Tag: SDK

  • Postman Bets on Better API Documentation with Fern Acquisition

    Postman Bets on Better API Documentation with Fern Acquisition

    Postman CEO Abhinav Asthana explains how the acquisition of Fern will significantly improve the quality and consistency of documentation generated for application programming interfaces (APIs) and software development kits (SDKs), as well as the impact on developer experience and modern API-driven development.

    Fern, Asthana explains, has built momentum by helping companies generate higher-quality SDKs and developer portals—tools that make APIs easier to discover, learn and consume. By bringing Fern into Postman’s broader API platform (spanning design, collaboration, testing and monitoring), the goal is to improve the “last mile” of API programs: turning well-built APIs into well-adopted APIs.

    Asthana also argues that good documentation is becoming even more critical as developers begin relying on AI agents and automation to interact with services. Agents still depend on accurate metadata and clear descriptions to choose the right endpoints and use them correctly, and that context often comes from documentation. While AI can help generate drafts and drive consistency across large portfolios of APIs, Asthana stresses that humans remain essential in the loop—reviewing, validating and preventing hallucinations.

    API management varies by industry: fast-moving tech teams may prioritize speed, while regulated sectors demand stronger governance and lifecycle discipline. Regardless, he says discoverability and consistency are foundational. Better documentation doesn’t just help developers; it can prevent duplication, speed internal reuse, and make API-first strategies actually work in practice.

  • Hasura Adds “Supergraph” to Platform for Managing APIs

    Hasura Adds “Supergraph” to Platform for Managing APIs

    Hasura, whose product helps compose GraphQL APIs backed by databases and services, today made available in beta an update to its platform. The company is adding a graph modeling framework that makes it simpler to manage application programming interfaces (APIs) at scale.

    The goal is to make it easier for IT teams to declaratively create APIs and then manage them at scale, said Hasura CEO Tanmai Gopal. As application environments made up of multiple backend services and databases become the enterprise norm, there is a pressing need to simplify the management of what has become thousands of APIs in an enterprise IT environment using query compilers and routing capabilities built into the platform, he added.

    In version 3.0 of the Hasura Data Delivery Network (DDN), the “supergraph” execution engine is based on a serverless runtime engine that, the company says, will replace its previous graph technologies to manage both GraphQL and REST APIs.

    In addition, all connectors provided by Hasura have been rebuilt using an open specification and are now available as open source software on the Hasura Connector Hub. Hasura is also making available a software development kit (SDK) to enable IT teams to build custom connectors.

    Written in the Rust programming language, the supergraph framework eliminates the need to create and manage GraphQL servers or services to deploy a graph. Additional data domains as a result can be added or replaced without breaking the graph used to manage other APIs.

    The update to the Hasura DDN also adds new build system to provide instant API previews and support for rollbacks, a redesigned console featuring a graphical supergraph viewer, API analytics, observability, and auto-generated API documentation capabilities. Every iteration of the Hasura supergraph is instantly available as an immutable build that can be tested in preview. Every change to the supergraph is also validated before build, letting users identify potential bugs, stylistic issues, syntax, and type errors.

    In addition, Hasusa has added a sub-millisecond cold start capability to enable rapid autoscaling and plane to shortly add caching to improve API performance in edge computing environments.

    Longer term, the company plans to add additional a range of artificial intelligence (AI) capabilities to enable IT teams to identify issues requiring troubleshooting earlier and generate reports, Gopal added.

    While REST APIs are still more commonly used than GraphQL, more IT teams are employing the latter. That’s because GraphQL provides more control over how data is accessed and consumed. Most organizations will soon be using a mix of REST and GrapgQL APIs, but it might be years before REST is supplanted as the dominant format simply because those APIs are more familiar to developers and easier to create.

    Regardless of the type of API used, however, their numbers continue to steadily increase with each microservice added to an IT environment. It’s not always clear which teams within an IT organization are managing those APIs but increasingly best DevOps practices are being used to deploy, manage, secure and update them alongside every other type of software artifact. The challenge, of course, is making it simple to manage those API workflows in a way that doesn’t require yet another specialist to be added to the DevOps team.

