Enterprise DevOps Platform

Pragmatic Approach to Moving From Jenkins Pipelines to DevOps Pipelines

Contemplating moving from a Jenkins pipeline or the Jenkins Blue Ocean pipeline to something completely different? Is your colleague encouraging you to ditch Jenkins? 80% of most development teams have multiple Jenkins and are struggling to find a path forward to an improved model/tool/architecture. Why is that? This blog explains the reason why and how to move forward WITH your Jenkins and how to get to an end-to-end DevOps Pipeline.

The journey from custom scripts to Jenkins, to the Blue Ocean plugin

In the beginning, there were custom scripts, and all was good.  Jenkins was a great start towards Continuous Integration (CI) over the past decade and has been a workhorse for development teams.  Developers could support just about any use paradigm or corner case they wanted.  Jenkins was and is today ubiquitous across teams small to large.  Whether a product or service is a legacy app or a new cloud-native microservice, Jenkins was always there to assist. Whether you were a developer, or in this new role of DevOps, or QA/Test, or you were in charge of deploying code – Continuous Deployment (CD) to production, Jenkins pretty much enabled you to accomplish your automation.  

At some point in time, your process expanded to multiple steps and you integrated a wide variety of different tools.   Jenkins helped you achieve a Jenkins Pipeline. With well over 100,000 instances of Jenkins, there was a large community of developers who you could depend on.  You could even take your skills and drive a mile further down the road and get a job doing similar in slightly nicer digs.

Inevitably Jenkins was so popular everybody wanted one.  And guess what, they got it.  I have heard of some organizations with over 1000 Jenkins instances.  Each one doing exactly what its owner wanted.  Just imagine the potential nightmare of pipelines crossing instances, owners, and teams.   

While building automation with Jenkins pipelines that fit right into your coding-centric point of view, many developers wanted a visual representation of the pipeline.  Blue Ocean was an attempt at that and was born over 5 years ago.

“Blue Ocean is a project that rethinks the user experience of Jenkins, modeling and presenting the process of software delivery by surfacing information that’s important to development teams with as few clicks as possible, while still staying true to the extensibility that is core to Jenkins.” – https://www.jenkins.io/blog/2016/05/26/introducing-blue-ocean/ 

From the Jenkins Blue Ocean plugin to DevOps pipelines

Five and half years later and we still don’t have an easy to use highly functional graphical pipeline in Jenkins.  There are many issues with Jenkins that make an inbuilt graphical pipeline that covers CI/CD a tall task.  Look at this blog from Mark Hornbeek.  The developer, test, and release management communities have moved toward a DevOps pipeline, that supports the major principles of DevOps.  In the multi-year gap across e Blue Ocean, the need developed for a DevOps pipeline with new and improved constructs.   This has led to the rise of other tools to solve for the CI, Continuous Test (CT), and CD.  The rise of ReleaseIQ, CircleCI, Harness, Spinnaker, Atlassian BitBucket, and Bamboo pipelines, GitLab, and Microsoft tooling has begun to fill some of these gaps.  

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Say what?  Yes, you heard me, this is what many shops are hearing (being told).  Start over, get rid of your trusted old friend Jenkins, and rip and replace it with a new tool.  Hey, it only takes 30 days to migrate!  In 30 days your competitors just ate your lunch, four times over.  Who has the time, resources, and opportunity cost to do this?  Did the cloud-native/microservices/K8s triad replace all the existing development paradigms and platforms out there?  You see where this is going.  Over time we can make major changes in architecture and implementation, but it takes time and a pragmatic approach to piecewise migration.  Many hops from rock to rock across the DevOps Pipeline river chasm. 

Rip and replace?

I recently spoke to a Fortune 20 software leader and they were adamant that the best teams just retire the old stuff as quickly as possible.  In my younger days at HP, I whacked the enterprise management toolset from 500 tools to 150.  It took four years and reduced funding/layoffs alchemy to get the “buy-in” to do this.  Rip and replace in the real world doesn’t happen that often.  Ripping off the bandaid can transform an organization in ways that Agile methods can’t really fix. Few organizations can really make wholesale changes in tools because they are inexorably intertwined with both the process and the culture.  

