Out Scaling Peak Load

Out Scaling Peak Load

Not building your website for scale can be extremely detrimental to your service / product line and reputation – and can become an expensive mistake in the long term! Surges in genuine traffic are a rare opportunity, which makes it terrible timing for your website to be crashing.

In this short 25 minute talk, Morgan Atkins, DevOps and Continuous Delivery Consultant at ECS Digital, covers:

  • Why you want to engineer for scale
  • How you can build your services to scale
  • What the common success factors are
  • Where this technology is moving to next, and how this evolution will support scale beyond the Cloud



You can also watch the video for free on our YouTube channel here and learn how you can get yourself in the best position to react to unforeseen, performance-critical traffic spikes to your website.

If you want to talk to the team about any specific parts of the lecture, please reach out to hello@ecs-digital.co.uk and one of our consultants will be in touch to help answer your questions.


Banner Photo credit: Farzad Nazifi on Unsplash

Morgan AtkinsOut Scaling Peak Load
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Q&A: The Evolution of the term ‘DevOps’

Q&A: The Evolution of the term ‘DevOps’

Use of DevOps practices has soared in recent years. Commonly, this is the result of an increased number of organisations seeking to respond more effectively to their business challenges with agile methodologies and ways of working. And yet, the term ‘DevOps’ seems to be diluting at a similar pace.

People appear to be referring to their own digital transformations by referencing DevOps practices without necessarily having these in place – certainly not in the traditional sense. Is the term ‘DevOps’ simply losing its specificity, or is it becoming altogether redundant? Or should the term DevOps embrace a widened context in the wake of changing industry trends?

We sat down with both ECS Digital’s Founder & Managing Director, Andy Cureton, and Head of DevOps, Jason Man, to discuss the evolution of DevOps as a practice, and how the term ‘DevOps’ looks to be changing.

Here’s what they had to say:

Q: How would you summarise DevOps in a sentence or two?

Jason: “DevOps is about delivering speed, quality and business value. It’s not about the technology out there or using the right tech to be captivating your audience, but actually about what business value it’s bringing”.

Andy: “DevOps is about aligning all areas of an organisation to leverage modern ways of work and technology to deliver the target business outcomes.”.


Q: Have you heard customers, or people from within the industry describe DevOps in other ways?

Jason: “People tend to use terms like digital transformation, engineering capability, platform engineering as a way to describe the DevOps methodology as a whole, broadening the term far beyond its traditional meaning. DevOps is the overall encapsulating term for all the different practices, one term which has risen and what I see may be the next term for this is Customer Experience (CX).  CX is on the rise as this is ultimately what organisations look to improve, how they achieve this would be implementing DevOps practices, adopting agile methodologies and so forth.”.

Andy: “Engineering or Digital Transformation are more commonly used to describe programmes of work to adopt DevOps. One of the reasons for this is the overuse of the term ‘DevOps’.  There is also the challenge in the breadth of things that the term DevOps is being used to describe. I believe this reflects the broader adoption in the industry where there are organisations well advanced on their journey and those at or towards the beginning. There are comparatively few in between. The early adopters have provided the hard data around DevOps that has led to the conclusion that it is essential to the success and survival of businesses. At one end of the spectrum you can find people referring to DevOps practices to describe the introduction of source code management or continuous integration. At the other end the same term is used to refer to continuous deployment to dynamic serverless production infrastructure 10s of times a day yet there is no distinction in how the term is being used. For this reason, people tend to refer to the specific technology or practice, for example continuous delivery or continuous integration rather than the overarching term DevOps.


Q: Is there an element of the ‘Cloud-wash’ effect happening?

Andy: “Yes. People attach the word DevOps to everything in the same way they attach the word Cloud to everything as a way of implying modern, cool, agile or technologically advanced. In both instances, it betrays what true DevOps or Cloud is and creates a negative stigma around the terms. A CIO told me over a year ago that he “would be shot if he went to the board to ask for money to do DevOps” and that the conversation to have would be about investment to reduce lead time to production, increase service availability etc.

