19 pandemic era.

Key highlights from TOC:

Product terrain
Product gamut: Web-Based , Cloud-Based and On-Premise
Records of the returns and market share garnered by each product category.

Application scope

Application range: Large Enterprises and Small and Medium-sized Enterprises (SMEs
Statistical coverage of the product demand and market share held by each application segment.
Forecasts for the yearly growth rate of each application segment over the analysis period.
Geographical landscape

Regional bifurcation: North America, Europe, Asia-Pacific, Latin America and Middle East & Africa
Total sales and revenue generated by each regional market.
Growth rate forecast for each regional contributor.
Competitive arena

Top-tier players:
3Pillar Global
Idexcel Inc
Mindtree
Agile Thought
Daffodil Software
EPAM
ICAgile
Wizeline
Netcracker
Infosys
Macro Solutions and HARMAN International
Market concentration ratio assessment.
A catalogue of each company’s product offerings with detailed specifications and top applications.
Manufacturing units of the leading players across the operational regions.
Documentation of the pricing model, sales, returns, and market share of the listed firms.
Latest developments including mergers, acquisitions, collaborations, partnerships, and expansion proposals.
To sum up everything that has been stated so far, an all inclusive analysis of the Agile and DevOps Services market is conducted by fragmenting it into different parts. Further, a compilation of all intricate details is carriedpertaining to the industry value chain, so as to help businesses effectively rollout their products & services into the marketplace.

Covid-19 Impact

The sudden outbreak of the Covid-19 virus in December 2019 has left the entire world in a disarray as the disease continues to rapidly spread across the globe with the World Health Organization issuing a public health emergency. Over 40 countries declared a state of emergency and almost all industries were severely affected, and the Agile and DevOps Services market isn’t an exception. This can be ascribed to travel bans and quarantines, restriction of indoor/outdoor activities, temporary halt of business operations, supply chain disruption, falling business assurance, stock market volatility, and uncertainty about future among the other spurring challenges.

Key Indicators Analyzed

Product Type Analysis: The report encloses majority of the product types in Agile and DevOps Services industry, including product specifications by each key player, volume, and sales by value (Mn USD) and volume.

Application Type Analysis: Major applications segments are covered, and market size, CAGR, and forecasts for each application is provided.

Market Analysis at Global and Regional Scale: The report offers global & regional market status and outlook for 2020-2026, breaking down the business landscape in each region & countries with respect to the production, consumption, import & export, and forecasts for sales volume & revenue.

Market Players & Competitor Analysis: Leading players are assessed in terms of their business profiles, product portfolio with specifications, production capacity/sales, pricing, revenue, and sales & gross margin 2016-2026 by product types.

Market Trends: Key industry trends including continuous innovations and increased competition.

Drivers and Opportunities: New technologies and identification of the growing demands.

Porter’s Five Force Analysis: Degrees of competition is measured based on five basic forces: bargaining power of suppliers, bargaining power of buyers, threat of substitute products or services, existing industry rivalry, threats of new entrants.

Businesses are at a pivotal moment in time. The International Monetary Fund (IMF) estimates that global GDP shrank by 4.4% in 2020, and contraction in the most advanced economies is estimated to be 5.8%. Today, however, vaccine availability and distribution brings us the brightest glimmer of hope yet that slowing the devastation of the virus may be a reality. More effectively addressing the health crisis also means economic recovery is becoming a stronger possibility – if businesses can lean into change and embrace new ways of working.

To enable this recovery, organisations across every industry are accelerating their shift to digital solutions. Turning to cloud technology promises to solve their most challenging problems and enable opportunities amidst changing customer demands and regulatory frameworks. In fact, McKinsey estimates the pandemic has fueled a three- to four-year acceleration of companies adopting digital technologies to support their customer and supply chain interactions. The most innovative companies need to rethink how employees collaborate and how they can digitise customer experiences.

Here are three key ways in which companies can use technology to their advantage and fuel their own recovery.

Businesses need to lower their costs and replatform for the future
Macroeconomic and geopolitical uncertainties create unknowns for every business. As a result, CEOs and CFOs are naturally seeking to optimise areas of their organisations.

Buying, maintaining and upgrading the technology infrastructure needed to run a business is not only difficult, but increasingly it is prohibitively expensive. Fixed IT systems require users to accurately predict their future needs, which now seem out-of-touch with our ever-changing business landscape. By contrast, a cloud server ensures that you only invest in the right amount, enabling users to flexibly adjust their consumption to meet fluctuating demands. This allows businesses to reinvest the remaining capital in creating customer experiences that will drive value creation. Gartner estimates that infrastructure-as-a-service is expected to grow 27.6% in 2021, precisely because of these cost savings and operational efficiencies – two of the greatest benefits of moving to the cloud.

Additionally, companies are realising the potential of a multicloud strategy. This set-up allows businesses to achieve an open, secure and agile infrastructure that can run in any environment, on any cloud. To grow and innovate within a company may mean moving entire on-premise IT infrastructure to the cloud, to transform digital operations.

Every business needs a digital front door
The remote nature of our lives—which is a permanent shift—is compelling businesses to use data and analytics to understand their customers better, overall enriching the customer experience.

Lockdowns have accelerated customer preferences for digital alternatives. Face-to-face customer service – a physical front door- is no longer enough to sustain a growing business. Today, customers also demand a ‘digital entrance’, and it’s transcending virtually every industry. In retail, companies are using AI and machine learning to deliver a better, more accurate online experience. Healthcare providers need secure, scalable platforms that support digital patient visits known as telemedicine.

Digital front doors are also changing the way governments work, like leveraging the cloud to distribute unemployment insurance online. With digitisation comes the opportunity for businesses to use data and analytics to make smarter decisions and get closer to their customers by creating more useful and productive experiences. By investing in innovative digital front doors now, companies will remain agile throughout the pandemic, whilst pivoting with changing customer expectations. Companies should celebrate the ease of digital experiences, which are personalisable and in no way mean a sacrifice on quality.

Companies need to embrace new ways of working
The future of work—and, for that matter, the definition of “workplace” itself—has transformed. While the pandemic as we know it will one day subside, our new way of working is here to stay, and it’s heightened the need to rethink how people get things done. We see the need for a new hybrid work environment, where companies and employees can use a digital workspace that allows them to collaborate on a flexible, cloud-native platform to generate new ideas and connect with each other. A successful transition into this new era of work is contingent on how successfully companies keep their people engaged, productive, and connected while reevaluating existing communication and collaboration tools.

No one can predict what the coming years will bring, but companies can control how they respond to uncertainty by investing in agile infrastructure that keeps people and connection at the heart of their operations. At this inflection point in the story of work, the ways in which each company responds to the challenges and opportunities it brings will define their relevance in the future. Those who lean into change, no matter how uncomfortable, and embrace the opportunity to fundamentally transform, will be stronger than before.

The global Cloud Computing in Retail Banking market report analyzes market trends, with data from 2021 and projections of compound annual growth rates (CAGR) until 2027. It explores a detailed overview, which includes market definition, product/services applications, and different manufacturing methods used across regions. Also, the global Cloud Computing in Retail Banking market report mentions major global regions and the market in the context of its present size and potential in these regions. It also explains the nature and structure of the industry, with the profiles of major players in the market. The report also forecasts sales in the market and major categories of the market in the given time frame.

Major vendors in the Cloud Computing in Retail Banking market include Amazon Web Services (AWS),Ellie Mae,IBM,Infosys,Intuit,Medidata,Microsoft,Oracle,Salesforce,SAP,TCS,Veeva Systems,Wipro,Workday,BBVA,Bankinter,Intel,Google,Alibaba,Tencent,Kingsoft,Ucloud,Baidu,Huawei,China Telecom,China Unicom

Regional Description

On the basis of region, the market has been segmented into Americas, Europe, Asia Pacific (APAC), and the Middle East and Africa (MEA). Regional segmentation has been provided at a high level and a more detailed level in terms of a country-wise analysis of the market in each region. This regional analysis points out regions with highest consumptions and production rates and also provides a comparative study basis these factors. The revenues generated in these regions, the market growth rate and the compound annual growth rate percentage are also discussed in detail.