Benefits of modern DevOps pipeline tools

  • Speed – Yes Jenkins is very extensible, with the plugin community you might find a solution, you might not.  When the pipeline moves as fast as the code is changing, many times relying on Jenkins may not give you the speed you need.  Remember, Jenkins was designed for on-premise traditional applications and architectures.  New pipeline automation tools can indeed provide the agility for very fast configuration changes to a new pipeline architecture or tooling.
  • Reduced maintenance – Hands down, Jenkins is notable for its very high maintenance requirements.  This is a great example of free open source software having the hidden aspects of maintainability.  Supporting and maintaining your own infrastructure, Jenkins applications, plug-ins, and other aspects make Jenkins very sticky.  Once you get it working it works well.  Make a change and you will be dealing with issues until you can lock it down again.
  • Plugin sprawl – No doubt about it, pluggable architectures are a key design win for any system.  However, Jenkins takes that pluggability very far.  A typical pipeline can touch a dozen plug-ins.  Like stone balancing, who wants to maintain that, or rely on that when you have a mission-critical hotfix.  Modern pipeline tools reduce the complexity of the installation through native support.
  • Debugging – Visibility when something goes wrong in your pipeline is a must-have.  While all the logs may be present, the modern tools provide greatly increased visibility when the inevitable happens.
  • Notification – Getting notified (Slack or other) when something is amiss is critical in the always-on world.  When you get those Jenkins plugins dialed in that is good.   But what about when you have different tools for CI, vs. CT, vs. CD.  How does that all work together?
  • Built-in analytics and dashboards – Jenkins is an automation framework, obtaining the analytics layer and visualization in Jenkins is hard enough as it is.  Now consider gaining that visualization across multiple tools. 
  • Tribal knowledge and excessive customization – I have bumped into a few shops that had very little idea how their CI pipeline worked or what it actually did.  The people who built that heavily customized solution are long gone.  Sound familiar?
  • High availability and scale-out – It is important that your team own your code, services, and architectures.  On top of that larger installation needs to support increased compute grids with scale-out and HA.  Add even more time to supporting Jenkins at scale.  Modern SaaS tools handle this for you.
  • Manage, coordinate and orchestrate across multiple Jenkins – How many complex applications use just a single Jenkins for CI, running tests, and CD?  In addition, teams typically have different Jenkins for different purposes, one for Dev, one for Production, etc.  Different teams from development, test, and DevOps have different Jenkins.  How can you see across all of this? This is where modern CI tools shine in bridging or orchestrating the gaps and providing the visibility modern teams need.  

Pragmatic approach to moving from Jenkins pipelines to DevOps pipelines  

Back to the original discussion of do you rip and replace your multi-year investment in Jenkins tooling, plugins, infrastructure, and processes running fairly well in your environment?  You may have seen or been exposed to those vendors who ask you to replace that environment with their shiny new automation framework.  Yes, you will get future value, but at what costs the current situation?  

A more practical and pragmatic approach is one where you and your team can get end-to-end DevOps pipelines by overlaying a solution like ReleaseIQ on top of your existing tools.  Take your complete pipeline tooling: Jenkins, CircleCI, Bamboo, Bitbucket Pipelines, Spinnaker, JFrog, and others.   Overlay the ReleaseIQ Automation and Orchestration Platform above that.  Get all the advantages of orchestrating the end-to-end pipeline, with the unified visibility across all the tools, troubleshooting when something goes wrong, you have a normalized set of analytics and dashboards to improve your DevOps practices.  AND THEN, you can decide over time, at the pace you’re comfortable with to change the underlying tooling.  No need for a discontinuity in your pipelines and processes.  

Learn more about the ReleaseIQ Essentials for Jenkins.  If you are building multi-tool DevOps pipelines, check out or Premium Edition capabilities.

Building E2E DevOps Pipelines

This blog describes some of the best practices we have seen over the years in developing, building, testing, and deploying software. Most engineering organizations have at least a basic understanding of the value proposition of a DevOps pipeline. However, engineering leadership may focus too heavily on simplicity, opting to go for the “one stop shop” approach, instead of picking and choosing the best of different tools. I emphasize that engineering teams should be free to pick and choose the best tools for a given use case, rather than going all-in on a one-stop-shop solution.

Release velocity is one of the most crucial metrics to focus on for a high-performing DevOps organization. Companies that can iterate quickly, releasing more features and new products, are more competitive and more successful in their respective markets. Engineering leaders who want to improve their team’s release velocity and overall release quality should pay careful attention to the tools and services being utilized. Empowered DevOps teams choose the tools best suited to support delivering critical workloads. Tools like Jenkins may already be in place to provide a solid CI/CD foundation. Augmenting Jenkins with additional capabilities can still provide a sizable ROI.  Teams that are looking for a place to start should follow the path of the software development lifecycle: going “left to right”.

