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DevOps and Cloud: A Symbiotic Relationship Aimed at Business Success
DevOps and cloud computing are not mutually exclusive, though their relationship has often been uncertain and confusing from a layman’s perspective. While cloud computing relates to technology and services, DevOps is more about processes and process improvement. However, both DevOps and cloud computing are vital in every organization’s journey toward an effective digital transformation.

Cloud-centric DevOps Automation

Cloud computing’s centralized nature enables a standard and centralized platform for DevOps automation. Using a cloud platform resolves issues in centralized software deployment caused by the distributed nature of enterprise systems.

DevOps objectives including continuous integration (CI) and continuous delivery (CD) are supported by most of the private and public cloud service providers. This ensures centralized governance and control, in addition to reducing the costs associated with DevOps automation on-premises. DevOps utilizes orchestration systems that can proactively monitor the cloud data sets and application workloads. End-to-end automation is a prerequisite for deriving the full advantage from the cloud.

By expanding the concept of continuous improvement to cloud-based platforms, DevOps ensures lesser system vulnerabilities and greater security.

DevOps Best Practices for Effective Cloud-Based Computing

DevOps provides several core capabilities that assist organizations in effectively handling cloud challenges. These include:
- Infrastructure as Code (IAC): IAC comprises the provisioning of servers and installation of application code, the core components of the system architecture.
- Automated Application Deployments: DevOps practices facilitate the creation of a fully automated application deployment pipeline that is of great importance in the development life cycle.
- Application Lifecycle Management (ALM): DevOps principles such as continuous integration and delivery help in effective ALM in the cloud.
- Continuous Quality Assurance (QA) and Testing: DevOps capabilities address the challenges for QA and testing in the cloud by provisioning multiple test environments using cloud-based resources that result in enhanced quality and productivity.
- Knowledge-Sharing with the Cloud Provider: DevOps promotes the concept of knowledge sharing between organizations and SMEs of the cloud service providers throughout the application life cycle using online communities that are focused on fostering communication and collaboration, thereby ensuring that most risks are mitigated effectively.
The Significance of Cloud Computing vis-á-vis DevOps

Cloud computing complements DevOps in several ways. The application-specific infrastructure in the cloud enables developers to own more components easily and enhance their productivity and efficiency. It allows developers to create the development environments quickly without the need for IT operations to provision resources and infrastructure.

Cloud computing ensures flexible IT infrastructure in addition to enabling greater business agility. It propels IT transformation by helping organizations in streamlining and embedding DevOps processes.

DevOps tools and services eliminate human error and help in establishing repeatability by automating and streamlining the process of building and managing code.

IT Transformation Enabled by DevOps with Cloud Technology

Cloud computing coupled with DevOps ensures that scalability becomes an integral part of application development, thereby contributing to reduced infrastructure costs and increased global reach.

Cloud-based operations increase the availability and failover ability of applications in addition to eliminating downtime, which leads to improved business reliability and rise in customer satisfaction.

DevOps automation and IAC help in reducing the complexity of the cloud and improving system maintenance. Additionally, the automated repeatable processes increase security controls. Process streamlining and faster access to the development environments ensure improved product time to market.

In Conclusion

By realizing the importance and prioritizing the usage of DevOps in the cloud, organizations can derive a huge number of potential benefits including enhanced agility and reduced operational costs.

— Veritis
April 5, 2018
VMware Adds Analytics to Automate IT Operations Based on Intent

VMware is moving to make it easier for organizations to automate data centers and public cloud based on its core hypervisor technology by injecting advanced analytics into its VMware vRealize Suite, enabling them to manage IT environments based on intent rather than having to manually manage every process themselves.

At the core of those update is the Capacity Analytics Engine, which is being added to version 6.7 of vRealize Operations. Mahesh Kumar, senior director of product marketing for cloud management at VMware, said the capacity analytics engine makes use of Autoregressive Integrated Moving Average (ARIMA) techniques to forecast future system events based on historical data points that identify a long-term trend of sudden spikes in usage. Armed with that data, vRealize Operations can now provide cost analytics that include advice on ways to adjust application size and reclaim idle resources on either a public cloud or inside a local data center. IT organizations can also run “what if” scenarios, Kumar said.

