Category: DevSecOps

  • Five Great DevOps Job Opportunities

    Five Great DevOps Job Opportunities

    devopsy.kinsta.cloud is now providing a weekly DevOps jobs report through which opportunities for DevOps professionals will be highlighted to better serve our audience.

    Our goal in these challenging economic times is to make it easier for DevOps professionals to advance their careers.

    Of course, the pool of available DevOps talent is still relatively constrained, so when one DevOps professional takes on a new role it tends to create an opportunity for others.

    The five job postings shared this week are selected based on the company looking to hire, the vertical industry segment and, naturally, the pay scale being offered.

    We’re also committed to providing additional insights into the state of the DevOps job market. In the meantime, for your consideration:

    Dice.com

    R&T Deposit Solutions
    New York, New York
    DevOps Engineer
    $145,000 to $175,000

    Indeed.com

    Caterpillar
    Chicago, Illinois
    DevOps Engineering Manager
    $141,000 to $178,000

    SimplyHired.com

    Takeda Pharmaceutical
    Boston
    Machine Learning Infrastructure/Platform Engineer
    $130,000 to $186,000

    LinkedIn

    M&T Bank
    Wilmington, Delaware
    DevOps Manager
    $123,000 to $206,000

    CareerBuilder.com

    Fidelity Investments
    Westlake, Texas
    DevOps Engineer
    $120,000 to $160,000

  • What DevOps Teams Should Know About Phishing and the Supply Chain

    What DevOps Teams Should Know About Phishing and the Supply Chain

    The DevOps pipeline is a critical component in any organization, and it has broader implications that can affect other organizations as well. Some of the biggest cybersecurity breaches of recent years were supply chain attacks, in which attacks infiltrated the development systems of one organization to break into the systems of its customers downstream. Needless to say, this had catastrophic consequences for the organization under attack.

    According to Deloitte, 91% of cyberattacks begin with a phishing email, and supply chain attacks are no exception. By understanding this common threat and preventing it, DevOps organizations can significantly improve their resilience to these attacks. Of course, phishing awareness and prevention should come as part of a broader cybersecurity program that addresses additional supply chain risks. 

    What is Phishing?

    Phishing is a method used by cybercriminals to trick you into revealing sensitive information. They do this by creating a replica of a legitimate website or email and asking you to provide personal information such as passwords, credit card numbers, and social security numbers.

    Phishing attacks can take various forms. Some of the most common include email spoofing, where the attacker sends an email that appears to be from a trusted source, and website spoofing, where the attacker creates a fake website that looks identical to a legitimate one.

    Regardless of the method used, the goal is the same: To trick you into providing sensitive information. Phishing is a serious threat to both individuals and businesses. It’s not just about losing money; it can also lead to identity theft, damage to your reputation, and even legal consequences. Get more background in this detailed blog post about phishing prevention.

    Implications of Phishing for the Software Supply Chain

    Entry Point for Larger Attacks

    The supply chain is a prime target for phishing attacks. This is because it provides an entry point for larger attacks. For example, a phishing attack on a supplier could compromise their security, allowing the attacker to infiltrate organizations that use their software downstream.

    This kind of attack can have devastating consequences. It could lead to the theft of sensitive information, disruption of operations and even compliance risks.

    Information Theft

    Information theft is one of the most significant risks associated with phishing attacks on the supply chain. When a supplier falls victim to a phishing attack, the attacker can gain access to a wealth of valuable information belonging to the supplier and, in some cases, to its customers or partners. This could include everything from financial data to proprietary business information.

    The loss of such information can have severe implications. It could lead to financial loss, damage to the company’s reputation, and legal consequences.

    Disruption of Operations

    Another significant risk associated with phishing attacks on the supply chain is the potential for disruption of operations. A successful phishing attack could compromise a supplier’s systems or the systems of organizations that rely on that supplier, leading to downtime and delays in the supply chain.

    This kind of disruption can cause significant damage to a business. It could result in lost sales, damage to customer relationships and even the potential for business failure.