Report Objectives

Analyzing the size of the global Cloud Computing in Retail Banking market on the basis of value and volume

Accurately calculating the market shares, consumption, and other vital factors of different segments of the global Cloud Computing in Retail Banking market

Exploring key dynamics of the global Cloud Computing in Retail Banking market

Highlighting important trends of the global Cloud Computing in Retail Banking market in terms of production, revenue, and sales

Deeply profiling top players of the global Cloud Computing in Retail Banking market and showing how they compete in the industry

Studying manufacturing processes and costs, product pricing, and various trends related to them

Showing the performance of different regions and countries in the global Cloud Computing in Retail Banking market

Forecasting the market size and share of all segments, regions, and the global market.

Key questions answered in the report:

What is the growth potential of the Cloud Computing in Retail Banking market?

Which product segment will grab a lion’s share?

Which regional market will emerge as a frontrunner in the coming years?

Which application segment will grow at a robust rate?

What are the growth opportunities that may emerge in the Cloud Computing in Retail Banking industry in the years to come?

What are the key challenges that the global Cloud Computing in Retail Banking market may face in the future?

Which are the leading companies in the global Cloud Computing in Retail Banking market?

Which are the key trends positively impacting the market growth?

Which are the growth strategies considered by the players to sustain hold in the global Cloud Computing in Retail Banking market

Table of Contents: Cloud Computing in Retail Banking Market

Chapter 1: Overview of Cloud Computing in Retail Banking Market

Chapter 2: Global Market Status and Forecast by Regions

Chapter 3: Global Market Status and Forecast by Types

Chapter 4: Global Market Status and Forecast by Downstream Industry

Chapter 5: Market Driving Factor Analysis

Chapter 6: Market Competition Status by Major Manufacturers

Chapter 7: Major Manufacturers Introduction and Market Data

Chapter 8: Upstream and Downstream Market Analysis

Chapter 9: Cost and Gross Margin Analysis

Chapter 10: Marketing Status Analysis

Chapter 11: Market Report Conclusion

Chapter 12: Research Methodology and Reference

ReportsAndMarkets.com allocates the globally available market research and many company reports from reputed market research companies that are a pioneer in their respective domains. We are completely an autonomous group and serves our clients by offering the trustworthy available research stuff, as we know this is an essential aspect of Market Research.

“A detailed market assessment is provided by the Continuous Integration Tools Market Analysis by highlighting information on various features, including drawbacks, drivers, hazards, and opportunities. In the global market study, competitive landscape analysis, advancement trends, and strategic regional development status are included. This report offers a thorough numerical overview of the Continuous Integration Tools Market sector and provides statistics for preparing and strategizing to fuel market growth. The study also assesses the gross profit, market size, revenue, price and market share, growth rate and business model for decision-making.

COVID-19 Market Effect

It offers further comments on the recession, the current market scenario, and the implications of COVID-19 around the industry. It also offers qualitative details about when market participants are reconsidering their priorities, evaluating the situation and the industry’s future behavior.

Companies are facing growing business-critical issues related to the coronavirus outbreak, including an increasing risk of recession, supply chain instability, and a possible decline in consumer spending. However, these conditions across various states and sectors will turn out differently. The report helps organizations to make accurate and timely choices in these difficult times.

Major Market Study Features

Market Study :

This research offers breakthrough inputs and insights into market-related variables such as competition, size, trends, forecasts, analysis, etc. The study covers secondary and primary data sources, in addition to qualitative and quantitative practices, and thus guarantees data accuracy. The study provides capacity, product specifications, company profiles, 2016-2028 market shares for key vendors, and production value.

Insights on Market Study:

The Continuous Integration Tools Market analysis report offers a full market evaluation, which includes forecasts with an appropriate set of assumptions, thoughtful observations, historical data, facts, statistically supported information, market data, and industry validated methodology. It offers research and information for categories such as countries, market segments, medium of distribution, and product type.

Market Segments

This research report categorizes the global market through products, players, styles, regions, and applications. The market study offers insights into business trends, circumstances that are increasingly complex, including situational variables, and industry features. The market analysis details the report by examining individual circumstances and circumstances that foster business growth.

Regional Assessment:

The Continuous Integration Tools Market is evaluated and offers market scope and information to regions (countries). The major regions covered in the Continuous Integration Tools Market research are North America, Europe, Asia Pacific, Middle East, South America, and Africa. It also encompasses main regions (countries) such as Germany, Canada, the United Kingdom, France, Germany , Italy, China , Russia, Japan , India, Australia, Indonesia, Taiwan, Thailand , the Philippines, Malaysia , Vietnam, Brazil , Mexico, Turkey , Saudi Arabia, etc.

Competitive Evaluation:

A full overview and quantitative figures as well as player revenue forecasts for the 2016-2028 period are included in the report. It also provides a detailed overview accompanied by reliable revenue forecasts for the 2016-2020 periods (global and regional level) from participants. Included are major industries, business overview, the company’s overall revenue and sales, recent developments, and revenue generated in the Continuous Integration Tools Market, etc.
Market Highlights

The study is an all-inclusive research study that takes into account recent developments, drivers of growth, technologies, a competitive landscape, and opportunities for the global drug market for opioid agonists. Market researchers and analysts have performed a broad study of the global Continuous Integration Tools Market with the aid of testing methodologies such as Porter’s Five Forces analysis and PESTLE.

The study will include data on the nearest approximations of the total industry volume numbers and the sub-segments to the market leaders / new entrants. This study will help stakeholders understand the competitive environment, gain more insights in order to better position their businesses, and prepare efficient go-to-market strategies..

QMI has the most comprehensive collection of market research products and services available on the web. We deliver reports from virtually all major publications and refresh our list regularly to provide you with immediate online access to the world’s most extensive and up-to-date archive of professional insights into global markets, companies, goods, and patterns.

The rise of COVID-19 defined 2020 for nearly every industry. Cloud computing is no exception, though growth in the sector continued this year. Gartner estimates that $257.9 billion will be spent on public cloud services in 2020, up 6.3% from 2019. IDC reports that almost half of IT spending is cloud-based, “reaching 60% of all IT infrastructure and 60% to 70% of all software, services and technology spending in 2020.” These projections came in mid-2020, which proves that cloud adoption and spending were not greatly impacted by the pandemic.

You can make the argument that cloud computing itself is the trend of 2020. Blockchain, quantum computing, machine learning and AI all deservedly earn a lot of headlines in the tech press. But at a more basic level, cloud computing is changing the way we do business. Whether it is the way they store their data, improvements to agility and go-to-market for faster release of new products and services, or how they develop and operate services remotely in today’s “locked-down world,” cloud computing is benefitting all businesses in every sector.

In short, cloud computing had a strong year in 2020 despite COVID-19 and appears to have a very bright future. Several key trends, perhaps overshadowed by the pandemic, helped define a dynamic year for the sector. These include the following:

Continued Dominance of ‘The Big Four’ – All of the big four cloud providers—AWS, Azure, Google Cloud and Alibaba Cloud—reported strong growth and collectively grew 40% in Q320. Together they still account for 63% of the entire cloud sector.
Rise of Managed Services – The global cloud managed services market, in particular, is growing rapidly and is expected to reach $116 billion by 2026, growing from $62.4 billion in 2020, according to a study conducted by Markets and Markets.
Serverless and Containers – There used to be some talk about serverless and containers replacing the use of traditional virtual machines (VM). But I mostly see customers realizing that VM infrastructure is not going to disappear anytime soon, though container use certainly rose over the last 12 months.
Automation – The push toward greater automation continued in 2020. I noticed users accepting greater automation in their infrastructure environments, and there was simply more demand for it across the board. This is great news as one of the major advantages of a DevOps approach is automating away the manual tasks that bog down critical projects.
Growth in home use – This may seem an obvious one, but with the COVID-19 pandemic leading companies across the globe to new “work from home” policies, virtual desk infrastructure (VDI) usage exploded.
Security – Especially with a remote workforce, cloud security faced new challenges this year. One example of this playing out is in Snowflake’s massive IPO.
Other trends of note this year included the continued growth of hybrid and multi-cloud and desktop as a service (DaaS). So, while COVID-19 truly defined 2020 for most people, the cloud sector was busy with the trends discussed above. It will certainly be interesting to see how these trends play out in the year ahead. Whatever new trends arise, it seems likely that cloud computing will continue to transform the way we all do business.

Cloud computing has become as crucial to the information environment as it has to consumer’s lives. Its collaboration capacities (prominently manifested in telemedicine, internet banking, and e-commerce) typify the remote interactivity of a big data landscape shifting, inexorably perhaps, towards the edge.