On top of that capability, VMware is also now adding predictive analytics that enables IT organizations to define a set of intents such as workload balancing to reduce software license cost, prioritize one set of application to maintain a service level agreement (SLA) or make sure certain workloads only run on servers that have been shown to comply with a specific regulation or mandate. Tighter integration between vRealize Operations 6.7 and vRealize Automation 7.4 then can be continuously employed to automate DevOps processes in a closed-loop manner at higher levels of scale without having to add additional headcount, Kumar said.

In addition, the latest version of VRealize Automation includes more than 120 free, curated blueprints and OVF (Open Virtualization Format) files out of the box. VMware has teamed with Bitnami to add 20 new blueprints and 100-plus new OVFs of applications and databases including GitLab, Hadoop, Jenkins and MongoDB to speed application development and deployment. VMware also updated the Custom Form Designer and added multitenancy capabilities.

Finally, VMware vRealize Operations is sporting a new user interface and integrates with VMware Wavefront monitoring software.

Longer term, Kumar said vRealize Operations will be where VMware applies machine learning algorithms to enable artificial intelligence (AI) models to automate the management of VMware environments.

Collectively, Kumar said the VMware vRealize Suite moves IT organizations that have standardized on VMware in both their local data centers and in the public cloud much farther down the DevOps maturity curve. In effect, VMware vRealize Suite creates an “easy button” for managing complex VMware environments spanning multiple clouds, Kumar said.

VMware is also betting that AI models will make it a lot easier for organizations to make a cultural adjustment as the management of compute, storage and networking becomes more unified. It’s not clear how long it will take for those machine learning algorithms to manifest themselves in VMware management software. But it’s clear most IT organizations running VMware soon will need to rethink who is responsible for running what inside an IT operations team.

— Mike Vizard

April 4, 2018
IBM Unfurls Cloud Platform for Building Microservices

IBM has unveiled a new development environment in the cloud designed to make it easier to build microservices.

John Duimovich, IBM CTO for Java, said Microclimate provides a complete framework building applications based on microservices written in Java, Node.js or Swift.

Microclimate runs on an instance of IBM Cloud Private, a private cloud based on Docker containers that is hosted on the IBM public cloud. Once those applications are developed, organizations can either deploy them on-premises or in a public cloud of their choice.

Microclimate makes use of Kubernetes and Docker containers to create and orchestrate the microservices development process, which can quickly become a complex endeavor. Because of the issue, Duimovich said, more organizations will be pushing development of microservices into cloud computing environments that provide access to what amounts to a turnkey application development pipeline.

Duimovich noted it’s possible to more closely mirror the production environment an application will be deployed on using compute resources that can be invoked on demand. Instead of developing an application on a laptop, developers can stress test microservices in the cloud by, for example, engage in “chaos monkey” testing, wherein developers allow a microservice to fail to see how the overall application reroutes requests to other microservices, said Duimovich.

Developers also can engage in A/B testing in a way that would not be economically feasible to engage in when applications are developed on-premises simply because of the amount of additional IT infrastructure that would have to acquired and provisioned, said Duimovich.

The cloud also makes it easier for teams of developers to collaborate on the development of microservices-based applications regardless of geographic location, Duimovich added. Developers may still choose to write code on their local PC, but when it comes time to load it into an application, the Microclimate platform makes it easier for everyone on the team to observe how that microservice behaves within the context of a larger application.

IBM will also make available diagnostics tools to enable developers to more easily discover why their applications might be behaving in a certain way.

While not every application may lend itself to being constructed using microservices, many organizations are now concluding they are simply a better way to develop reliable software. In addition, developers can be given ownership of specific sets of microservices end to end, which not only gives them more control but also makes them accountable for their overall quality. Of course, building applications made up of hundreds of microservices is going to require organization to implement DevOps best practices, which Duimovich said IBM is more than willing to share with customers.

No one knows for sure when most applications running in a production environment will be made mainly of microservices. But given the rate at which they are now being used to develop applications, it’s now only a matter of time before such applications become dominant.

— Mike Vizard

March 30, 2018
Google Unveils Suite of APM Tools

Google today announced that it is making available application performance management (APM) tools based on the same technology it employs to manage its internal IT environment.

Morgan McLean, a product manager at Google, said Stackdriver APM is based the open source StackDriver Trace and Debugger tools Google originally developed for its DevOps teams.

The APM offering, available in beta, also includes Stackdriver Profiler, a tool Google developed to enable DevOps teams to explore how their code is running in a production environment.

