1. Why Communication Matters in DevOps

DevOps breaks down silos between development, operations, QA, and business stakeholders. Effective communication ensures:

• Rapid incident response (clear alerts and escalation).
• Collaboration on code and infrastructure (shared visibility).
• Continuous feedback loops (faster iteration).
• Cultural alignment (transparency and shared responsibility).

Without the right tools, even the best CI/CD pipelines will fail because teams won’t be aligned.

2. Key Communication Needs in DevOps

When choosing tools, evaluate them against these communication categories:

1. Real-Time Chat & Collaboration – For quick discussions, decisions, and alerts.
2. Asynchronous Communication – For documentation, knowledge sharing, and time zone differences.
3. Incident & Alert Management – For critical events and on-call coordination.
4. Code-Centric Collaboration – For PR discussions, reviews, and traceability.
5. Visual Collaboration & Planning – For workflows, retrospectives, and design discussions.
6. Cross-Platform Integration – For connecting monitoring, CI/CD, and ticketing systems into communication hubs.

3. Evaluating Tools by Category

A. Real-Time Chat & Collaboration

• Slack: Widely used; integrates with Jenkins, GitHub, Datadog, PagerDuty.
• Microsoft Teams: Strong enterprise adoption, good if using Azure DevOps.
• Mattermost / Rocket.Chat: Open-source, self-hosted alternatives for compliance-driven orgs.

👉 Best for: day-to-day DevOps chat, pipelines notifications, CI/CD status updates.

B. Asynchronous Communication

• Confluence / Notion: For documenting runbooks, architecture, retrospectives.
• GitHub Discussions / GitLab Wiki: For community-driven discussions within code platforms.
• Google Workspace / Office 365: For documentation and decision records.

👉 Best for: knowledge retention, cross-timezone collaboration, compliance audits.

C. Incident & Alert Management

• PagerDuty: Incident response orchestration, escalation policies, on-call rotation.
• Opsgenie: Atlassian’s incident tool, integrates tightly with Jira.
• VictorOps (Splunk On-Call): Strong in post-incident reporting.
• ServiceNow: For enterprises with ITSM/ITIL processes.

👉 Best for: structured incident management and automated escalation.

D. Code-Centric Collaboration

• GitHub / GitLab / Bitbucket: PR/MR review workflows, inline comments, integrated CI/CD notifications.
• Gerrit: For enterprises needing advanced code review workflows.

👉 Best for: dev-to-ops collaboration on infrastructure-as-code and feature reviews.

E. Visual Collaboration & Planning

• Jira / Azure Boards: Popular for backlog management and release planning.
• Trello / ClickUp: Lightweight planning and task-tracking.
• Miro / Lucidchart: Whiteboarding for architecture and incident diagrams.

👉 Best for: sprint planning, retrospectives, workflow visualization.

F. Cross-Platform Integration Hubs

• Slack / Teams Bots: Integrate build failures, alerts, deployments.
• Zapier / n8n / GitHub Actions: Automate communication triggers across systems.
• Statuspage / Status.io: Communicate outages externally to customers.

👉 Best for: unifying communication across DevOps ecosystems.

4. Selection Criteria for the Right Tools

When deciding, weigh tools against:

• Integration capability – Does it connect to your CI/CD, monitoring, version control?
• Security & Compliance – Self-hosted vs. SaaS, encryption, audit logs.
• Scalability – Handles large, distributed teams without slowing workflows.
• Cost – SaaS pricing vs. self-hosted infrastructure overhead.
• Adoption & Familiarity – What your team is already comfortable with.

5. Example Tool Stack for a Mature DevOps Workflow

• Slack: Real-time collaboration + integrated CI/CD alerts.
• Confluence + GitHub Wiki: Knowledge base and documentation.
• PagerDuty: Incident management and on-call scheduling.
• GitHub + GitHub Actions: Code collaboration and pipeline feedback.
• Jira: Agile planning and reporting.
• Miro: Visual brainstorming for retrospectives and system design.

This creates a single loop of communication: Code → Build → Deploy → Monitor → Alert → Learn → Improve.

6. Best Practices for DevOps Communication

• Automate status updates (don’t manually copy CI/CD logs into chat).
• Define clear on-call escalation rules.
• Use chatops (run commands directly from chat).
• Maintain single source of truth (avoid scattering documentation).
• Record postmortems publicly inside the team’s knowledge base.
• Foster a blameless culture in communications.

✅ Bottom line:
The right communication tools in DevOps are those that integrate seamlessly into your toolchain, provide visibility, reduce noise, and support collaboration across teams and time zones. A balanced mix of chat, async knowledge tools, incident management, and planning boards ensures that DevOps communication is transparent, automated, and effective.

Only 1 in 10 developers deploy software on demand, multiple times per day, according to the Cloud Delivery Foundation’s 2021 State of Continuous Delivery report.

Continuous delivery is a key part of how organizations deliver value to their customers, providing the ability to make small changes to software reliably and at any time, according to the report.

The study, completed by research firm SlashData from data collected from more than 19,000 developers, asked for information on lead time for changes, deployment frequency, time to restore services, and change fail rates.

Two-thirds of respondents indicated it takes at least a week for code to go from committed to successfully run in production. Only about 6 percent said they can move code from commit to production in under an hour.

The programming languages that rank highest for speed and stability in software delivery performance are the shell scripting languages (Bash and PowerShell), with Go/Golang and JavaScript being the next best choices. Interestingly, Ruby, Python and Java — three of the most popular languages based on Tiobe rankings, were poorest in terms of software delivery performance.

“Having access to new relevant data is critical to assessing and making the right decisions. By building this State of CD Report, we have produced an exclusive dashboard for use by our community that shows the current state of continuous delivery for deployment frequency, lead time for changes, time to restore service, and more,” said Tracy Miranda, Continuous Delivery Foundation executive director. “Moving forward, we will publish this report annually in order to track the world’s capacity to deliver software with speed and security.”

CloudBees, the enterprise software delivery company, has shared results from a study conducted on its behalf by Forrester Consulting which revealed organisations with a high level of software delivery maturity are three times more likely to grow at 15% or more annually. Conversely, those not modernising their software delivery processes face increasing roadblocks that limit growth, slow DevOps transformations and expose security and risk vulnerabilities.

“The organisations that unravel the complexities of the software delivery process exceed business objectives and grow revenue faster than those that do not,” said Stephen DeWitt, CEO at CloudBees. “Those that don’t, face issues with collaboration and communication across their organisations which can lead to siloed development, delivery bottlenecks and ultimately, customer dissatisfaction. It’s like driving on a dirt road instead of a four-lane highway to achieve your goals. You can get where you’re going faster and with fewer pot-holes along the way.”

The study, Modernizing Software Delivery with End-to-End Automation, Orchestration and Collaboration, was commissioned by CloudBees and is based on a survey of 317 IT decision-makers.

According to the study, ‘Organisations that pair delivery automation capabilities with effective collaboration practices see more successful Digital Transformations and exceed business expectations at a higher rate than those that cannot. Software delivery maturity is correlated with improved market share, user adoption, innovation and customer loyalty.”

Organisations that reach high levels of software delivery maturity also generate continuous business benefits. According to the study, they are more likely to:

Succeed with their DevOps transformations: High-maturity respondents are more than five times as likely to say their DevOps transformation is exceeding business expectations (35% to 6%).
Grow revenue faster: High-maturity organisations are more likely to grow revenue at a higher rate than their less mature peers — they are almost three times as likely to be growing at 15% or more year over year.
Adapt to changing market conditions: High-maturity respondents in the survey are nearly twice as likely than low-maturity respondents to say their organisations responded to the pandemic better than their peers (49% to 27%).
Although there is considerable progress, perfection remains out of reach for most.