Cloud computing, which supported the world’s economy, worldwide supply chains and remote workforces during the coronavirus pandemic, will keep on being a fundamental objective for companies searching for increased scalability, business continuity and cost efficiency in 2021.

According to the study of Cisco, 94% of the worldwide workloads will be controlled by the leading cloud data centres of the world. Though, IDC as of late demonstrated that the 5-year CAGR for IaaS will rise by 33.7%.

Here are top cloud computing trends that we will witness in 2021

Hybrid Cloud Computing to dominate 2021
Numerous organizations as of now utilize the hybrid cloud computing system to upkeep their workflow and production. Numerous specialists believe that by 2021, various companies will take on hybrid cloud computing. The primary points of interest that you can hope to get from hybrid cloud computing are ideal speed, remarkable control, and improved security.

Serverless Computing
Serverless computing has noticed an expansion in popularity as a broad improvement. This is ascribed to the rising requirement for conventional innovation to go serverless for headways. It reallocates the entire foundation by isolating the start and end apart from the application.

For instance, the pay as you go system is serverless models that have an ordinary structure. Such projects are flexible and empower companies to have more command over their costs in cloud hosting.

The Edge
Multi-cloud’s enterprise utility (and mounting use cases) mirrors the developing distribution of the data landscape. The fluctuating levels of isolation ascribed to the current public health climate are increasing this pattern, and edge computing’s viability at the cloud’s fringe. Progressively heterogeneous conditions basically strengthen the need to connect them, which is the place where multi-cloud deployments excel.

FaaS Implementation in Cloud
FaaS (otherwise called Function as a Service) is a main subpart of the cloud computing service. It underpins an engineer with code usage while maintaining a strategic distance from the adoption of complex infrastructures.

FaaS is a part of serverless computing and principally centers around gateways, storage, API and competitions. These are FaaS service categories. Being a simpler assistance, in contrast to its IaaS and DaaS partners, it permits the developer to save time on coding. You can create confounded codes with FaaS quicker.

By 2021, more tech goliaths will pick FaaS as a tool for their normal work. As indicated by a study by Cision, FaaS can encounter a market expansion of almost USD7.72 million. Therefore, the annual growth rate will reach up to 32.7%.

Multi-Cloud And Joint Cloud Provider Offerings
2021 will see the beginnings of multi-cloud and joint provider cloud contributions, as suppliers acknowledge they can partner to quicken go-to-market launches, capitalize on mutual strengths and “take on the 800-pound gorilla” that is AWS. The Oracle-Microsoft interconnect relationship that began in June of 2019 is an illustration of a relationship that could be extended to exploit Oracle’s networking and Microsoft’s ML capacities

Hyper-scale Data Centers
In the digital age, instant consumption has driven organizations to work at a boisterous speed. They need their IT frameworks to deliver services at a pace than any customary framework. They likewise need an IT infrastructure that can scale at a speedy movement to provision increased demand. This requirement for business in the digital age is prompting the demand for hyper-scale data centers.

The hyper-scale data center can scale dramatically and quickly to react to progressively heavy demand. In a research report by Markets&Markets, they have assessed that the hyper-scale server data center market will ascend at a CAGR of 26.32% between 2017-22.

Data Security
Security strategies for data in motion are exemplified by software-defined perimeters, which orchestrate public key access with encryption while “opening up a safe UDP port, briefly, to frame an application-level connection, and afterward it disappears. Automation capabilities for container platforms resolve multi-cloud access “so companies have a compelling way how they can characterize, for various cloud suppliers or for various infrastructure or various sorts of cloud, policies in an automated way.

Joined services of Big Data, Cloud Computing and IoT
Cloud computing will improve in 2021 as it joins with Big Data and IoT. The main tech goliaths will without a doubt join the consolidated services, making it a trend. Both Big Data and IoT are ongoing advances, and a few companies are running on their help.

Big Data provides data identified with a specific enterprise after it is processed and analyzed. IoT is where the physical devices with legitimate interconnection can be for production.

According to desires, if cloud computing converges up with big data and IoT, an organization can improve its production. Organizations can gain admittance to the crucial information of their rivals and put more exertion into settling on better business choices for what’s to come.

Automated Cloud Orchestration And Optimization
Cloud platforms will keep on creating automated cloud orchestration and optimization as the multifaceted nature of overseeing both the quality and quantity of interconnected services across applications overpowers even the savviest of IT companies.

Automated service and performance management must be one of the main parts of picking a cloud provider in 2021, as organizations may need to deal with a hundred or more services from a single cloud provider

Disaster Recovery Services
The expense of downtime is expanding quickly as an ever-increasing number of companies take the digital path. Gartner expressed that the normal expense of IT downtime is near $5,600 every minute. For instance, in e-commerce firms’ downtime implies botched opportunities for sales. Then again, companies are under guidelines, for example, GDPR to handle data of customers with care.

Companies should be after all the legitimate terms while making their disaster recovery strategies. Thus, companies today are progressively moving towards at DR-as-a-Service which is a technique that can altogether decrease recovery time.

Despite the unrelenting turmoil currently defining the year 2020, the software development industry has collectively continued to make significant progress. As CDC-recommended social distancing guidelines force industries to adapt to these unprecedented times, companies’ reliance on SaaS programs continues to grow, allowing software industry leaders to capitalize on business owners’ shifting needs.

Late in 2019, experts made bold predictions regarding the software industry’s future in 2020, without any knowledge of a global pandemic lurking around the corner.

Calls for increased digital transformation related to A.I. and machine learning
Increased development of software directed at automated processes
Focus on time-stamping of all data
More focus on voice and speech recognition software
During 2020, some of these trends came to fruition, while a host of other trends appeared on the software development horizon. Some of the trends that came into focus during 2020 include:

Increased spending on A.I. technology (hardware and software)
Increased focus on blockchain technology as a means of tracking data
The development of software to assist in the capturing of big data
The transformation of the entertainment industry by combining AR (Augmented Reality) and VR (Virtual Reality) technologies
A more concentrated focus on continuous integration + continuous deployment (CI/CD) to aid in faster dispersion of mobile app software
Introduction of Internet of Things (IoT) technology guided by software and devices
With the pandemic’s end nowhere in sight, software industry leaders must step up to the plate and respond to the COVID-19 era’s debilitating uncertainty with resilience. As software developers nationwide adopt an out-with-the-old-and-in-with-the-new mindset, software developers should strive to remain competitive in the industry. How can developers attain that competitive edge? By tracking these expert-predicted software development trends of 2021. Additionally, those in the tech sector should harness the power of a reliable software QA company.

Before software hits the marketplace, there needs to be absolute assurance the software will perform at optimal efficiency. An unwavering dedication to QA (Quality Assurance) and QC (Quality Control) is critical in maximizing company time and resources. After all, a well-oiled quality assurance strategy will help save time and money, protect the software company’s reputation, and confirm that necessary security features are in place.

Software trends to watch for in 2021
As we stumble into the year 2021, there’s no reason to expect that software advancements will wind to a halt. With that in mind, here are ten must-watch trends to look for as we ring in the new year.

Native app development
With people living their lives and earning a paycheck through their mobile devices, software developers will strive to create native apps specifically designed for the iOS and Android operating systems.

The Internet Of Things (IoT)
In 2021, experts expect that the demand for IoT hardware (devices), software, system integration capabilities, and data and telecom services will continue to surge.

Big data computation
Software platforms that perform calculations will garner more attention, as they’ll be able to complete real-time calculations on-demand without resorting to data storage.

Human Augmentation
The world can expect to see further advancements in human augmentation software and devices. These advancements’ primary focus will be on improving bodily functions such as seeing and hearing.

Artificial Intelligence (AI) expansion
The AI development train will continue rolling as more industries look to increase productivity and improve the customer experience through machine learning and speech processing.

Introduction of progressive web apps
With users moving away from websites and dedicating concentrated focus on mobile apps, software developers will continue to develop progressive web apps that are easier to access.

Continuous Integration and Deployment (CI/CD)
CI/CD technology will allow software developers to fix bugs and have the fixes ready in real-time. That way, developers can avoid productivity-stalling and sales-stifling updates.

Low-code development platform (LCDP)
LCDP is a trend that will allow software developers to address complicated programming issues in the production of simpler software interfaces.

Cross-platform and hybrid development
While experts anticipate that native apps will receive more attention in the software industry, that’s not to imply that hybrid platforms will be laid to rest. Some industries will still need the flexibility granted by having access to hybrid platforms, as these hybrid platforms will allow business owners to conserve time and financial resources.

