Everyone’s talking a good game when it comes to DevOps strategies – but automation is not as widespread in organisations as one might think.

That’s the key verdict from software management provider Puppet in its latest report. The report, State of DevOps Market Segmentation, aims to ‘reveal additional insights’ from the company’s most recent State of DevOps report, issued last year.

The 2017 analysis polled almost 3,200 technical professionals from organisations worldwide, and found that high performers have 46 times more frequent code deployments, significantly lower change failure rate, and 440 times faster lead time from commit to deploy.

Yet while there is an evident difference between the highest and lowest performers, the difference in low performers via industry is startling. The media and entertainment industry only had 23% who were categorised in the ‘low performer’ category, while financial services (54%), industrial and manufacturing (53%) and insurance (53%) were significantly more bottom-heavy in comparison.

Leadership particularly affects performance, as this publication reported analysing last year’s report noted – but in the highest cases, a good leader does not necessarily mean good practices across the board. DevOps success also required ‘suitable architecture, good technical practices, [and] use of lean management principles’, the report said.

The majority of respondents said they reported high levels of manual work across configuration management, deployment, testing, and change approval processes. Many organisations start their DevOps journeys at the areas where the pain is most acute; version control, continuous integration and infrastructure automation among others. Puppet says that while automation is ‘a key enabler’ across organisations’ journeys, the process remains ‘inconsistent and spotty’.

Perhaps the most interesting part of the study was assessing how expectations have changed in DevOps initiatives over recent years. “As practices become more widespread, expectations are rising,” the report notes. “What many might have considered ‘great’ IT efforts just a few years ago might appear as fair to middling today.

“That’s an interesting twist that suggests that the gains provided by DevOps – getting departments and teams to work better across an organisation – is no longer just a ‘nice to have’ but a given,” the report adds. “DevOps is simultaneously raising the bar and expectations of what’s possible.”

“Today, every company around the world has the same priority – automation at scale – and they’re achieving this through DevOps,” said Nigel Kersten, report author and chief technical strategist at Puppet in a statement. “While the data shows that companies of all types and sizes are making progress, we still have a long way to go to eliminate manual work that prevents companies from scaling automation success.”

You can find out more about the report here (email required).

Esther Kezia Thorpe

Bobby Hellard

In 1747 Lord Chesterfield used the immortal line ‘Take care of the pence; for the pounds will take care of themselves’ in a letter to a friend.  It still holds true today. The cost of a cappuccino and avocado on sourdough every morning on the way into the office soon adds up.

But however lax we are with our pennies, none of us would continue to pay the barista for that early morning caffeine hit if we decide to give up coffee. Oddly, though, that is what many large businesses do every day – albeit not for undrunk coffee but for unnecessary and unwieldy technology contracts.

Ghost spending and a spider’s web of contracts

Getting a firm hold on this ghost spending is vital as enterprises look to migrate to the cloud to boost agility and cut costs. If you don’t have full visibility of all IT costs at the start, then any cost savings identified as part of a cloud migration business case are going to be ‘finger in the air’ estimates. Furthermore, it will be hard to determine whether it makes financial sense to move specific workloads to the cloud, or leave them where they are.

Costs are rarely the sole motivation for moving to the cloud with the operating model, agility and saleability also influential. Despite this, the financial arguments tend to sway the board.

There are various reasons for the lack of a single, holistic view of IT expenditure. Sometimes the people who set up long-term contracts with suppliers have moved to new positions and no one has since thought to check the details. In other cases, individual business units may be merrily spinning up their own marketing apps in the cloud without the knowledge of IT teams, leaving trails of multiple cloud service charges in their wake.

Unravelling this spider’s web of contracts and other unnecessary overheads is made more difficult by the headcount cuts that have lacerated many IT departments over the last 15 or so years.  

During this time, cost optimisation has often taken a back seat but now it is coming back in vogue as organisations realise they need a digital clean up to ensure the commercial structure and cost base are fully aligned ahead of a drive to the cloud.

Digital feather dusters

While it makes financial sense to deploy new applications in the cloud, the decision for existing workloads is often less clear-cut. If you have a Technology Business Management (TBM) function, then the first step in any digital spring clean is to engage with them; if not, consider setting up at TBM with the help of a specialist third party.

Begin by undertaking a cost transparency exercise to establish a baseline. By breaking down the total IT bill into chunks – for example payroll services or email services – you can identify the share of these costs across the relevant IT towers e.g. networks or compute – making it easier to sniff out areas where savings can be made. Doing this, one global company managed to cut its annual network run costs by more than a third.