Not quite continuous deployment: Just 27% of respondents said that they practice continuous deployment with automation from commit through testing, build/integration, package and final release.
Risky business: Only 25% rate their governance, risk and compliance (GRC) capabilities for software delivery as very mature, with 40% saying they are not mature.
Status unknown: Fewer than three in 10 high-maturity respondents say they have all the information they need in a single study to understand software release status, dipping to a woeful 2% for low maturity.
Finding bottlenecks: Fewer than half of high-maturity respondents, and only one in 10 low-maturity, can pinpoint the bottlenecks in their delivery processes in order to fix them.

The idea of continuously delivered, quality software vetted through a collaborative and highly automated series of steps from inception to deployment is an enticing one, hence the appeal of DevOps. However, while just about everyone says they are pursuing DevOps, the reality on the ground has been mixed at best.

The urgency of DevOps has only increased over the past year, as the Covid crisis scattered corporate workforces and physically separated IT teams. “We need to rethink connection and integrations, both on a technical level and a human one,” says Ed Macosky, head of product at Boomi .”While it may seem that many DevOps teams don’t have any trouble working remotely, two out of five said that remote work is affecting their ability to innovate and be creative, with the majority noting this is due to a lack of in-person connection with colleagues. DevOps teams bring innovations to life at a company.”

However, it’s been difficult to organize and maintain DevOps teams, especially at this time of uncertainty. “With employee churn, DevOps teams are often left to deal with a script-based dumpster fire,” warns Ashish Kakran, principal with Thomvest Ventures. For instance, while DevOps is supposed to put development and operations on the same page, the two groups often are still taking their own separate paths. “We’re seeing DevOps implemented separately and differently in different functional areas of the same organization,” says Brian Dawson, DevOps evangelist with CloudBees. “Operations may implement their own DevOps tools and processes, while application development implements their own DevOps tools and processes.”

So while the perception on the ground is everybody is doing DevOps, “the reality is also that we still have work to do it right, do it at scale and achieve universal maturity,” Dawson adds. “DevOps is about connecting development and operations. The challenge is to build those connections, universally, between leaders and practitioners, Dev and Ops.”

Cultural issues create this disjointed relationship between Dev and Ops. “Culture is the number one missing component, but there is also a failure to truly connect and automate across functional silos,” Dawson says. “This results in lack of shared visibility, consistent feedback to drive improvement and, potentially, a negative experience which inhibits adoption.”

There are too many tools competing for Dev and Ops teams’ mindshare as well. “A single team may have anywhere between 20 to 50 tools,” says Kakran. “Separating signal-from-noise when you are bombarded by hundreds of alerts per hour is quite challenging.”

The continuous delivery piece is also a snag in the continuous integration/continuous delivery (CI/CD) that should flow effortless through DevOps. “Enterprises are lagging in test automation and are increasing efforts to automate continuous testing, which is a core component of CD,” says Venky Chennapragada, DevOps architect with Capgemini North America.. “Some enterprises are unable to adopt a high level of CI/CD because their application portfolio mostly consists of packaged software, legacy software or ERP systems.”

Security is another issue that slows down DevOps practices. “The modern DevOps environment is full of creative people who are encouraged to build fast and hard to hit innovation targets,” says Kevin Breen, director of cyber threat research at Immersive Labs. “The problem is, security teams only step in at the end of the CI/CD pipeline and point out vulnerabilities. Often this is after code has been committed, and sometimes even after the developer has moved on to another build.” As a result of the too-late entry of security-minded teams, “this causes friction and destroys productivity as it means resources are pulled back.”

What’s being missed with DevOps efforts, Chennapragada adds, is strong governance. This “is leading to multiple versions of implementations and pipelines.” These workflows, he continues, “should be built based on patterns so they are easy to replicate, leading to better maintenance and support that can be executed by DevOps engineers.”

What can be done to make DevOps more cohesive and transformative? Industry thinkers provide some suggestions to get things on track:

Move more responsibility to developers. Yes, DevOps is not always a 50/50 proposition. Kakran calls for an acceleration of the “Shift-Left” phenomenon, which puts more responsibility for the process in the hands of developers. “In this world, dev tools filling the ‘X-as-Code’ category will have an outsized impact on an organization’s ability to deliver faster, more frequently and with fewer number of failed deployments,” he says. “The ‘X’ here is a critical application component – infrastructure, security, compliance, and others. This combination of more empowered developers and more efficient DevOps tools will dramatically accelerate software delivery even more than the past.”
Promote more DevOps training, education and awareness. “DevOps and security teams need to reduce tension through skills development,” says Breen. “By imbuing engineers with an understanding of the baseline tenets of security, and gradually helping them understand the more technical nuances, they will begin to develop more secure code as part of their daily work. This reduces friction, stops code being recalled and helps innovation flourish.”
Tie DevOps to the ultimate customer. “We see more success in enterprises where there is a DevOps champion at the CX level who can remove obstacles due to culture, process, or tool issues when they arise,” Chennapragada says.
Watch the market for more integrated solutions. “End-to-end integrated DevOps platforms will become a norm,” says Kakran. “Such platforms will offer a few best-in-class components with built-in automation and will enable organizations to integrate other DevOps tools in a plug and play manner. Mergers and acquisitions will accelerate in 2021 with bigger companies rushing to acquire smaller companies who have the best-in-class tools which would help them provide an integrated solution.” As a result, he says, “CIOs will be able to dramatically improve their teams’ productivity by leaving integration and maintenance hassle of CI/CD pipelines to integrated platforms. The trend of internal teams writing scripts or generating tickets will be replaced by automation provided by integrated tools from third party vendors will accelerate in a big way in 2021.”
Communicate more. “It’s key that DevOps has the tools and resources to continue creating and integrating quickly at their disposal,” says Macosky. “It boils down to improved communications and leveraging time saving tools like low-code. New ideas can emerge when we’re connected. Then we can solve more problems and teams can prevail, regardless of the situation.”
Ultimately, in the months and years ahead, “the adoption of cloud-native, container-based microservice architectures necessitates the adoption of DevOps culture and tools, says Kakran. “Newer applications are entirely being built using containers and Kubernetes and hosted in a hybrid-cloud environment. This is true even for the largest financial institutions that have historically been hesitant to adopt cloud. Lift-and-shift of legacy applications is a harder problem to solve but serious efforts are underway even there because the benefits of cloud outweigh the cost of adoption. 2021 will be the year of prominence for the 50 million software developers around the world delivering software with very high velocity with higher quality than ever before.”

Global Continuous Delivery market research report provides a thorough analysis of the market status, market size, market growth, share, trends, and cost structures. The report also provides key market drivers and challenges along with the top players. The global Continuous Delivery market report also explains strategic assessment and analysis of the forecast period and predicted growth.

The focus of Continuous Delivery market report is the competitive environment and future trends along with crucial factors and challenges which also include market size, futuristic possibilities and new product/new project development opportunities. This report offers a SWOT analysis along with statistical data and revenue shares of the Continuous Delivery market. The Continuous Delivery market report delivers a wide range of information of various aspects of the Continuous Delivery industry such as the growth strategies, segmentation by product type, applications, regions, and key players. Along with key players, the Continuous Delivery market report includes company perspectives and marketing strategies of the leading companies.

Vendor Landscape
Atlassian
IBM
Xebialabs
CA Technologies
Electric Cloud
Puppet Enterprise
Chef Software
Cloudbees
Microsoft
Flexagon
Micro Focus
Clarive

The research report on Continuous Delivery market includes the impact of COVID-19 on Continuous Delivery market and the post pandemic strategies for recovery along with anticipated growth and regional analysis. Both long term and short-term perspective of the pandemic is explained in the Continuous Delivery market report. Its influence on the industry chain and industry demand is also shared. An overview of the pre-pandemic and post-pandemic market status is analysed. Statistical and regional analysis done in the Continuous Delivery market consists of the import/export consumption so far and post COVID-19, supply and demand figures, cost structure and changes, market share, policy implementation and new strategies and policies price, revenue, and gross margins. Segmentation of the Continuous Delivery market based on the application is done by type and application, along with end-user demands. A classified information portfolio on companies and firms and regions are also included in the report.

