devopsy.kinsta.cloud

Author: Mike Vizard

Agile Stacks Extends Reach of DevOps Automation Platform

Agile Stacks this week announced it is extending the reach of its namesake DevOps automation platform to Kubernetes and additional cloud services.

Company CEO John Mathon said that by extending the reach of the company’s platform to include Google Cloud Platform (GCP), Microsoft Azure and Red Hat’s OpenShift distribution of Kubernetes alongside existing support for Amazon Web Services (AWS), Agile Stacks will make it easier for organizations to implement best DevOps practices across hybrid cloud computing environments.

Agile Stacks made the announcement at the HPE Discover 2019 conference. The company counts Hewlett-Packard Enterprise (HPE) among its investors, and at the conference this week, HPE this week outlined how Kubernetes is core to the company’s evolving hybrid cloud computing strategy.

Mathon said the Agile Stacks platform provides a framework for automating the creation of DevOps pipelines across multiple tools and continuous integration/continuous deployment (CI/CD) platforms. In all, there are more than 80 DevOps tools and platforms available in the Agile Stacks Service Catalog, including Kubeflow, Jenkins, GitLab, Spinnaker, Harbor, Minio, Ceph and Portworx.

At the core of the Agile Stacks platform is a SuperHub automation hub, which accelerates software delivery based using a set of custom composable stacks that can be configured by the DevOps team. Each component of a stack is auto-configured to deploy, upgrade, rollback, promote, clone, backup, generate test scripts, perform merges, conduct performance testing, scan for vulnerabilities and execute functional testing.

In effect, Mathon said Agile Stacks is essentially automating the DevOps automation. Organizations that have embraced best DevOps practices tend to rely on multiple tools from different vendors, which inevitably leads to silos of automation that often work at cross purposes. Agile Stacks provides an extensible GitOps framework for integrating all those tools that enable organization to evolve more easily as their DevOps processes mature, added Mathon.

In addition, he said Agile Stacks expects to play a role in making DevOps more generally accessible by reducing the complexity organizations initially encounter when trying to embrace DevOps practices.

As hybrid cloud computing starts to become more commonplace, thanks in part to the rise of Kubernetes, Mathon said DevOps complexity is only likely to increase. Organizations have made it clear they want to leverage multiple clouds alongside their existing on-premises IT environment. Right now, however, the DevOps processes associated with each of those platforms is, at best, fragmented. In addition to making it easier to unify DevOps processes across multiple platforms, Mathon noted Agile Stacks can also enable organizations to keep better track of cloud spending by applying automated cloud tagging via Superhub.

Of course, most organizations are challenged automating the development and delivery of software on a single platform. However, regardless of how far down the path any organization is toward DevOps, the business is moving forward. In many cases, the rise of hybrid cloud computing will finally force many organizations to implement a set of best DevOps process enterprisewide. As part of that process, organizations will look to standardize on a specific set of DevOps tools whenever possible, or at least until developers discover the latest DevOps tool to supplant all others.

— Mike Vizard

June 21, 2019
GitLab Expands Scope of DevOps Ambitions

GitLab, with the release of its 12.0 update, is extending the reach of its namesake continuous integration/continuous delivery (CI/CD) platform to include both cybersecurity professionals and traditional IT operations staff.

John Jeremiah, senior product marketing manager at GitLab, said the goal is to provide organizations with a single CI/CD platform that unifies the management of everything from source code to best DevSecOps processes.

To address that latter requirement, GitLab 12.0 adds a dashboard designed specifically for security personnel along with the ability for cybersecurity teams to approve merge requests and automatically apply patches for vulnerabilities detected. Those capabilities complement existing support for scanning and secrets detection.

New capabilities embedded in the platform for IT Operations professionals include an operations dashboard and an embedded incident management capability that makes it easier to create a coordinated response to a specific event.

GitLab 12.0 also adds support for feature flags to better manage the application delivery process, along with a platform-as-a-service (PaaS) environment to provision and maintain the infrastructure needed for developing and launching an application.

Jeremiah said the new and existing capabilities in GitLab will make it possible for organizations to unify their DevOps tool chains in a way that also enables IT operations teams and cybersecurity professionals to be included in the process.
At the same time, GitLab is making DevOps more accessible by eliminating many of the silos between various tools that have emerged over the years, including, for example, built-in support for feature flagging versus requiring organizations to acquire and maintain a separate tool, he noted.