    Compliance Risks

    Lastly, phishing attacks on the supply chain can lead to compliance risks. Many industries are subject to strict regulations regarding data security. If a phishing attack leads to a data breach, the companies involved could face hefty fines and penalties.

    Additionally, a data breach could damage a company’s reputation, making it harder to do business in the future.

    Practical Steps to Secure the DevOps Pipeline

    1. Implementing Security Awareness Training

    The first and most crucial step in countering phishing risks is implementing security awareness training. This involves educating all team members about the various forms of phishing attacks and how to recognize them. Interactive sessions, workshops and webinars can be very effective in conveying this knowledge.

    Another vital aspect of security awareness training is teaching employees how to respond to suspected phishing attempts. They should know the steps to take, such as not clicking on any links in a suspicious email, reporting the incident to the IT department and deleting the email.

    2. Deploying Anti-Phishing Tools and Technologies

    While awareness and education are critical, they are not enough on their own to protect against phishing attacks. This is where anti-phishing tools and technologies come into play. These tools can help detect phishing attempts and prevent them from reaching the intended targets.

    There are several types of anti-phishing tools available, including email filters that detect and block phishing emails, browser add-ons that warn users when they attempt to visit a phishing website and AI-based tools that can recognize even sophisticated phishing attempts.

    3. Incorporating Security into the Software Development Life Cycle (SDLC)

    Incorporating security into the software development life cycle (SDLC) is another crucial step in countering phishing risks. This means considering security at all stages of software development, from planning and design to coding, testing and deployment.

    Security should be a primary consideration when designing software systems. This includes designing systems to be resilient to phishing attacks, for example, by using secure coding practices to prevent common vulnerabilities that phishers can exploit.

    During the coding and testing stages, it’s crucial to conduct regular security audits and vulnerability assessments to identify any potential weaknesses that could be exploited by phishers. Any identified vulnerabilities should be promptly addressed.

    Finally, during the deployment stage, it’s vital to ensure that all software components are securely configured and that any security patches or updates are applied promptly. This can help prevent phishing attacks that exploit software vulnerabilities.

    4. Regular Phishing Simulations and Drills

    Finally, conducting regular phishing simulations and drills is an excellent way to test the effectiveness of your phishing prevention measures. These simulations involve sending mock phishing emails to employees to see how they respond. The results can provide valuable insights into areas where further training or technical measures may be needed.

    Phishing drills should be conducted regularly and should cover various phishing techniques. The results of these drills should be shared with all team members, along with feedback and recommendations for improvement.

    Phishing simulations should also be used to test the effectiveness of your anti-phishing tools. If a significant number of mock phishing emails get through your defenses, this could indicate that your tools are not effective and need to be updated or replaced.

    Conclusion

    In conclusion, the integrity of DevOps pipelines—and, by extension, the entire supply chain—is increasingly under threat from phishing attacks. This is a grave concern given the potentially devastating implications ranging from data theft, operational disruption, legal consequences and considerable compliance risks. 

    However, organizations can proactively safeguard their DevOps pipelines by fostering a security-conscious culture underpinned by regular training and awareness programs. Deployment of state-of-the-art anti-phishing technologies and the integration of security at all stages of the SDLC can further strengthen defenses. 

    Additionally, regular phishing simulations and drills can be instrumental in testing and enhancing the resilience of these measures. The war against phishing is continuous and staying one step ahead of the threat requires constant vigilance, innovative strategies and robust technical defenses.

  • JFrog swampUP: Addressing the Advent of AI

    JFrog swampUP: Addressing the Advent of AI

    At JFrog SwampUp 2023, the buzz with all about AI, especially with JFrog’s announcement of Machine Learning (ML) Model Management capabilities. These conversations around AI and ML reflected these technologies’ growing influence and importance in the DevOps world. How much of the generative AI conversation is just hype, though? And what does that mean for AI and ML as a whole? Alan Shimel, CEO of Techstrong Group, and I sat down with Stephen Chin, VP of DevRel at JFrog, to find out.