SQL Databases
Moving forward, more companies will begin to accept that SQL databases are essential for the development of business applications.

Final word
Much like in other neighboring industries, industry leaders should avoid stagnation at all costs. By tuning into upcoming trends, business owners can outrank their competitors and stay relevant among their target audience.

Technology has enabled businesses to continue operating this year, and the cloud has taken center stage — going forward, it will only play a larger role in the enterprise.

According to CloudTech, public cloud spending is expected to grow from US$229 billion in 2019 to US$500 billion in 2023, with a compound annual growth rate (CAGR) of 22.3%.

Key players Amazon Web Services (AWS), Microsoft Azure, Google Cloud, and Alibaba, and are expected to grow yet bigger, and by the end of 2021, 60% of companies will leverage containers on public cloud platforms and 25% of developers will use serverless.

As this market continues its growth and evolution, here are three trends to watch in 2021.

Serverless computing
A cloudless server is a technology that implements functions in the cloud on a necessary basis. Enterprises rely on serverless computing because it provides space to work on core products without the pressure to operate or manage servers. Microsoft CEO Satya Nadella favors serverless cloud and he believes serverless computing can not only respond and focus on back-end computing but also become key to the imminent future for distributed computing.

Serverless was among the top five fastest-growing PaaS cloud services for 2020, according to the Flexera 2020 State of the Cloud report.

Hybrid cloud joins providers
Choosing between public, private, or hybrid cloud environments, has proved challenging for some organizations — each offers advantages and disadvantages when it comes to flexibility, performance, security, and compliance.

According to Gartner, in 2019, the actual number of companies using hybrid cloud was 58%, up 6% from 2018. Hybrid cloud benefits include speed, control, and security. In terms of speed, it optimizes the network to reduce the latency and speeds up the data so that it can reach where it needs to be. For control, companies can customize the end of their hybrid cloud model, optimize it, and adjust it according to their needs rather than trusting a third-party cloud provider.

The continued demand for hybrid cloud could lead the world’s biggest providers to partially break out from their walled garden approach. By collaborating and introducing some interoperability, they can continue to satisfy multi-cloud demands. This will enable better data sharing and access between partners, who may be working across diverse applications and standards.

Virtual Cloud Desktops
A virtual cloud desktop refers to the software requirements of a device being fully managed by cloud service providers. The user just needs to have a screen and some basic hardware while the rest of the processing power will be seamlessly handled by cloud-based services.

Virtual cloud desktop users only pay on cloud usage, eliminating costs associated with acquiring powerful new hardware, updating the existing hardware, and the disposal of redundant computing equipment.

Sometimes known as desktop-as-a-service, this model of computing is offered by Amazon via the Workspaces platform and Microsoft with Windows Virtual Desktop. Google also offers functionality through its Chromebook devices. In practice, this can increase efficiency across a workforce by ensuring everyone is using up-to-date, synchronized technology.

The Coronavirus pandemic has catapulted digital transformation to the top of the must-haves in the minds of CIOs. It has been a go-to enabler for organizations to enhance their customer experience and generate higher ROI. Businesses with brick-and-mortar presence were shifting their approach towards building a digital presence to stay relevant and ahead of their competition. Many have already begun their digital transformation journey, while some are in the designing phase. Technology landscape is dynamic in nature. While the pandemic forced businesses to adopt digital drivers such as automation, big data, digital workforce, etc., they were soon replaced with the next big wave of digital transformation. This new wave has brought in new trends that will shape up the next normal. Let’s look at 5 new such trends that will soon become the next must-haves.

Customer Experience Reimagined
It’s not just about having the best products anymore. The new wave of millennials prefers convenience over loyalty. Create digital experiences that support modern web in the form of progressive web apps, true native mobile apps with best-in-class UX, intelligent chat-bots, conversational apps, wearables, and immersive experiences that leverage augmented reality. Organizations are trying to maximize the use of components and backend integration that leads to a unified and seamless experience across channels.

The next big thing in Customer experience (CX) is to design amazing applications for any audience across any device with no limits on user experience taking full advantage of the underlying device OS for native and full power of modern browsers for web. Omni-channel tools eliminate data siloes, and bring all the data in one place. Be it a web presence, a physical store visit, or a mobile application click, omni-channel binds all customer-facing interfaces together, integrated at the back-end, and helps in better CX and data visibility across the board.

Data and User Privacy
In the wake of privacy concerns amongst digital users, we will be seeing organizations focusing on user and data privacy. This will soon become a unique selling proposition for many to leapfrog their competitors. This could mean that users in the next normal will be able to allow/deny access to their data residing on applications, web and other digital channels. The user will be the owner of his/her data. Data privacy has shaken even multi-national brethren, forcing them to comply with new regulations laid by authorities. EU has already entered the game with the General Data Protection Regulation (GDPR) compliance policy and other regions have followed suit.

APIs – The Road to Cloud
Cloud is already adopted by most organizations to create a seamless business continuity and fasten go-to market. Application programming interfaces (APIs) are key in building economies of scale. From converting legacy infrastructure to micro-services, APIs will help businesses to reduce data silos and create collaborative experiences. It will also help them convert scattered applications into one behemoth of a data mart, helping them in making critical business-decisions and increase their overall ROI.

XaaS (Everything-as-a-Service)
As-a-Service (aaS) has already become the norm to become a truly digital-native enterprise. The new trend in the aaS model is Everything-as-a-Service (XaaS) where services rendered and delivered will completely reside on the cloud with virtual access to almost everything. Tools such as the Internet of Things (IoT) and Artificial Intelligence (AI) will play a crucial role in building those services or augmenting existing services to achieve the digital-native status quo.

AIaaS (Artificial Intelligence-as-a-Service)
AI technologies are already used by 77% of consumers. A number of technological innovations such as data processing, and face & speech recognition have become possible due to AI. AI is a vast area that includes AI platforms, chat-bots, machine learning (algorithm category consisting of various libraries and frameworks), deep learning, and analytics.

AI has led to rise in the use of machine learning in computing. AI has contributed significantly in creating a framework for cloud computing. Many IT industry giants are already betting huge on AIaaS (Artificial Intelligence as a Service) with new line of services such as digital assistance, cognitive computing, machine learning, business intelligence, and so on.

These services can have a significant impact on the day-to-day lives of consumers. With the help of vital statistics from health-care organizations, AI can help identify patterns and predict the desired outcome of a given situation in a focused environment. AI can also help in tracking of smart devices, thereby, creating a footprint of individuals. It can help marketers and advertisers with predictive data on what one is likely to do in a given event. This will help marketers to show relevant ads to consumers at the right time that could help them fetch better returns for their marketing dollars.

Needless to say, the new wave of digital technology trends can reduce human interactions, increase productivity, initiate automation, and simplify lives. Organizations need to understand the importance of this technology paradigm shift, and leverage it to create digital ecosystems and become future-ready enterprises to welcome the next normal with both hands.

IoT and Embedded Video Will Expand the Attack Surface

Malcolm Murphy, Technical Director EMEA at Infoblox, highlighted video-capable IoT devices as an emerging security concern.

“I strongly suspect that video cameras in IoT connected devices, such as video doorbells and embedded cameras in smart speakers, will be the next big threat to the network due to the richer information sets they hold. Since these devices are collecting more and more data, they are becoming increasingly interesting targets for hackers, so that data is at a higher risk of being compromised. Despite this risk, security is still not being prioritised by manufacturers in the design of smart products, so until this is addressed, we’ll continue to see breach levels rise.”

Malcolm Murphy, Technical Director EMEA, Infoblox

The prediction reflects a persistent gap in IoT security: hardware manufacturers have historically deprioritised security in favour of speed-to-market, leaving network defenders to compensate downstream. This remains a live concern for DevSecOps teams integrating smart devices into enterprise environments.

IT Will Need to Govern Citizen Developers

Jennifer Gill, Senior Director of Product Marketing at Pegasystems, foresaw the governance challenges that low-code adoption would create.

“Low-code platforms have been touted for their ease of use so business professionals can develop their own applications. But without IT’s involvement, applications can go rogue and cause governance, maintenance, and usability issues. To ensure citizen developers don’t go too far astray, IT departments will utilise low-code platforms with templates to keep business users within the guardrails of corporate governance.”