Because those capabilities are embedded in the platform, organizations will be able to make the cultural shift required to adopt DevOps more easily, he added. IT teams don’t always know what other tools they will need as their DevOps skills mature. With all the tools embedded in GitLab readily available, it becomes easier for organizations to expand their DevOps processes as the organization starts to implement more sophisticated processes, Jeremiah said.

That approach is starting to resonate with the 100,000-plus developers actively using the GitLab platform and more than 2,000 contributors actively contributing code to the underlying open source platform, he added. GitLab in March saw its millionth merge request.

It’s too early to tell how broadly any CI/CD platform might be able to consolidate the DevOps toolchain. Developers are notorious for adopting new tools as they see fit. Internal IT teams, of course, are not always excited to be asked to support yet another tool. The right level of balance between ultimate flexibility and the need for a standard set of processes that can be implemented across multiple application development teams must be determined by each organization.

In the meantime, DevOps processes are starting to expand beyond traditional development team to now include IT operations staff and cybersecurity personnel. The challenge now that they’ve been invited to the proverbial DevOps party is making them feel welcome and appreciated.

— Mike Vizard

June 20, 2019
HPE Extends Hybrid Cloud Computing Strategy

Hewlett-Packard Enterprise (HPE) today advanced its hybrid cloud computing strategy by announcing at its HPE Discover 2019 conference an alliance with Google to embrace Kubernetes in hybrid cloud computing environments and then extending the reach of its software-defined infrastructure for building private clouds to legacy ProLiant servers.

Lauren Whitehouse, director of marketing for the software-defined and cloud group at HPE, said the HPE Composable Cloud now extends beyond new ProLiant servers to include everything from legacy hardware to cloud computing platforms running virtual machines or as bare metal servers optimized for Kubernetes.

To achieve that latter goal, HPE will make it possible to deploy Google Anthos, a previously announced framework for delivering cloud-native computing services across public clouds and on-premises IT environments, on HPE-managed platforms.

HPE is giving customers the option of deploying configuring local servers with virtual machines with either a VMware vSAN storage software or the HPE SimpliVity hyperconverged infrastructure platform. Additionally, customers can choose to deploy Kubernetes on those platforms or run Kubernetes on a bare-metal server. On top of those stacks, HPE also embeds the HPE OneView IT infrastructure management and HPE Composable Fabric networking solution to create what the company calls a composable rack environment.

Finally, HPE announced it will extend the reach of the HPE InfoSight artificial intelligence engine, which it gained for storage environments when it acquired Nimble Storage, to the rest of its data center portfolio.

Whitehouse said that, by extending the reach of its composable computing strategy to include legacy servers, HPE seeks to make it easier to modernize on-premises IT environments within the context of a larger hybrid cloud computing strategy.

One of the primary reasons so many workloads are being deployed in the cloud is because of the inherent flexibility of the IT environment. HPE is investing in higher levels of infrastructure abstractions to enable an equivalent amount of agility to be injected into on-premises IT environments. Those efforts will then make it easier for organizations to extend best DevOps practices across a hybrid cloud computing environment, said Whitehouse. The company is now removing the objection by organizations to have to implement a forklift upgrade across their entire on-premises IT environment to achieve that goal, she added.

It’s not immediately clear who will manage what in this brave new world of hybrid cloud computing. Application developers have been exercising a lot more influence over platforms, while advances in automation appear to be heralding a consolidation of management functions within the local data center. As site reliability engineers, or so-called “super administrators” capable of managing compute, storage and networking infrastructure continue to emerge, the silos around job functions in the enterprise were built are breaking down. In fact, the more organizations embrace DevOps best practices, the faster consolidation of job functions is occurring.

In the meantime, whoever provides the infrastructure that remains in an on-premises IT environment had better be able to enable local IT teams to be just as flexible as any cloud service provider an application developer is likely to encounter.

— Mike Vizard

June 18, 2019
Moogsoft Advances AIOps Workflow

Moogsoft is moving to make it easier to create custom workflows around its AIOps platform while expanding the number of integrations provided to include connectors to New Relic Insights, Microsoft Teams and proxy support for polling integrations with IT platforms Zenoss, Zabbix, vCenter, vSphere, Solarwinds, Spectrum and SevOne.

Gabe Coelho-Kostolny, senior product management and product marketing leader at Moogsoft, said a Workflow Engine that has been added to version 7.2 of the Moogsoft AIOps platform makes it possible to trigger actions such as notifications, ticket creation and other automated tasks within Moogsoft and external systems. Those actions can be employed within incident management workflows ad other automated remediation tools, he said.