Global Continuous Delivery market Segmentation:

Analysis by Type: .
On-premises
Cloud

Analysis by Application:
Banking, Financial Services, and Insurance (BFSI)
Telecommunications
Media and entertainment
Retail and eCommerce
Healthcare
Manufacturing
Education
Others (government, transport and logistics, and energy and utilities)

Regional Assessment: Global Continuous Delivery Market
This referential document assessing the market has been compiled to understand diverse market developments across specific regional pockets such as Europe, North and Latin American countries, APAC nations, as well as several countries across MEA and RoW that are directly witnessing maneuvering developments over the years. A specific understanding on country level and local level developments have also been mindfully included in the report to encourage high rise growth declining market constraints and growth retardants.

The global Continuous Delivery market report shares recent trends, and new marketing strategies and channels. Analytical and statistical data regarding contribution from regions such as North America, Latin America, South America, Europe, Asia Pacific, and Middle East is defined in the Continuous Delivery market report. One of the most important topics covered in the market report include sustainability and feasibility of new projects and investments which is essentially a major concern of every industry.

Highlights of the Continuous Delivery market report
• Market share by key players
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The urgency of DevOps has only increased over the past year, as the Covid crisis scattered corporate workforces and physically separated IT teams. “We need to rethink connection and integrations, both on a technical level and a human one,” says Ed Macosky, head of product at Boomi .”While it may seem that many DevOps teams don’t have any trouble working remotely, two out of five said that remote work is affecting their ability to innovate and be creative, with the majority noting this is due to a lack of in-person connection with colleagues. DevOps teams bring innovations to life at a company.”

However, it’s been difficult to organize and maintain DevOps teams, especially at this time of uncertainty. “With employee churn, DevOps teams are often left to deal with a script-based dumpster fire,” warns Ashish Kakran, principal with Thomvest Ventures. For instance, while DevOps is supposed to put development and operations on the same page, the two groups often are still taking their own separate paths. “We’re seeing DevOps implemented separately and differently in different functional areas of the same organization,” says Brian Dawson, DevOps evangelist with CloudBees. “Operations may implement their own DevOps tools and processes, while application development implements their own DevOps tools and processes.”

So while the perception on the ground is everybody is doing DevOps, “the reality is also that we still have work to do it right, do it at scale and achieve universal maturity,” Dawson adds. “DevOps is about connecting development and operations. The challenge is to build those connections, universally, between leaders and practitioners, Dev and Ops.”

Cultural issues create this disjointed relationship between Dev and Ops. “Culture is the number one missing component, but there is also a failure to truly connect and automate across functional silos,” Dawson says. “This results in lack of shared visibility, consistent feedback to drive improvement and, potentially, a negative experience which inhibits adoption.”

There are too many tools competing for Dev and Ops teams’ mindshare as well. “A single team may have anywhere between 20 to 50 tools,” says Kakran. “Separating signal-from-noise when you are bombarded by hundreds of alerts per hour is quite challenging.”

The continuous delivery piece is also a snag in the continuous integration/continuous delivery (CI/CD) that should flow effortless through DevOps. “Enterprises are lagging in test automation and are increasing efforts to automate continuous testing, which is a core component of CD,” says Venky Chennapragada, DevOps architect with Capgemini North America.. “Some enterprises are unable to adopt a high level of CI/CD because their application portfolio mostly consists of packaged software, legacy software or ERP systems.”

Security is another issue that slows down DevOps practices. “The modern DevOps environment is full of creative people who are encouraged to build fast and hard to hit innovation targets,” says Kevin Breen, director of cyber threat research at Immersive Labs. “The problem is, security teams only step in at the end of the CI/CD pipeline and point out vulnerabilities. Often this is after code has been committed, and sometimes even after the developer has moved on to another build.” As a result of the too-late entry of security-minded teams, “this causes friction and destroys productivity as it means resources are pulled back.”

What’s being missed with DevOps efforts, Chennapragada adds, is strong governance. This “is leading to multiple versions of implementations and pipelines.” These workflows, he continues, “should be built based on patterns so they are easy to replicate, leading to better maintenance and support that can be executed by DevOps engineers.”

What can be done to make DevOps more cohesive and transformative? Industry thinkers provide some suggestions to get things on track:

Move more responsibility to developers. Yes, DevOps is not always a 50/50 proposition. Kakran calls for an acceleration of the “Shift-Left” phenomenon, which puts more responsibility for the process in the hands of developers. “In this world, dev tools filling the ‘X-as-Code’ category will have an outsized impact on an organization’s ability to deliver faster, more frequently and with fewer number of failed deployments,” he says. “The ‘X’ here is a critical application component – infrastructure, security, compliance, and others. This combination of more empowered developers and more efficient DevOps tools will dramatically accelerate software delivery even more than the past.”
Promote more DevOps training, education and awareness. “DevOps and security teams need to reduce tension through skills development,” says Breen. “By imbuing engineers with an understanding of the baseline tenets of security, and gradually helping them understand the more technical nuances, they will begin to develop more secure code as part of their daily work. This reduces friction, stops code being recalled and helps innovation flourish.”
Tie DevOps to the ultimate customer. “We see more success in enterprises where there is a DevOps champion at the CX level who can remove obstacles due to culture, process, or tool issues when they arise,” Chennapragada says.
Watch the market for more integrated solutions. “End-to-end integrated DevOps platforms will become a norm,” says Kakran. “Such platforms will offer a few best-in-class components with built-in automation and will enable organizations to integrate other DevOps tools in a plug and play manner. Mergers and acquisitions will accelerate in 2021 with bigger companies rushing to acquire smaller companies who have the best-in-class tools which would help them provide an integrated solution.” As a result, he says, “CIOs will be able to dramatically improve their teams’ productivity by leaving integration and maintenance hassle of CI/CD pipelines to integrated platforms. The trend of internal teams writing scripts or generating tickets will be replaced by automation provided by integrated tools from third party vendors will accelerate in a big way in 2021.”
Communicate more. “It’s key that DevOps has the tools and resources to continue creating and integrating quickly at their disposal,” says Macosky. “It boils down to improved communications and leveraging time saving tools like low-code. New ideas can emerge when we’re connected. Then we can solve more problems and teams can prevail, regardless of the situation.”
Ultimately, in the months and years ahead, “the adoption of cloud-native, container-based microservice architectures necessitates the adoption of DevOps culture and tools, says Kakran. “Newer applications are entirely being built using containers and Kubernetes and hosted in a hybrid-cloud environment. This is true even for the largest financial institutions that have historically been hesitant to adopt cloud. Lift-and-shift of legacy applications is a harder problem to solve but serious efforts are underway even there because the benefits of cloud outweigh the cost of adoption. 2021 will be the year of prominence for the 50 million software developers around the world delivering software with very high velocity with higher quality than ever before.”

Continuous Integration and Continuous Delivery (CI/CD) can bring a seamless integration from end-to-end for the software development and deployment process. By doing this, CI/CD allows developers to dedicate more of their time developing code to improve software features instead of worrying about the deployment.

Yet, they are still faced with many security challenges. CI/CD might speed up the process but not the security. With DevSecOps – Development, Security, and Operations -, however, there is a possibility to accelerate the delivery of security within the software. DevSecOps engineers try to operate most security controls as part of the software by introducing it as a design constraint and then getting it checked by the CI/CD pipelines without damaging the integrity of controls.

Why DevSecOps?

As digital transformations increase, there is a vital need for safe and secure software, otherwise, everything, from the building to the delivery can be at risk. Security breaches are now one of the biggest threats to companies and products.