Google also said it has integrated Stackdriver Debugger with GitHub Enterprise and GitLab to extend the number of repositories developers can use to create mirrors of their code.

DevOps teams will have the option of deploying Google APM tools either on-premises or on a public cloud.

McLean noted that rather than throwing additional compute resources at a performance issue, Stackdriver Profile enables DevOps teams to discover and remediate issues and ultimately reduce costs. To minimize the impact of Stackdriver Profile on the performance of a production application, Google opted to employ statistical methods to create a profile of a piece of code. Specifically, Stackdriver Profiler collects data via lightweight sampling-based instrumentation that runs across every instance an application. Data showing CPU time, wall time, RAM used and contention, for example, is then displayed on a flame chart.

At the core of the Google APM toolkit is a the Stackdriver Trace software the company developed to collect latency data about applications deployed in a distributed computing environment. McLean said that in the age of microservices it’s not feasible to managed modern distributed applications without any ability to instrument them. For many IT organizations, however, the cost of acquiring APM software or employing a cloud service has forced them to limit their use of APM technologies to only their most critical applications.

Google is trying to remove cost as significant APM factor, which ultimately will result in the applications deployed on the Google Cloud Platform (GCP) becoming more robust and reliable. The Google APM tools can be applied to applications running on virtual machines and containers, as well as the Google AppEngine, a framework Google exposes on its cloud service to enable the development and hosting of applications. In effect, Google is making it easier for organizations to consume open source tools that IT operations previously would have had to stitch together on their own.

Reliance on APM tools is at the heart of any DevOps process. But DevOps processes are not universally employed, largely because in addition to acquiring new tools, organizations must evolve their processes and culture. The debate many of them have comes down to an argument over whether they need to buy tools before they change those processes or change their processes to justify buying the tools. Most often, it’s the initiative of handful of developers that force the issue. It’s only once that team is successful that senior managers start to think about replicating the DevOps process employed by that team across the rest of the organization. Via Stackdriver APM, Google is clearly hoping to accelerate the rate at which those transition to DevOps occur.

— Mike Vizard

March 28, 2018
Barracuda Networks Survey: DevSecOps Is Hard

Organizations that have adopted DevSecOps processes may be making progress when it comes to improving cybersecurity, but it’s far from easy. A survey of 618 IT decision-makers conducted by Dimensional Research on behalf of Barracuda Networks, a provider of IT security software and appliances, finds half have adopted either DevOps, DevSecOps or a continuous integration/continuous development (CI/CD) platform. A full 93 percent of those IT decision-makers said they faced challenges integrating security into those practices.

Top challenges cited include: Existing security technologies don’t integrate with application development environments (63 percent), application developers are not comfortable with security (48 percent), and security processes have not evolved (48 percent).

Much of the frustration can be tied to reliance on firewalls that don’t feature application programming interfaces (APIs) or are natively integrated with a public cloud, said Tim Jefferson, vice president for public cloud at Barracuda Networks. Each cloud service provider has a unique environment that requires providers of IT security software to write code that natively integrates with that platform. IT organizations can’t simply cut and paste security controls created for on-premises IT environments mainly because the cloud provider has already implemented its own controls at the infrastructure level. The IT organizations need to develop their own controls for the application layer, each of which then must be layered on top of the controls put in place by the cloud service provider.

In the absence of those capabilities, developers get frustrated because a firewall running on a virtual machine on a public cloud presents them with a graphical user interface (GUI) rather than an API. Developers in the age of the cloud are not going to engage with any technology that they can’t programmatically invoke via an API, Jefferson said.

Not surprisingly then, the survey finds the most requested firewall capabilities requested are cloud-native integration (74 percent), ease of deployment and configuration by cloud developers (59 percent), ability to regulate traffic flows between on-premises IT environments and public clouds (56 percent) and distributed policy enforcement (53 percent).

Because many IT professionals don’t have these capabilities many of them conclude on-premises IT environment are more secure than public clouds. More than half the respondents (56 percent) say on-premises cybersecurity is still superior to a public cloud. Clearly, there a lot of technical and emotional factors that go into those assessments, but regardless of the truth, perception remains reality.

Regardless of the approach taken, however, organizations that deploy firewalls in the cloud are expecting to pay for those services on a consumption basis, which doesn’t always align with taking a firewall running on virtual machine and then deploying it on a public cloud.