  • Stytch Launches New, Flexibility-First SDK

    Stytch Launches New, Flexibility-First SDK

    Passwordless solutions have been a trend for a while now, improving user experience (UX) while reducing exposure to common attack vectors. Now, Stytch’s new JavaScript SDK aims to make password-free authentication a bit easier by increasing customization and flexibility while offering fully baked authentication out of the box.

    Julianna Lamb, Stytch CTO, said the solution provides dual benefits by doing the heavy lifting of implementation while providing the flexibility to create a powerfully branded UX from the customer’s first sign-on experience. The Stytch JavaScript SDK can offer an all-in-one experience that handles the entire user auth journey with a pre-built frontend component. But it can also give teams complete control over designing a sophisticated and tailored authentication journey. In an era where tech companies chase the ultimate customer experience as their holy grail, this should appeal to teams wanting to improve a customer’s first impression of their brand, Lamb said.

    Multiple Options for a Smarter Front Door

    Like many authentication tools, Stytch’s product suite originally offered two options: One was a standard widget to handle frontend components while backend APIs provided logins. The other option provided direct API integration, in which the developers built their frontend, handled tasks like session management and setting cookies on the frontend and used the API to do things like send a one-time passcode or email a magic link.

    “But we found people really want flexibility when it comes to any solution they’re using,” Lamb said. “They also don’t want to do the heavy lifting when it comes to things like session management. Those things can be complex to reason through and having those out of the box is really compelling.”

    The new SDK decouples drop-in UIs from helper functions, giving teams multiple options. They can place Stytch’s UI components anywhere they want in the product, sculpting the authentication flow to their specifications. As a headless SDK, it can be embedded client-side in the application to handle all the calls to the API, do the authentication, create a session and check its validity. The result: Less backend code to write and less logic to implement.

    Customizable UI flows mean that teams can fully own the UX experience and build a UI that is customized exactly how they want it to look—and they can do this without having to build an internal API to route authentication requests from client to server. Teams looking for ways to make a brand impact right out of the gate can capitalize on this ability by creating a unique user experience.

    “Authentication is the front door to your application,” Lamb said. “Sign-up is the first impression the user has of your app—and the ability to customize it with your brand look and feel so the UI fits your aesthetic is super-critical.”

    Frictionless Flexibility in Identity Verification

    Because teams may have different authentication needs within one product, the SDK can be used in tandem with the core Stytch API to meet shifting needs. Teams could generate embedded magic links via the API while providing Google OAuth and Google One-Tap sign-in options via the SDK.

    The solution also reduces friction by making it easier to not only authenticate users but verify them on return visits to continue the same session. By loading the SDK on the frontend, teams can automatically connect Stytch’s sessions product to the browser cookie, feeding user session data directly into the cookie.

    The Stytch team is currently building out more SDK functionality and frontend components, Lamb said. Given the ongoing evolution of simple authentication tools that meet complex requirements, it will be interesting to see where innovative authentication goes next.

     

  • Top iOS Security Gotchas

    Top iOS Security Gotchas

    Ensuring the security of user data within your app is critical to building trust in your business and contributing to the online safety of customers.

    Here’s a list of the top 10 essential security mechanisms that Apple offers to up the security posture of your iOS applications. Adopting these technologies and APIs within your products is an effective step toward writing more secure applications, giving you a lower risk of potential data compromise and increased confidence in your security posture.

    Opting Out of System Data Protection

    iOS provides the data protection setting, a robust way to automatically encrypt any files created by your app. This is an important security setting, however, it is turned off by default and many developers never enable it. Leveraging the system’s data protection mechanism is an easy win for increasing the security of user data within your app.

    Transmitting Data Over Insecure Connections

    It’s critical to ensure that any data-in-flight is transmitted over secure connections. By using encrypted HTTPS connections for all apps’ network activities, a wide variety of data-in-flight compromises are mitigated. Additionally, organizations are recommended to leverage SSL pinning for maximum transport-layer security.