DevSecOps promotes collaboration between the development and security teams, hence, avoiding late handoffs to security professionals. By introducing security at the beginning of the process, the value and quality of the product can only be reinforced. Indeed, without DevSecOps, the software might be considered unsafe at the last minute, thus causing multiple costly iterations. With DevSecOps, security standards are implemented directly into the pipelines making the products more secure from the beginning.

Overall, DevSecOps ensures credibility and agility in the market, as well as trust with consumers.

DevSecOps in CI/CD

There are many security vulnerabilities that can exist in open-source software. Hence, implementing DevSecOps practices within CI/CD will bring continuity to securing software deliveries.

Integrating automated security checks within the pipeline will allow developers to have early warnings of vulnerabilities and monitor any security defects or else. With an integrated continuous security approach, companies can expand while upgrading their security and development process as it goes.

Moreover, unit tests and static code analysis operate close to source code as well as run checks without executing the code. Hence, investing in security unit tests and static analyzers will only be beneficial as it can speed up the lifecycle while detecting quickly any vulnerabilities.

The future of DevSecOps and CI/CD pipelines

With the many challenges our world bring today, security is crucial in order to remain on top of the market. With DevSecOps, companies are able to speed up their CI/CD pipelines all the while keeping it secure from any vulnerabilities. Collaboration and communication are then vital between development and security teams and shouldn’t be overlooked.

With the rise of DevSecOps, security has become an important part of the continuous delivery pipeline. Having continuity and security ensures the best software delivery.

What Is DevOps?

DevOps is a cultural and organisational movement — a combination of practices, ideas, tools, and processes designed to break down the traditional silos between software development and IT operations teams. Its core goal is to enable organisations to build, test, and release software faster, more reliably, and with higher quality.

In Patrick Debois’s own framing, DevOps represents “a movement of people who think it’s time for a change in the IT industry — time to stop wasting money, time to start delivering great software, and building systems that scale and last.”

Key attributes of a DevOps culture include:

• Shared ownership — development and operations teams are jointly responsible for product quality and uptime.
• Continuous feedback loops — teams monitor production systems and feed insights back into the development process.
• Automation-first thinking — repetitive manual tasks (provisioning, testing, deployment) are automated wherever practical.
• Incremental delivery — software is shipped in small, frequent batches rather than large, infrequent releases.
• Collaborative tooling — teams share dashboards, on-call rotations, and post-mortems instead of working in isolation.

DevOps is not a specific tool, a job title, or a pipeline. It is a way of working — a cultural shift that must be adopted at the team and organisational level before any tooling decisions are made.

Why DevOps Exists: The Historical Context

Historically, development teams wrote code and then “threw it over the wall” to operations teams who were responsible for deploying and running it. This handoff model created conflict, slow feedback, finger-pointing during outages, and long release cycles. DevOps emerged as a direct response to these friction points, encouraging the two groups to collaborate throughout the entire software lifecycle rather than only at handoff moments.

DevOps in Practice: A Real-World Example

Facebook is a widely cited example of DevOps practices at scale. Its engineering approach has long emphasised code ownership, automation, incremental changes, and continuous improvement — all hallmarks of DevOps thinking. The company reportedly completed a migration of its infrastructure and back-end services to the Chef configuration management platform around 2015, allowing it to manage thousands of servers and push multiple code updates daily. Some of those Chef cookbooks were also made publicly available.

This example illustrates that DevOps is not a single tool or pipeline — it is a philosophy that shapes how an entire engineering organisation operates.

What Is CI/CD?

CI/CD stands for Continuous Integration / Continuous Delivery (and sometimes Continuous Deployment). It is a concrete set of engineering practices and automated workflows — often implemented as a “pipeline” — that enable teams to integrate, test, and release code changes frequently and reliably.

Where DevOps is the culture, CI/CD is one of the most important technical implementations of that culture. Think of DevOps as the philosophy and CI/CD as a key part of the machinery that puts that philosophy into practice.

Continuous Integration (CI)

Continuous Integration is the practice of developers merging their code changes into a shared repository frequently — ideally multiple times per day. Each merge triggers an automated build and a suite of automated tests. The goals are:

• Catch integration bugs early, before they compound.
• Keep the main branch in a consistently deployable state.
• Give developers rapid feedback on whether their change broke anything.

In their book Continuous Delivery, Jez Humble and David Farley recommend that developers check in to the main branch at least a couple of times a day. The longer a branch lives in isolation, the harder — and riskier — the eventual merge becomes.

Continuous Delivery (CD)

Continuous Delivery extends CI by ensuring that every change that passes automated tests is also automatically prepared for release to production. Critically, the final push to production still requires a human decision. A staging or pre-production environment is typically used for user acceptance testing (UAT) or manual review before deployment is approved.

The key benefit of Continuous Delivery is that releases become low-risk, routine events rather than high-stakes, infrequent ordeals. Because the software is always in a releasable state, the business can choose when to ship based on business needs rather than technical readiness.

Continuous Deployment (also CD)

Continuous Deployment goes one step further: every change that passes all automated test stages is automatically pushed to production without any manual approval step. This requires a high level of confidence in the automated test suite, because there is no human gate before the change reaches users.

Continuous Deployment is not appropriate for every organisation or every product. Regulated industries, for example, may require manual sign-off before production releases. However, for mature teams with comprehensive test coverage, it can dramatically accelerate the feedback loop between developers and end users.

Summary: The Scope of Automation in Each Practice

CI/CD in Practice: A Real-World Example

The ReactJS framework maintained by Facebook (now Meta) is a publicly visible example of CI/CD in action. The project’s GitHub repository includes status badges — such as CircleCI build status and code coverage reports via Coveralls — that reflect the results of their automated pipeline on every pull request. Clicking through those badges shows the individual steps of their CI process and how the pipeline is configured. This transparency also serves as a useful learning resource for teams building their own pipelines.

CI/CD vs. DevOps: The Core Distinction

The confusion between CI/CD and DevOps is understandable — both aim to speed up and improve software delivery, and CI/CD is almost always present in a healthy DevOps organisation. But they operate at different levels:

• DevOps is the culture and strategy. It defines how teams are structured, how they communicate, and what values guide their work. You cannot buy DevOps as a product or install it as a tool.
• CI/CD is a set of technical practices and automated pipelines. It is one of the most powerful enablers of a DevOps culture, but it is possible to run a CI/CD pipeline without having a genuine DevOps culture — and conversely, a DevOps culture encompasses much more than just CI/CD (including monitoring, incident management, infrastructure as code, and organisational design).

A useful analogy: DevOps is to CI/CD what Agile is to Scrum. Agile is a set of values and principles; Scrum is a specific framework that implements many of those principles. Similarly, DevOps is the broader cultural philosophy, and CI/CD is one of the most important concrete frameworks for living it out.

Why the Distinction Matters

Getting this distinction right has practical consequences:

• Tooling decisions: Choosing a CI/CD tool (Jenkins, GitHub Actions, GitLab CI, CircleCI, etc.) is a technical decision. Adopting DevOps requires leadership buy-in, team restructuring, and cultural change — no tool alone delivers it.
• Diagnosing problems: If your deployments are still slow and painful despite having a CI/CD pipeline, the root cause may be cultural — siloed teams, poor communication, lack of shared ownership — not a pipeline configuration problem.
• Setting expectations: Promising stakeholders that “we’re adopting DevOps” when you mean “we’re setting up a Jenkins pipeline” sets up a gap between expectation and reality that can undermine confidence in the initiative.

Key Takeaways

• DevOps is a cultural and organisational philosophy that bridges the gap between development and operations to enable faster, higher-quality software delivery.
• CI/CD is a set of engineering practices and automated pipelines — Continuous Integration, Continuous Delivery, and Continuous Deployment — that automate the building, testing, and releasing of software.
• CI/CD is one of the most important technical pillars of a DevOps culture, but the two terms are not synonymous.
• You can implement CI/CD without a full DevOps transformation, but you cannot achieve a true DevOps culture without some form of CI/CD automation.
• The key differentiator among CI, Continuous Delivery, and Continuous Deployment is the degree of automation applied — particularly whether the final production deployment requires human approval.