Jefferson said that as cybersecurity in the age of the cloud continues to mature, expectations are rising regarding the capabilities a firewall should be able to provide—especially when it comes to controlling the flow of traffic coming into and out of a public cloud.

Obviously, anything to do with DevSecOps these days is still evolving. But whatever the cybersecurity future holds the relationship between on-premises and cloud security is far more nuanced than many appreciate.

— Mike Vizard

March 22, 2018
Salesforce Details Integration Plan Post-MuleSoft Acquisition

Salesforce this week announced it will plunk down $6.5 billion to acquire MuleSoft, a provider of application integration software currently used by more than 1,200 organizations. Once the deal is complete, MuleSoft will continue to operate as a unit of Salesforce with current MuleSoft Greg Schott continuing as CEO.

However, there will be two integration platforms once the merger is completed: MuleSoft will continue to offer its Anypoint platform that can be deployed on-premises or accessed as a service, while Salesforce plans to unfurl a separate Salesforce Integration Cloud based on the Anypoint platform.

Schott said the merger will accelerate digital transformation projects that in many cases are hampered by developers writing custom point-to-point code at a cost of more than $400 billion a year. By relying on an integration platform, he said, organizations will be able to take advantage of an application network to unlock the value of data locked in legacy systems faster using a standard set of application programming interfaces (APIs) than they would if the two companies had simply decided to form a technology alliance.

The reason for two separate integration platforms comes down to how different customers engage with MuleSoft and Salesforce, he said. The two companies have a roughly 60 percent customer overlap. That means a significant portion of the MuleSoft base is not integrating applications involving software-as-a-service (SaaS) applications from Salesforce. The Salesforce Integration Cloud will be targeted specifically at customers that are, for example, making use of Salesforce Lightning low-code application development tools to create applications that extend the core capabilities of the Salesforce application portfolio.

In addition, MuleSoft provides a complementary capability to the Heroku platform-as-a-service (PaaS) environment that Salesforce already owns.

Salesforce estimates moving into the application integration space will increase the size of its available market by more than $20 billion through 2022. But the company acknowledged that MuleSoft has as of late been operating at a minimal loss—its sales grew 58 percent last year to $297 million, but that’s a fraction of the total available market. Salesforce is betting that its sales staff combined with an ecosystem of partners will be able to drive the revenue MuleSoft currently generates higher by several orders of magnitude.

However, competition across the application integration category is fierce. Not only is there no shortage of options, but many developers often prefer to write custom code than incur the cost of employing an integration platform. As digital business transformation projects accelerate, Salesforce is essentially arguing that the pace of integration required will make it impractical for developers to continue writing custom code. The rise of microservices also creates a requirement for integration at a level of scale that is difficult to keep pace with when employing custom code.

The degree to which digital transformation coupled with microservices will transform application integration remains to be seen. But it is apparent that the need to integrate disparate sets of code using a structured set of DevOps processes has never been greater.

— Mike Vizard

March 21, 2018
NATS Messaging Entering Cloud Native Purview

The Cloud Native Computing Foundation (CNCF) has expanded the scope of its purview by adding open source NATS messaging software to an expanding list of technologies it now oversees.

NATS messaging software has been commonly employed in environments such as platform-as-a-service (PaaS) environments. But with the rise of microservices, a campaign to make NATS a part of the portfolio of technologies that members of CNCF consortium will advance has begun in earnest, said Derek Collison, who lead the development of NATS and is now CEO of Synadia Communications, which is dedicated to enabling organizations to more easily deploy and manage messaging systems based on NATS.

The ultimate goal, Collison said, is to not only make messaging ubiquitous, but also effectively invisible.

Collison said he and the CNCF envision a world where messaging just comes baked into every application. PaaS environments may have driven mainstream adoption of NATS messaging to integrate various elements of an application, but microservices will make messaging a fundamental requirement for building applications that can efficiently scale, he said, adding too many organizations already run into these issues because they are depending on HTTP to integrate various microservices.

NATS is already widely employed by a number of vendors and organizations including Apcera, Apporeto, Baidu, Bridgevine, Capital One, Clarifai, Cloud Foundry, Comcast, Ericsson, Faber, Fission, General Electric, Greta, HTC, Logimethods, Netlify, Pex, Pivotal, Platform9, Rapidloop, Samsung, Sendify, Sensay, StorageOS, VMware Acadiant, Weaveworks and Workiva.

