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Category: Continuous Testing

Continuous testing is the process of executing automated tests as part of the software delivery pipeline to obtain immediate feedback on the business risks associated with a software release candidate.

ActiveState Makes All Tiers of Curated Artifact Repository Service Free

ActiveState today announced it is making all tiers of its ActiveState Artifact Repository service available for free for a limited time. The move aims to enable organizations to better secure open source software components incorporated within applications.

Loreli Cadapan, vice president of product for ActiveState, said the ActiveState Artifact Repository exposes a set of curated instances of open source software for creating binaries that are validated to be secure. That capability reduces the likelihood vulnerabilities will be inadvertently introduced into application environments by developers that have downloaded open source modules from repositories that may contain compromised code, she added.

In addition, the ActiveState Artifact Repository also makes it possible to automatically generate software bills of materials (SBOMs) that identify which software components were used to build an application after all the code used to construct an application is stored in the repository, Cadapan noted.

ActiveState’s repository is delivered as a cloud service to organizations that would otherwise have to build their own. Cadapan noted that the goal is to make managing and securing software supply chains simpler when more attacks are being launched against them.

Most organizations have limited visibility into how they are consuming open source software. It’s become apparent many organizations have no idea what software components have been incorporated across their software supply chain. As a result, when a vulnerability is discovered, there’s no easy way for them to know whether they are impacted.

However, awareness of this issue has risen, thanks to an executive order issued by the Biden administration which requires federal agencies to have an SBOM for every application they employ by next summer. The executive order was issued in the wake of a zero-day vulnerability in the Log4j tool discovered late last year that is widely used to create logs within Java applications. Many organizations are still looking for all the vulnerable instances of Log4j in their application environments. SBOMs must provide a list of the “ingredients” used to create an application to make it easier to find any component that might one day be similarly affected by a zero-day vulnerability.

Organizations that want to implement a similar SBOM policy will spend massive amounts of time cataloging software on an ongoing basis. Every time an application is updated, there will be a need to once again verify what components are being employed within the context of larger DevSecOps workflows.

SBOMs will undoubtedly play a critical role in improving overall application security. However, having an SBOM is not the same thing as operationalizing it. Organizations are ultimately hoping to be able to use an SBOM to decide whether to green-light the deployment of an application, so DevOps teams should expect to be required to not only provide an SBOM but also continuously update it. The challenge, of course, will be determining how many internal resources to devote to that effort versus relying on external platforms to manage that process.

December 14, 2022
CloudBees Survey Sees VSM Driving Digital Transformation

A global survey of 600 senior executives conducted by CloudBees suggested a high correlation between investments made in value stream management (VSM) and digital business transformation success.

The survey found 90% of respondents agreed that organizations that committed to VSM are likely to be further ahead in terms of achieving their digital business transformation goals, with 92% noting VSM also creates more time to focus on innovation.

Hope Lynch, senior director for platform at CloudBees, said the challenge is that too many executives equate VSM with legacy Six Sigma processes rather than application development and deployment processes that advance digital business transformation initiatives. The survey found that while 90% of senior executives claimed they were familiar with the VSM concept, only half could select the correct answer when asked. In fact, two in five respondents confused the concepts of value stream management and value stream mapping. Nearly two-thirds (72%) of respondents admitted there is still confusion about what VSM is.

VSM traces its lineage back to lean manufacturing methods, which called for each step of a manufacturing process to be continuously measured. As software development has evolved and organizations realize how dependent they are on software, there is a growing appreciation for the value of monitoring things such as the impact of missed software development deadlines on the business. At their core, VSM platforms aggregate DevOps metrics and then match them to a set of key performance indicators (KPIs) defined by business leaders. Once those metrics are gathered and correlated, organizations can apply advanced analytics.

Eventually, the goal is to apply algorithms and other forms of predictive analytics that will enable organizations to more easily identify the precise impact software development processes have on the business, noted Lynch.

In the meantime, the CloudBees survey identified manager commitment as the main roadblock to VSM adoption, with 35% of respondents saying getting mid-level employees committed and 31% saying getting senior leadership committed are the biggest roadblocks. That’s a significant issue because more than half of respondents (56%) said C-level executives make VSM investment decisions.