Testing Is Still in the Dark Ages

The uncomfortable truth in software delivery is that testers, test engineers, and developers spend a disproportionate amount of their working day waiting. Even teams that have adopted continuous integration, continuous testing, and continuous delivery pipelines still contend with systemic inefficiency: too much waste, too much complexity, too many bottlenecks, and too much idle time.

That waiting persists whether a team runs automated pipelines or traditional waterfall processes. Every delivery process has choke points, and the most consistent bottleneck in software delivery is testing.

Software testing became a formal discipline in the 1990s. Despite decades of advances in automation, tooling, and practitioner skills, the fundamental approach has changed surprisingly little. The application under test remains largely a black box. Testers rarely get meaningful visibility into how code is executed at runtime, so they compensate by casting the widest possible testing net — hoping to catch defects through sheer coverage breadth.

The problem with a broad net is twofold:

• The holes are often too large — defects escape.
• The net is sometimes aimed in the wrong direction — tests validate code paths that haven’t changed while genuinely risky areas go untested.

Teams compensate by growing their test suites and automating more. But automation has a ceiling. Once the cost and effort of maintaining tests outweighs the value those tests deliver, further automation becomes its own form of waste. At that point, the principle of less is more — running fewer, better-targeted tests — becomes more effective than adding more test cases.

Consider this: a large proportion of the tests run in any given iteration cover code paths that haven’t changed in that build cycle. Those test runs produce no new information. Meanwhile, genuinely risky, recently changed, or poorly covered code paths may receive inadequate attention. The result is applications that reach production carrying hidden quality risks.

How AI Can Illuminate Testing

Artificial intelligence is broadly defined as the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.

AI performs best when it has large volumes of data to analyse, pattern-match, and draw inferences from. Software testing generates exactly that kind of data at scale. Modern applications can comprise millions of lines of code and thousands of associated test cases. The sheer volume makes human analysis impractical — no team can manually reason about which tests to prioritise across a codebase of that size for every build.

AI and quality analytics address this by instrumenting the application under test and observing how code is actually executed. By gathering millions of data points across test interactions — tracking which lines of code each test exercises and what behaviour it validates — an AI system can:

• Identify untested or under-tested code paths (test gap analysis).
• Correlate specific code changes to the tests most likely to detect regressions in those changes.
• Produce prioritised recommendations for where to invest new test effort.
• Surface actionable quality analytics in seconds, rather than requiring manual review of coverage reports.

In short, AI shifts testing from trawling with a broad net to targeted spearfishing: fewer tests, better aimed, with a higher probability of finding real defects.

Reducing Quality Risks Through AI

Even in mature Continuous Delivery pipelines, applications typically pass through multiple test stages — unit, integration, system, and user acceptance — before reaching production. Most teams rely on static code coverage tools to understand how much of their codebase is tested. However, static coverage metrics tell you whether a line of code was touched during testing, not how well the behaviour of that code was validated across different test stages and real interaction paths.

This gap in understanding creates hidden quality risks. Test suites can show high coverage percentages while still leaving critical logic paths unverified. Defects in those unverified paths escape to production.

AI-driven quality analytics address this by tracking the detailed “footprint” each test leaves across the application at runtime. By processing those footprints at scale, an AI system can:

• Identify the highest-risk areas of the application — code that is complex, frequently changed, or poorly covered.
• Pinpoint specific test gap traps where existing tests provide the illusion of coverage without meaningful validation.
• Guide teams to allocate test investment where it will reduce the most risk, rather than where it is easiest to add tests.

Reducing Test Execution Time Through AI

In a typical regression test cycle, the vast majority of the code being tested has not changed since the previous build. Tests that re-validate unchanged code paths provide no new signal — they consume time and infrastructure without improving confidence in the release.

If AI can identify which code has changed and which tests meaningfully exercise that changed code, teams can run a precisely targeted subset of their full test suite for each build. Advocates of this approach argue that intelligent test selection could reduce test execution time and commit-to-deploy cycle time significantly, though specific figures will vary by codebase, pipeline, and tooling.

An AI-powered test selection system can factor in multiple signals when composing an optimised test run:

• Change impact: Which tests cover the code paths affected by the current code diff?
• Flakiness: Which tests have an unstable pass/fail history that warrants closer attention?
• Production usage: Which parts of the application are accessed most frequently by real users, making regressions there most damaging?
• Complexity: Which recent changes introduced significant new complexity and therefore carry higher inherent risk?
• Historical failure rates: Which tests have the highest probability of detecting defects and should therefore run first and most often?

This targeted testing model finds defects earlier in the pipeline, tightens the feedback loop between code commit and defect detection, and reduces the cognitive overhead on developers waiting for test results. Faster, more precise feedback also means testers get quicker confirmation when their work uncovers a real problem — a meaningful improvement to day-to-day job satisfaction.

Embracing AI in Your Testing Strategy

Modern applications — particularly microservices architectures — involve millions of lines of code, complex dependency graphs, and thousands of test cases accumulated over years of development. No human team can reason about that volume of information in real time for every build. That is not a criticism of testing professionals; it is simply a scaling problem that manual processes cannot solve.

As business demands push teams toward faster release cadences and shorter cycle times, AI-augmented testing offers a practical path to:

• Maintaining or increasing delivery velocity without proportionally increasing test infrastructure costs.
• Closing coverage gaps that static analysis tools miss.
• Eliminating the repetitive, low-value work that leads to tester burnout.
• Giving developers and testers faster, more actionable feedback.

AI does not replace skilled testers — it removes the drudgery and amplifies their impact by directing effort where it produces the most value. The teams that adopt intelligent quality analytics early will carry less technical debt, ship with greater confidence, and spend more time on the creative and investigative work that testing professionals find most rewarding.

Originally written by Scott Dainty, Head of Enterprise Sales at SeaLights, a Software Quality Intelligence Platform. First published on softwaretestingnews.co.uk (October 2019).

Gone are the days when teams could work on a project for months (or even years) before releasing it to production. Now even two-week cycles are too long due to ever more demanding customer expectations and an always-growing field of competitors.

Organisations today expect to deliver new features to production on a weekly, daily or even hourly basis. This accelerated timeline lets organisations adapt to market shifts and technological changes. It keeps companies on the same pace as their competitors. Most importantly, it enables businesses to continuously deliver value to customers.

There is no question that being better, faster and more reliable is beneficial. But how can businesses achieve that? The short answer is through DevOps.

DevOps saves time by speeding delivery and eliminating lean time

Which phases of the software development life cycle take the most time? The answer, perhaps surprising, is none of them. The most time is wasted not in any one phase, but in between phases. Developers wait for business analysts to give them requirements. Testers wait for developers to finish their code, and developers wait for testers to tell them whether the code works. Both developers and testers wait for system administrators to deploy new releases to different environments. And sysadmins wait for everyone else to tell them why deployments failed. 

The sad truth is that in many companies a significant effort is spent on tasks that do not bring value to the company. Waiting does not bring value, yet many organisations have processes in place with time built in for waiting for another team or colleague to do something. Repeating the same set of manual tests over and over again does not bring value, yet this is a normal practice for many businesses. Handing over deployments to a different department when the team in charge of an application could do it themselves by executing a single command does not bring value, yet there are often separate departments for deployment.

DevOps enables seamless collaboration between teams

Who is in charge of a product? The answer is usually “no one in particular”. Everyone is in charge of a particular aspect or phase of the development life cycle, but no one is in charge of a product from beginning to end. And to make things even more complicated, employees often focus solely on their assigned roles.