The core NATS server and NAT Streaming software are maintained by Synadia. There are clients for Python, Ruby, Node.js, Elixir, Java, NGINX, C and C#, as well as third-party contributions that add support for Arduino, Rust, Lua, PHP, Perl and others.

Longer term, Collison sees NATS evolving to include functionality to support real-time applications, many of which today are using Apache Kafka software. Rather than having to deploy NATS and Kafka for different use cases, Collison said it will make more sense to have a common control plane to address multiple classes of use cases for messaging.

Messaging systems in one form or another have been at the heart of integration platforms for decades now. But the assumption was always that integration would be addressed after the applications were deployed. In the future, the assumption is that all cloud-native applications need to be integrated, which is much easier to accomplish if they all come with some form of messaging capability baked in. Integrating and managing federated instances of messaging systems still will be required. But much of the lower-level functions now being centrally processed will be pushed out into the applications being integrated.

Collison is the first to admit that messaging is not some new, emerging technology. But as microservices architectures continue, messaging will prove to be core to a new generation of cloud-native applications, he said. The CNCF is clearly betting that a consortium of vendors working on a common code base for messaging will accomplish that goal a whole lot sooner.

— Mike Vizard

March 16, 2018
OpsRamp Looks to Fuel IT Operations Consolidation

One of the biggest challenges associated with DevOps is cutting through all the various platforms and applications alerts to make sense of what’s occurring in an IT environment, much less manage it. In fact, there’s been a pressing need of consolidate management tools for IT operations for quite some time now.

OpsRamp is now making just that case with the unfurling of Unified Service Intelligence, a set of integrated IT management applications that are all delivered using a software-as-a-service (SaaS) model that makes it possible to unify multiple dashboards.

Deepak Jannu, director of marketing for OpsRamp, said that although there are more application programming interfaces (APIs) being exposed than ever, it’s still too difficult for IT operations teams to correlate data in a way that creates meaningful actionable intelligence. For the most part, IT operations teams are still swiveling between different consoles in the hopes that some insight will magically make itself apparent, he said.

To make it easier to separate the signal from the noise, Unified Service Intelligence combines discovery and monitoring health dashboards with incident management capabilities in single application layered with hundreds of best-practice monitoring templates to simplify IT administration.

Jannu noted many IT organizations struggle when transitioning to DevOps because they are confronted with a classic chicken-and-egg challenge. Most of them rely on legacy tools that are not integrated. Trying to modernize IT operations processes is simply too difficult without the right set of tools in place. The only way to make modern tools affordable for most organizations is to deliver them as a set of SaaS applications, he said.

As IT organizations find themselves embracing multiple clouds as well as emerging technologies such as containers, Jannu noted it’s now only a matter of time before IT operations reaches a breaking point inside most organizations. It was difficult enough trying to navigate different dashboards for IT infrastructure and applications running on-premises. The cloud, in most cases, just adds another series of platforms to an already-inflexible mix of isolated processes, he said.

Just as significantly, he added, an integrated platform also is key to cutting down IT operations fatigue. Most IT operations teams don’t discover critical issues early enough because it’s simply too difficult to understand what an “alert storm” being generated by disparate management tools signifies. After a while, the IT operations team becomes inured to all the alerts being generated.

Longer term, Jannu said OpsRamp will be better positioned to apply machine and deep learning algorithms to automate IT management than the average IT organization would be by running tools locally on its own. OpsRamp already generates 3 billion records of events a day, all of which can be used to inform artificial intelligence (AI) tools that require access to massive amounts of data to effectively train models. Locally installed IT management tools will never generate the required volume of data required to train an AI model.

It remains to be seen how fast the IT operations management space will consolidate. There are a lot of constituencies inside IT organizations that have a vested interest in one tool or another. That said, the writing on the wall heralding that consolidation already has been inscribed.

— Mike Vizard

March 13, 2018
Datical Helps Pull DBAs into Modern DevOps Age

As organizations move to embrace DevOps, some have inadvertently left database administrators (DBAs) behind. As a result, developers increasingly find themselves managing databases, as DBAs can’t keep up with the rate of change introduced by DevOps processes. To help narrow that growing gap between developers and DBAs, Datical created a namesake platform that applies continuous deployment/continuous integration (CI/CD) processes the management of databases.