    Deserialization Fails

    The default protocol to serialize and deserialize data on iOS, NSCoding, is vulnerable to object substitution attacks, which could potentially allow an attacker to gain remote code execution. Apple offers a near drop-in replacement, NSSecureCoding, which is not vulnerable to this attack. To convert a serialized class to use the NSSecureCoding mechanism, Apple has outlined steps in its documentation. Making the recommended changes allows the system to enforce safe deserialization.

    Opting Out of App Transport Security

    App Transport Security (ATS) is a mechanism provided by Apple to mediate all network connections made by the app and validate that data is being transmitted securely. Opting out of ATS by use of NSAllowArbitraryLoads, or similar exemptions, is an easy way to shoot yourself in the foot and turn off a powerful security mechanism.

    Cryptography API Misuse

    Encrypting user’s data is a no-brainer, but care must be taken to ensure that it’s done in a cryptographically secure way. Some system APIs, such as CommonCrypto, are easy to misuse. This results in the illusion of security, while still allowing an attack vector for user data to be compromised. Be sure to use these APIs with secure options, and never statically embed encryption keys or use an encryption key which is trivially derived.

    Leaking PII to NSUserDefaults

    When handling personally identifiable information (PII) within an app, it can be tempting to store it in a convenient and straightforward way, such as using an NSUserDefaults entry. However, this approach allows any other app on the device to read this potentially sensitive data. Sensitive data, especially identifiable user information, should always be stored in a secure location, such as the device’s keychain, and encrypted when necessary.

    Unsafe Keychain Usage

    While the keychain is the most secure store of data on the Apple device, developers must still take care to ensure they’re using it correctly. It’s possible for developers to save data to the keychain in such a way that the data is always unencrypted and accessible, even when the device is locked and data would otherwise be encrypted. When saving sensitive data to the keychain, ensure that you’re using the strongest possible data-protection settings to maximize security.

    Wherever possible, utilize “kSecAttrAccessibleWhenUnlocked,” the strongest protection class, when saving items in the keychain. This protection class tells the system that data should be encrypted when the user is not actively using your application. If your app needs to access this data while running in the background, you may need to fall back on the “kSecAttrAccessibleAfterFirstUnlock” protection class, which ensures the data is encrypted only until the user has unlocked the device after boot.

    Embedding Vulnerable SDKs

    When an SDK is linked into your application, you’re also implicitly exposing your app to any potential vulnerabilities in the SDK. Compromised SDKs have led to a variety of mobile app attacks, such as a vulnerable AFNetworking version leading to data compromised through a MitM attack. Without a security audit of the SDKs used within the app, developers are blind to the potential vulnerabilities they are introducing.

    Allowing Third Party Keyboards on Sensitive Input Fields

    While installing third party keyboards are useful for user customization, they introduce a new vector for data leakage. This is because the developer of a third party keyboard may be able to extract any information typed on the keyboard. As a result, it’s in the user’s best interest to disable these keyboards when handling sensitive data, such as identifiable information or credit card numbers.

    Leaking PII to Device Logs

    It’s all too easy to leave debug logging, which may include PII, in production builds. Before release, validate that any log statements which might include sensitive data are scrubbed from the code. This might be achieved by way of flags, which only enable these log statements in debug builds. Since logs may be visible to anyone with physical access to the device, it’s paramount to exclude sensitive data from them.

    Since adopting the newest technologies often introduces unforeseen risks, defensive security is a constant endeavor. However, following these top 10 tips will increase your organization’s security posture and reduce vulnerabilities introduced by iOS risks.

  • Oracle Adds APIs to Java SDK To Advance DevOps

    Oracle Adds APIs to Java SDK To Advance DevOps

    Oracle announced it is making available the Java 14 software development kit (SDK), which provides access to several additional capabilities designed to help advance DevOps adoptions within IT organizations that still rely heavily on Java to build enterprise applications.

    Those capabilities include a set of application programming interfaces (APIs) to enable continuous monitoring of JDK Flight Recorder data and a set of APIs that make it easier to access foreign memory.