Developers don’t always consider how their work affects testing and deployment, since it’s not their responsibility. They may not even know how their applications are tested or deployed. The same can be said for all other departments. Sysadmins likely do not consider how much time others spend opening Jira tickets in order to deploy something. No one team considers the complete life cycle of an application, because responsibility is split among too many silos. There is a lack of empathy. Communication between teams is limited and one team does not understand how their actions affect another.

DevOps addresses the disconnect between teams by building empathy between all those involved in an application’s life cycle. The practice unites distinct teams into a single team that responds to a single product owner. It dismantles silos by creating self-sufficient teams fully in charge of everything related to their application from start to finish. Such teams are in charge of requirements, development, testing, deployment to production, and even monitoring and pager duty. They are in full control of what’s happening with their application.

As a result, there is nothing to be handed over to other teams or silos. There is no need for inefficient handovers in the form of Jira tickets, emails or other administrative hurdles. DevOps is all about cultural changes aimed at creating autonomous and self-sufficient teams in charge of the entire life cycle of one or more applications. Therefore, creation of “DevOps departments” and employment of “DevOps engineers” completely misunderstands what DevOps tries to accomplish.

DevOps is not about creating more silos, nor it is about renaming existing departments as “DevOps departments”. Instead, it’s about people working together to accomplish a common goal: successful release of new features to production.

When everyone works as a single team focused on a single product, communication improves, the need for administrative overhead decreases and ownership is established. Working together and understanding how one department’s actions affect others create empathy. As a result, productivity and quality increase, and costs and time to market decrease. 

Eliminating lean time and automating repetitive processes inevitably increases the time teams have at their disposal. Saved time combined with better cooperation between those involved in application life cycles allows teams to focus entirely on actions that bring value by dedicating precious time and effort to solving problems and innovating.

For real innovation to happen, everyone in the company needs to be involved. Elimination of wasted time and resources, improved collaboration and decentralised innovation are the three key ingredients that allow organisations to focus on what really matters. They allow businesses to move from trying to catch up with competitors to being able to innovatively tackle today and tomorrow’s challenges.

Interested in hearing industry leaders discuss subjects like this and sharing their experiences and use-cases? Attend the Cyber Security & Cloud Expo World Series with upcoming events in Silicon Valley, London and Amsterdam to learn more.

CloudBees Doubles Down on Enterprise Continuous Delivery

At the DevOps World | Jenkins World 2019 conference, CloudBees announced a significant update to its continuous delivery (CD) platform, originally acquired through its purchase of Electric Cloud. The rebranded product, now called CloudBees Flow, represents the company’s continued investment in enterprise-grade application release orchestration (ARO) — and signals an ambition to own the “last mile” of the DevOps pipeline.

CloudBees CEO Sacha Labourey framed the release as a direct response to a persistent gap in enterprise DevOps maturity: while SaaS-native companies have refined their delivery processes over years, most traditional enterprise IT organizations are still defining — let alone standardizing — their end-to-end DevOps practices.

What’s New in CloudBees Flow 9.1

Version 9.1 of CloudBees Flow introduces several capabilities aimed at improving visibility, control, and compliance across complex release pipelines:

• Release inventory visibility: Teams can now view exactly what is being deployed to a given environment at any point during a release, reducing ambiguity in multi-team delivery scenarios.
• Sub-pipeline insights: Deeper observability into all the sub-pipelines that compose an overall release makes it easier to pinpoint bottlenecks or failures in large, orchestrated workflows.
• Granular pipeline execution controls: More fine-grained controls over release pipeline execution allow teams to pause, approve, or roll back specific stages without affecting the entire pipeline.
• Customizable Release Command Center dashboards: Teams can tailor their operational view to surface the metrics and pipeline states most relevant to their release process.
• Data archiving for compliance: New archiving capabilities make it easier for organizations to meet regulatory requirements by retaining auditable records of release activity.

The ARO Platform and the Last Mile of DevOps

Application release orchestration addresses one of the hardest problems in enterprise DevOps: coordinating deployments across multiple teams, environments, and interdependent applications. While continuous integration (CI) tooling has matured considerably — Jenkins being the dominant example — continuous delivery at enterprise scale remains a significantly harder problem to solve.

Common pain points include ensuring the right infrastructure resources are available for a new release, managing environment drift, handling rollback scenarios, and debugging production deployments. CloudBees Flow is positioned to address these challenges by sitting on top of existing CI/CD pipelines and orchestrating the full release process, not just the build and test stages.

A Roadmap Toward Unified Continuous Delivery

Labourey outlined a longer-term goal: unifying CD processes across multiple platforms under a coherent CloudBees umbrella. The platforms in scope include:

• CloudBees Flow (formerly Electric Flow) — enterprise ARO for complex, multi-tier application releases
• Jenkins — the widely adopted CI/CD automation server
• Jenkins X — a Kubernetes-native CI/CD platform optimized for cloud-native and microservices workloads
• Spinnaker — a multi-cloud continuous delivery platform also optimized for microservices on Kubernetes

Each platform addresses a different segment of the delivery landscape, and unifying them under a common framework is a non-trivial engineering and organizational challenge. However, having a portfolio that spans traditional enterprise applications and modern cloud-native services positions CloudBees to serve organizations at varying stages of their DevOps journey.

CloudBees and the Continuous Delivery Foundation

Earlier in 2019, CloudBees became a founding member of the Continuous Delivery Foundation (CDF), a Linux Foundation project dedicated to fostering best practices, open-source tooling, and vendor-neutral standards around continuous delivery. Other founding members included Google, Netflix, and Capital One. Membership in the CDF positions CloudBees as both a commercial vendor and an active contributor to the broader CD ecosystem — a dual role that can help build credibility with enterprise buyers who are evaluating long-term platform bets.

Why Continuous Delivery Remains Hard for Enterprises

Despite years of investment in DevOps tooling, continuous delivery continues to lag behind continuous integration in enterprise adoption. Several structural challenges account for this:

• Organizational complexity: Enterprise releases often involve dozens of teams, each with their own pipelines, approval gates, and deployment targets.
• Environment heterogeneity: Unlike greenfield cloud-native apps, most enterprise applications span on-premises infrastructure, legacy systems, and cloud environments simultaneously.
• Risk tolerance: Production deployments in regulated industries — financial services, healthcare, government — carry compliance and audit requirements that slow down automated release cadences.
• Toolchain fragmentation: Few enterprises use a single CI/CD toolchain; most have accumulated a patchwork of tools across business units and geographies.

These are precisely the problems that ARO platforms like CloudBees Flow are designed to address — not by replacing existing tooling, but by orchestrating across it.

The Broader DevOps Context

The question for most mature enterprises has shifted. It is no longer whether to adopt DevOps, but which processes, platforms, and standards to standardize on across the organization. As software delivery velocity becomes a direct competitive differentiator, the pressure on engineering and platform teams to get this right has increased substantially. Legacy deployment processes — manual approvals, infrequent releases, siloed change management — simply cannot scale to meet the expectations of modern digital businesses.

CloudBees Flow 9.1, and the broader CloudBees portfolio, reflects a bet that enterprises need a commercial platform layer above open-source CI/CD tools to manage the scale, governance, and cross-team coordination demands of enterprise software delivery. Whether that bet pays off depends heavily on how well CloudBees can deliver on its platform unification roadmap.

Clippy Returns — This Time on a Mac

Clippy, Microsoft’s love-it-or-hate-it virtual assistant that first appeared in the 1990s, has come back to life as a free application for Apple’s macOS. The project was released on GitHub by Devran “Cosmo” Ünal, a senior product engineer at optics company Zeiss Group, and quickly attracted widespread attention from developers and nostalgic users alike.

The revival taps into fond — and not-so-fond — memories of an era when Microsoft dominated the desktop productivity market. The timing is notable: Microsoft has spent recent years successfully repositioning itself around cloud services and subscriptions, reclaiming its place among the world’s most valuable public companies.