Another area that would benefit from a pre-cloud spring clean is technology demand. As business priorities evolve over time you will find you have unwanted services that can be ditched and low priority services that can be scaled back. Once this demand optimisation has been achieved the cloud journey can commence in earnest.

All technology expenses need to be reviewed. We find that organisations typically overpay their telecoms provider by up to 15%, often because they are being charged for services that they no longer use or have been decommissioned. In the cloud environment, the billing tends to be accurate but does not include a single view of resource consumption. Without this, it’s hard to maximise the true economic benefits of the cloud and it’s easy to end up paying for capacity you no longer need.

Modelling the cost savings

Once these baseline costs have been reviewed and adjusted, cost transformation can begin. A ‘before and after’ cost analysis lets organisations model different cloud options (e.g. IaaS, PaaS and SaaS), as well as single versus multi-cloud, and determine the most cost-effective approach.

We typically find that large organisations can cut IT costs by about 15% by migrating to the cloud or outsourcing alongside the benefits of agility, flexibility and scalability. In one example, a client made a saving of over £10 million a year on their run costs by moving test environments to the cloud. Mindful of the move away from sunk to variable costs, the team were also far more aware of the cost of spinning up every test environment and worked smarter as a result.

Watertight governance

Despite the positive steps taken by this particular test team to regulate usage, it’s essential to put in place watertight governance procedures. Only then can you ensure that everyone in the organisation is aware of the rules surrounding the use of cloud services and prevent money leaks.

Fine-tuning costs

As well as keeping an up to date record of all the software/hardware owned, it’s good practice to have a single view of all cloud service contracts. This becomes even more important in a multi-cloud model. With intuitive dashboards you can see what cloud services are being used where, and by whom at any time.

From here it’s a natural step to fine-tune the costs based on usage. In an IaaS scenario, for example, swapping out a 4-processor server for the same configuration in the cloud will deliver substantial savings as you tend to move from a fixed cost model to a variable cost model. By monitoring the peaks and troughs in resource usage, further cost savings can be identified – and an optimal profile agreed with your cloud provider.

Turning on a dime

There’s no denying the many benefits of moving to the cloud. But it’s impossible to evaluate the true cost implications without first having a single, granular view of all current expenditure. To gain the agility from the cloud that allows your business to turn on a sixpence, you first need to count your pennies.

Read more: Why organisations need 'reality check' on cloud costs

Cloud Pro

How do you balance your cloud and on-premises budget – and how do you get the most out of it? It has long been a problem for organisations once they decide they want to move their systems to the cloud – and according to new research from SoftwareONE, companies continue to suffer from high costs and low visibility.

The study, which polled 300 C-level and IT decision makers in North America, had some interesting data points alongside some less surprising results. More than half (53%) of those polled said they were looking at a hybrid approach to IT – a stat for the latter category. Yet a similar number (45%) said they were either increasing or maintaining their on-prem investments in the coming year.

The problem is naturally built around cost and management. Even organisational budgets have discrepancies depending on who you talk to. On average, according to respondents, IT perceives its annual budget at $5.05 million, while the C suite sees it at $6.3m. What’s more, C-level sees 43% of their perceived budget going onto cloud services this year, where IT sees it more towards a third.

On the management side, 42% of firms polled said they rely on external, third party software to manage cloud deployments. A quarter (26%) believe cloud pricing models were more complex than on-prem equivalents.

A hybrid approach is therefore here to stay, with a four-phase application plan – retire, retain, re-host and re-platform – advocated. To avoid major cost headaches, the report argues that a fine grain approach to the architecture of applications is required – examining ‘how all aspects of the cloud can be used to finely engineer the on-premises applications to realise the maximum benefits.’

Regular industry watchers will be aware that a sub-genre of companies have sprung up with the goal of giving organisations better visibility into their cloud spend. With the most popular cloud providers, such as Amazon Web Services (AWS) and Microsoft Azure, the plentiful resources and tools at their disposal means it can take a lot of expertise to use their products efficiently.

As this publication reported last year, the sector was becoming especially hot with M&A and funding activity ramping up. CloudCheckr, a Rochester-based cloud management platform, secured $50 million in series A funding last March, while Boston-based CloudHealth Technologies raised $46m a few months later in a series D – with European expansion plans coming to fruition.