Jason: “The DevOps term is being overused, unlike the Agile Manifesto, there is no definitive way to describe if you have adopted DevOps or not. It could be as simple as adopting a CI server or going full blown immutable infrastructure with every part of your pipeline provided “as a service”. DevOps is a bit like a New Years’ Resolution, in the sense that at the beginning of the year everyone sets out good intentions to introduce a new resolution. It’s almost like everybody feels they need to have one and most will set out to stick to one. But then after a couple of months, the novelty wears off and they lose their discipline and go back to how things were originally.


Q: How have you seen the DevOps methodology evolving, and do you think the term should evolve too?

Jason: “DevOps is a continually evolving term, as the whole concept is constantly improving. In 2009 – when the term came into place – you can actually see that there has been quite a lot of improvement. DevOps didn’t used to involve containers but now they’ve come in recently. Serverless is coming in and now people are talking about Machine Learning and AI being introduced too. Whether or not it will remain being called DevOps, that is something to look out for, but ultimately it continues to evolve. We do see that the traditional practices are now being adopted at scale across all sectors including finance and public sectors. The newer and niche practices are setting out on their early adopters and proving its value, which hopefully will end up with scalable enterprise adoption.”

Andy: “As discussed earlier the use of DevOps practices has exploded as their benefits have been increasingly documented. The practices themselves have not evolved but with increased adoption and advancement of technology, they have been applied to different use case and technologies. For example, using AI/ML to perform previously manual exploratory testing, container technologies being applied to use cases ranging from technology currency to cloud migration.


Q: What do you see in the future for DevOps? Is there a risk the term will die out as its scope widens?

Andy: “DevOps practices have become a critical element to the success and survival of companies in this increasingly software driven world. The term will die out for two reasons. Firstly, because it is overused and attached to things incorrectly it has diminished in value. Secondly, the term will die because the practices that DevOps covers are now becoming the new normal. These practices including continuous integration and continuous delivery will however continue to be referred to. As mentioned before, the benefits seen by organisations who have adopted DevOps are well documented and transformational to the fortunes of those companies. As IDC says DevOps is no longer optional, it’s mandatory. It is therefore becoming the new normal.

Jason: “The term DevOps will die, and I would almost say that it has died. It will be termed under a different methodology due to its overuse. IT has gone through this change many, many times. I have only been in the industry for 10 years and I’ve seen three different methodologies that cover the same thing.

With regards to its scope, in the past organisations used to outsource engineering capability because it was seen as a cheaper methodology to run. But more recently, people are bringing this back in house as they have the talent available. I can see people in the future saying the cost is too high and we should outsource again specially if they are not seeing the results the market is promising. It is a continually evolving methodology, every organisation is a software company hopefully with the ultimate goal to improve customer experience.”


Q: Where are the areas of DevOps that need additional tools or support to help optimise its capabilities?

Andy: “DevOps isn’t about tools; DevOps refers to a group of ways of working and practices. These practices can and are being applied to new technologies and use cases that will see the use of “DevOps” evolve and grow. The question should therefore be, what are the technologies and use cases that need DevOps practices to optimise them? These will continue to be uncovered as new technologies or use cases for existing technologies are discovered.

Jason: “An area that is still underplayed or underutilised is the data side of things – people are talking about collating data and baseline metrics, but I feel like there is room to improve and manage this data. Everything flows through systems and computers and we need to look at how we can analyse this data in a better form because actually, in order to continually improve, you can’t always be looking, discovering or finding out what is it that we need to improve. Whereas if you have a proper data metric system, you can immediately know what’s needed. This space is overcrowded already but I would go as far as saying there is no outright leader in the space”.


With the increase in businesses undergoing Digital Transformation, DevOps has become an industry buzzword. A way for businesses to feel like and project externally that they are achieving the same as others, without fully understanding what it means to adopt DevOps. As we’ve seen with terms such as Cloud and agile, as the frequency of use increases, the murkier the meaning becomes.

Puppet’s VP of Ecosystem Engineering, Nigel Kersten states that an increasing number of people will claim that DevOps is ‘dead,’ not because the practice is dead, but more that the “lessons from the DevOps movement [will] become increasingly internalised in new companies and projects, [where] we’ll stop seeing the cool kids talk about it at all.” This was a prediction of Andy’s some time ago which he spoke about within a 2016 DevOps Online article – he stated that DevOps will no longer be called DevOps as it will become the new normal, an integral part of all companies without any questions asked.