Survey respondents also reported that scaling VSM efforts throughout the organization is a significant issue for a third (33%) of respondents.

In general, many VSM initiatives were sidetracked by the COVID-19 pandemic, noted Lynch. However, organizations will now be looking to evaluate the results of those efforts, she added. Digital transformation plans are in place and going well, according to 96% of survey respondents, with only 18% reporting that they are moving, but not fast enough.

However, all software development processes could be improved by surfacing real-time insights, added Lynch. Most senior executives today don’t have a lot of visibility into the software development processes that are driving multiple digital transformation initiatives, she added.

In theory, VSM platforms should one day help narrow the divide that has long existed between IT and the rest of the business, as dashboards make it simpler for everyone involved to appreciate the cascading impact a software development decision has across the entire business.

December 13, 2022
Shift Left Testing in Microservices Environments
By now, it’s common knowledge that the later a bug is detected in the software development life cycle (SDLC), the longer it takes and the more expensive it is to fix that bug.

In 2017, the Ponemon Institute found that it cost around $80 on average to fix a defect detected early in the SDLC and around $7,600 to fix the same defect if it was detected in the production stage.

Relative Cost of Fixing a Defect Based on Development Stage

Design

Implementation

Testing

Maintenance

Cost of Fixing Defects

1x

6.5x

15x

100x

While these numbers can be debated, it’s clear that early detection of defects can save organizations significant time and money while enabling those organizations to deliver higher quality software more rapidly. For these reasons, many organizations are implementing shift left testing practices, including in microservices environments.

Shift left is a set of practices intended to find and prevent defects early in the software delivery process instead of during the testing and maintenance stages. The idea behind shift left testing is to improve software quality by making actionable test signals and feedback available as early in the SDLC as possible.

Here, we’ll highlight how shift left testing, in combination with test automation, can better enable both innovation and fast delivery of high-quality software. We’ll also address some of the challenges involved in implementing shift left testing in microservices environments, as well as introduce a valuable strategy for successful microservices implementation.

Shift Left Testing Benefits

The waterfall model of development involved the explicit passing of responsibilities between highly specialized design, development, QA, and release teams. It also involved lengthy feedback loops.

Scrum and agile methodologies made the entire SDLC more flexible and nimble by introducing sprints and allowing more frequent iterative development and delivery. Further, DevOps and DevSecOps focus on removing the silos between development, operations, and security through tooling and automation. As a result, the time to market and quality have improved dramatically. Adding shift left testing into the mix better positions teams to handle the broad range of responsibilities from the design stage through the maintenance stage as effectively as possible.

Shift left testing focuses on prevention rather than detection. Shift left benefits include the following:
- Increase efficiency by eliminating bugs earlier in the SDLC.
- Reduce human errors and associated costs.
- Increase delivery speed and reduce the time between releases.
- Improve the quality of software.
- Gain a competitive advantage.
It may be helpful to think of shift left testing like this: Test early and in parallel with development, instead of the traditional waterfall model of development followed by QA testing.

Shift Left Testing Challenges in a Microservices Environment

By structuring an application as a collection of loosely coupled, independently deployable services, a microservices architecture enables frequent delivery of large, complex applications.

While shift left testing practices bring many benefits, shift left testing also comes with three challenges that organizations must address when implementing it across a decentralized, microservices-based stack:
1. Building and managing each microservice separately reduces development time. However, implementing shift left testing at the microservices level means shift left practices must be applied to each individual microservice.
2. Microservices developers can choose the programming language and service dependencies best suited to their development needs. However, as a result, shift left testing practices need to be implemented and managed across different programming languages and dependencies.
3. To ensure that microservices function as expected, teams usually run integration tests, end-to-end tests, and performance tests that assess functionality in the context of the larger stack. Shift left testing is especially challenging in the microservices context because of the complexity of testing against the stack.
Microservices, each with their own SDLC pipeline

Pipeline Scaling Considerations

Several classes of automated shift left tests can be integrated into the DevOps pipeline, including unit tests, integration tests, performance tests, and security tests. Different microservices will have different testing needs.