    As far as Chin is concerned, even as more companies create and leverage AI models, these models must be managed like any other software component. Chin said JFrog Artifactory acts as a staging ground to operationalize models using DevSecOps best practices. Algorithms and models will continue to grow in size and complexity, and they will require robust processes around deployment and management – just like any other software artifact. The key, Chin said, is to think of ML as just another development language and leverage tools that standardize and streamline working with it. Compared to traditional enterprise applications, though, DevOps workflows for AI/ML are still relatively immature, but Chin said JFrog’s new model management capabilities aim to provide that missing automation and governance using DevSecOps best practices for governance, security, and licensing compliance.

    Additionally, Chin noted that AI/ML have become essential for development teams to keep up with the explosive demand for code. At this point, AI has become table stakes. In the AI arms race, the winners are those who understand AI has become a vital development tool to enhance productivity. In terms of job security, the losers are the ones who can’t keep up with the volume of code. According to Chin, you are out of the running if you don’t embrace AI.

    Looking ahead, AI will not make developers obsolete, though – quite the opposite. Given the quasi-unlimited appetite for new code, Chin emphasized that developers who embrace AI will have more work than ever. One way to think of it is that AI provides a new form of “outsourcing” to boost human productivity, much like previous waves of innovation in computer science.

    When it comes to security, there are still challenges that need to be addressed; code generated by today’s AI solutions still has significant drawbacks like potential data bias, lack of explainability and simple errors. In the long term, though, Chin believes AI itself will provide the solution to secure an exponentially growing codebase, given its superior scale. Just as AI will make individual developers more productive, it can also supercharge security teams – but it can also empower bad actors. The key will be continuing to democratize the benefits to even the playing field. AI promises to be a transformative technology on the scale of the Bronze Age or Quantum computing, Chin said, but the path forward will require humans and machines working together to ensure it’s used for good.

    It’s clear that the pace of innovation in AI and ML is rapidly accelerating. As these technologies become further democratized and integrated into developer workflows, they promise to transform how software is built and secured, Chin said. Companies must take advantage of this technology innovation by providing the pipelines and governance for this software revolution, he added. Chin believes the future will likely see a more symbiotic relationship between humans and AI assistants collaborating to generate, refine and safeguard code. By proactively shaping the responsible use of these technologies, it’s possible to maximize the benefits while minimizing the risks. While this journey has only just begun, the destination is an exciting new era of human potential unlocked by AI, Chin said.

  • Splunk: Creating a Resilient and Dynamic Organization

    Splunk: Creating a Resilient and Dynamic Organization

    Mitch Ashley: I have the pleasure of being joined by Ryan Kovar, Ryan is a distinguished tech security technologist and leader of SURGe with Splunk, and Cory Minton who’s field CTO for The Americas with Splunk. Welcome, guys.

    Ryan Kovar: Thank you.

    Mitch Ashley: Good to be chatting with you both. A topic that’s very top of mind for CISOs or IT leaders, of course, is how do we create a resilient and dynamic organization that can keep pace with the business and the change that we see in the technology landscape, whether it’s our own infrastructure, own application portfolio, cloud, et cetera, all of those things, but also, of course, the tax services that are evolving and changing as what the bad guys, the threat actors, are doing. We’ve also not only got to have a great and resilient technology stack, but organizationally, process-wise, all of those things have to fit together into a cohesive strategy.

    We’re here to talk about that, thinking about it as an IT leader, whether you’re in security or IT or combination of both, and discussing your all expertise experience, but also you talk to a lot of customers as leaders in Splunk and the kind of things that you do. Cory, it’d be great to have you kick things off. Maybe we should start with if you want to start with the people domain or maybe you want to set it up a little bit differently. I’d love to hear your initial thoughts on this.

    Cory Minton: Yeah. No people’s perfect. I think the people process technology lens on tackling any sort of problem for leaders today is an appropriate framework. I’m happy to talk about the people portion of building great cybersecurity and IT organizations that, like you said, deliver resilience.

    Ryan Kovar: For me, at least when we think about this, you said IT leaders, and I think one of the big changes I’ve seen across for cyber for CISOs is it’s no longer IT or security. It is business leaders. When we started talking about people, that to me starts resonating because that is a cognitive change in how CISOs think of themselves and they think of their value, which we often get stuck in the technology part of people process and technology because a lot of us are technologists at heart, but I think the big change that Cory and I have seen when we start talking to CISOs and CIOs is this convergence of skills and the need to support the business differently.