“Challenges remain in migrating high availability applications to the cloud, and hybrid and multi-cloud deployments are only adding to that complexity,” the report concludes. “Organisations succeeding with the cloud are conducting full, purpose-built migrations and relying on third party tools to better manage and fully utilise their investments in cloud.

“Organisations must have a clear vision and strategy for governing, managing and optimising their IT investments – on-premises and in the cloud – especially as they embrace the hybrid cloud,” the report adds. “To fully reap the benefits of the hybrid cloud, organisations must have complete transparency from on-premises to the cloud in order to maximise the value of their IT investments.”

You can find out more and read the report here.

• Worldwide big data market revenues for software and services are projected to increase from $42bn in 2018 to $103bn in 2027, attaining a Compound Annual Growth Rate (CAGR) of 10.48% according to Wikibon
• Forrester predicts the global big data software market will be worth $31bn this year, growing 14% from the previous year. The entire global software market is forecast to be worth $628bn in revenue, with $302bn from applications
• According to an Accenture study, 79% of enterprise executives agree that companies that do not embrace big data will lose their competitive position and could face extinction. Even more, 83%, have pursued big data projects to seize a competitive edge
• 59% of executives say big data at their company would be improved through the use of AI according to PwC

Sales and marketing, research & development (R&D), supply chain management (SCM) including distribution, workplace management and operations are where advanced analytics including big data are making the greatest contributions to revenue growth today. McKinsey Analytics’ study Analytics Comes of Age, published in January 2018 (PDF, 100 pp., no opt-in) is a comprehensive overview of how analytics technologies and big data are enabling entirely new ecosystems, serving as a foundational technology for artificial intelligence (AI).

McKinsey finds that analytics and big data are making the most valuable contributions in the basic materials and high tech industries. The first chart in the following series of ten is from the McKinsey Analytics study, highlighting how analytics and big data are revolutionizing many of the foundational business processes of sales and marketing.

The following ten charts provide insights into big data’s growth:

Nearly 50% of respondents to a recent McKinsey Analytics survey say analytics and Big Data have fundamentally changed business practices in their sales and marketing functions

Also, more than 30% say the same about R&D across industries, with respondents in High Tech and Basic Materials & Energy report the greatest number of functions being transformed by analytics and big data. Source: Analytics Comes of Age, published in January 2018 (PDF, 100 pp., no opt-in).

Worldwide big data market revenues for software and services are projected to increase from $42bn in 2018 to $103bn in 2027, attaining a Compound Annual Growth Rate (CAGR) of 10.48%

As part of this forecast, Wikibon estimates the worldwide big data market is growing at an 11.4% CAGR between 2017 and 2027, growing from $35bn to $103bn. Source: Wikibon and reported by Statista.

According to NewVantage Venture Partners, big data is delivering the most value to enterprises by decreasing expenses (49.2%) and creating new avenues for innovation and disruption (44.3%)

Discovering new opportunities to reduce costs by combining advanced analytics and big data delivers the most measurable results, further leading to this category being the most prevalent in the study. 69.4% have started using big data to create a data-driven culture, with 27.9% reporting results. Source: NewVantage Venture Partners, Big Data Executive Survey 2017 (PDF, 16 pp.)

The Hadoop and big data markets are projected to grow from $17.1bn in 2017 to $99.31bn in 2022 attaining a 28.5% CAGR

The greatest period of projected growth is in 2021 and 2022 when the market is projected to jump $30bn in value in one year. Source: StrategyMRC and reported by Statista.

Big data applications and analytics is projected to grow from $5.3bn in 2018 to $19.4bn in 2026, attaining a CAGR of 15.49%

Big data market worldwide includes Professional Services is projected to grow from $16.5B in 2018 to $21.3B in 2026. Source: Wikibon and reported by Statista.

Comparing the worldwide demand for advanced analytics and big data-related hardware, services and software, the latter category’s dominance becomes clear

The software segment is projected to increase the fastest of all categories, increasing from $14B in 2018 to $46B in 2027 attaining a CAGR of 12.6%. Sources: Wikibon; SiliconANGLE; Statista estimates and reported by Statista.

Advanced analytics and big data revenue in China are projected to be worth ¥57.8bn ($9bn) by 2020

The Chinese market is predicted to be one of the fastest growing globally, growing at a CAGR of 31.72% in the forecast period. Sources: Social Sciences Academic Press (China) and Statista.