What Was Clippy, Exactly?

Clippy — officially named Clippit — was one of several animated characters bundled into Microsoft Office as a feature called the Office Assistant. It debuted in Office 97 for Windows and Office 98 for Mac. Ironically, despite being associated with Windows, Clippy was originally designed on a Mac.

Users could choose from a roster of Office Assistant characters, including:

• Clippit — the smirking anthropomorphic paper clip that became universally known as Clippy
• The Genius — a character resembling Albert Einstein
• A diamond-shaped, multicoloured Office logo character
• An MS-DOS prompt character, created for reviewers — a self-referential Microsoft callback noted by former Microsoft executive Steven Sinofsky

These assistants would pop up contextually inside Microsoft Word, Excel, and other Office programs, offering help — often unsolicited — based on what the user appeared to be doing.

Beloved and Reviled in Equal Measure

Clippy inspired strong reactions. For some users, the assistant felt like a friendly companion during long work sessions. Ünal, the developer behind the macOS port, described a personal connection to the character:

“Without him, I was basically staring at a blank document. He was part of my childhood and my hero when a paper was due for school.”

— Devran “Cosmo” Ünal

Others were far less charitable. The New York Times described Clippy as “annoying to the point of distraction” — a sentiment shared widely enough that Microsoft took action.

In 2001, with the release of Office XP, Microsoft demoted Clippy by turning the Office Assistant off by default. The company went further, launching a website featuring a game where users could shoot Clippy with rubber bands — an unusually self-deprecating move for a major software vendor.

A History of Unofficial Revivals

Despite Microsoft’s decision to retire the character, developers have repeatedly brought Clippy back in unofficial capacities:

• 2013: Clippy was implemented as an embeddable JavaScript library that could be added to websites.
• 2017: A developer in Italy built an open-source Clippy extension for Visual Studio, Microsoft’s software development environment.
• 2019 (earlier): Clippy stickers for Microsoft Teams appeared on GitHub under Microsoft’s own Office Developer account — and were pulled within a single day.
• 2019 (September): Ünal released the macOS application on GitHub, drawing praise from Steven Sinofsky — an Andreessen Horowitz investor and former Microsoft executive who was directly involved in Clippy’s original development — on the Product Hunt forum.

Microsoft’s Official Position

Despite the enduring grassroots interest, Microsoft has consistently declined to officially revive Clippy. When CNBC contacted the company in September 2019, a spokesperson responded with a characteristically dry statement:

“Clippy is flattered by the attention, but has no plans to come out of retirement.”

— Microsoft spokesperson, via CNBC

Nostalgia as a Product Strategy

The Clippy revival exists within a broader cultural moment for tech nostalgia. Console makers like Nintendo, Sega, and Sony have commercially re-released miniaturised versions of classic hardware. Microsoft itself re-released a “classic” version of its IntelliMouse — originally launched in 1996 — in 2018. With 40-plus years of product history, Microsoft has ample material to draw on.

For now, though, Clippy’s return lives in the open-source community rather than in any official Microsoft product. If you want to experience the paper clip’s particular brand of well-meaning interruption on your Mac, Ünal’s project on GitHub is your best option.

Why This Matters for Developers

Beyond the nostalgia angle, Clippy’s recurring resurrections are a useful reminder of enduring UX tensions: proactive, contextual assistance versus user autonomy and focus. The debate Clippy sparked in the late 1990s about when software should intervene versus stay out of the way remains directly relevant to the design of modern AI-driven assistants, IDE integrations, and productivity tools.

The fact that developers keep rebuilding Clippy — independently, for free, in their spare time — says something about how powerfully a piece of interface design can lodge itself in collective memory, for better or worse.

DevOps Has Come a Long Way—and It Is Still Moving

DevOps has moved well past the “interesting experiment” stage. Organisations ranging from internet-native companies like Google, Amazon, and Netflix to traditional enterprises such as General Motors and The Gap have made significant investments in DevOps practices. For most industry observers, the debate has shifted from whether an organisation will adopt DevOps to when—and, crucially, what form that adoption will take.

The original premise was straightforward: remove the wall between development and operations to eliminate bottlenecks in software delivery. That goal has not changed, but the scope, tooling, and cultural expectations around it have expanded dramatically.

Blurring the Line Between Dev and Ops

Gene Kim—researcher, author of The Phoenix Project, former CTO of Tripwire, and organiser of the DevOps Enterprise Summit—describes the current moment as a “dev-ification of ops.” Operations teams are adopting developer practices: version-controlled infrastructure, automated testing, continuous integration pipelines, and peer code review for configuration changes.

Kim is quick to add that the reverse is also true. “There’s also an ops-ification of dev,” he says, pointing to developers taking greater ownership of deployment, monitoring, and production reliability. His broader prediction is striking: “A decade from now, the vocations of development and operations are going to look very similar.”

The practical implication for engineering organisations is that rigid role boundaries—”that’s an ops problem” or “developers don’t touch prod”—become liabilities rather than governance guardrails.

DevOps Is No Longer Just Dev and Ops

When Kim talks about what “DevOps” actually encompasses today, he reaches well beyond two teams. “At first blush, it seems as though the problems are just between dev and ops,” he says, “but test is in there, and you have information security objectives, and the need to protect systems and data. These are top-level concerns of management, and they have become part of the DevOps picture.”

If you want a more honest label for the modern discipline, Kim’s implication is something closer to DevOpsQATestInfoSec. The rise of DevSecOps—embedding security practices directly into the CI/CD pipeline—reflects exactly this expansion. Quality assurance is no longer a gate at the end of a release cycle but a continuous activity woven through every stage of delivery.

Moving Beyond Agile: Optimising the Full Value Stream

“It definitely starts with agile,” Kim says, “but as you get into it, you realise you have to go beyond that to the entire value stream and flow of work and visibility.”

The shift he identifies is companies moving from optimising for cost to optimising for speed. In an environment where most significant business initiatives depend almost entirely on the technology value stream, the ability to deploy frequently and safely is not an engineering concern—it is a strategic one.

“When you have long iterations, your ability to out-experiment your competition is tremendously compromised,” Kim says. At the executive level, the conversation changes from ROI justification to survival: do whatever it takes to stay in—or get into—the game.

Prerequisites for Enterprise DevOps Success

Kim, working alongside researchers including Jez Humble (Thoughtworks), Nigel Kersten (Puppet Labs), and Nicole Forsgren (Chef Software at the time of original reporting), identified three core prerequisites for DevOps to succeed at enterprise scale:

1. High-trust cultural norms. Teams must operate in an environment where psychological safety is real—where failure surfaces quickly because people are not afraid to report it.
2. An architecture that supports testability and deployability. Monolithic, tightly coupled systems resist continuous delivery regardless of how good the tooling is. Architectural choices—microservices, well-defined APIs, independently deployable components—are prerequisite, not optional.
3. A cluster of technical practices. This includes continuous integration, continuous delivery, automated deployment, and proactive production monitoring. None of these practices works well in isolation; they reinforce each other.

The Role of Tooling

DevOps philosophy has always been cautious about over-emphasising tools—the Agile Manifesto explicitly values “individuals and interactions over processes and tools.” But tooling has become unavoidable. Research firm Gartner (as noted in the original source) recognised that the discipline “demands a linked tool chain of technologies to facilitate collaborative change.”

At the time of writing, commonly cited tools in a mature DevOps pipeline included:

• Continuous integration: Jenkins
• Containerisation: Docker
• Version control: Git
• Build management: Apache Maven
• Application performance monitoring: New Relic
• Operational intelligence: Splunk
• Configuration management: Puppet, Ansible, Chef
• Security and compliance: Tripwire

The list continues to grow. Kubernetes has since become central to container orchestration, and GitOps workflows have further blurred the line between version control and deployment. The principle to keep in mind is that tools should serve the value stream, not define it.