Moogsoft has also added tools that make it possible to visualize alert clustering algorithms in real time and, if needed, fine-tune them. That capability is intended to provide IT operations teams with more confidence in the recommendations being generated by the AIOps platform, Coelho-Kostolny said.

Finally, Moogsoft is making available an analytics dashboard dubbed Individual Statistics, which enables managers to drill down from the team level to better understand the workload and key performance indicators of each team member.

Coelho-Kostolny noted there is already a high correlation between organizations that have adopted best DevOps practices and those moving to implement AIOps. The complexity of many DevOps environments is in many cases forcing the AIOps issue because all the alerts being generated creates a level of fatigue among human IT administrators that results in them not being able to keep pace with the overall rate of change, he said. The concern now is no longer so much whether human IT administrators will be replaced by artificial intelligence (AI) as much as it is enabling IT teams to stay on top of all the tasks required. The opportunity now, he said, is to make it easier for organizations that have embraced DevOps to also customize the AIOps platform.

Of course, AIOps platforms presuppose that IT organizations have access to massive amounts of accurate data about the IT environment. Collecting that data often winds up being a bigger challenge than most organizations appreciate. In general, Coelho-Kostolny said it’s clear AIOps platform adoption is reaching a tipping point in the enterprise. Organizations, however, need to be careful distinguishing between what is truly artificial intelligence and what may be simply a rules-based engine that has been added to an existing IT service management (ITSM) platform, Coelho-Kostolny said.

Regardless of the AI path chosen, the ongoing shortage of IT expertise with critical skills means organizations will continue to experiment with AI. The real issue is determining to what degree of confidence IT teams will have in those AI platforms. After all, if the assumptions an AI system is relying on to make a recommendation prove faulty, the potential for harm tends to be a lot greater than any mistake a single human IT administrator might ever make on their own.

— Mike Vizard

June 17, 2019
VMware to Acquire Avi Networks for NetOps Capability

VMware announced it intends to acquire Avi Networks for an undisclosed price as part of an ongoing effort to close the gap between network operations (NetOps) and DevOps.

Once this deal closes, sometime between now and August, VMware plans to add a software-based load balancer, along with a web application firewall (WAF) and a service mesh to its network virtualization software portfolio.

Tom Gillis, senior vice president and general manager for the networking and security business unit at VMware, said the goal is ultimately to make it as simple to deploy applications in an on-premises IT environment as it is on a public cloud by enabling IT organizations to automate the provisioning of network resources exposed via the VMware NSX network virtualization overlay. Avi Networks will extend those capabilities by adding a high-performance programmable load balancer, which eliminates reliance on legacy load balancers based on proprietary hardware platforms that are both expensive and rigid.

Gillis said VMware will then infuse the WAF technology developed by Avi Networks into its network overlay platform to further secure east-west traffic in the data center.

Finally, VMware intends to marry the service mesh technology from Avi Networks that supports a high-performance ingress controller with its ongoing efforts to integrate the open source Istio service mesh with NSX.

Once all that work is completed, Gillis said it should be possible to deploy a workload on any platform with a single click. The challenge organizations face today is that provisioning and securing the network resources required to deploy an application outside of a public cloud computing environment still takes multiple days to sometimes weeks. VMware has already signaled its intention to make NSX network overlays available across multiple clouds and on-premises IT environments.

Avi Networks CEO Amit Pandey noted that both companies are on a similar trajectory to leverage x86 processors to eliminate reliance on proprietary networking hardware. That shift to software-based networks and security services is driving the biggest transformation in the data center in the last 25 years.

In terms of leveraging application programming interfaces to automate the provisioning of networks, it’s clear networking technologies have been lagging behind advances made in both compute and storage infrastructure. The challenge and the opportunity vendors such as VMware now see is the ability to more holistically manage IT environments spanning from the network to the application. As part of that strategy, VMware has been making a string of acquisitions to extend its core virtual machine franchise.

It’s still too early to say whether all those investments will pay off for VMware. Reliance on VMware technologies in public clouds is relatively slight compared to the dominance VMware has today in on-premises IT environments. VMware is banking that its ability to extend the reach of its portfolio to foster the development of hybrid cloud computing, which is strongly anchored around on-premise IT environments that still run the majority of the workloads in the enterprise, will prevail.