Jennifer Gill, Senior Director Product Marketing, Pegasystems

The tension between empowering non-technical users and maintaining platform integrity has only intensified since 2020. Platform engineering teams now frequently publish internal developer portals and golden-path templates for exactly this reason — providing guardrails without blocking productivity.

Automotive OEMs Will Embrace Mobility-as-a-Service

John Phillips, MD EMEA at Zuora, predicted that Mobility-as-a-Service (MaaS) would push automotive manufacturers toward subscription-centric, customer-focused models.

“In 2020, we will see automotive OEMs use this knowledge and pair it with technology that will help them integrate their services with other suppliers both inside and outside of the auto supply chain in order to realise the full potential of Mobility-as-a-Service. The true winners in MaaS will place customer relationships at the centre of their businesses.”

John Phillips, MD EMEA, Zuora

From a DevOps perspective, this prediction foreshadowed greater demand for continuous delivery pipelines capable of supporting over-the-air (OTA) software updates, API-driven integrations with third-party mobility providers, and real-time telemetry pipelines for subscriber data.

Open Standards Will Underpin Agile DevOps at Scale

The Open Group argued that as organisations scaled their DevOps practices, open standards would become critical for maintaining consistency across complex value chains.

“Open standards, including information models such as the IT4IT Reference Architecture, can provide a framework for agile development, helping to enable the standardisation of components and interfaces, and allowing teams to seamlessly interchange information on product delivery and use without disrupting the entire value chain.”

The Open Group

This aligns with the broader industry movement toward standardised software supply chain specifications, such as SLSA (Supply-chain Levels for Software Artifacts) and SBOM (Software Bill of Materials), both of which gained significant traction after 2020.

DevOps Will Move Up the Value Stream

Mark Levy, Director of Strategy for Software Delivery at Micro Focus, predicted that DevOps would expand beyond engineering teams to encompass portfolio and product management.

“In 2020, there will be a greater focus on connecting portfolio/product management with the other practices of DevOps. Fast feedback should not only be in the boundaries of Dev and Ops but encompass the entire value chain. DevOps starts to move up the value stream to provide better alignment with the business.”

Mark Levy, Director of Strategy – Software Delivery, Micro Focus

This prediction maps closely to what became known as value stream management (VSM) — a discipline that gained significant adoption as organisations sought to measure and optimise the flow of work from business idea to production deployment.

DevOps Will Mature Into a “So What” Topic

Edge Testing offered a contrarian view: that the hype surrounding DevOps would dissipate as the methodology matured into standard practice — much as Agile had done before it.

“DevOps will go the same way as Agile in that it will become a ‘so what’ topic. Agile is now a fully matured methodology with the majority of testers having some exposure which they can put on their CVs. DevOps will follow this route. Although we will continue to see one new tool or another being launched weekly to bolt onto the DevOps tool suite, the main set of tools are maturing nicely and the skill sets to support these in the industry are growing.”

Edge Testing

This proved largely accurate. By the mid-2020s, DevOps had become a baseline expectation for engineering roles rather than a differentiator, and attention shifted toward more specific disciplines such as platform engineering, SRE, and DevSecOps.

The CISO Will Become a Full Member of the DevOps Team

Malcolm Isaacs, Head of ADM Solutions Marketing at Micro Focus, predicted the full integration of security leadership into DevOps pipelines — what the industry now calls DevSecOps or shift-left security.

“Just as DevOps strives to deliver value quickly to the customer, it has the potential to unintentionally introduce security vulnerabilities quickly as well. Over the course of 2020, any remaining barriers between CISO staff and DevOps teams will be broken down, with CISO staff becoming full-fledged members of the DevOps team. Security will no longer be a bolt-on activity, and will become a standard component of any DevOps pipeline.”

Malcolm Isaacs, Head of ADM Solutions Marketing, Micro Focus

High-profile supply chain incidents — including the SolarWinds compromise in late 2020 — dramatically accelerated this shift and made security integration in CI/CD pipelines a regulatory and business imperative rather than a best-practice aspiration.

Open Source Business Models Will Need to Reinvent Themselves

Perry Krug, Architect at the Office of the CTO at Couchbase, identified the growing tension between open-source projects and cloud providers that commoditise their distributions.

“In 2020, vendors will have to realise that the Open Source game has changed. They must instead see themselves as service providers, from management to support and other value-adds, in order to ensure that they can offer something that others cannot. The business model is to innovate — where cloud providers won’t — and to provide better and more differentiated service, not just differentiated software.”

Perry Krug, Architect – Office of the CTO, Couchbase

This tension played out publicly with licensing changes from projects including Elasticsearch, HashiCorp Terraform, and MongoDB, all of which adopted more restrictive licences to limit cloud-provider free-riding. The debate around open-source sustainability continues to evolve.

“No-Ops” Will Die — Ops Will Evolve

New Relic argued that the concept of eliminating the Ops function was misguided, and that automation would elevate Ops professionals rather than replace them.

“Next year, more organisations will start to ditch the notion of ‘No-Ops’ and recognise value in their Ops team members. Companies will always need Ops people, but as technology and automation processes mature, Ops professionals will be able to work on higher-quality problems.”

New Relic

The rise of Site Reliability Engineering (SRE) as a formal discipline bears this out. Rather than eliminating Ops, organisations increasingly embed SREs within product teams to own reliability, scalability, and observability — exactly the higher-order problems New Relic described.

Disruptors Will Set the Pace for Customer Engagement

David Parry-Jones, VP EMEA at Twilio, predicted that API-driven communications platforms would push traditional businesses to match the customer engagement capabilities of digital-native disruptors.

“With the advent of APIs and cloud-based communications platforms, customers can now be easily reached across a multitude of different channels according to their preference, and call-time vastly reduced through the application of AI. In 2020 more organisations should begin to ask — why can’t we do this too?”

David Parry-Jones, VP EMEA, Twilio

For DevOps teams, this translated into demand for event-driven architectures, API gateway implementations, and real-time notification pipelines — all areas that saw rapid tooling investment in the years following this prediction.

Data-as-a-Service Will Become a Revenue Stream

Alberto Pan, CTO at Denodo, predicted that organisations sitting on proprietary datasets would begin packaging and monetising that data for third parties.

“Since many big companies will now own high-value, unique data and services, the next logical step is reusing this infrastructure in order to offer them to third-parties. This trend will be significantly accentuated during 2020 in all major industries. From the investment standpoint, this will involve higher demand for the technologies involved in creating and exposing data as a service, like GraphQL, Data Virtualisation and API management tools.”

Alberto Pan, CTO, Denodo

The prediction preceded a significant expansion in data mesh architectures, data marketplaces, and regulatory scrutiny of commercial data sales — particularly around location and behavioural data. DevOps teams in data-intensive industries increasingly own pipelines that serve external as well as internal consumers.

IT Will Reclaim Its Strategic Influence

Brian Kelly, CEO at CloudBolt, closed the predictions roundup with a broadly optimistic view: that IT practitioners — not just CxO-level decision-makers — would drive tool selection for hybrid cloud management.

“The IT community (not the obvious power players) will determine the winners of the go-to tools for managing hybrid cloud infrastructures, as they seek extensible, easy-to-deploy, cloud-native solutions.”

Brian Kelly, CEO, CloudBolt

This bottom-up adoption pattern is well documented in the DevOps toolchain space — platforms like GitHub Actions, Terraform, and Kubernetes gained enterprise foothold primarily through practitioner adoption before receiving top-down endorsement.

Key Themes Worth Tracking

Looking across these predictions, several recurring themes emerge that remain relevant for DevOps and platform engineering practitioners:

• Security shifts left — and becomes shared: DevSecOps is no longer optional. CISO involvement in pipeline design is increasingly standard practice.
• Ops evolves rather than disappears: Automation raises the floor for operational work; it does not eliminate the need for operational expertise.
• Open-source sustainability is unresolved: The conflict between open-source ideals and commercial cloud distribution is ongoing and actively reshaping licensing strategies.
• Citizen development requires governance: Low-code proliferation without platform guardrails creates technical debt and compliance risk.
• Value stream visibility matters: Fast delivery is only valuable when aligned with business outcomes — a principle central to modern platform engineering and DevOps measurement frameworks.

Original predictions sourced from DevOps Online, published December 2019. Contributor affiliations reflect their roles at time of publication.

Why Secure Cloud Migration Still Matters

Cloud adoption has become the default infrastructure strategy for most organizations, spanning both the public and private sectors. With that growth comes an expanding attack surface, increasing regulatory scrutiny, and the practical challenge of moving sensitive data out of on-premises environments without introducing new risk.