SDLC DevOps

Planning and Design

At the far left of the SDLC is the planning and design phase. While teams may overlook this in the context of the “pipeline”(think CI/CD), planning and designing is the foundational piece of a finished product or feature.

DevOps is the marriage of development and operations teams, but the planning and design phase is the inflection point where product and engineering teams meet. Feature requests and product requirements transform into living, breathing code. There are still powerful tools and services that automation teams can employ in this phase to improve the overall pipeline. Tools like Trello and Jira help manage ticketing and work items, offering Kanban boards and other Agile tooling. For architecture and system design, services like Draw.io and LucidChart provide a capable set of design tools. Key is the current emphasis on cloud-native and cloud-first architecture.  Improved planning and design will lead to better requirements, which are the primary inputs into the next phase of the pipeline.

Committing Code and Testing

When development teams start writing code is where the “rubber meets the road”. The requirements and feature requests that were developed during the planning and design phase start to take rough shape. The overall software quality, and critically, security, are heavily influenced by the quality of work in this phase. Untested, inefficient, and insecure code will lead to a “garbage in, garbage out” scenario: production environments will be more susceptible to outages and compromise, regardless of operational tooling and monitoring.

At a minimum, development teams should use some form of version control system(VCS). Version control provides a centralized repository that tracks changes and authorship for code. A VCS like Git or Subversion enables teams of developers to contribute to the same codebase in parallel, contributing changes without impacting or overwriting prior or ongoing work. A version control-enabled codebase is so critical to modern DevOps workflows that it seems almost redundant to mention. There are still organizations that do not make use of it. It’s not surprising that “Codebase ” is the first principle listed in the Twelve-Factor App philosophy.

Before committing code to a VCS like Git, the tooling team should provide developers with the tools to help enforce and guide coding standards. A VCS is simply a repository of code, good or bad. Simple workflows are enabled at the individual developer level that will improve the overall quality of organizational application code. Most integrated development environments(IDE) like VSCode and PyCharm include linters. These linters are specialized tools that highlight basic logic and syntax errors in the code, and in some cases can suggest and correct fixes. Pre-commit hooks can also be utilized. These simple scripts and automation perform further linting and testing around code and code quality prior to submission for review.

In the course of software development, more comprehensive, in-depth tooling is typically required to fully test code for functionality, potential bugs, and susceptibility to security issues and compromise. Static analysis tools can analyze and evaluate code without requiring it to be running as a live application. Tools like SonarQube can be integrated into the developer IDE, or deployed as part of a CI/CD pipeline with tools like Jenkins.

Code written in languages like Java or C++ is compiled into a binary before being integrated and deployed into live environments. In legacy environments, software was often compiled on individual developer machines before being uploaded. In larger, modern environments that model no longer scales. A centralized build system provides homogenous configuration and ensures build artifacts adhere to standards before being pushed into a CI/CD pipeline. Build tools like Maven, Gradle, and Bower are popular choices, and integrate well with most CI/CD infrastructure.

Integration and Deployment

Once a feature or application is finished, the completed build artifact is then integrated and deployed to the live environment. Once it reaches production, the “value” is realized. Value realization is a result of customer interaction with the new feature or service. Consequently, it is critically important to make sure that production workloads are tested, deployed, and monitored with the right tooling.

The core piece of infrastructure for integration and deployment is the Continuous Integration/Continuous Delivery(CI/CD) pipeline. Replacing legacy software deployment methods like FTP, CI/CD pipelines provide a holistic automation platform, encompassing build/compilation, testing, integration, and deployment in a single interface. CI/CD pipelines form the backbone of almost any environment that adheres to DevOps principles. There is a broad selection of CI/CD software available: SaaS tools like TravisCI, CircleCI, and AWS CodeDeploy, as well as self-hosted solutions like Jenkins and Spinnaker. Container solutions like Docker and Kubernetes can provide immutable build artifacts, further enhancing the functionality of CI/CD architecture.