The High-Trust Environment: Culture as Infrastructure

Of Kim’s three prerequisites, culture is arguably the hardest to engineer—and the most consequential. He points to the blameless postmortem, a practice borrowed from patient safety and healthcare, as a concrete mechanism for building the kind of trust that DevOps requires.

The online marketplace Etsy became a widely cited example of this approach: by making it explicitly safe to talk about failure, the company found that problems surfaced faster and information spread more widely. The net result was improved system reliability, not increased risk.

“DevOps succeeds in this kind of environment,” Kim says. “It requires a culture that’s less about ‘Did you carry out your orders?’ and more about ‘What did you learn today?’ Messengers are trained, not shot; responsibilities are shared; and new ideas are welcomed.”

For engineering leaders, this translates into concrete policy decisions: how incidents are reviewed, whether on-call burden is distributed fairly, whether post-incident reports are shared across teams, and whether individuals are recognised for surfacing problems rather than penalised for them.

The Shift from Bottom-Up to Top-Down Adoption

Early DevOps transformation was often driven from below—engineers and coders with, as Kim puts it, “the political skills” to pursue risky changes without full management backing. “That requires an admirable level of courage and conviction,” he says. But it also has severe limits: bottom-up change struggles to reshape culture or restructure architecture across an entire enterprise.

Kim noted an encouraging signal at the DevOps Enterprise Summit: a growing number of attendees in management and executive roles. DevOps transformation that starts with leadership buy-in—not just grassroots engineering enthusiasm—has a fundamentally different chance of success because it can address organisational structure, incentive systems, and funding models, not just CI pipelines and deployment scripts.

Community as a Multiplier

Perhaps the most durable development in the DevOps landscape is the emergence of a coherent professional community. The DevOps Enterprise Summit, the State of DevOps Report, and a growing body of practitioner writing have created a shared vocabulary and a mechanism for organisations to learn from each other’s experiences—both successes and failures.

“This is a community of professionals who are actively helping each other,” Kim says. “They are already influencing—and elevating—the state of the practice.”

For any organisation beginning or continuing a DevOps journey, engaging with that community—through conferences, published case studies, open-source project governance, and shared tooling—is itself a strategic advantage. The patterns that work have been documented; the mistakes that cost teams months have been catalogued. The knowledge is available. The question is whether your organisation is structured to use it.

Key Takeaways

• DevOps has expanded well beyond dev and ops to encompass QA, security, and full value-stream visibility.
• The convergence of development and operations roles is ongoing; expect job functions to continue blending.
• Architectural decisions—testability, deployability, loose coupling—are prerequisites for continuous delivery, not afterthoughts.
• Culture (especially psychological safety and blameless postmortems) is as foundational as any tool or process.
• Executive sponsorship dramatically increases the odds of successful enterprise-wide transformation.
• The DevOps practitioner community is a practical resource; the patterns for success are well documented.

CloudBees Brings Feature Flag Management Into Its CI/CD Platform

CloudBees announced on June 11, 2019, that it had acquired Rollout, a feature management company whose platform gives developers and product teams fine-grained control over when specific features become visible to end users. The acquisition extended CloudBees’ continuous integration and continuous delivery (CI/CD) portfolio by addressing one of the last high-risk steps in software delivery: the moment a new feature is actually exposed to production traffic.

Why Feature Flags Matter in a CI/CD Pipeline

Continuous delivery solves the problem of getting code into production quickly, but it does not on its own control when users experience a new capability. Feature flags — sometimes called feature toggles — solve that gap. A flag is a conditional in the codebase that routes traffic to either the old or new code path based on rules defined at runtime, without requiring a redeployment.

This separation of code deployment from feature release has several practical advantages for engineering and product teams:

• Incremental rollouts: Expose a new feature to 1%, 10%, or 50% of users before a full release, limiting blast radius if something goes wrong.
• Instant rollback: Turn a feature off at the flag level without reverting a deployment or executing a hotfix release cycle.
• Production testing: Run A/B experiments or canary tests against real traffic to gather behavioral data before committing to a feature.
• Trunk-based development: Developers merge incomplete features behind a flag, keeping the main branch always releasable.
• Cross-platform control: Flags can govern feature exposure on web, backend services, and mobile clients from a single control plane.

Forrester Research noted in a January 2019 report (AD&D Pros: Stop Guessing And Start Experimenting, Christopher Condo and Bill Seguin) that “getting ideas in front of users faster — ‘continuous discovery’ — is the new normal,” and that feature flags give application development and delivery teams “complete control of when to expose a particular feature to users, allowing administrators to turn it on and off at the flip of a switch.”

What Rollout Brought to the Table

Rollout positioned itself as a developer-first feature management platform with an emphasis on security and ease of integration. Key capabilities included:

• SDK-based feature flag implementation compatible with multiple languages and mobile platforms.
• Targeting rules that let teams segment rollouts by user attributes, geography, account tier, or custom properties.
• Audit trails and governance controls suited to regulated or enterprise environments.
• Instant kill-switch rollback that operates independently of the deployment pipeline.

These capabilities complemented CloudBees’ existing Jenkins-based CI/CD tooling by closing the loop between pipeline automation and controlled feature exposure.

Strategic Rationale for CloudBees

Sacha Labourey, CEO and co-founder of CloudBees, framed the acquisition around risk reduction: “Our goal is to help organizations deliver great, feature-rich software efficiently while minimizing risks associated with the deployment process. The acquisition of Rollout gives CloudBees customers the flexibility to decouple features from software versions.”

Erez Rusovsky, CEO and co-founder of Rollout, joined CloudBees as product director for the Rollout offering. He described the combination as additive: “Feature flags and CI/CD combined help companies truly become continuous and increase the pace of innovation.”

From a market positioning perspective, the deal signaled that end-to-end software delivery management must extend beyond pipeline automation to include runtime feature control. Organizations practicing trunk-based development or pursuing high deployment frequencies need a governance layer that keeps releases safe after the pipeline finishes.

How Feature Flags Fit Into a Modern DevOps Workflow

A typical integration of feature flags into a CI/CD pipeline looks like this:

1. Development: The engineer wraps new functionality in a feature flag. The flag defaults to off, so the code ships without user impact.
2. CI: Automated tests run against both flag states (on and off) to prevent regressions in either code path.
3. CD / Deployment: The artifact is deployed to production with the flag still off. No user-visible change occurs.
4. Controlled release: The product or ops team enables the flag for an internal test group, then expands to a percentage of users, monitoring error rates and business metrics.
5. Full release or rollback: If metrics are healthy, the flag rolls out to 100% and is eventually removed from code. If something breaks, the flag is turned off instantly—no deployment required.

This workflow eliminates the “big-bang” release model, where all users receive an untested change simultaneously, in favor of a controlled drip that surfaces problems early with limited exposure.

Context: CloudBees’ Broader Platform at the Time

At the time of the acquisition, CloudBees described itself as the largest contributor to Jenkins and Jenkins X and a founding member of the Continuous Delivery Foundation (CDF). Its customer base included over 3,500 organizations and more than 50% of the Fortune 500, according to the company’s own figures. The Rollout acquisition was part of a broader strategy to build what CloudBees called a “software delivery management” (SDM) system that covers the full lifecycle from code commit to production feature exposure.

Key Takeaways for DevOps Teams

• Feature flags are a risk management tool as much as a developer productivity tool; they decouple the binary choice of “deploy or don’t deploy.”
• Integrating flag management into a CI/CD platform (rather than bolting it on afterward) enables consistent governance, audit logging, and policy enforcement across the delivery pipeline.
• The acquisition reflected growing industry recognition that deployment frequency alone is not sufficient—controlled feature exposure is the final mile of safe continuous delivery.
• Teams evaluating feature flag platforms should assess SDK coverage for their target platforms (web, mobile, backend), targeting granularity, rollback latency, and integration depth with their existing CI/CD tooling.