The key is to apply shift left testing practices to each microservice while maintaining the flexibility and decentralization of those microservices. The ideal workflow system and DevOps pipeline implementation must simplify pipeline creation while enabling development teams to manage the pipeline and requiring minimal input from DevOps and platform teams. In other words, shift left practices must be tailored to the specific needs of the microservice in question to make the testing process scalable and easy for development teams to manage on a continuous basis.

As just one example, GitHub Actions and similar CI/CD pipeline tools enable development teams to use GitOps-based practices to configure, manage, and administer the entire pipeline for their microservice while leaving infrastructure testing and testing that relies on or affects other parts of the system to DevOps teams.

Test Environment Considerations

Test environments are environments where unit tests, integration tests, performance tests and security tests can be run on an isolated collection of microservices and configurations. The nature and quality of these test environments directly correlate with the effectiveness of shift left testing.

A cloned production or staging environment can be used for testing when the number of microservices is low and overall complexity is relatively low. However, once an organization reaches a threshold number of microservices or a threshold level of complexity, runaway infrastructure costs and operational burdens make such environments untenable.

In response, some organizations rely upon smoke testing (minimal viable stability testing) and mock-based integration testing early in the SDLC. While such tests can prove useful in the near term, deferring essential testing to a later stage in the SDLC often introduces test signal and validity problems in the staging environment and can lead to delivery delays and serious issues with software quality.

So how can shift left testing be used successfully in a microservices environment? The solution involves the use of scalable, ephemeral test environments.

Ephemeral Shift Left Testing Environments

The availability of high-quality test environments is a common bottleneck for organizations looking to scale shift left testing practices. Using a few high-fidelity staging environments for signal testing can slow the release process. More to the point, it tends to slow down the entire SDLC and increase stack instability over time.

Ephemeral test environments offer a fundamentally different approach. These sandbox environments use isolated environments that enable users to test independently without impacting other users. In particular, they enable isolation while sharing resources (e.g., external cloud dependencies and hosted databases) using application-level multitenancy instead of the resource duplication approach in traditional environments.

The idea is that microservice test environments can be used to test changes against a much larger stack of services. Because multiple tests can be conducted at the same time, test coverage and resource efficiency vastly increase.

High-quality sandbox environments can spin up in seconds and scale to tens of thousands of microservices. In fact, each pull request, branch, or commit can have its own test environment without significantly increasing infrastructure and operational costs. Any change, no matter how small, can be tested in isolation to ensure performance and stability against the entire stack.

Shift Left Testing Solutions for Microservices

A microservices-based organization looking to scale shift left testing across the organization must first address several challenges. Considerations include the need to apply testing practices to separate microservices, the need to accommodate different programming languages and service dependencies and the need to test against the stack.

The right tooling and automation are needed before shift left testing practices are scaled across the organization. In addition, a cultural shift may be required in order to help developers understand the ways in which shift left testing can expedite and improve the core functionality that they are developing.

To apply valuable shift left testing practices in a microservices environment, organizations should consider using ephemeral sandbox environments. Using the right set of tools in a sandbox environment can enable development teams to test microservices throughout the SDLC. In doing so, organizations can ensure those services follow security best practices and perform exactly as intended, both independently and against the stack–all while reducing costs, speeding time to market and improving software quality and user satisfaction.
December 13, 2022
Massive Number of Transitive Dependencies Traced to Open Source Code

An analysis of nearly 2,000 software packages published by Endor Labs found 95% of all application vulnerabilities can be traced back to a transitive dependency created when a developer used an open source component.

The study, conducted by the Station 9 research arm of Endor Labs, a provider of a platform for identifying software dependencies, concluded there’s still a 32% chance those software packages would have known vulnerabilities even after components are upgraded to the latest version.

Endor Labs CEO Varun Badhwar said vulnerabilities often remain because the last update made to one of those software components may have been made several years ago even though there are existing known vulnerabilities that affect it. Development teams can’t assume the latest version of a software component is secure, he added.

In general, functional dependencies are created whenever developers download a third-party component, he noted. The most important thing for any software development team to determine when assessing actual risk levels created by those dependences is determining how accessible any given vulnerability is to an attacker regardless of its severity score, noted Badhwar.