    In addition, via an incubator module Oracle is now providing access to a Packaging Tool that will enable developers to package Java applications and runtimes for distribution in platform-specific formats. That capability is being exposed as an incubator module because the associated APIs have not been finalized, which means they are subject to change in future releases.

    The Java 14 SDK adds Java language support for switch expressions to be used as either an expression or statement and extends the availability of the low-latency Z Garbage Collector to macOS and Windows.

    Finally, Oracle has added support for a Pattern Matching capability that eliminates the need for boilerplate code and a preview of a tool that makes it simpler to declare data immutable.

    Aurelio Garcia-Ribeyro, director of product management for Java SE, said a lot of the capabilities being added to Java SDK were developed as part of the ongoing Panama and Amber research projects that in some cases have been in development and testing for years.

    Despite the rise of rival programming languages, Garcia-Ribeyro said enterprise IT organizations continue to rely on Java to build most of their applications, especially mission-critical backend systems.

    The challenge is modernizing the processes via which Java applications are built and deployed. Many organizations, for example, are embracing containers and microservices to build next-generation applications. As that transition occurs the need to embrace best DevOps practices becomes more apparent because applications themselves are becoming more complex. The upside, of course, is that microservices also make it possible to build more robust applications faster, which has become a critical requirement as organizations embrace digital business transformation.

    Of course, no two organizations are likely to be at the same point on the DevOps maturity curve. In fact, in many cases, DevOps adoption is being driven from the bottom up as developers embrace new capabilities being added to familiar tools such as the Java Development Kit from Oracle. In some cases, the SDK will be used to build new applications while other members of the development team employ it to modernize legacy applications. Before long, however, IT operations teams start to realize how monitoring APIs and packaging tools are transforming how IT operations are managed.

    Naturally, Oracle is hoping all these new capabilities will help keep organizations focused on Java as the primary means for building enterprise applications at a time when developers have more options than ever. The one thing that Oracle has most in its favor is that most organizations don’t want to retrain developers to learn how to master a new programming language unless it can’t be avoided.

    — Mike Vizard

  • DevOps Chat: Security Graph SDK Powers Better Policies, with vArmour

    DevOps Chat: Security Graph SDK Powers Better Policies, with vArmour

    The increasing breadth and complexity of the environments we manage are nothing short of breathtaking. Understanding the security risks and applying policies across the cloud, multi-cloud, private clouds and a plethora of software technologies is a challenge faced by every enterprise.

    vArmour recently announced version 5 of the vArmour Application Controller, which opens more significant access to vast amounts of information the Security Graph represents and organizes through its Security Graph and SDK. By streaming cloud, network and agent information into the Security Graph, enterprises now have a centralized understanding of application relationships across their multi-cloud infrastructure, enabling centralized risk and policy management that is simple, accurate and secure.

    In this DevOps Chat, Marc Woolward, vArmour CTO and CISO, and I discuss how establishing and assessing policies becomes more manageable through expanded access to information about software infrastructure, systems, environments across the organization.

    As usual, the streaming audio is immediately below, followed by the transcript of our conversation.


    Transcript

    Mitch Ashley: Hi, everyone. This is Mitch Ashley with devopsy.kinsta.cloud, and you’re listening to another DevOps Chat podcast. Today, I’m joined by Marc Woolward, who is CTO and CSO at vArmour. We’re talking about policy and risk of cloud applications, how to manage it. Marc, welcome to DevOps Chat.

    Marc Woolward: Thanks, Mitch. It’s great to be here.

    Ashley: Well, thanks for flying over from across the pond, too. [Laughter] You’re in the U.S., with your U.K. accent, so thanks for being on.

    Woolward: There’s quite a few of us out here in Silicon Valley. To be honest, I think it’s half British.

    Ashley: There are, there are quite a few of you here. [Laughter] Would you do us a favor and just introduce yourself, tell us a little bit about you, what you do at vArmour, and just a brief on what vArmour does.