ECS DigitalQ&A: The Evolution of the term ‘DevOps’
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Two steps forward with one shift left

Two steps forward with one shift left

Limitation of the linear development process 


Source: Intellectsoft (www.intellectsoft.net)

Spend enough time in the industry, and you’re sure to have encountered your fair share of development design processes. Often, they’ll be in a form similar to the waterfall design image above, starting from the Design to the Coding, then Testing and, finally, ending in Acceptance and Deployment. What the image doesn’t fully express is how much time and resources is dedicated to fixing the problems that crop up along the way. And, critically, how draining and arduous the process of referring back to previous stages can be. 

Why testing in the testing stage is too late 

By virtue of its purpose, the testing stage is where the majority of project problems and issues are caught. Here is where mountains of error logs are generated and a proportionally high volume of resources are required to identify and eliminate bugs. 

By now, the code would have been months, at best weeks, into development. With each new dependencyintroduced, each script developed, the code becomes exponentially harder to debug. Developers will often spend long periods of time re-familiarising themselves with solutions they themselves built, but forgot how it works. 

Security and Compliance, whether included in the testing stage or in a section of its own, brings its own set of headaches as well. Vulnerable libraries, outdated software and a whole list of similar issues caught here will need addressing, often having regressive effects on other tests and the overall solutions. 

All this effort makes organisations unable to adapt to market demands and industry competition, due to slow and unresponsive processes. Time that could be spent performing actual development work and improving processes is, instead, used trudging through the exact same work simply to be able to understand how to solve problems. Mitigating these disruptions is where the shift left philosophy comes in – allowing you to move forward with greater agility. 

What is Shift Left? 


Source: Checkmarx (www.checkmarx.com)


As the name implies, the Shift Left philosophy is all about the moving stages left in the sequence. In this case (image above), Security and Testing. Immediate efficiencies can be derived by including testers in the Development and Design phase, while also ensuring that developers perform Test-Driven Development. All of these actions will measurably reduce unforeseen delays and disruptions, as well as ensuring enough time and resource is dedicated to fixing these issues.  

Debugging solutions that were built only yesterday is a far simpler task than pouring through logs of processes developed months ago and integrated with multiple other projects. Keeping teams lean and flexible makes organisations better equipped to react to market forces and cuts project costs. 

Shifting Left is the DevOps way 

Having established what Shifting Left is, the question now moves to: ‘How to go about Shifting Left? Here is where the DevOps culture and processes comes into play. As a quick refresher, DevOps comes from the idea of combining Development and Operations together and is about continuous feedback and the dissolution of programming silos (groups) to encourage cooperation and quicker responses. 

This culture of cooperation, to continually gather feedback and iterate on the solutions allows you to be flexible and adaptable to market changes. Testing earlier also prevents massive fatal errors from taking the entire system down, instead keeping issues small and manageable. 

Adopting DevOps also entails embracing automation because, and where there is automation, there are resources to be freed. These automated processes facilitate keeping costs low and permit scalability at the same time. With a sufficiently rigorous infrastructure in place, it becomes possible for future projects to benefit from previously generated solutions and processes, thereby improving business gains. 

How to begin 

So, how do you begin to embrace DevOps and start Shifting Left? What tools are available to do so? How much process should be moved left and when? Let us at ECS Digital bring you up to speed on what to do using some of the best practices we’ve established in multiple industries. After this course, you will not only have a better understanding of how DevOps will improve your processes, but in a far better position to apply these learning to your organisation. Step forward and we’ll show you how to Shift Left.  

Register for our Adopting DevOps training course in Singapore from 7th to 9th May 2019.

Matthew SongTwo steps forward with one shift left
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Using AI and DevOps to streamline communications

Using AI and DevOps to streamline communications

The way in which organisations deploy enterprise technologies has undergone a shift in recent years. Today, there is a cry for more agile ways of working. But to achieve this agility, teams need to establish a communication stream that works for both the techies and non-techies, the influencers and implementers, the stakeholders and the individual. In short, the more integrated and familiar your employees are with one another, the less painful (and costly) your communication has to be.