    Cory Minton: Yeah, and it’s an interesting sort of people market, too. I think leaders have to think about the fact that, yeah, in technology, there has been some turmoil in some of the big tech companies, but there’s still a lot of really great talent out there. I think that there’s choice. With unemployment so low, and there’s, what, like 16 million jobs unfilled currently in the US and a lot of those being in the tech sector, people have choice and they have a place where they can go.

    I think, leaders, if they’re going to build a talent pipeline and build a great organization, they have to find folks where they are and bring them in and connect them to a value, a mission and a vision that they get excited about. Certainly, securing digital services and protecting against bad actors is exciting in and of itself for many folks, but actually connecting those people to how it affects the outcomes that matter to the business and that whole value creation process, I think, is a real critical skill for folks to understand today as they, again, are out communicating and interacting in the network, building networks of talent pools. I think that clear vision of why it matters and why the work that somebody would do with you matters is critically important.

    Ryan Kovar: That reminds me of the cliche, of course, that people don’t quit jobs, they quit leaders. When you flip that around, one of my mentors, Susan St. Ledger, told me, you can evaluate the success of a leader by how many people follow them to another company. I know right now, in this market, what I’m finding is people are staying longer because they like the people they work for or they like their leadership team, they like the culture. The money, even if they’re not making as much as they were last year because of inflation, the people I know who stuck around longest are the people happy with the people that they work for and work with.

    Mitch Ashley: It’s interesting when we talk about people. I’ve worked in part of my career where the sort of higher the purple unicorn that doesn’t exist, that got eight skills, that needs 20 years of experience for things that have only been around for three. We set our subs up to hire these phenomenal people of which there may only be a few in the world that are like that, but it’s about growing our people, but also growing our organizations, developing them. It’s not just hiring people. It’s building a team. It’s building an organization that’s got the right talent at the right time at the right place to match with the business needs, and that changes. That means you can’t always hire for it. You’re partnering for it. You’re working with companies like Splunk to bring in skills and expertise maybe you need for the moment, you need for a project, you need for strategy, all of those things. Love to hear your perspective about broaden what we think about people and how we incorporate that part of it into our strategy.

    Cory Minton: Yeah. I’ll say, top to bottom, start at the executive level down to practitioners. Everybody has a partner. Everybody has a consulting partner typically that they bring in to, like you said, fill those gaps where it’s a new skill, it’s a new technology, it’s a new capability that they’re trying to deploy for the reasons that they’ve chosen to do so. They’re valuable, but you may not have those skills internally. Training takes time and, oftentimes, just finding that partner that can help you solve that particular problem is incredibly important. I think, as the security landscape and, frankly, the tools being used to deliver and develop the latest digital services continues to get more complex, expecting to hire that skillset completely, probably not realistic especially as digital transformation objectives have an ebb and a flow of momentum and the amount of work being done on particular projects.

    Yeah, I see it as one of the top areas where, when I’m talking to CIOs and CTOs and CISOs, when they think about, “Hey, we want to deploy this new capability within Splunk,” or, “We’re, frankly, trying to figure out how to integrate better with our observability and IT teams to derive more value from the tools we’ve already purchased,” it’s oftentimes that people conversation of, “How do I actually leverage your talent to show us what good looks like and bring the experience from other companies similar to us that have already been down this path to, call it the cheat code, how do I do the thing that you guys already know how to do? How do I buy that capability?” Oftentimes, it’s through people.

    Ryan Kovar: My experience, I’ll go the other side of the halo and horns there down to just the nitty-gritty hiring. Recently building out my team, I intentionally carved out three slots for entry level, early career folks into our cybersecurity team, which is pretty rare for Splunk and pretty rare for a lot of security research teams, but the way I did that was really rewriting the job description to be embracive of second-career people. I actually really dislike the term “there’s a problem with the pipeline for hiring”. I think that’s completely false. The problem is not in the pipeline. The problem is we have a valve on incredible talent and gate-keeping who actually gets into the pipeline. We do see a problem with the pipeline when I start looking for folks who are underrepresented in cyber especially 15, 20 years down.