The scale of adoption also means that cloud security is no longer a niche concern. Hybrid cloud platforms are now mainstream, IoT is generating massive data volumes that flow through cloud pipelines, and shadow IT means that data is frequently moving to cloud services without formal oversight. Against that backdrop, a structured approach to secure cloud migration is essential, not optional.

The seven recommendations below address the full lifecycle of a migration: what you need to understand before you move data, how to structure access and encryption, and how to verify that controls are actually working once data is in the cloud.

Before You Migrate: Four Foundational Steps

The first four tips focus on your current data environment. Skipping this preparation phase is one of the most common and costly mistakes in cloud migrations.

1. Know Your Data

Before a single byte moves to a cloud provider, you need a clear inventory of what data you actually hold and where it lives. Think of it like decluttering and cataloguing before putting belongings into storage — moving unexamined data into the cloud does not make it safer or more organized; it just makes the problem harder to see.

• Identify where sensitive data currently resides across all systems, including end-user devices and departmental servers.
• Audit shadow IT: many teams are already using cloud services — SaaS tools, file-sharing platforms, collaboration apps — without formal approval or visibility.
• Classify data by sensitivity. At minimum, distinguish between public, internal, confidential, and regulated data categories (for example, data subject to HIPAA, PCI-DSS, or GDPR).
• Document existing protections so you have a baseline to replicate or improve in the cloud environment.

Numerous vendors offer data discovery and classification tooling that can accelerate this process at scale.

2. Define and Enforce a Data Lifecycle Policy

A data lifecycle policy answers the fundamental question: what happens to data from the moment it is created to the moment it is destroyed? Without this policy in place before migration, you will replicate your existing data governance gaps into the cloud.

• Document what data is collected, where it flows, how long it is retained, and when it should be deleted.
• Assign clear ownership and accountability for each data category — not just on paper, but in practice.
• Verify that staff training is current and that employees understand the policy as it applies to cloud services.
• Establish governance mechanisms — ideally automated policy enforcement — that govern how data moves between on-premises and cloud environments.

3. Understand Your Cloud Deployment Options

Choosing the right cloud model for your data is an architectural decision, not just a procurement one. The four primary deployment models each carry different security and compliance implications.

A common mistake is conflating the terms private cloud and private sector. A private cloud is defined by dedicated resource pooling for a single organization — it is independent of whether the owning organization is public or private sector. Align your architecture team on these definitions before vendor discussions begin.

4. Map Identity and Access Management (IAM) Before You Move

In cloud environments, the customer — not the cloud provider — is responsible for defining who can access what within their tenancy. This is a fundamental aspect of the shared responsibility model, and it catches many organizations off guard.

• Document data owners, data custodians, and all roles that have read, write, modify, or delete permissions for each sensitive dataset.
• Design IAM policies around the principle of least privilege: grant only the permissions required for a given role, and no more.
• Build role-based access control (RBAC) structures that can be audited and updated efficiently as staff join or leave.
• Establish processes for privileged access management (PAM) for system administrators, including background checks and segregation of duties as required by your compliance framework.
• Understand that compliance requirements — PCI-DSS, HIPAA, FedRAMP, SOC 2, and others — will shape your cloud architecture. Map those requirements to IAM policies before finalizing your design.

After Migration: Three Controls to Enforce and Verify

5. Apply End-to-End Encryption

Encryption is non-negotiable for sensitive data in the cloud — but it is frequently misconfigured or partially implemented. A meaningful proportion of cloud databases are deployed without encryption enabled, representing a significant and avoidable exposure.

• Data at rest: Ensure that storage volumes, databases, and object stores are encrypted using strong, current algorithms (AES-256 is standard). Confirm this is enforced by policy, not just available as an option.
• Data in transit: Enforce TLS for all data moving between services, between environments, and between users and cloud endpoints. Disable deprecated protocol versions.
• Key management: Determine who controls the encryption keys. Customer-managed keys (CMK) give you control but require operational discipline. Provider-managed keys are operationally simpler but reduce your independence. Consider whether a dedicated key management service (KMS) or hardware security module (HSM) is appropriate for your risk profile.
• Scope: Decide whether you will encrypt all data or only classified/sensitive data, and document that decision with a rationale your auditors can review.

6. Test Your Controls Continuously

Moving data to the cloud and assuming it is secure is not a security posture — it is wishful thinking. Controls must be verified regularly, and cloud environments change frequently enough that annual assessments are insufficient.

• Require your cloud provider to demonstrate support for vulnerability scanning and penetration testing within their environment. Most major providers have documented processes for authorizing customer-initiated testing.
• Run vulnerability assessments on a scheduled and on-demand basis, with frequency calibrated to the sensitivity of the workload.
• Implement cloud security posture management (CSPM) tooling to continuously monitor for misconfiguration — exposed storage buckets, overly permissive security groups, disabled logging, and similar issues.
• Establish an incident response plan specific to your cloud environment, and test it. Tabletop exercises that simulate a cloud-specific breach scenario (e.g., compromised service account credentials, a misconfigured S3 bucket exposing sensitive data) are valuable and underutilized.
• Ensure you have sufficient visibility into your cloud environment: logging, monitoring, and alerting should be configured so that anomalous access or data movement is detectable in near real time.

7. Back Up Data in a Distinct Fault Domain

Availability is part of security. Data that cannot be recovered after an incident — whether a ransomware attack, accidental deletion, or provider outage — is effectively lost.

“To spread risk most effectively, back up all data in a fault domain distinct from where it resides in production. Some cloud providers offer backup capabilities as an extra cost option, but it isn’t a substitute for proper backups. Customers, not cloud providers, are responsible for determining appropriate replication strategies, as well as maintaining backups.”

Gartner

• Store backups in a geographically separate region or with a different provider than your production environment. A failure or attack affecting one region should not affect your backups.
• Test restores regularly. A backup that has never been restored is an untested assumption, not a verified control.
• Understand your provider’s native backup capabilities and their limitations. Managed database snapshots, for example, may not protect against application-level corruption or accidental bulk deletion.
• Align backup retention schedules with your regulatory obligations and recovery time objectives (RTO) and recovery point objectives (RPO).

Additional Considerations

These seven tips address the core security controls for a cloud data migration, but they are not exhaustive. A complete cloud security program also requires attention to:

• Contract terms: Understand what your cloud provider is and is not liable for. The shared responsibility model varies by service type (IaaS, PaaS, SaaS) and by provider.
• Cost management: Wasted cloud spend on non-production resources is a real and well-documented problem. Tagging strategies, budget alerts, and regular rightsizing reviews help ensure that resources — and the security controls applied to them — remain intentional rather than accidental.
• Vendor lock-in: Evaluate your ability to exit a provider or move workloads. Portability considerations influence both architecture decisions and your negotiating position on contract terms.
• Ongoing governance: Cloud environments are dynamic. A migration is not a one-time event; governance processes must be continuous and adaptable as new services, new data types, and new threats emerge.

Organizations that moved sensitive data to the cloud years ago cannot assume that past decisions remain appropriate for new workloads or new business areas. Each new migration deserves the same structured evaluation outlined above.

Summary

1. Know your data — inventory and classify before you migrate.
2. Define a data lifecycle policy — govern data from creation to deletion.
3. Choose the right cloud model — private, public, community, or hybrid, based on your requirements.
4. Map IAM roles and responsibilities — you own access control in your cloud tenancy.
5. Encrypt end to end — at rest, in transit, and with clear key management ownership.
6. Test controls continuously — vulnerability scanning, penetration testing, and posture management.
7. Back up to a distinct fault domain — and verify restores work.

Cloud migration security is a discipline that requires upfront preparation, rigorous implementation, and continuous verification. These seven steps provide a practical framework for technology and security leaders navigating that journey.

Background: Why a Separate Technical Conference?

The Agile movement has firmly taken hold in software development. Standups, user stories, and sprints are now standard vocabulary across most engineering teams. Yet over roughly four years, the flagship Agile Alliance conference — which grew from around 900 to 1,500 attendees during that period — steadily reduced its technical content. The DevOps track continued to grow, but sessions on programming and testing drew smaller audiences. Fewer technical practitioners attended, fewer attended technical sessions, and organizers responded by scheduling fewer technical talks the following year — a self-reinforcing cycle.