CI/CD pipeline capabilities extend beyond software deployment; the underlying infrastructure can be defined and deployed using code as well. Tools like Ansible, Chef, and Puppet enable DevOps engineers to define the configuration of applications and services in code, automatically applying them during deployments, and maintaining minimal configuration drift. For infrastructure, tools like Terraform, Cloudformation, and recently Pulumi can be employed to define and control the provisioning of resources like compute nodes, databases, and even entire networking zones. Teams that integrate configuration management and infrastructure-as-code tools in their CI/CD workflows have end-to-end deployment and release automation systems, which allow for faster iteration and feature delivery.

Once production workloads are live, choosing robust operational tooling is key to ensure that the customer experience remains positive and that any issue or performance degradation provides immediate, actionable feedback. The modern ecosystem of highly available, highly performant customer-facing applications has given rise to a landscape of cloud and web-focused monitoring and operational services. Tools like DataDog, AppDynamics, and New Relic can provide a granular look into the health of application infrastructure. Log aggregation and searching platforms like Elasticsearch enables critical application data to be found from the vast sea of information generated by modern applications.

Utilize Diverse Tooling to Build a Robust DevOps Pipeline

The modern DevOps landscape offers engineering teams a broad selection of tools at every stage of the SDLC. Rather than going all-in on one vendor or toolchain, teams should be empowered to pick and choose the best functioning and best fitting tool or service for their use case.

Each step in the SDLC is important, even before the first line of code is written, thus the importance placed upon picking the best tools at each stage. Once teams have settled on their pipeline tooling, the next key focus should be a unified way to manage and monitor the complexity of a diverse toolchain.

Learn more about Enterprise DevOps platforms with this white paper.

DevOps Maturity (How to measure and improve it)

This post will discuss the different levels of DevOps maturity and measurement using DORA Metrics and recommendations on how to improve your DevOps practices.  Through careful analysis of your DORA metrics you can accelerate your practice.

As a methodology, DevOps is not a step-by-step guide for building an application or website but rather a way of thinking about the entire lifecycle from development through deployment. The main objective behind developing the software is to deploy frequently, with very little human intervention. Maintaining and improving code quality and high reliability is also top of mind.

DevOps maturity is a measure of how well a team is performing according to the three ways of DevOps. Maturity in this context refers to the level of automation, the ability to deploy frequently and reliably, and how well a team is working together.

DevOps Maturity Levels

The DORA DevOps Maturity Model defines four levels: Low, Medium, High, and Elite. The teams performing at an Elite level are twice as likely to meet or even exceed performance goals within their organization.

The following Figure summarizes the different levels.

Dora Metrics - DevOps

Low – Manual everything

There are no automated processes at this stage; all work must be done manually by developers and operations staff alike. Deployments require significant coordination between teams which leads to bottlenecks. Examples of that are when one team holds up another for lack of resources or knowledge necessary for their tasks

In addition, deployments are slow because every change must be carefully reviewed before being released into production. This typically can mean that multiple people at different stages in the pipeline. Deploying changes will take time since it cannot happen quickly without sacrificing quality control. The releases often break due to human error during manual testing or missing a critical step when deploying new code into production.

Medium – Scripted everything

With scripted tools such as Chef or Puppet, configuration management becomes automated so the servers can be configured automatically. Subsequent provisioning can be by automated tools like Ansible or SaltStack or Terraform. While this reduces errors caused by manual configuration changes, it does not eliminate them. Mistakes can still be made in other areas of responsibility.

In addition, many elements of the application and infrastructure may still be tested manually once live. Deployments are still slow, with test results and approval from other teams before deploying new code into production delaying the progress.

High – Automated everything

With automated deployment tools such as Jenkins, Capistrano, or Chef Server, deployments can be fully automated so that changes can be released into production without any human intervention. This reduces human error in deployments but does not eliminate it entirely since there are still many things that could go wrong even if the deployment is fully automated. For example, a bug in the code itself could cause a deployment to fail, or a change could have unintended consequences failed to be discovered during testing.

Elite – Continuous everything

Continuous deployments require continuous integration (CI) and continuous delivery (CD), as well as automated testing. However, every change must be deployed into production automatically with no human intervention.

This also means all tests must pass before any changes are deployed into production. The process of deploying new code into production must be fully automated, without direct oversight and without sacrificing quality control. At a minimum, manual tests and approvals should be part of the release flow, triggered and tracked automatically.

To achieve this level of automation, you need to have a highly mature DevOps culture, with everyone onboard, focussing on the team’s success.

Once you achieve this level of maturity, deployments become fast and friction-free because they do not require human intervention or availability. Finally, deployments also become more reliable as they undergo thorough and reproducible automated testing before being released into production.