In the wake of a series of high-profile breaches, there has been an increased focus on software supply chains. The challenge is most developers don’t have a lot of cybersecurity expertise. They often create patches for applications based on a list of potential vulnerabilities surfaced by cybersecurity teams. The issue, of course, is that just because there is a vulnerability it does not immediately follow that the affected software component can be externally accessed.

Endor Labs is making a case for a graph-based platform that identifies dependencies between the software components that make up an application environment. That approach makes it simpler to prioritize remediation efforts based on the impact a vulnerability might actually have and narrows the current divide between cybersecurity teams and application developers. By the time cybersecurity teams alert developers to a vulnerability they often have moved on to other projects. As a result, developers often lack context because it may have been months since they last looked at the impacted code.

Of course, the inclusion of DevSecOps best practices should improve the overall state of application security as more responsibility for it shifts left toward developers. However, achieving that goal will require more than just giving developers access to software composition analysis (SCA) tools that only surface vulnerabilities in source code as it is being developed, noted Badhwar.

In the meantime, the efforts to remediate all existing application vulnerabilities will be measured in years, so organizations need to determine where to focus their efforts. After all, every minute spent developing and deploying patches is less time that can be allocated to building and deploying new code. The trouble is that as more new code is written, the number of vulnerabilities that could be exploited increases and makes a bad situation worse.

December 12, 2022
5 Tips to Consider When Introducing Infrastructure Automation

Although we discuss infrastructure automation often, the fact is that a lot of manual processes still exist throughout DevOps. Whether it’s rewriting scripts to spin up new servers, updating cloud-native policies or configuring computing environments, manual toil is an all-too-common reality. To make matters worse, engineers commonly create lengthy scripts that work in isolation but are too bulky to be reusable by other developers working with slightly different constraints.

More infrastructure automation is the key to increasing deployment agility, but setting aside time to automate your daily workflow can easily take a back burner, especially when developers are already behind on their long list of to-dos. So, for the time-pressed, where should they start? What exactly should be automated? And how can we effectively reuse and share automation to help other areas of the business?

I recently connected with John Laffey, technical product marketing director, Puppet. Laffey has thirty years’ worth of tech support and engineering operations knowledge under his belt and was “doing DevOps before it was called DevOps.” He shared with me five helpful tips to think about when introducing more infrastructure automation into your workflows. Below, we’ll expand on each of those points and consider other best practices around automation as the industry moves toward platform engineering.

1. Automate Things That Interrupt Your Day

First, Laffey recommended starting with the things that are easy to fix. These are the tedious actions that interrupt your day. Perhaps a disk runs out of space and troubleshooting takes 15 or 20 minutes. Minor interruptions like this might seem like part of the job, but they definitely add up over time.

2. Automate Things You Can Reuse

Secondly, try not to automate things for an ultra-specific purpose, said Laffey. Instead, focus on building automation that is more generic and can have more value to others. This follows the DevOps mantra of teamwork and collaboration. One-off automation that is too verbose or specific to a certain condition won’t apply well across groups.

3. Automate Stuff That Doesn’t Change Much

Next, automate the infrastructure that isn’t prone to change. These are fairly reliable things that you’re sure will be part of your systems for the foreseeable future. Because if a component does end up having to be updated often, supporting the automation could be more hassle than it’s worth. “Don’t trade fixing problems for fixing automation,” said Laffey.

4. Start Small

Here’s some sage advice applicable to most new projects with a big scope—start small. Laffey recommended starting by automating the easy stuff that has proven immediate value. These tasks should be modular and do one specific thing, like rebooting a machine or draining a log file. “Automate things in chunks that you can put into a toolchain.”

Too often, teams try to automate everything all at once. But by taking big bites, you can quickly get off track and potentially add to technical debt. If you keep things modular, you’ll find it easier to change and reuse this automation.

5. Share and Be Open

This last tidbit is more of a cultural change—don’t code so that you’re the only one who knows about it! Sometimes, engineers don’t necessarily want the world to know about the automation they create. They might worry about automating their job away. Yet, Laffey said, these worries are misplaced. There will always be more work to do, and automating toil away can free up time to help you focus on more exciting projects.

So, Laffey encouraged DevOps and SREs to be open about the automation they create. Ensure they’re well documented and stored in a centralized repository to allow other departments to reuse your code. This can avoid the duplication of having five different versions of the same script written in different languages within the same organization!