— Mike Vizard

June 13, 2019
RDX Eases Oracle Database Migration to PostgreSQL on AWS

RDX this week launched a set of tools designed to make it easier to convert applications running on an Oracle database to Amazon Aurora, an instance of an open source PostgreSQL database running on the Amazon Web Service (AWS) cloud that is compatible with Oracle databases.

Announced at the AWS Summit event in Washington D.C., the clckwrk Refactoring Service for Oracle promises to reduce the amount of manual effort associated with refactoring applications for the Amazon Aurora platform by automating as much as 60% of the database schema conversion process.

James Ball, chief strategy officer for RDX, said in addition to reducing costs, many organizations want to shift applications to open source databases in the cloud to further their DevOps ambitions. Each time an application needs to scale, an organization will incur additional Oracle licensing fees. In contrast, an open source database enables DevOps teams to scale database instances as required automatically, he said.

AWS has been making a concerted effort to convince customers to give up proprietary databases in favor of open source databases running on its cloud platform. That competitive pressure is a driving force behind new alliances that previously would have been considered unimaginable. Oracle, for example, recently partnered with Microsoft to promote the integration of the Oracle Cloud platform with the Microsoft Azure cloud. Oracle would prefer its database run on its cloud, but through the alliance is signaling its willingness to work with Microsoft to deploy Oracle database on Azure, a cloud platform that is the leading industry alternative to AWS. Microsoft, of course, has its proprietary database to adopt in the form of Microsoft SQL Server.

Ball said RDX not only provides tools to accelerate the conversion to Amazon Aurora, but it also provides managed services for customers that want to outsource the management of Amazon Aurora to RDX.

It takes most organizations several months to migrate a legacy application on to a public cloud. AWS has a vested interested in helping accelerate that process whenever possible. But many organizations that have embraced best DevOps practices find their efforts are hampered by reliance on proprietary databases. In fact, one of the reasons so many developers tend to favor open source databases is to avoid all the headaches associated with getting approvals for new database licenses.

It’s unclear to what degree the rise of DevOps in the enterprise will ultimately shift database allegiances. Oracle is trying to maintain as much control as possible by making its databases available as a managed service that eliminates some of the purchasing overhead associated with spinning up new instances. However, the cost of an Oracle database license is still buried in the cost of the managed service.

Not every organization is looking to transition away from a proprietary database, but there is now enough momentum around the “open source first” movement to make it worthwhile to build tools that automate the refactoring of legacy databases not just to reduce costs, but also to make IT a lot more agile.

— Mike Vizard

June 13, 2019
Pulumi Advances DevOps on AWS

Pulumi announced the availability of Pulumi Crosswalk for Amazon Web Services (AWS), an open source framework for deploying applications on Amazon Web Services (AWS).

Company CEO Joe Duffy said Pulumi Crosswalk for AWS provides a software-as-a-service (SaaS) application through which DevOps teams can automate the deployment of applications on AWS infrastructure using software development kits (SDKs) from Pulumi. The SDKs are based on programming tools such as JavaScript, Python, TypeScript and Go, which most developers already know how to use. That approach eliminates the need for DevOps teams to learn how to employ YAML files or to acquire tools such as CloudFormation or Terraform to deploy applications on AWS, he said.

Pulumi Crosswalk for AWS also embeds the best DevOps processes recommended by AWS directly within its SaaS tools, including patterns for containers and serverless computing frameworks, Duffy noted.

Pulumi Crosswalk for AWS is available on GitHub. It is designed to be integrated with existing Team and Enterprise Editions of Crosswalk that come with support and training provided by Pulumi.

In addition to AWS, Pulumi Crosswalk supports other cloud platforms, including Microsoft Azure and Google Cloud Platform (GCP). The company also plans to provide support for private clouds and leverage Kubernetes clusters to automate deployments across hybrid cloud computing environments.

Duffy noted that despite all the enthusiasm for DevOps, many IT operations teams have been left behind. While much time and effort has been put into unifying backend cloud services, the operational experience in the cloud still revolves around low-level application programming interfaces (APIs) or specialized tools that are challenging for IT operations teams to employ. That situation often creates a backlog of applications for IT operations to deploy. Crosswalk enables IT operations teams to leverage the skills developers have to deploy applications they approve on AWS, he said.