People, then tech

Whilst digital transformation is often perceived to be technology focused, you’d be mistaken to put the onus of change wholly on your DevOps team. According to PMI’s 2018 Success in Disruptive TimesReport, 29% of failed projects mention inadequate/poor communication as the primary cause of those failures.

Part of this problem is how different departments approach work, their interest in the change and the different language they use. Then there’s the fact that many departments are so busy working towards their own goals that they lose sight of the overall needs of the business – they can’t see the forest for the trees, as it were.

Rather than throwing work over the wall for unengaged individuals to pick up, creating communication streams that encourage collaboration and demonstrate value are fundamental to delivering a successful transformation.

Take automation. If the basic challenge behind DevOps is to keep moving parts in sync to enable a fail fast, fail often approach, having a collaborative team will reduce the number of moving parts that need to be synced – simplifying the process and accelerating deployment.

The same applies for feedback loops. Software developers use a DevOps approach to quickly release apps and gather feedback on new features – and not just when applications are in production. This enables teams to have full visibility over the development of products, testing as they build and releasing more rapidly with more confidence.

How is Artificial Intelligence (AI) strengthening DevOps Programs?

One of AI’s greatest strengths is that it can flex its intelligent, data-grabbing fingers a whole lot quicker than the average Joe. Not only does this help automate the extraction of knowledge from vast amounts of data at pace, it consolidates data from multiple sources, centralising data and granting teams a way of searching data pragmatically.

It also offers a greater degree of flexibility. Take Cloud tools as an example. There are so many different pathways of how to approach Cloud / implement the appropriate tools that whilst you might feel you know the best way to approach something, there is every chance a better alternative exists. And this is where AI comes into its own. Intuitive by design, AI can collate hundreds of thousands of examples, spot anomalies in this data and then recommend best practice based on what others have done. This intelligence offers a more holistic view and gives insights far beyond your companies’ four walls.

“It’s one thing to understand what’s happening, and it’s another to decide what to do. We see people turning to AI to help optimise their decision-making as the intelligence AI provides enables businesses to have a more holistic view over the data whilst remaining specific to the problem the business is trying to solve”

 Babak Takand, ML Specialist & DevOps Consultant at ECS Digital 

How is AI helping to streamline communications?

As touched on above, communication and feedback are two of the biggest challenges when it comes to moving to a DevOps methodology. Ideally, you need to be setting up channels that can revise workflows on the fly. Automated technology, chatbots and other systems enhanced with intelligence and learning abilities, are capable of doing just that, enabling communication streams to be simplified and more proactive.

As the communication streams begin to become slicker, businesses can begin to apply more pressure on their DevOps process with the confidence that the agility and tools in place will make it go faster than humans could go on their own.

Ultimately, tools are there to help you identify problems and to add flexibility to your system. Teams trained in these tools – like ECS Digital – are then on hand to train individuals on how to use these systems and adapt them to how things operate.

For those of us knee deep in sci-fi media, the utopia would be to invert this internally, so the system adapts to how you want your tech to work automatically. In other words, if you are wanting to use a specific DevOps tools, you could voice / code what it is you want to achieve, and the AI tool will have a good enough understanding that it will identify your needs and set it up for. Failing that, it will generate a set of steps you need to take to instead.

Leading by example

At ECS Digital, we are putting our tools where our mouth is.

For the past year, as part of our R&D initiative in AI and machine learning, we have been looking at what we can extract from our own internal communications, and utilise that knowledge to enhance our internal processes by looking at popular topics, reoccurring sentiments, and monitoring issues being flagged by individuals / teams. Using various tools – from nature language processing, visualisation, sentiment analysis and traditional analytics – we have the ability to capture the data we need totake a more proactive stance when it comes to problem solving.

Whilst the data is anonymised, the picture it paints is specific to the business and most importantly, it’s honest, meaning ECS Digital has greater visibility over the business communications to help it improve.

We have also begun trialling an automatic assistant for one our clients, introducing a fully automated tool that monitors the reaction of people and maps pathways in conversation. These insights are already helping to improve the customer journey. By flagging pain points and enabling the team to rework the available conversational pathways, our client is truly leveraging the power of AI to align their offerings with what the customer expects.

How can you leverage AI to streamline your communications?