Leveling Up – DORA Metrics

To understand your team or organization’s maturity level, you need to measure performance against four key DORA metrics, the results of which will offer clear insight into the area of improvement in each stage. This will be reflected in the overall performance across the entire software lifecycle.

Release Frequency – How often do we deploy?

The goal of DevOps is to be able to deploy changes into production frequently and reliably. This can be measured by the number of deployments per month or year, as well as the time it takes for each deployment to go from code committed to production. The more frequent deployments are, the better since problems can be found and fixed quickly. This reduces risk and allows teams to respond faster when issues arise in production instead of waiting until a new release is ready before addressing a problem. In addition, if releases and new features take too long, you may lose users and customer interest in your product.

Deployment Velocity – How quickly do we deploy?

To measure the frequency of deployments, you also need to measure how quickly each deployment takes from start to finish. This includes how long it takes for a developer to write code and push it into version control and how long it takes for that code to be tested by a tester and then deployed into production. If releases take too long, end-users will lose interest in your product.

Release Stability – How reliable are our releases?

While automated deployments reduce human error during the release process, there is still risk involved with any changes deployed into production. This can be measured by tracking incidents related to releases which could include anything from a minor bug report to an outage caused by a bad deployment. The fewer incidents, the better since your deployments are more reliable and less likely to cause problems for your users or customers.

Recovery Speed – How quickly can we recover from a failure?

It is true that automated deployment reduces human errors during the release, there is always a slight risk involved with any changes deployed into production. This risk can be measured by how quickly you can recover from a failure in production. The faster you can recover, the better for your product.

These four key DORA metrics are helpful for measuring performance across each stage of the DevOps lifecycle. They also provide insight into where improvements need to be made across each stage to improve overall performance across the entire lifecycle. For example, if your team is having trouble releasing new features quickly enough, it may be because releases take too long and/or require too much manual intervention before being deployed into production. If so, improving your deployment velocity should be a priority for your team. On the other hand, if problems are found in production after every release, then recovery speed should be a priority instead since these issues could cause significant damage to your company’s reputation or bottom line if they are not addressed quickly enough.

Summary

DevOps is a set of practices that enables teams to move faster and deliver higher quality software. It helps teams to work together more effectively by breaking down silos between development, testing, and operations, adding value to their users or customers.

To achieve this level of collaboration, DevOps requires significant cultural changes within an organization and important investment in tools and automation to make the process efficient and reliable.

While there are no hard-and-fast rules for measuring maturity in DevOps, DORA metrics provide a framework for understanding how well your team is performing across each stage of the lifecycle from development through deployment into production.

In addition, they offer insight about improvements applicable across each stage, boosting overall performance across the entire lifecycle from development through deployment into production.

Imagine having a dashboard that looks something like this…

DevOps Dashboard

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Commit-Based Visibility in DevOps

Commit-Based Visibility in DevOps

The complexity of modern DevOps environments requires tooling that enables engineering teams to have maximum visibility into the health and behavior of their workloads. Having an acute understanding of the “moving parts” of an application means issues are resolved faster. However, it’s often the case that outages or unexpected behavior are a result of internal change, like code commits. Engineering organizations struggle to understand and account for the sum total of change in their environments.

 

Utilizing commit-based visibility means that each unit of change (commit) can be identified and tracked across their entire lifecycle, as well as multiple environments. Being able to pinpoint individual commits across an entire engineering organization has the potential to provide meaningful gains in critical metrics like Mean Time To Resolution (MTTR). Organizations that can drive down MTTR will improve the ever crucial customer experience.

 

Implementing commit-based visibility means first understanding the underlying instrument of change: the commit. Afterwards, understanding the lifecycle of a commit and how it’s deployed will reveal an opportunity to improve visibility even further.

 

What is a Commit? (And Why This is a Critical Construct)

A commit in this context refers to a specific process in which a change in the source code is sent to a Version Control System(VCS) repository, where it is hashed and stored as part of a continuous log of changes. In the course of a single day, development teams may push thousands of individual commits to multiple repositories.

 

Any one of these commits, at a basic level, represents a net change to the destination environment. The code could be part of application source code, or perhaps represent configuration and orchestration code for infrastructure. The key point is that any change has the potential to bring about unexpected behavior, including an outage or interruption in service. In the past, operations teams were often forced to spend critical minutes tracking down the at-fault change through a variety of version control systems and deployment automation.