As cloud computing evolves in the age of DevOps, the relationship between developers and the IT operations team is becoming more nuanced. IT operations teams still need to put guardrails in place, but they can’t afford to be perceived as a bottleneck slowing down the rate at which applications can be deployed in the cloud. The challenge IT operations teams must overcome is finding a way to enable developers to self-service their application deployment requirements as much as possible within a set of policy guidelines defined by the internal IT team. That approach will enable developers and IT operations teams to get out of each other’s way.

It may be a while before IT operations and developers find the right DevOps balance that best suits their organizations. Individual teams within enterprises tend to define their own best practices based on the expertise available within the team. Ideally, those best practices are then shared and implemented as appropriate across the rest of the enterprise.

In the meantime, it will be interesting to see how aggressively cloud service providers embrace tools such as those from Pulumi. Cloud service providers have a vested interest in getting as many workloads deployed in their clouds as quickly as possible. They tend to be a little less enthusiastic about anything that makes it easier to move those workloads anytime a DevOps team sees fit.

— Mike Vizard

June 12, 2019
Akamai Extends Reach to the IoT Edge

Akamai today unveiled a strategic initiative to extend the reach of its global network out to applications deployed on the network edge.

Announced at the Akamai Edge World conference, the Edge Cloud portfolio will consist of a mix of existing, new and forthcoming offerings. In terms of new offerings, Akamai launched IoT Edge Connect, which provides access to the Message Queuing Telemetry Transport (MQTT) protocol that gives internet of things (IoT) applications access to a publish-and-subscribe service. Akamai claims IoT Edge Connect will scale to support hundreds of millions of endpoints and is capable of processing 10 times more messages than other IoT or in-app messaging cloud solutions. Those capabilities not only will optimize data delivery, but also should also reduce the amount of power devices will need to send messages, according to the company.

Scott MacGregor, senior director of engineering at Akamai, said IoT Edge Connect will join Akamai Over The Air (OTA) Updates, an existing service for updating applications using a wireless cellular network, in the Edge Cloud portfolio. Those two offerings will be joined in the future by a key-value store that will make it possible to store data on a local IoT gateway and a tool for running functions on an IoT endpoint, he said.

Akamai intends to provide the same capabilities it makes available to web applications to a new generation of edge computing applications that need access to a global network, MacGregor noted. In some cases, the data those applications need to access will be stored on local gateways. In other cases, the data being accessed will be stored within the network managed by Akamai. DevOps teams tasked with building IoT applications would view the Akamai network as just another platform they need to push code to from whatever continuous integration/continuous deployment (CI/CD) platform they choose to employ, he said.

In general, MacGregor said many organizations underestimate the challenges associated with building and deploying distributed IoT applications at unprecedented levels of scale. IoT applications that span global networks are challenging to build, and the processing occurs at the edge, on local gateways and in the cloud.

Akamai, of course, is not the only provider of a global network looking to entice organizations to leverage their infrastructure to deploy edge computing applications. Everyone from carriers including AT&T and Verizon to cloud service providers such as Amazon Web Services (AWS) and Microsoft are making similar cases. It’s too early even to hypothesize which platform providers might ultimately triumph. Akamai, however, is counting on its relationships with developers to become an edge computing force to be reckoned with, said MacGregor.

Akamai made its mark in the enterprise by providing a global content delivery network (CDN) that web developers leverage to extend the reach of their applications by leveraging cache memory Akamai makes available on a global network. Since then, the company has been extending the service to include a range of security services that isolate web applications from various potential threats. If Akamai has its way, those same services soon will be pervasive across a broad range of edge computing applications.

— Mike Vizard

June 12, 2019
Acquisitions to Fuel Programmable Analytics

Now that Tableau Software has agreed to be acquired by Salesforce and Looker is set to become a part of Google, the rate at which analytics will be embedded within almost every application is about to accelerate.

Tableau today is relied on by more than 86,000 organizations to surface business intelligence via data visualizations created by professional analysts and line of business executives. That user base accounts for why Salesforce is willing to spend $15.7 billion to acquire Tableau.

Competition within the analytics software space, however, has always been fierce. The rise of the cloud has resulted in several analytics startups challenging incumbents for a piece of one of the fastest growing sectors of the enterprise software market. One of those startups is Looker, which created a cloud-based analytics platform that Google is now set to acquire for $2.6 billion.

Google has already signaled its intent to make Looker a part of its expanding Google Cloud Platform (GCP). As such, Google Cloud CEO Thomas Kurian last week noted one of the primary reasons for the Looker acquisition is to add a software-as-a-service (SaaS) offering that will enable developers to embed analytics within their applications by invoking a set of application programming interfaces (APIs) exposed via a cloud service. Today that analytics service runs on GCP alongside the Google BiqQuery data warehouse. Google, however, has also signaled its intent to make Looker available on multiple clouds alongside the rest of its software portfolio.