Non-relational analytic data stores are projected to be the fastest growing technology category in big data, growing at a CAGR of 38.6% between 2015 and 2020

Cognitive software platforms (23.3% CAGR) and Content Analytics (17.3%) round out the top three fastest growing technologies between 2015 and 2020. Source: Statista.

A decentralized general-merchandise retailer that used big data to create performance group clusters saw sales grow 3% to 4%

Big data is the catalyst of a retailing industry makeover, bringing greater precision to localization than has been possible before. Big data is being used today to increase the ROI of endcap promotions, optimize planograms, help to improve upsell and cross-sell sales performance and optimize prices on items that drive the greatest amount of foot traffic. Source: Use Big Data to Give Local Shoppers What They Want, Boston Consulting Group, February 8, 2018.

84% of enterprises have launched advanced analytics and big data initiatives to bring greater accuracy and accelerate their decision-making

Big data initiatives focused on this area also have the greatest success rate (69%) according to the most recent NewVantage Venture Partners Survey. Over a third of enterprises, 36%, say this area is their top priority for advanced analytics and Big Data investment. Sources: NewVantage Venture Partners Survey and Statista.

Additional big data information sources

4 Pain Points of Big Data and how to solve them, Digital McKinsey via Medium, November 10, 2017

53% Of Companies Are Adopting Big Data Analytics, Forbes, December 24, 2017

6 Predictions For The $203 Billion Big Data Analytics Market, Forbes, Gil Press, January 20, 2017

Analytics Comes of Age, McKinsey Analytics, January 2018 (PDF, 100 pp.)

Big Data & Analytics Is The Most Wanted Expertise By 75% Of IoT Providers, Forbes, August 21, 2017

Big Data 2017 – Market Statistics, Use Cases, and Trends, Calsoft (36 pp., PDF)

Big Data and Business Analytics Revenues Forecast to Reach $150.8 Billion This Year, Led by Banking and Manufacturing Investments, According to IDC, March 14, 2017

Big Data Executive Survey 2018, Data and Innovation – How Big Data and AI are Driving Business Innovation, NewVantage Venture Partners, January 2018 (PDF, 18 pp.)

Big Data Tech Hadoop and Spark Get Slow Start in Enterprise, Information Week, March 20, 2018

Big Success With Big Data, Accenture  (PDF, 12 pp.)

Gartner Survey Shows Organizations Are Slow to Advance in Data and Analytics, Gartner, February 5, 2018

How Big Data and AI Are Driving Business Innovation in 2018, MIT Sloan Management Review, February 5, 2018

IDC forecasts big growth for Big Data, Analytics Magazine. April 2018

IDC Worldwide Big Data Technology and Services 2012 – 2015 Forecast, Courtesy of EC Europa (PDF, 34 pp.)

Midyear Global Tech Market Outlook For 2017 To 2018, Forrester, September 25, 2017 (client access reqd.)

Oracle Industry Analyst Reports – Data-rich website of industry analyst reports

Ten Ways Big Data Is Revolutionizing Marketing And Sales, Forbes, May 9, 2016

The Big Data Payoff: Turning Big Data into Business Value, CAP Gemini & Informatica Study, (PDF, 12 pp.)

The Forrester Wave: Enterprise BI Platforms With Majority Cloud Deployments, Q3 2017 courtesy of Oracle

DevOps with IBMz? You heard right. Maybe you’re wondering what a developer can do to speed up the entire development cycle–coding, testing, source code management, and deployment-? In this session you will learn about how to integrate z application assets into a DevOps pipeline using familiar tools like Jenkins and UrbanCode Deploy, plus z/OSMF workflows, all of which can increase deployment speeds while simultaneously improving reliability. You will also learn how to provision mainframe system as cloud-like service.

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Today, the entire blockchain/cryptocurrency hairball is itself in a massive bubble. Rather than speculation in cryptos driving the market over the cliff, however, it’s speculative interest in initial coin offerings (ICOs).

This is no mere currency play. Deep pockets with more money than sense are betting on an entire market full of startups, largely because of FOMO – ‘fear of missing out.’

All this hullabaloo is giving me a serious case of déjà vu. I’ve lived through such a bubble before – the dot-com bubble of the turn of the century.

Unlike most of the blockchain/crypto players out there who were children at the time, I saw the craziness of the dot-com runup and bust from the inside. Similarities to the current bubble abound.

Lest we make the mistakes of the past, however, it’s also important to point out the differences. In truth, the two bubbles only have superficial similarities. We can only gain wisdom by understanding both how they are alike – and how they are different.

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