    Woolward: Yeah, of course. Alright, well, hi, everybody. As Mitch said, I’m Marc Woolward, I’m chief technology officer and also, in my spare time, the CSO at vArmour. My background is, I’ve been at vArmour for five years or so and I look at kind of the strategic direction, I speak to the senior technologists and our customers to understand their challenges with cloud security, and I lead some functions such as, you know, the data science team, and handle things like CCPA and GDPR in my role as CSO.

    So, my background is, before I joined vArmour, I was a technology fellow, and I was the CTO for telecommunications and networking at Goldman Sachs. I think I was there for 18 years. Did lots of things there. One of the interesting parts of the role of a tech fellow at Goldman Sachs is, you kinda get involved in all sorts of things. So, I was a member of the private cloud architecture team, you know, almost a decade ago, we built one of the first private cloud environments. And also, I had an interest in application resilience and application design patterns, despite my background keynote infrastructure. So, that kinda set me up really well for a job in a product company in Silicon Valley.

    Ashley: Yeah, very much so, especially the proliferation of cloud and all of that. So, let’s jump into it. I think we’re gonna talk about an announcement that was made back in October—what was it, version 5 of the application controller from vArmour?

    Woolward: Yes.

    Ashley: Can you tell us a little bit about what that announcement was, and then we can get into some of the effects that you’ve seen in the market from it?

    Woolward: Yeah, of course. Well, I mean, first of all, I think I probably should tell everyone a little bit about what vArmour does.

    Ashley: Oh, yes. Please.

    Woolward: So—yeah, no problem. I didn’t answer that in your last question. So, really, we focus on helping our customers to understand how their applications behave within cloud and multi-cloud environments. So, we have a risk and a policy engine that kind of builds a picture of your application behavior, its dependencies, and suggests the ways in which the application should be secured from a policy standpoint, and we help to make it—we make it simple for our customers to implement safe, secure, simple policies within cloud environments.

    So, what version five was all about, underpinning the application controller function itself is a security graph, and affecting that is a graph that describes all of the nodes, you know, the compute instances, the Kubernetes pods, the servers within a multi-cloud environment and the relationships between them. And what we’ve been doing is enriching that graph with all sorts of information about the application, compliance requirements, information about what the application does, is it there, what ___, what realm does it run in, what region does it run in?

    And really, what version 5, release five was about was opening that up and exposing more of the information within the graph so that customers can benefit from it more. So, what that means is the ability to plug more and more information into the graph to gain more value out of it. Things like information that reside in CMDBs, information from systems that handle vulnerability management, information from control planes, things like Kubernetes so that that information within the graph becomes richer and richer and more valuable. And it can be used for all sorts of use cases, and it also allows companies to build the policies based upon their view of risk and their view of their applications, whether that’s compliance driven or risk driven or business unit driven.

    Ashley: Now, can you kinda dig down and open up the hood a little bit more for us? Talk about how all this information gets into vArmour addition the application controller. Are you taking it from logs, configurations, active applications? What are some of the sources for this?

    Woolward: Yeah, and—great question. And what I do, I’ll start out by answering that by saying, in the cloud, we do not have a deficiency of data. So, if you’re running a reasonable sized cloud environment, you have tremendous volumes of logs—you know, cloud trail logs, flow logs, all sorts of event based information. And that’s—well, event based data. And that’s data.

    The problem with that is data—it’s unstructured, and it’s in huge volumes and it’s very difficult to kind of glean too much value from it. And what the application controller does is, it takes the data and it transforms it into knowledge. So, it provides you with insight into your application, which makes it a lot easier to make good security decisions.

    Ashley: Mm-hmm.

    Woolward: So, I’ll kinda come back to that in a minute. But the way that we do it is, we have a distributed telemetry pipeline where we use edge compute functions distributed out to the cloud environments that consume the logs and also consume events off of event buses and APIs. So, when a compute instance is deployed, we pull all of the metadata associated with it.

    The edge compute function we call message bus summarizes that data, enriches it, and then distributes it into the centralized graph where we effectively are transforming that data from being the individual flow log information into adding information into an edge within a graph, which represents the relationship. So, all the time, we’re enriching and summarizing, and that enrichment provides context, which makes it a lot easier to understand what your application is all about.