You can’t have intelligence without data, and you can’t have data without formalising how you collect that information from various input streams.

Data collection is a fundamental part of DevOps and requires creating structure around your data collection pipeline.By creating structure, you are enabling the process to be repeated again and again and again, creating the perfect environment for an AI or Machine Learning tool to read your data and generate insights.

In the words of Babak: “As part of your DevOps experience, you will have information that is being submitted left, right, and centre. How you collect this data, how you store it, how you keep it, how you look it, that is important – make your data collection process uniform”.

ECS Digital can help you formalise that structure.

With over 15 years’ experience delivering successful digital transformations, ECS Digital can help you deliver better products faster through the adoption of DevOps, agile ways of working and modern software delivery tools. Talk to the team today to find out how we can help you leverage AI to streamline your communication streams.

Want to read more? Check out our ‘Why you need to embrace AI in your software testing’ blog here.

Babak TakandUsing AI and DevOps to streamline communications
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ECS Digital at Cloud Expo Europe

ECS Digital at Cloud Expo Europe

This week saw thousands of IT professionals head to the Europe’s largest Cloud exhibition – including ECS Digital and our village of partners!

From blockchain and IoT vendors, to datacentre climate control systems manufacturers and cable suppliers, the crowds enticed anybody interested in Cloud-first, scaling up, refining, or just getting started with the tools and technology.

As has been echoed in previous events, Cloud Expo Europe is an unrivalled opportunity to meet with leading technology innovators and service providers, and network with your peers. Attendees also gain access to a wealth of knowledge and advice including emerging trends, tech deep dives, lessons learned and market forecasts.

ECS Digital once again have donned their conference apparel and deployed Europe’s only DevOps Partner Village, bringing together vendors from across the DevOps tool chain. This included Sonatype, New Relic and Storage OS – experts in application performance monitoring and artifact lifecycle management to dynamic container storage, all under one red, white and blue banner.

As you’ll probably know by now, ECS Digital is an agnostic DevOps and continuous delivery consultancy that provides professional and DevOps expertise to thousands of customers, and this year they have been showcasing the newest feather in their cap; Enablement Pods™.

Enablement PodsTM introduce a new way of working, processes and tooling. By remaining flexible in their resource profiling, our fixed priced outcome-based engagement model enables you to transform at scale by embedding – for short periods – in existing engineering teams to enable them to implement true change. What’s more, you decide the outcomes and objectives for each sprint, and we put our fees at risk to ensure we deliver.

It really is that simple.

During their talk on day one, Young DevOps Consultant of the Year 2018 Michel Lebeau and Pod Delivery Lead Tom Chapman described Enablement Pods™ as ECS Digital new weapon for making long-lasting and impactful changes in the Enterprise space. They also walked guests through how they are using Enablement Pods™, some of the challenge case studies and what Enablement Pods™ has achieved. If you missed the talk, you can learn more here.

ECS Digital also introduced a second, equally exciting initiative at Cloud Expo Europe. The DevOps Playground is supporting the tech community by giving enthusiasts a platform to explore new technology and tools. We’re also super chuffed that the Playground reached 4,000 members worldwide during the show – we’re giving credit to the talk our team delivered on day two!

I was fortunate enough to deliver the DevOps Playground story, describing how ECS Digital have used the DevOps Playground to build a tech community that encourages tech enthusiasts to not only learn about tools, but to gain hands-on experience under the supervision of engineers.

Each month, the DevOps Playground welcomes large numbers of tech-enthusiasts to one of our four worldwide locations – London, Singapore, Pune and Edinburgh. Each Playground lasts for around 2.5 hours, with a chunk of that time set aside for individuals to run and use the chosen tech / tools on their own laptop.

Attendees can expect to follow along with a structured and comprehensive exercise, designed to jumpstart new users with unfamiliar technologies and to highlight the best ways to use the technology. If this is the first you’ve heard of it, head over to the DevOps Playground website to find out more.

Other key takeaways from the show include:

  • Containers are driving the Cloud adoption of software development for 90% of the customers we spoke to
  • DevOps is the new standard for Cloud and agile working and is driving the need to modernise the more traditional methods
  • Cloud Expo is the one-stop-shop for all things Cloud – it was an eye opener seeing how much physical infrastructure goes into the ‘Cloud’

And that is just the tip of the iceberg. We will be revealing a mini-video series about Cloud Expo over the next couple of weeks to recapture some of the best moments from the show – watch this space!