Commit Messages Are Important

 

A single commit contains only a limited amount of metadata about itself, which has limited usefulness in understanding whether it could be implicated in issues with a wider scope. While most commits make it possible to identify the original author, they provide very little actual information around the context of the change, and under what circumstances it was requested. Sparse commit messages can result in an even greater mystery around the actual intent of a given commit.

 

Implementing a system with Continuous Integration/Continuous Delivery(CI/CD) provides a wealth of features to test and integrate code before it is deployed to critical production workloads, helping teams avoid issues resulting from untested code changes. Successful implementation of a DevOps initiative typically depends on a well-functioning CI/CD infrastructure.

 

Commits in CI/CD

CI/CD systems are a critical pillar in DevOps. They allow individual commits to be tested and deployed in an appropriate level of isolation. CI/CD pipelines can be modeled to fit a variety of development and deployment scenarios, and provide fast feedback on interoperability and overall code quality. Earlier stages of a pipeline typically focus on smaller scale unit tests, with some checks occurring on the local development machine *before* code is pushed into the pipeline.

jenkins pipeline

Courtesy of www.jenkins.io

The example pipeline is from Jenkins, a widely used CI/CD platform. In this instance, several stages and pipeline components have been configured, weaving together different testing and isolated deployment steps into a cohesive suite of release automation. Individual commits make their way through each appropriate stage, providing commit-based visibility throughout the pipeline. Developers and other engineering teams can receive immediate, visual feedback on the health and state of a commit at any part of the pipeline.

 

Unfortunately, a single pipeline or CI/CD instance may only represent an individual team or workgroup, or may only be a specific application or production service. Even within a single application stack, infrastructure and application code may be deployed through separate CI/CD pipelines. In a distributed system, outages may not present an immediately obvious cause when a variety of changes may be flowing into the environment simultaneously. Multiple engineering teams may maintain their own decentralized CI/CD infrastructure, making holistic visibility across all pipelines and platforms difficult to achieve.

Commit-based Visibility in CI/CD

Fully-functional CI/CD infrastructure brings massive gains to previous logistical paradigms in software development and deployment. However, modern distributed systems typically require multiple CI/CD instances to fully cover every corner of the stack. In those types of environments, ReleaseIQ tooling can tie disparate CI/CD infrastructure into a single, unified “pane of glass” view.

Jenkins Pipeline

When a breaking change is introduced to an environment, MTTR is crucial: it’s very likely that customer experience is at stake. Long interruptions to critical services may leave customers dissatisfied and heading for the exit. With a single source of truth for identifying and remediating breaking changes, operations and development teams can work in close concert to quickly resolve issues resulting from malformed changes.

 

One of the main objectives of DevOps is to remove the logical barriers that have traditionally existed between development and operations teams. In legacy environments, development teams often kicked their completed code “over the wall”, leaving operations teams scrambling to integrate and test new features, often incurring long hours debugging unexpected behavior and performance issues. CI/CD helped bring down that wall to some degree, but offering commit-based visibility across the entire pipeline environment provides a new level of shared ownership between operations and development.

 

Being able to identify broken changes across engineering organizations can also provide longer-term statistical data for identifying trends. If certain teams or application stacks are more prone to introducing negative change into the environment, additional engineering resources can be focused to help improve testing and reliability. Without this level of holistic visibility, it will be much harder for leadership to know where to focus a limited pool of resources. In the case of commit-based visibility, problem areas surface themselves in an easy to understand system of visualization and metrics.

 

Commit-based Visibility Provides Value

With commit-based visibility, stakeholders and engineering teams alike have better visibility into completed, ongoing, and planned changes. When a change-induced outage occurs, identifying and rolling back the “at-fault” change ASAP is key for customer experience. As with any new initiative, getting buy-in across technical and non-technical stakeholders is critical: engineer teams should be able to demonstrate clear business value in justifying additional resource commitments. With commit-base visibility, there is a clear line of value drawn from reduced outage minutes to customer experience to greater realized value.

 

Over time, improved commit-based visibility will improve overall code quality and reduce operational firefighting, resulting in happier and more productive engineering teams. Another benefit is increased release velocity. Organizations that stay successful and profitable long term focus on delivering more features to customers faster, safer, and more stable.

Want to learn more about our solution ReleaseIQ Essentials for Jenkins?  All you need is more than one Jenkin’s instance and you can sign up here.