Next Step: Move From Scripts to Industry-Standard Tooling

It can be challenging to argue for investing time and energy into infrastructure automation, especially when engineers are hard-pressed to keep the lights on. Yet, small gains in automation can make huge waves in the long term.

Eventually, said Laffey, you’ll want to move away from using scripts within your toolchain, which he describes as a low-end DevOps maturity. But as you update your process, you’ll want to replace these scripts with more modern industry-standard tools like Terraform or Puppet’s DSL. He recommended slowly revamping scripts in a toolchain as you update them one by one. “Start where you are and avoid a monolithic approach.”

In essence, platform engineering, Laffey explained, is wrapping DevOps principles at a higher level to make them more efficient. And we will likely see an increased emphasis on infrastructure automation as platform engineering gains more mindshare. “It’s going to become a necessity.”

December 12, 2022
Codenotary Extends Dynamic SBOM Reach to Serverless Computing Platforms

Codenotary has extended the reach of its platform for automatically generating software bills of materials (SBOMs) to serverless computing platforms running software constructed using functions.

Codenotary CTO Dennis Zimmer said because serverless apps are dynamically created, it’s not possible to generate SBOMs using traditional approaches. The TrueSBOM platform makes it possible to create an SBOM in real-time by adding one line to the source code of any application. The TrueSBOM for Serverless edition of the platform now extends that capability to the serverless computing frameworks made available in the cloud by Amazon Web Services (AWS), Microsoft and Google.

That approach makes the SBOM a part of the application itself rather than a text file that is stored separately, he noted. Each time an application is updated or a scanner discovers a new vulnerability, a new SBOM is automatically generated, added Zimmer.

Awareness of the need for SBOMs has skyrocketed since an executive order issued by the Biden administration made it clear that federal agencies would require them from software providers starting next year. Many enterprise IT organizations are likely to follow suit as part of a larger effort to better secure software supply chains in the wake of a series of high-profile cybersecurity breaches.

Most internal DevOps teams already have a good handle on what software components are used within the applications they deploy. The issue is that the organizations that use that software can’t easily verify what components are being used, noted Zimmer. That’s problematic because an organization may prohibit deployment of a specific software component because of a known vulnerability. TrueSBOM allows organizations that use an application to maintain control over their software environment regardless of what software artifacts are used to build closed or open source components, Zimmer added.

It’s unclear how most organizations will operationalize SBOMs now that more of them are being created. Ideally, organizations should be able to approve only software with components that have been verified as secure.

As SBOM mandates become more stringent, the number of application providers that are anxious to comply with rules for securing software supply chains should increase. The issue now is finding a way for both the developer and consumer of that software to streamline a verification process that, in its current form, is too cumbersome to manage effectively. As a result, many organizations are now putting together dedicated teams made up of cybersecurity professionals and software developers to manage SBOM processes, said Zimmer.

Of course, there is a massive amount of code that has already been deployed that today doesn’t show up in an SBOM. While many emerging applications—created using artifacts such as functions and containers—are likely to be increasingly instrumented to dynamically generate an SBOM, the number of legacy applications that might need to be similarly instrumented is several orders of magnitude greater. As a consequence, the amount of effort required to generate SBOMs for every application in use might be greater than teams first anticipated.

December 9, 2022
Survey Surfaces Agile Development Challenges

A survey of 3,220 software development professionals published this week found that among the 80% of respondents that embraced Agile practices for building software, just under half are tracking on-time delivery (47%) and business objectives achieved (44%).

The survey, conducted by Regina Corso Consulting on behalf of Digital.ai, a provider of a value stream management (VSM) platform. The survey also found a total of 19% of respondents were not sure what metrics were used to track software development progress.

At the same time, 40% of respondents noted they are dissatisfied with Agile at their organization; a clash with company culture was listed as the leading cause (41%) of unsuccessful delivery. Half of respondents use a combination of Agile, waterfall and/or iterative processes, but 27% noted this combination of frameworks was a struggle for them.

The survey also noted that just over a third of product and application owners (36%) that participated in the survey have adopted Agile.