Morgan AtkinsECS Digital at Cloud Expo Europe
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How to go from good to great with Jenkins and ECS Digital

How to go from good to great with Jenkins and ECS Digital

With an unparalleled plugin ecosystem, Jenkins supports project build, deployment, automation and practically every tool within your delivery pipeline. Owned by CloudBees, Jenkins currently has 1,650,000 global users, and is arguably the world’s most loved open source build servers. But with so many features, many users stick to the basics without tapping into the rich value streams Jenkins has to offer.

This infographic takes a look at some of the features you should be paying attention to and how ECS Digital can help you get the most out of your Continuous Integration (CI) software:

Official Jenkins Training

As well as being the Cloudbees’ Service Delivery Partner of the Year, ECS Digitals are also authorised training partners, offering a range of official Jenkins training courses for all skills levels. We are currently  running a 4-day official training course in Singapore from the 25th to 28th March.

If you are interested in learning about Continuous Integration concepts, project build, deployment, automation, and practically every tool with your delivery pipeline, register for our training course.

Here at ECS Digital we’re always happy to talk about what we do, why and how. If you’re interested in finding out how we can help you, please do get in touch.

Kok Hoong WaiHow to go from good to great with Jenkins and ECS Digital
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Addressing the whale in the room

Addressing the whale in the room

This infographic is aptly named addressing the whale in the room due to the scepticism around ‘popular’ Docker misconceptions. Namely that is it insecure, requires the Cloud and is unable to compete with others in the orchestration space given it is open source.

As Docker Authorized Consulting Partners, ECS Digital have been using this technology to significantly add value to our customers by bringing the benefits of containerisation to more traditional applications.

Whilst we know first-hand why this technology is worth investing in, we wanted to take a closer look at who’s using the technology, the statistics behind Docker’s platform and the benefits those currently using Docker as their enterprise-ready containerisation tool are experiencing, so you can see its true value too.

Here we go.

Docker Infographic


Here’s how ECS Digital can help you use Docker:

ECS Digital is a leading Docker Certified Delivery Partner. There are significant benefits to containerisation, including portability, improved security and increased infrastructure efficiency.

Docker Modernising Traditional Applications

ECS Digital has the knowledge and experience to bring the benefits of containerisation to your more traditional applications. Working with Docker customers across EMEA, undertaking MTA Modernising Traditional Applications engagements, taking a traditional application into containers to realise the value of Docker in just five days with a turnkey program.

  • 1 week onsite support / 3 weeks remote
  • Deploy Docker EE to cloud or on-prem infrastructure
  • Containerize an existing application
  • End-to-end app deploy using Docker EE
  • App operations using Docker EE

Official Docker Training

As Well as Docker Authorised Consulting Partners, ECS Digitals are also Docker Authorised Training Partners, offering a range of official docker training courses for all skills levels.

Enablement PodsTM 

ECS Digital’s Container Enablement PodsTM are an outcome-focused solution that deliver the capability you need, when you need it. Each Enablement PodTM starts with a Sprint Zero in order to establish a backlog of target outcomes with measurable KPIs and the resource.

Our approach Enablement PodTM approach has been massively successful in delivering large scale digital transformation projects in some of the UKs largest retail and commercial banks, as well as News outlets and international energy providers.

Here at ECS Digital we’re always happy to talk about what we do, why and how. If you’re interested in finding out how we can help you, please do get in touch.

Morgan AtkinsAddressing the whale in the room
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DevOps Playground: CI with Blue Ocean

DevOps Playground: CI with Blue Ocean

The Speaker: Matthew Song – https://www.linkedin.com/in/matthew-song-a16b37142/ 

Cloudbees Jenkins is the most popular open source software orchestration tool on the market due to its wealth of plugins and easy set-up of infrastructure as code. Yet where does one begin using the Jenkinsfile for setting up new project and DevOps pipeline?