    Ashley: Well, and given the dynamic nature of our applications—cloud native, all of that, whether it’s Kubernetes clusters instances, microservices, just knowing what you have is half the battle, more or less what’s this information telling you? So, that’s got to be a value, too.

    Woolward: For sure. And, you know, Kubernetes is a fantastic example. Because if you’re capturing that information at the wrong level, if you’re looking at the IP address level or even the pod level, there’s a tremendous amount of noise in there and it’s very temporal and it doesn’t make any sense. If you can consume that at the abstraction, that makes sense to the application, so that would be at the deployment or at the service level and you ingest that into the graph you can build a picture of your application over time.

    And then when the, kind of the instantiation that’s just been deployed now varies from that model, you can see it very quickly. So, what we’re trying to do is summarize the information and represent it as—I say represent it as knowledge while continuing to process kind of the very dynamic and very high volume data and look for the anomalies and look for places where it varies.

    Ashley: That sounds, too, like a perfect application for a graphing technology to be able to visualize, explore, dig in deeper, back out, look at it at different levels.

    Woolward: Yeah. For sure, and you know, like I said, my background of working at Goldman and working in financial services, graph technology is fantastic for describing relationships, and that relates to risk. So, if you look at financial risk modeling, that has been almost the archetype application for graph technology for over a decade. I really would take that same approach and that same principle to cyber risk and cloud security risk.

    Ashley: Very good. Now, I know also that you’ve introduced an SDK with this. What are some of the applications where customers might want to use the SDK?

    Woolward: The whole point of the SDK—so, we integrate with all of the common cloud environments and we integrate with SDNs and the other product is designed to integrate into these different environments, just as part of the product out of the box.

    Ashley: Mm-hmm.

    Woolward: But what we’ve been finding with our customers is, they have different repositories for this context that would enrich an understanding of risk. So, if you have a vulnerability scanner, you have a tremendous wealth of information about the posture of the individual systems running in your environment. By plugging that into the graph, and by using the SDK, it’s very easy to do that for whatever system you’re using, you can begin to ask questions like, “Well, for my application, do I have any dependencies on systems with, let’s say, a CB severity of seven or above.” So, the SDK is a way of pulling in the vulnerability information, pulling the specific fields that are of value to you from your CMDB from, say, your service now, effectively plugging in that context that kind of illuminates your whole kind of understanding of your application and your risks.

    So, really, it’s about allowing our customers to integrate the data sources that matter to them into this graph that plugs into their cloud.

    Ashley: Mm-hmm. So, both in kind of an in and out application—bring in more data, also be able to pull it out for other uses reporting.

    Woolward: Yeah. That’s a superb point. I missed that. Another application that customers use the graph for is, embedded within the app controller, we have classification engines. So, what we do is, we will classify systems based upon our understanding of their behavior, based upon the relationships they have and the systems they have relationships with, we’ll classify them.

    So, one great use of the SDK is to compare the results of our systems classification with the information within a CMDB. So, you know, does your intent, which is in the CMDB match what’s actually happening in the cloud environment?

    Ashley: Mm-hmm.

    Woolward: And by doing that, what you can do is, you can validate that your inventory information is correct, is accurate, continues to be so—which, again, improves your security posture because, you know, one of the fundamental pillars of security is understanding what you have, and having an accurate understanding of the systems that you want to secure, so yes, for sure.

    Ashley: Absolutely.

    Woolward: But, you know, it’s a two-way thing, the SDK.

    Ashley: Well, and you’ve got a little bit of time under your belt with GDPR and we have the California Consumer Privacy Act coming up here. How does this kinda technology help satisfy, meet, report compliance—what are the various ways that you could leverage vArmour and the application controller to help you with those challenges to meeting regulatory requirements?