Derek Holt, general manager of Agile and DevOps at Digital.ai, said that percentage suggests that Agile principles are now being adopted beyond the engineering teams that construct software. As that appreciation for Agile principles continues to grow, the organizations these individuals work for also tend to start tracking value stream metrics, he added. That transition typically begins with a few pragmatic metrics before the organization matures enough to justify the adoption of a VSM platform, Holt noted.

In time, however, that VSM platform not only helps organizations identify bottlenecks but also identifies potential quality issues and risks to the business, Holt added.

Overall, the top three top Agile development priorities identified by respondents are to accelerate time-to-market (52%), delivery predictability (44%) and lower risk (31%). However, from a business perspective, the top three priorities are company goals (54%) and end customer satisfaction (43%) followed by time-to-deliver (35%).

More than half (51%) of respondents, however, also noted that DevOps teams are not incorporating business feedback regularly. Well over half (58%) said the most valuable improvements to DevOps teams would be end-to-end visibility and traceability from business initiative through development, test and deployment to end users, while 55% said the ability to measure cycle time, wait time and bottlenecks would be an important improvement.

Regarding Agile tools used, Scrum led the pack at 87%, followed by Kanban at 56% and Scrumban at 27%. The Scaled Agile Framework (SAFe) framework has been adopted by more than half of respondents (53%), while Scrum@Scale/Scrum of Scrums was adopted by 28% of respondents followed by Lean Management at 8%, according to survey respondents.

The top benefit of Agile is increased collaboration (69%) followed by better alignment with the business (54%) and better work environment and increased visibility in the application development life cycle at 39% each.

The debate over the merits of Agile frameworks, of course, remains fierce and no two organizations may ever have the same level of adoption. However, as the pressure to deliver quality software faster in the age of digital business transformation continues to mount, the more crucial it will become to align Agile and DevOps best practices.

December 9, 2022
Chainguard Adds Private Edition of Code Signing Platform

Chainguard today added a private preview of a Chainguard Enforce Signing service, enabled by the open source Sigstore project, that allows developers to generate digital signatures for software artifacts using identities and one-time-use keys they create themselves.

Kim Lewandowski, head of product for Chainguard, said Chainguard Enforce Signing provides an alternative to relying on a public service to generate those digital signatures. It also allows organizations to bring their own key and certificate so that key usage can be monitored and audited per compliance and privacy requirements.

In addition, Chainguard added a library of policies that administrators can deploy directly from the Chainguard Enforce web console to their environments.

The Chainguard Enforce Signing feature is based on Sigstore, an open source project that provides a protocol to simplify cryptographic certificate generation by removing the need to manage keys. At its core, Sigstore creates a set of short-lived ephemeral keys with a trust root based on an auditable public log. Because it creates an immutable log, everyone participating in the software development process, including auditors, can now transparently track the chain of custody for any software artifact.

Key management, key compromise/revocation and the distribution of public keys and artifact digests are challenging to manage. Developers are also required to determine which keys to trust in addition to learning how to sign them when different platforms are employed.

Chainguard’s alternative is enabling organizations to host their own immutable log rather than relying on a public service to eliminate the need to manage keys, noted Lewandowski.

Historically, code signing platforms have been problematic because they were susceptible to tampering. Cybercriminals can, for example, swap out digests to gain access to compromised credentials. Digests and public keys are also often distributed across vulnerable websites susceptible to hacks or inadvertently stored on a public Git repository.

Code signing—along with software bills of materials (SBOMs)—is one of two technological advances that will improve the security of software supply chains. SBOMs, of course, are going to be considered more reliable when the software components they describe are signed by the developers that created them.

Less clear is whether the signing of code will improve its overall quality. Most developers take pride in their code, but the overall quality of the software deployed in production environments could always be improved. Developers may decide to review the code they contribute to a build more intently if they know they will be required to sign it.

In the meantime, it’s only a matter of time before organizations require that developers sign code before it is deployed in a production environment. In addition to increasing confidence in the quality of the code employed, those signatures make it simpler to track down the development team that created code whenever there is an issue that needs to be resolved. After all, the most challenging issue organizations encounter when trying to update software is not so much the creation of a patch as much as it is identifying who should create that patch based on their knowledge of the software components used.