Let Blue Ocean take the hassle of setting up a jenkinsfile from scratch by providing an intuitive, modern coat of paint on Jenkins user interface. With its modern design and intuitive features, Blue Ocean is here to facilitate a quick and easy setup of new Jenkins pipeline with minimal hassle.

Following the video below you’ll begin to see how easy it is to set up a new Jenkins maven Job using the Blue Ocean plugin and the intuitive feedback it provides through its modern design.

I’ve also written a step by step guide to help you through it all: https://medium.com/ecs-digital/building-a-ci-pipeline-with-blue-ocean-6bb9b02788eb

If you’re interested in attending more hands on sessions, DevOps Playgrounds are held once a month in four locations:

You can also find all the information and resources you need about DevOps Playground sessions, upcoming events and past events on our website: https://devopsplayground.co.uk

Matthew SongDevOps Playground: CI with Blue Ocean
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Five ways Artificial Intelligence is already impacting DevOps

Five ways Artificial Intelligence is already impacting DevOps

Artificial Intelligence and Machine Learning have gained a lot of media attention over the past few years. Many commentators have pointed out how these new technologies are going to create new and interesting developments in a variety of fields – from law to medicine, transportation to education. At ECS Digital, we see AI and ML having a direct and lasting impact on DevOps, and here’s why.

DevOps is a business-driven approach to delivering software, creating an intense collaboration between developer and operations. Whilst human input remains an important cog within the system, DevOps focuses on encouraging businesses to automate repeatable processes to encourage efficiency, reduce variability and improve quality at every stage of the pipeline.

Artificial intelligence vs humans – posted on Targetprocess


Emerging AI tools stand to generate even bigger gains. Set to transform how teams develop, deliver, deploy and manage applications, AI and ML perform tasks which would have traditionally required human intelligence. Most notably, these technologies are capable of processing vast amounts of information – picking up the menial tasks and freeing up IT staff to do more targeted work. They can learn patterns, anticipate complications and recommend solutions, all of which fit perfectly within a DevOps culture.

Essentially, AI makes up the technology that integrates into the DevOps systems – affecting both the tools DevOps teams use, and the people who use them.

Here are five ways that AI can work with DevOps to improve software and delivery for the better:

  1. Feedback on Performance

DevOps uses continuous feedback loops at every stage of the process. This involves gathering huge amounts of data in the form of performance metrics, log files and other reports to provide feedback on the operational performance of running applications.

The more advanced monitoring platforms are already applying machine learning to proactively identify problems early in the process and make recommendations. ML in turn is enhancing the continuous feedback loops critical to DevOps by feeding these recommendations straight back to the relevant teams so they can ensure the application service remains viable.

This means you have the 20 highest priority tasks to hand and your AI system can analyse and help pinpoint certain root causes for you to immediately remediate.

  1. Increased Communication

Communication and feedback within teams is one of the biggest challenges when an organisation moves to a DevOps methodology. The sheer amount of information within a company’s systems forces companies to reconsider how teams are interacting with one another, with most businesses setting up a wider variety of channels to set and revise workflows as quickly as possible.

Many of our own team have experienced being blocked by administrative tasks whilst helping clients adopt new technology and ways of working. These tasks often take several weeks to complete, delaying progress in projects and momentum of change. “In these cases, it is advantageous to have access to self-service portals or ChatBots that will help me to orientate in customers’ infrastructure” – Marian Knotek, DevOps Consultant at ECS Digital.

AI systems such as ChatBots are essential to supporting the automated technology that DevOps offers, helping these communication channels become more streamlined and proactive.

  1. Smooth monitoring

To operate efficiently, DevOps teams need to simplify tasks. This is becoming increasingly more difficult as environments become more complex. The sheer volume of data in today’s dynamic and dispersed application environments has made it tricky for DevOps teams to effectively gather and apply information that can help resolve customer issues.

Start with monitoring tools for example, teams tend to use multiple tools that monitor an application’s health and performance in different ways. Extensive amounts of data produced by various platforms and tools are usually aggregated by tools like Splunk’s Artificial Intelligence for IT operations solution harnesses log, application, cloud, network, metric data and more. By automating routine practices, accuracy and speed of issue recognition are increased and operations become streamlined.