An update to the Datical platform now adds real-time views and dashboards that illustrate the status of database deployments. DevOps teams now can simulate the impact of changes before they are deployed in a production environment and enforce rules to meet audit and compliance requirements. A new management tool also makes it easy to track database changes across the pipeline as well.

Pete Pickerill, vice president of product strategy for Datical, said Datical 5 now makes it possible to automatically apply the updated changes to a database without many of the steps that slow down application development on top of databases.

Finally, with this release, Dacital also provides a mechanism for centrally managing all the credentials attached to database.

While agile development methodologies have lead to an increase in the rate at which code is being written, database management continues to act as a drag on the rate at which applications are being deployed and updated. Datical decided to address that problem by creating a platform that specifically applies DevOps processes to the management of databases, said Pickerill.

Organizations that still rely largely on manual database processes often find the level of tension between developers and database administrators to be high. Developers often will simply opt for a database they can manage themselves rather than engage a DBA. That can result in suboptimal choices being made for different classes of application workloads that become apparent once the application starts to scale. The challenge and opportunity is to put tools in the hands of DBAs that enable them to respond rapidly to changing application dynamics, said Pickerill.

Of course, in many instances developers have simply taken over the database administration task. But every minute spent on those tasks is one less minute a developer is writing code. The more efficient option is to find a way to integrate DBAs into the overall DevOps process. The effort requires both providing DBAs with access to new tools as well as changing an IT culture where many DBAs assumed the application development strategy revolved around their ability to find time to manage a database. Today, DBAs are now being asked to manage a multitude of types of databases that are being deployed in unprecedented numbers. Clearly, processes rooted in approaches to database management developed a decade ago or longer no longer suffice.

Not every DBA will make that transition. But at this juncture it’s clear that fundamental change to the way databases are managed is now a matter of when rather than if.

— Mike Vizard

March 12, 2018
Sauce Labs Adds Analytics to Continuous Testing Platform

Sauce Labs has added additional debugging and analytics capabilities to its testing platform to make it easier to manage continuous testing across multiple application development projects.

Lubos Parobek, vice president of product at Sauce Labs, said DevOps teams need to prioritize which bugs to address first across multiple development projects occurring simultaneously. In fact, according to the latest annual survey of 1,091 technology professionals conducted by Dimensional Research on behalf of Sauce Labs, DevOps teams on average are now taking longer to address bugs. These days there are many more issues that require debugging across multiple development projects, which is overwhelming DevOps teams, who must then prioritize some debugging requirements over others.

Specifically, the survey found only 21 percent of respondents report they fix bugs immediately, down from 23 percent in 2017.

Analytics capabilities included in Sauce Labs’ rechristened Continuous Testing Cloud include the ability to view test results by browser and operating system, visibility into pass/fail and error trends and the ability to see how a single test behaves over time so DevOps teams can more easily identify tests inconsistent with overall test run time and pass/fail rates.

Scheduled to be available in the second quarter, the Continuous Testing Cloud makes it possible to more easily reconcile advances in the rate at which applications are being developed and constrained testing and debugging tools, Parobek said.

The Sauce Labs survey results also show progress being made in the realm of mobile application testing. A full 77 percent of respondents said they now use a mix of both real devices and simulators or emulators for mobile testing, up from 34 percent in 2015. That approach results in higher fidelity to the actual experience of an end user on each device, said Parobek.

That shift, however, may also explain why there is more manual testing. More than half (56 percent) said they do as much or more automated as manual testing, a minor decrease from 59 percent (2017) and 60 percent (2016), the report found. Just under half (45 percent) said they do, however, expect to increase spending on test automation in 2018.

Parobek said organizations are moving into what he describes as the third era of testing. The first two eras were manual testing followed by a shift to automated testing. The third era is marked by continuous testing that leverages automation to make it possible to test code as it’s being developed rather than after, when the application is complete.

Naturally, each organization is not as far down the path toward continuous testing as every other. Parobek said for the most part, early adopters of DevOps practices employ continuous testing more widely than traditional enterprise IT organizations that are still in the early stages of embracing DevOps. The good news is the latter have an opportunity to leverage a much larger body of DevOps best practices than the organizations that originally pioneered the concepts.

— Mike Vizard

March 8, 2018