Enterprise DevOps Platform Addresses End-to-End Pipeline Pain-Points

Co-written with Marc Hornbeek a.k.a. DevOps_the_Gray esq, www.EngineeringDevOps.com

DevOps CI/CD pipeline tools such as open-source Jenkins are popular because they are easy to get started with, and for simple CI applications, do not cost very much for limited deployments. However, as an organization’s DevOps capabilities requirements mature, there is a tendency for “tool sprawl” and requirements exceed the capabilities of open-Jenkins alone.

As indicated in the white paper “Unified Enterprise DevOps Platform Why? How? And What?” the enterprise needs a more complete, high-performance, end-to-end automated DevOps platform. The platform must be extremely reliable, scalable, secure, and maintainable. Out-of-the-box DevOps tools, such as open-source Jenkins, are not sufficient, on their own, to meet the needs of Enterprise level DevOps platform requirements.

In his March 26, 2021 article “Unified DevOps Platforms Eliminate Bottlenecks”, Marc Hornbeek indicated that the following are general requirements for a unified enterprise DevOps platform.

  • A unified approach that supports end-to-end capabilities for continuous delivery of software, as a managed service, for multiple streams of pipelines.
  • Unified metrics that show business value, costs of the value stream and timing for end-to-end continuous delivery flow across multiple pipelines.
  • Unified capabilities including visibility, orchestration, integration, security, governance, traceability and management of flow for application value streams across multiple pipelines.
  • Capabilities to unify continuous testing/QA, troubleshooting, and debugging.
  • A unified approach to simplify and accelerate toolchains that support new cloud-native and cloud-adapted applications, infrastructures, machine learning, commercial off-the-shelf and open source, software.

Release IO’s Unified Enterprise DevOps Platform was developed to address the above requirements and overcome specific pain points that occur with pipelines that are constructed solely with open-source Jenkins.

The following are pain points with pipelines using open-sourced Jenkins that are addressed by ReleaseIQ’s Enterprise DevOps platform, working together with Jenkins.

  • Tribal knowledge and excessive customizations are needed to connect different Jenkin pipeline segments into an end-to-end value stream. ReleaseIQ provides end-to-end automation, that connects the different pipeline segments in a consistent manner and documents end-to-end automation processes and workflows.
  • Plugins for integrating tools with Jenkins are not well maintained. Plugin upgrades are a frequent source of pipeline downtime. ReleaseIQ’s platform capabilities integrate, test, and monitor end-to-end pipeline performance and quickly identify and diagnose faults in the pipeline to ensure that faulty plugins are detected early and mitigated quickly.
  • High Availability configurations are not supported with open-source Jenkins. By integrating Jenkins’s pipeline segments into the end-to-end ReleaseIQ DevOps platform, availability is improved.
  • Connecting Jenkins data to popular dashboards to improve pipeline visibility is difficult and error-prone. By integrating Jenkins’s pipeline segments into the end-to-end ReleaseIQ DevOps platform a consistent and flexible ReleaseIQ dashboard improves consistency for monitoring the performance of the pipeline and application changes.
  • Jenkins does not have features to coordinate orchestration and get visibility across parallel pipelines. By integrating Jenkins’s pipeline segments into the end-to-end ReleaseIQ DevOps platform the ReleaseIQ platform can be used to orchestrate and provide insights across multiple pipelines.
  • Jenkins does not have good features for the management of multiple Jenkins servers. Integrating Jenkins pipeline segments into the end-to-end ReleaseIQ DevOps platform and using ReleaseIQ administration capabilities improves the management of the Jenkins servers.
  • In many applications, multiple Jenkins servers are required because one Jenkins server has performance limitations. Integrating Jenkins pipeline segments into the end-to-end ReleaseIQ DevOps platform provides a higher performance solution than Jenkins alone.

WHAT THIS MEANS

Mature Enterprises need a DevOps Platform tool that is more capable than the capabilities offered by open-source Jenkins alone. ReleaseIQ’s Enterprise DevOps Platform addresses all the pain points inherent in pipelines that were constructed using open-source Jenkins alone. The ReleaseIQ solution supports end-to-end capabilities for continuous delivery of software, as a managed service, for multiple streams of pipelines.

A New Approach to Automation and Orchestration Across Multiple Jenkins Instances

 

Within 30 minutes you can get starting building pipelines with ReleaseIQ’s Essential Edition for Jenkins. Try it for free here.