    Woolward: For sure. Yes, so, I mean, there were different regulatory frameworks that are more or less specific about the security controls required. So, if you take something like PCI, it’s very specific and it’s very directed in terms of the way in which you structure your controls. So, the app controller can allow you to scope your in scope infrastructure around your card holder data environment and build the layers of controls around the tiers of systems, according to the PCI DSS. So, it’s very good at doing that.

    If you look at something more abstract, which talks more about the outcome rather than the means of getting to the outcome—so, if you say it’s something like GDPR where you’re looking at protecting personal information relating to data subjects in Europe or CCPA where it’s more around protecting the personal information around California based consumers, that really comes down to managing risk and ensuring that the control—suitable sets of controls are placed around the systems that either store or process this information. And the first step to do that is to understand the scope of the problem and the scope of the relationships of the systems that are processing this personal information.

    So, the app controller, first and foremost, can allow you to understand, you know, the scope of these environments and begin to put controls and reporting around their behavior and access to those systems. So, it all starts from scoping and understanding your environments and ensuring that you can put the controls around the—you know, place the controls around the edge of them, and you continue to monitor that those controls are effective and that, effectively, in the cloud is what the app controller does.

    Ashley: Mm-hmm. Very good. Well, I certainly don’t profess to be an expert on either of those two regulatory frameworks. [Laughter] I’m really curious, we’re about a month, month and a half in since you’ve released version 5. As a former product creator myself, it’s always interesting to see what people do with new technology, new versions. But also, what you didn’t expect them to do with it. Have you seen kinda instances of both, you know—yep, we thought we’d help customers this way, it’s worked out that, and then we’ve also seen some interesting ways they’re using it they didn’t think they would.

    Woolward: Yeah. So, I’ll start with kind of what we expected and kind of the, if you like, the continued illustration of the value that we designed the product to offer. One of the things that we never—well, I never fail to be amazed by is, you deploy our system within a cloud environment and it begins consuming the telemetry. And within an hour or so, the graph is already beginning to hydrate and you’re finding hundreds or thousands of workloads.

    And all of a sudden, the extent of the interrelationship and often the external dependencies, the relationships outside of the VPC or outside of the VNET kind of are visualized. And almost every time, as we sit there for the first few hours with the customer, we’ll get into the same discussion about, “What’s that relationship? Oh, I have a dependency on something in GCP.”

    So, generally, that kind of uncovering the unknown and unsuspected dependencies opens up a whole kind of, you know, can of worms for understanding what’s going on here and ensuring that the correct policies are in place and ensuring that everybody  understands the extent of the attack surface and the blast radius. So, that, we always see, and that’s just accelerated with version 5.

    In terms of what was less expected, that’s the beauty of the SDK. So, the SDK allows the customer to plug in the information and the metadata that’s important and pertinent to them. An area where I didn’t really expect it was actually the application not just to your traditional cyber risk and your attack surface and your blast radius, but asking some interesting operational questions.

    So, this use case came up about two weeks ago where a customer was taking kind of an operational term for their applications and plugging it into the graph, and asking the question around, for my critical tier applications, my systemically critical applications, if one of their dependencies, one of the applications that they depend upon for, I don’t know, reference data or for other types of communication, like communications gateways failed, what would be my recovery time?

    And all of a sudden, what you can do is, you can draw within the graph the relationship between your application and the dependencies and plug in that recovery time objective, and all of a sudden, I understand that if application A, B or C failed, I might be waiting eight hours for recovery, whereas my system has a recovery time requirement of one hour.

    Ashley: Mm-hmm.

    Woolward: So, they’re beginning to ask these questions that you would not expect from, necessarily, a cyber tool around operational risk. So, I think that’s the beauty and the power of the graph—it allows the customer to think about, what does risk mean to them, and they can plug the information or plug the data in that they require and then they can ask these questions that lead them to knowledge.

    Ashley: Excellent, yeah. It sounds like both information, operational information, but also behaviors of what’s happening between applications and greater insight into it.

    Woolward: Absolutely, yeah. Yeah, for sure. And I think the other thing, I mean, the final thing I’d say is, if you look at most of these data breaches over the last year or two, it kinda comes down to, if you look at cloud and you understand the way that security works, it’s this shared responsibility model. So, the cloud service providers provide a tremendous array of tools—you know, micro-segmentation, identity access management policy enforcement. There’s a tremendous suite of security capability there.