Artificial Intelligence for IT Operations (AIOps) platform by Splunk


In a nutshell, Artificial Intelligence and Machine Learning applications are capable of absorbing multiple data streams to find correlations, possible dependencies and issues in the system, giving the team a more holistic view of the application’s overall health.

  1. Prioritise alerts

Alert systems are fundamental to the DevOps culture of ‘fail fast, fail often’. But when a system has been set to flag inconsistencies and flaws in real-time, these can hit the team thick and fast with no differentiation between the severity of the problem – making it difficult for teams to react.

Machine Learning applications can help teams prioritise their responses. Pulling on data such as past behaviour, the magnitude of the alert and the source, DevOps teams can set up rules which enable machines to manage the influx and assort the data when it begins to overwhelm the system.

  1. Improved customer service

Improving the customer journey and providing a positive customer experience (CX) was ranked as the top strategic priority in a survey of global banking organisations for the 2017 Retail Banking Trends and Predictions Digital Banking Report. For many, understanding how users are interacting with their business and tweaking their software in response to these findings is a significant part of creating an all-round better CX. Businesses are also looking for ways to effectively support a 24/7 always on, internet-based, mobile-accessible consumer environment.

Artificial Intelligence and Machine Learning lend themselves perfectly to this landscape. Not only can they collect and analyse data, they can pre-empt questions that may come up during the customer journey and manage the bulk of enquiries to help ease human resource. ITSM tools such as ServiceNow are capable of fashioning a pattern of events before each previous failure is noted. This results in the creation of a support ticket before the event takes place, moving businesses from a reactive to a predictive approach.

This ability to solve a problem before it arises is a huge benefit, significantly lowering customer abandonment rates in the purchasing cycle. It has also been proven to reduce customer complaints and improve consumer satisfaction.

The Future of AI and DevOps

AI, Machine Learning and DevOps – none of these concepts are leaving the conversation any time soon. All are contributing huge amounts to innovation in the tech space and, whilst they are able to operate effectively on their own, there is an interesting dynamic between the maturity of one and the evolution of the others.

The IT industry right now is already in a very different place than where it was five years ago. Whilst DevOps has repeatedly proven its place, this fast development of IT requires reshaping the cultures and mindsets around how we can get the most out of an already successful tool. Most notably, these new approaches towards automated IT enable shouldn’t be ignored. Enterprises that do not make this adjustment and fail to adapt their DevOps efforts to work with Artificial Intelligence and Machine Learning are going to find themselves left behind.


ECS Digital is an experienced digital transformation consultancy that helps clients deliver better products faster through the adoption of modern software delivery methods. We help our clients transform at scale through the use of Enablement Pods – combining outcome focused teams and value-add sprints.

Our Pods deliver DevOps, CT, Cloud and engineering capabilities in one team. This means you get process, enablement and nearly two decades of experience on top of the first-rate engineering, tooling and testing you would expect.

It also means you have a team on board that can help implement the technology you need to embrace Artificial Intelligence and Machine Learning and enable your team in modern tools, technology and ways of working.

Want to know how we can benefit your business? Get in touch.

Andy CuretonFive ways Artificial Intelligence is already impacting DevOps
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DevOps Playground: Hands-on Visual Regression with AyeSpy

DevOps Playground: Hands-on Visual Regression with AyeSpy

The Speaker: Matt Lowry – https://www.linkedin.com/in/matthewlowry92/

Do you get frustrated by tools like Selenium where you are testing webpages in ways where it’s not intended?

Are you struggling to reduce the manual overhead of asserting that your site looks visually correct and checking that it has not regressed after implementing new changes? Visual regression testing is one of the lesser known tools in the SDET toolbox, but when implemented properly can be incredibly powerful.

AyeSpy is a new tool that we helped one of our clients News UK create to address some of the issues that existing open source visual regression tools provide. In this video, we will learn what AyeSpy is about and as usual, as this is a hands-on session, we’ll show you how to use AyeSpy to visually test your application on different viewports.

Thank you to everyone who attended. If you want to learn more about the tool, check out my recent blog on how AyeSpy is already delivering an incredible amount of business value to our client The Times.

Interested in attending our next DevOps Playground events. Follow us on Meetup to receive a notification about the next event

Matt LowryDevOps Playground: Hands-on Visual Regression with AyeSpy
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