Something had to change. In 2016, the Agile Alliance launched the Agile Alliance Technical Conference (AATC) as a dedicated venue for practitioners who wanted to go deep on engineering craft rather than process or management frameworks.

What Happened at AATC 2017?

The 2017 edition was held in Boston and drew approximately 300 attendees. The opening keynote was delivered by Ron Jeffries and Chet Hendrickson, two of the original signatories of the Agile Manifesto and long-time advocates of Extreme Programming (XP). They performed the bowling game kata — a form of deliberate practice in which a programmer (or pair) solves a well-defined problem repeatedly to build muscle memory for a specific skill.

In this case, the skill was test-driven development (TDD). Along the way, the two discussed code quality, sustainable pace, pair programming, and what “modern” Agile engineering looks like in practice. Because Jeffries and Hendrickson bring fresh nuance to the kata each time they perform it — despite having done it for over a decade — it still resonated as genuinely new material with the audience.

Other sessions at AATC 2017 covered:

• A keynote on Extreme Programming, celebrating its twentieth year as a methodology
• Fundamentals of test-driven development
• Practical refactoring techniques
• Writing and maintaining clean code

Notably absent from the three-day agenda: stories, standups, sprints, or discussions of trendy infrastructure tooling. The conference was deliberately focused on coding craft.

The Technical Renaissance: Are Agile Engineering Practices Going Mainstream?

At first glance, the fact that a technical conference needs to re-teach TDD and refactoring — practices that have existed for twenty-plus years — can look like a failure. It could be read as evidence that the industry is “post-Agile” in the worst sense: teams adopted the ceremonies while abandoning the hard technical disciplines.

But there is a more optimistic interpretation. Linda Cook, an Agile Alliance board member, explained the conference’s intent the evening before it opened: the AATC was designed to reach a different audience — practitioners who were not plugged into the conference circuit, who had not been exposed to XP or TDD through the usual channels, but who were hungry to learn and improve their craft.

Filling a hotel ballroom in Boston with developers eager to learn TDD and refactoring suggests something important: Agile technical practices may finally be reaching the mainstream, rather than remaining the province of a small community of early adopters.

The Diffusion of Innovation Lens

Sociologist Everett Rogers’ diffusion of innovation model describes how new ideas spread through a population across five groups:

• Innovators — create and experiment with new ideas
• Early Adopters — willing to try things with minimal evidence
• Early Majority — adopt after seeing others succeed
• Late Majority — adopt once a practice is well established, often under peer pressure
• Laggards — adopt only when the old approach is no longer viable, or not at all

Viewed through this model, the AATC audience looked like the early and late majority arriving for Agile engineering practices. These were not the innovators who invented TDD in the 1990s, nor the early adopters who championed XP in the 2000s. They were developers at mainstream organizations who had heard about these practices, sensed they were falling behind, and wanted structured help getting started.

Seeing 300 peers — all at different stages of the same journey — in one room is a powerful signal. It validates that the struggle is common, and that the practices are learnable. That is precisely the environment in which a late majority adopts a new approach.

Proto-Agile, Agile, and Post-Agile: Where Does the Industry Stand?

Each morning at AATC, a small group gathered for Lean Coffee — an open-agenda conversational format where participants propose topics, vote on priority, and then discuss in time-boxed rounds. One recurring theme was the state of technical practices: specifically, “Is Extreme Programming dead?”

Woody Zuill, a well-known practitioner and pioneer of Mob Programming, offered a useful three-stage framework at the table:

• Proto-Agile: “We know what we had before isn’t working, and we are discovering new things.”
• Agile: “We actually understand these modern methods and do them well.”
• Post-Agile: Continuing to innovate beyond established Agile practice — not abandoning it.

Zuill’s position was direct: XP cannot be dead, because he uses it every day. “Post-Agile” in the healthy sense means teams have internalized the core practices so deeply that they no longer need to label them — not that they have abandoned them in favor of stand-up theater.

What This Means for Engineering Teams

The signal from AATC 2017 is nuanced but important for anyone leading or working on a software engineering team:

• TDD, refactoring, and clean code are not niche or outdated — they are skills that a large segment of the industry is actively trying to acquire right now.
• The gap between process adoption and technical discipline is real. Many teams run sprints but do not practice continuous integration, TDD, or refactoring. Closing that gap is one of the highest-leverage investments an engineering organization can make.
• Deliberate practice works. Katas, pair programming exercises, and structured code review are how these skills transfer — not just by reading about them.
• “Post-Agile” is not an excuse to stop improving. If your team has abandoned technical practices in the name of pragmatism, the AATC data suggests you are likely in the early or late majority who have adopted Agile ceremonies without the engineering foundation that makes them effective.

Conclusion

The Agile Alliance Technical Conference 2017 offered a clear-eyed snapshot of where the industry stands: technical practices like TDD, refactoring, and clean code are no longer strange or radical ideas, but they are also not yet universal. They are in the process of diffusing from their innovative origins into the mainstream — and a growing number of developers are actively seeking to learn them.

For DevOps practitioners, this matters directly. The feedback loops that make continuous delivery reliable — fast automated tests, small refactored functions, clean interfaces — depend on exactly these skills. The infrastructure may be ready; the question is whether the engineering practices are keeping pace.

Overview

By 2017, DevOps had been influencing software and operations culture for roughly a decade. To understand how far the industry had actually come, Atlassian partnered with xMatters—a technology partner providing collaboration tooling for DevOps workflows—to survey practitioners across a range of industries. The resulting report highlighted meaningful progress as well as persistent gaps in three critical areas: Culture, Monitoring, and Incident Management.

DevOps Is Working—For Those Who Practice It

According to the survey, 41% of respondents reported actively practising DevOps. Of that group, more than 65% said their DevOps initiatives were delivering the benefits they had expected, including:

• Faster time to market
• Improved customer experience
• Fewer customer-facing incidents
• Faster incident resolution times
• A higher pace of innovation

The remaining 59% of respondents either did not know what DevOps was or were unsure whether their organisation was practising it. Those respondents were excluded from the detailed survey questions. This gap underscores a significant split in the industry: organisations that have embraced DevOps hold a measurable competitive advantage, while many others still treat it primarily as a buzzword.

For additional context, the 2016 Puppet State of DevOps Report noted that high-performing DevOps teams deploy code approximately 200 times more frequently than low performers—a figure that illustrates the scale of the performance gap between adopters and non-adopters.

Culture: Shared Tools, Not Shared Knowledge

Tool sharing between development and operations teams was the strongest indicator of cultural alignment found in the survey. 80% of companies reported that dev and ops share at least some tooling—a foundational step toward a genuine DevOps culture. Many of those organisations also shared information generated by those tools, though often with restricted access.

However, tool sharing alone does not equal a healthy DevOps culture. Genuine knowledge sharing—where cross-functional teams can access information dynamically and in real time—was far less common. Only 17% of companies reported having open information available to cross-functional teams in dynamic formats such as wikis and chat platforms. The large majority indicated that information is shared reactively and in static formats only when requested.

This gap matters because shared context is what allows teams to respond quickly to change. Without it, the cultural promise of DevOps remains only partially fulfilled, even in organisations with strong tooling adoption.

Monitoring: Extensive Data, but Still Missing Issues in Production

Organisations surveyed had invested heavily in monitoring. Key findings include:

• 75% monitored both infrastructure and applications/services
• 60% monitored transactions
• 51% monitored user experience
• Nearly two-thirds said their monitoring solutions could predict potential issues before users were affected

Despite this monitoring coverage, 50% of surveyed companies still reported finding issues in production after code was released. The likely cause is a combination of gaps in transaction and user-experience monitoring and the fact that barely half of surveyed organisations practised automated testing as part of their QA process.

The takeaway is straightforward: monitoring is necessary but not sufficient. Without automated testing integrated into the delivery pipeline, monitoring alerts act as a reactive safety net rather than a proactive quality gate. Organisations that combine broad monitoring with robust automated testing are better positioned to catch issues before they reach production.

Incident Management: Process and Information Bottlenecks

Incident management is often considered the most rigorous test of DevOps maturity. How quickly a team can detect, communicate, and resolve a major incident reveals the true state of its processes, tooling, and culture. The survey results showed that most organisations still had significant room for improvement:

• 50% of companies had to wait for the operations centre to formally declare a major incident before a response could begin
• 43% used manual processes to update customers and internal stakeholders during incidents
• 34% experienced delays in resolution while waiting for subject-matter experts to become available

The common thread across these bottlenecks is information and process overload. Monitoring tools generate large volumes of data, but translating that data into actionable decisions under pressure requires clear runbooks, automated alerting, and pre-defined escalation paths. Organisations that rely on ad-hoc communication and manual handoffs during incidents will consistently struggle to meet resolution time objectives.