    The problem is always that the lack of knowledge about the application means that the policies that are written and the permissions that are provided by the customer, because that’s their side of the, kinda the shared responsibility model have been deficient. And what the application controller allows you to do is to build the policy in a simple fashion that’s secure and meets your business requirements, and then that’s allowing our customers to meet their part of the shared responsibility model for cloud security.

    Ashley: Mm-hmm. Wow. Well, I feel like we’ve barely scratched the surface and we’re already out of time. Hopefully, we can get you back and we can explore this some more as we get closer to the CCPA coming into effect in January.

    Woolward: Yeah, and as the CSO of a California based company, I’m obviously spending a bit of time on that as well, so.

    Ashley: I’m sure you are.

    Woolward: That’d be fun.

    Ashley: Yeah, exactly. Well, Marc, thank you so much for being on DevOps Chat with us.

    Woolward: Yeah, it’s been a real pleasure, Mitch. Thank you—thank you for inviting me.

    Ashley: Absolutely. The pleasure has been ours. I’d like to thank my guest, Marc Woolward, CTO and CSO with vArmour and of course, thank you, our listeners, for taking your time to join us and listen to this podcast episode. This is Mitch Ashley with devopsy.kinsta.cloud. Have a great day, and be careful out there.

    — Mitchell Ashley

  • Testim Adds SDK to AI-Based Testing Platform

    Testim Adds SDK to AI-Based Testing Platform

    Testim this week launched a beta release of a software development kit (SDK) consisting for a set of JavaScript application programming interfaces (APIs) that will enable DevOps teams to build tests that leverage machine learning algorithms from within their integrated development environment (IDE).

    Company CEO Oren Rubin said the Testim Development Kit makes it possible to call capabilities such as the ability to record user interface interactions via an application programming interface (API).

    The Testim approach to applying artificial intelligence (AI) testing differs from rivals in that Testim allows DevOps teams to fully inspect how algorithms construct a test, he noted. DevOps teams can also customize those algorithms to fit their own requirements, which is critical when it comes time for DevOps to explain how tests were conducted as part of a compliance audit.

    Testim will continue to provide access to its platform via a graphical user interface, but with the edition of the SDK, Rubin said his company expects to see an increase in the number of DevOps teams that will incorporate Testim within the context of continuous development/continuous deployment (CI/CD). Once that occurs, the number of tests those teams will be willing to run against software before it’s deployed in a production environment should also increase, especially as more developers leverage APIs to create their own tests, Rubin said. That doesn’t eliminate the need for another set of eyes to test an application, but it should reduce the number of common errors made before any piece of code is tested by someone else on the DevOps team.

    One of the most time-consuming elements of any DevOps process is the time it takes to create tests for each application. The Testim platform employs machine learning algorithms to discover the entire application environment and then begin creating appropriate tests. As DevOps teams modify those tests, the Testim platform continues to learn how to build tests the way the DevOps team prefers.

    The Testim platform doesn’t eliminate the need for testing expertise on the DevOps team, but it does enable organizations to scale their testing processes by augmenting whatever testing expertise they have on hand to reduce bottlenecks and improve overall software quality. Those algorithms also provide the added benefit of never taking a day off or quitting to take a more lucrative position elsewhere.

    When it comes to AI, there is naturally a lot of fear and loathing. On the one hand, IT professionals become concerned AI will replace them. On the other hand, they are often disappointed when machine learning algorithms don’t instantly automate a process to their satisfaction. It takes a significant amount of time for algorithms to learn how any IT environment operates, with each update to that environment requiring those algorithms to discover new functions. At this juncture, it’s not a question of whether AI will play a role in DevOps processes, but rather to what degree. Given the repetitive nature of testing, Testim is betting application testing will prove to be an area that lends itself to AI sooner than later.

    — Mike Vizard

  • Pulumi Advances DevOps on AWS

    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