Tableau, which will continue to operate as an independent arm of Salesforce, is playing catch up in the cloud. Tableau is deployed widely in both on-premises and public cloud computing platforms, including as a managed service provided by Tableau through which the company manages a dedicated instance of its software on behalf of customers. The merger with Salesforce will create an opportunity for Tableau to add a full software-as-a-service (SaaS) application instance to its portfolio that leverages the same infrastructure that Salesforce employs to deliver customer relationship management (CRM), marketing and customer service applications. Salesforce CEO Mark Benioff this week said going forward, Salesforce fully expects analytics generated by Tableau to drive a raft of digital business transformation initiatives.

Most of the analytics that will be embedded within applications will manifest themselves in three forms. The first is embedded software that will be updated continuously as new data is entered in an application. The second is embedded predictive analytics modules that will invoke big data repositories and machine learning algorithms to surface recommendations on how to optimize a business process or customer experience. The third—and more ambitious—goal is an embedded prescriptive analytics capability that automatically optimizes business processes and customer experiences in real time based on events occurring, for example, within an internet of things (IoT) application.

Every provider of analytics capabilities, from traditional Tableau rivals such as Qlik Software and Microsoft to TIBCO Software, IBM, MicroStrategy, SAP, Oracle and host of others, is pursuing all these emerging use cases for programmatic analytics. Most recently, Information Builders revealed it has embraced Docker containers and Kafka messaging platform as a means for achieving that analytics goal.

The arrival of programmable analytics platforms will, of course, make implementing best DevOps practices all the more challenging. It’s hard to think of a business process that will not benefit to some degree from embedded analytics. The challenge DevOps teams will face is embedding and then continuously updating all the analytics modules embedded within the applications they deploy. The good news is that as organizations move to embed analytics everywhere increases, so too does the need to embrace DevOps to manage it all.

— Mike Vizard

June 11, 2019
CloudBees Acquires Rollout for Feature Flagging

CloudBees today announced it would extend the reach of the Jenkins continuous integration/continuous development (CI/CD) platform by acquiring Rollout, a provider of feature flag tool that gets employed to simplify testing of new modules within an application.

Company CEO Sacha Labourey said the acquisition of Rollout would result in a feature flag capability that is more seamlessly integrated with the gates that make up a CI/CD pipeline process. The goal is to make it easier for DevOps teams to apply A/B testing of new application features against a subset of users before deciding to update an entire application environment, he said.

Feature flagging, also known as feature toggling, enables DevOps teams to hide features from certain users at runtime. In effect, this creates multiple branches from the same source code that DevOps teams need to manage. Rather than having to employ a separate tool based on an entirely different user interface, CloudBees is moving to make feature flagging a core capability of its extended toolchain.

In theory, feature flagging should be more widely employed than it is today. Many organizations, however, have found it challenging to incorporate separate feature flagging tools within their DevOps processes. CloudBees is now using some of the money it has raised of late to address that issue.

Feature flagging today is largely confined to testing. However, there may come a day when more organizations will employ feature flagging to make different classes of user experience available to different end users. That approach, in theory, would make it possible to charge different fees for disparate application experiences using the same core application.

In the meantime, the goal is to garner more feedback concerning new capabilities that might be added to an application before the features are made generally available. Developers often spend months developing new features only to discover end users are not employing those capabilities because of some trivial glitch that could have been discovered easily using A/B testing.

There currently is no shortage of options when it comes to tools for implementing feature flagging. Labourey said CloudBees elected to acquire Rollout because the team behind it was deemed to have the best cultural fit with CloudBees. It’s too early to say whether other providers of feature flagging tools will be rolled up into other CI/CD platforms—providers of those platforms can either develop their own feature flagging toolsets or move to absorb a third-party provider either by acquiring them or forming a technology alliance. The depth of the toolchain being provided these days often has as much to do with what CI/CD platform ultimately gets adopted as the core integration and delivery capabilities.

Regardless of the path chosen, it’s apparent that thanks to feature flagging, continuous testing processes will become more sophisticated. That may require some adjustments to existing best DevOps practices, but the days when development teams blindly experiment on end users in the hopes they are building the next killer feature mercifully are coming to an end.

— Mike Vizard

June 11, 2019