December 8, 2022
Report: Impact of Bad Software on US Economy Reaches $2.41 Trillion

A report published this week by Synopsys in collaboration with the Consortium for Information & Software Quality (CISQ) estimated that software quality issues might adversely impact the U.S. economy to the tune of $2.41 trillion in 2022.

Cybercrime losses due to a rising number of software vulnerabilities alone are on track to increase 42% in 2022 after growing 64% in 2021, according to the report.

More troubling still, the number of failures due to weaknesses in open source software components accelerated by an alarming 650% from 2020 to 2021.

Finally, the report estimated that overall technical debt would increase to $1.52 trillion in 2022.

Dr. Anita D’Amico, vice president of cross-portfolio solutions and strategy for Synopsys Software Integrity Group, said that despite these issues, there is cause for optimism. The silver lining is that more organizations are aware of software supply chain issues in the wake of a series of high-profile breaches.

As more responsibility for application security also is shifted further left toward developers, the number of vulnerabilities being introduced into applications should also begin to decline steadily, she added. In addition, more organizations will soon be following the lead of the federal government by requiring software bills of materials (SBOMs) that will make it simpler to remediate vulnerabilities once they are discovered, noted D’Amico.

Of course, there are still many cultural and technical issues that need to be resolved before DevSecOps best practices are consistently employed across most organizations. However, the expectation is that cybersecurity teams will be able to concentrate more on crafting cybersecurity policies as application development and IT operations teams assume more responsibility for implementing those policies, said D’Amico.

But while giving individual developers the tools they need to write more secure code is a major step in the right direction, there is also a need to make sure the builds to which they contribute code also remain secure. As such, DevOps teams need to implement guardrails across every stage of a DevOps workflow to make sure vulnerabilities are not created as code is merged. In addition, DevOps teams now need to be aware of any malware added to an open source software component downloaded from a compromised repository. Even once patched, there’s a good chance another developer will have downloaded the same vulnerable component to construct a different application.

No one knows for certain how many vulnerabilities may have already been introduced into production environments, but it’s unlikely all those issues will ever be completely addressed. Organizations with limited technical resources will need to prioritize the patching of the most severe vulnerabilities in their application environment based on how accessible code may be to cybercriminals.

Cybercriminals certainly are getting more adept at exploiting vulnerable code. Developers may soon find themselves being required to update software components deployed by someone else many years earlier. In the meantime, more accountability for application security should lead to better quality code that, over time, will reduce the current unsustainable level of technical debt.

December 7, 2022
Looking to the Future of Developer Experience
Developer experience is where it’s at! Developer experience (DX) means taking a user experience approach to the developer journey. DX (also abbreviated as DevEx) is commonly applied to areas like documentation, sandbox environments, SDK ergonomics and more. By improving a developer’s experience with a tool, software providers can increase stickiness and retain more users.

Nowadays, having a sleek developer experience is a competitive advantage—especially since developers often have the discretion to purchase new tools. And amid an ongoing skills gap, maintaining quality DX for internal software ecosystems is also important to retaining happy engineers and avoiding burnout. All these factors mean developer experience is becoming a C-suite objective. So, where is DX heading? How will the developer workflow change in the near future?

I recently met with Ash Arnwine, director of developer relations, Nylas, to ponder what’s on the near horizon regarding developer experience. According to Arnwine, DX is still a very new concept. Yet, it has become an integral aspect of positioning modern software, especially for public-facing SaaS, and will undoubtedly drive purchasing decisions in the year ahead. Below, we’ll share some predictions of how DX will evolve within four general categories: onboarding, building, deploying, and maintaining.

State of Developer Experience

First off, what is the state of developer experience within the tech world at large? Well, Arnwine is quick to note that the concept is still relatively nascent. “Developer experience was something that we didn’t talk about that long ago.” Yet, the idea is growing in mindshare as developers exercise greater control over the software life cycle.

In fact, the 2022 StackOverflow survey found that 66% of professional developers have at least some influence over their organization’s purchases of new technologies, up from 56% in 2020. Furthermore, the way developers learn is changing. The new generation of programmers is primarily self-taught, relying on coding bootcamps or other online resources. An impressive 70% of developers learned how to code from online resources.