Key Takeaways for DevOps Teams

The 2017 Atlassian/xMatters report painted a picture of an industry in transition. DevOps was clearly delivering value for its practitioners, but most organisations had not yet realised its full potential. Based on the findings, the most impactful improvements organisations could make were:

1. Move from tool sharing to knowledge sharing. Adopt dynamic, open documentation platforms (wikis, persistent chat channels) so cross-functional teams can access context without waiting to be told.
2. Pair monitoring with automated testing. Monitoring production is essential, but automated testing earlier in the pipeline prevents many issues from reaching production in the first place.
3. Automate incident response workflows. Reduce reliance on manual communication and expert bottlenecks by implementing on-call automation, pre-defined escalation policies, and status-page tooling.
4. Define what a major incident means before one occurs. Clear, agreed-upon criteria for declaring incidents remove the delay caused by waiting on operations centres to make a call.

DevOps practices were well-established enough by 2017 to show measurable competitive benefits for adopters. The challenge for the years ahead was—and in many organisations remains—moving beyond surface-level tool adoption to genuine cultural and process transformation.

Cloud computing had already transformed many enterprises in the years before 2017, but analysts at Forrester Research argued the market was entering a meaningful second wave — one driven not by startups and early adopters, but by large enterprises migrating core business workloads. Forrester predicted the cloud market would accelerate significantly in 2017 as organizations sought compute efficiency at scale.

“The No. 1 trend is here come the enterprises,” said Forrester analyst Dave Bartoletti, primary author of the research. “Enterprises with big budgets, data centers and complex applications are now looking at cloud as a viable place to run core business applications.”

Forrester surveyed more than 1,000 North American and European enterprise infrastructure technology decision-makers and found:

• 38% were actively building private clouds.
• 32% were procuring public cloud services.
• The remainder planned to implement some form of cloud in the next 12 months.
• 59% said they were adopting a hybrid cloud model.

Based on this research, Forrester offered six cloud predictions for 2017. Each remains instructive for understanding how enterprise cloud strategy has evolved.

1. Regional Cloud Players Complement Mega-Providers

Amazon Web Services launched in 2006 with a handful of simple compute and storage services. By 2017, AWS was operating at an $11 billion annual run rate. Microsoft Azure, Google Cloud and IBM joined AWS as what Bartoletti termed “mega-cloud providers,” opening new data centers around the world and making regulatory concessions — such as Microsoft’s agreement to have T-Systems manage its cloud infrastructure in Germany to comply with data localisation requirements.

Despite their scale, these providers cannot address every regional compliance requirement, latency constraint or industry-specific need. Forrester predicted smaller regional cloud providers would see increased adoption in 2017 as a result. The practical guidance from Bartoletti: “Keep your options open and don’t be afraid to use multiple providers.”

This prediction proved accurate. Multi-cloud strategy became a dominant enterprise architecture pattern in the years that followed, driven by exactly the factors Forrester identified: regulatory complexity, data sovereignty and the limitations of any single vendor’s footprint.

Capital One’s public shift away from private cloud to AWS illustrated the broader enterprise momentum. CIO Rob Alexander explained the rationale: “We recognised that we were spending a lot of time, energy, effort and management bandwidth to create infrastructure that already exists out there in a much better state and is evolving at a furious pace.”

2. Cloud Cost Containment Becomes a Core Discipline

A common assumption in 2017 was that moving to public cloud automatically reduced IT costs. Forrester challenged this. CIOs managing multiple cloud providers faced increasingly complex vendor relationships, and poorly managed cloud consumption — such as leaving instances running over weekends when not needed — could result in spending more than an equivalent on-premises deployment.

Forrester predicted that IT organisations would mature their cost management practices in 2017. As a concrete example, Bartoletti cited a cloud architect at a large software company who reduced a $2.5 million annual cloud bill by $300,000 simply through consumption monitoring.

Cost management tooling from providers including AWS, Cloudability and Cloudyn was already available at the time. Bartoletti was direct: “There’s no reason in 2017 for your cloud costs to grow out of control.”

Cloud financial management — now commonly called FinOps — has since become its own engineering discipline, validating this prediction entirely.

3. Lift-and-Shift Migration Tools Accelerate Cloud Adoption

The ideal approach to cloud migration has always been to refactor or re-architect applications to take full advantage of cloud-native capabilities such as elasticity, managed services and auto-scaling. However, re-architecting is expensive and time-consuming — often impractical for large application portfolios.

Forrester predicted that lift-and-shift migration tools — which move existing applications to the cloud with minimal or no code changes — would lower the barrier to bulk application migrations in 2017. The trade-off is well understood: lift-and-shift gets workloads into the cloud quickly and cheaply, but organisations typically leave cloud-native efficiency gains on the table until they refactor later.

As Bartoletti put it: “In 2017, lift-and-shift migration tools will accelerate the rate of cloud migration, given their low cost for bulk application migrations.”

4. Hyperconverged Infrastructure Becomes the Private Cloud Foundation

Not every enterprise CIO was ready to move sensitive data to a third-party public cloud provider. For organisations committed to private cloud, building a capable, self-service infrastructure required advanced virtualisation, automation, standardisation and resource monitoring — capabilities that were difficult and expensive to assemble from discrete components.

Hyperconverged infrastructure (HCI) offered a compelling alternative: pre-integrated compute and storage resources in a single appliance or software-defined platform, designed to simplify private cloud deployment and reduce time to value. Forrester recommended HCI as the default foundation for private cloud builds, particularly for workloads requiring rapid, automated scale-out.

“HCI is quickly becoming the default infrastructure platform upon which to build the private portion of a hybrid cloud,” Bartoletti said.

Vendors such as Nutanix, VMware and Dell EMC drove significant HCI adoption in the years following this prediction, confirming the trend.

5. Containers Reach Every Major Cloud Platform

Containers — most prominently Docker — had been gaining developer adoption for several years by 2017. Forrester predicted that Linux containers would be available across every major public and private cloud platform by early 2017, moving from developer experimentation into production workloads at scale.

The adoption of containers brought new operational challenges, including security hardening, persistent storage, networking between containers, and production monitoring. Forrester advised organisations to carefully evaluate on-premises private Platform-as-a-Service (PaaS) options against managed public cloud development platforms before committing to a container strategy — noting that some organisations would need both.

Kubernetes, which Google open-sourced in 2014, was already emerging as the leading container orchestration system by 2017, and its subsequent dominance validated Forrester’s focus on containers as a defining trend of the era.

6. Enterprise Applications Move to Public Cloud

Perhaps the most significant signal of cloud maturity in 2017 was the willingness of large enterprises to run mission-critical business applications in the public cloud. Examples cited in the original Forrester research included:

• Dollar Shave Club running Apache Spark analytics workloads on AWS.
• Cardinal Health running Splunk on AWS.
• Multiple enterprises running SAP on AWS.

These examples represented a meaningful shift in CIO risk tolerance. Where earlier cloud adoption had focused on development environments, test workloads and commodity infrastructure, enterprises were now entrusting revenue-generating and compliance-sensitive applications to public cloud providers.

“Enterprises are turning great ideas into software and insights faster and the cloud is the best place to get quick insights out of enterprise data,” Bartoletti concluded.

Key Takeaways

Viewed from the present, Forrester’s 2017 predictions were largely accurate. Enterprise cloud adoption accelerated, multi-cloud became standard, FinOps emerged as a discipline, HCI grew rapidly, Kubernetes achieved dominance in the container space, and public cloud is now the default platform for enterprise application development. The six trends below summarise the framework:

1. Regional players complement mega-providers — Multi-cloud and regional compliance requirements drive vendor diversity.
2. Cloud cost containment — Consumption monitoring and FinOps practices become essential.
3. Lift-and-shift migration — Tooling lowers the barrier to bulk migrations even without refactoring.
4. Hyperconverged infrastructure — HCI simplifies private cloud builds within hybrid architectures.
5. Containers — Linux containers reach every major platform, introducing new operational challenges.
6. Enterprise apps on public cloud — CIOs grow comfortable running core business applications outside the data centre.

Original reporting by cio.com, based on Forrester Research analysis by Dave Bartoletti.