What we end up with, said Arnwine, is a growing developer population with a much wider range of skills than in the past. And since no one is there to hand-hold them, the technology itself must be usable and intuitive—the onus is on the software provider to craft frictionless self-service workflows. And with developers’ growing influence in purchasing, DX becomes a competitive advantage and an executive talking point, said Arnwine.

Onboarding

Developer experience is a broad topic, but it’s most often associated with the time it takes to get started with a tool. This is often referred to as ‘Time to First Hello World.’ But although it’s an important step, the metric might doesn’t always carry much significance. Time to value, on the other hand, said Arnwine, takes this a step further and is a better gauge of success.

For example, onboarding to a web API would likely involve the signup process, creating an account, getting API keys and perusing the documentation—all before a first call is sent. According to Arnwine, there are techniques to apply at this stage to help developers move faster throughout the onboarding process to reach value sooner.

Here are some ways in which developer onboarding is becoming more streamlined:
- Automatically generating keys upon signup.
- Providing a terminal within the developer dashboard to test sample code.
- Handing developers the code they need to be customized to their specific stack.
- Using specifications as a single source of truth for documentation.
Building

What can SaaS companies do to help improve DX while building? Well, one way is to enable auto-complete within IDEs. When developers onboard with a new tool, they are often handed an SDK and reference documentation. But, it doesn’t add value to send programmers back and forth between a browser to look up method names. Instead, Arnwine believes developer tools should be “baked into the IDE in a way a modern developer would expect.”

One example of auto-complete on steroids is Fig, a next-gen command line that supports auto-complete for over 500+ popular CLI tools. Taking this a step further is GitHub Copilot, an AI assistant that can take natural language prompts and generate pretty complex code suggestions. The industry appears to be heading toward more AI-fueled low-code software development—a trend that could significantly improve a developer’s experience during the construction process.

However, one potential downside of increased software development automation is ensuring the AI suggests correct code snippets. Thus, Arnwine said he anticipated possible troubleshooting and debugging problems. Furthermore, SaaS providers will have to vet systems that generate glue code to ensure it’s accurate and up-to-date with the latest versions. His advice to SaaS providers is to meet developers where they are, but do their best to maintain a quality experience that they can control.

Deploying

For a long period of software development history, IT administrators were the only ones able to deploy software. The old-school method required getting a hosting provider, installing Ubuntu and plenty of other legwork. Nowadays, however, software deployment has become far more drag-and-drop. DevOps has become more democratized in recent years, and we will likely see greater usability emerge in the years ahead.

One way to increase developer experience for deployments is through more custom automated routines via GitHub Actions or similar event-based systems. And plug-and-play pre-built actions could reduce the barrier to using such systems. Such connectivity is necessary to enable a docs-as-code approach, said Arnwine.

Maintaining

Another area that could use a serious developer experience upgrade is dependency management. Software dependencies go through a life cycle. They are versioned, updated, retired and sometimes replaced outright. As such, keeping track of an evolving surface area of third-party dependencies can be a headache. To make matters worse, software supply chain threats have complicated the integrity of many open source dependencies consumed by most applications.

Although it’s imperative for organizations to maintain parity with dependencies, a single person is rarely tasked with continuously checking dependencies and monitoring for security threats. Therefore, more automation for dependency management and security monitoring is necessary. For example, Arnwine uses Snyk, which sends a weekly report on the state of his dependencies.

Final Thoughts

Assuming you have the killer functionality to back it up, an investment into developer experience can help a developer tool stick out in a crowded marketplace. But of course, improving the DX means many different things depending on your context. It could be a subtle user interface tweak, adding relevant code samples or making your documentation more intuitive.

On the other hand, a negative developer experience can turn away potential users and cause frustration throughout the application support life cycle. This can instill a poor reputation among programmers.

To review, in the near future, we’ll likely witness the developer experience evolve in the following areas:
- Enhanced methods that streamline the signup process.
- Auto-complete and AI-driven code suggestions that understand a developer’s stack and meet them where they work.
- More intuitive, automated deployment models.
- Increased automation around the maintenance of dependencies.
While developer experience is a growing concern, it shouldn’t be the only measurement of a SaaS — the ongoing value it brings developer consumers and end users is just as (if not more) important to consider.
December 7, 2022