    What I don’t see is a problem of, basically, the reservoir. The reservoir is healthy. The reservoir is huge, but people either don’t feel like they’re welcome or they self-select out especially of cybersecurity. For me, a lot of the people problems that we have, if we can start working on the problems of today, future us, as a security leader, will be very happy if present me can help unlock that reservoir by turning open the valve by creating job descriptions and roles that are less around years of experience and understanding technologies that I can Google or generative AI my way through today.

    I think there’s just a lot of flexibility especially for folks who have critical thinking and communication skills. I can teach you TCP/IP. I can’t teach you how to communicate. I can’t teach you how to synthesize information. I need you to walk in the door with that. Something for me around people and these hiring gaps that we see is really about being more embracive of nontraditional cybersecurity and IT roles and then also facilitating them in ways they can succeed.

    Mitch Ashley: Well, and it’s also about hiring for what we need today, but also where the ball is going to be downfield when the ball lands. Part of that is hiring people who have demonstrated their ability to learn, adapt. Yesterday, they were TCP/IP expert. Today, They’re the security threat landscape expert. How did they do that? How did they get there? They learned it. It may have been on the job, but there’s also a lot of self-motivation and just skill in that learning, and that repetitive learning skill is I think something you can harness or leverage to accelerate their career as well as what you need.

    Cory Minton: Absolutely. It’s one of those things that, always, some folks get turned off. As Ryan said, sometimes there’s a valve, and one of those valves is like, “You must have a college education.” While I don’t necessarily believe that a college education is always the right thing, I think what it proves if you have one is that, as you said Mitch, you’re able to go through a structured learning process in an organization that’s institutional, understand dynamics and things and achieve an objective which was set before you that had some measurable outcomes that you had to deliver, which I think is something true for all of us in a corporate responsibility job as we have to operate in an institutional environment. We have to consistently learn new things. We have to interact with people around us. I think college is a good measure, but, as Ryan said, oftentimes, a second career is maybe even a more powerful measure of somebody who’s done that successfully.

    Like Ryan said, the technical skills are learnable and, frankly, the fun part is some of the technical skills are actually getting obfuscated by advancements in technology. As we think about things like, Ryan, you mentioned, generative AI, we can make the joke, but, candidly, wouldn’t you rather hire somebody who’s got incredible cybersecurity skills and understands the landscape more so than somebody who’s just really good at crafting queries because then, if you have somebody that has that domain expertise as technologies like generative AI and other sort of assistive technologies continue to evolve, then the domain expertise becomes the most important because then you start interacting on a natural language way and you don’t have to have those same technical skills to get there, which I think is probably one of the most interesting uses for generative AI is actually bringing out the barriers for technical ability to execute in a job like security or IT.

    Ryan Kovar: Prompt engineering will be one of the most significant requirements for entry-level and mid-level jobs by next year, in my opinion, categorically.

    Mitch Ashley: We’ve already been through one generation. It’s called search engines. Now, we’re doing it with generative AI.

    Ryan Kovar: Yeah. Yeah. No. We’re talking about this, but the reality is I’ve been doing cybersecurity and IT since 1999. Cory, there’s enough gray there. I’m sure you’re about the same generation. When I started, there was no Google and you had to read the Microsoft TechNet documentation, and then there was Google, and I put 65 CD binder in the trash and said, “Never again.”

    The fun thing that I always tell people that I’m mentoring or advocating for in cybersecurity is I’ve been doing this for 24 years and, of the 24 years, I have about four years of knowledge that’s relevant. I have 24 years of wisdom, but four years of knowledge that’s relevant. Everything else, no one cares that I can fix Exchange 5.5 driven pub EDB and I know how to defrag a Windows NT 4.0 server. That doesn’t matter. That’s one of the great things about cybersecurity and IT in the general is that you can become a subject matter expert in something very quickly and not have the bias of age.

    Mitch Ashley: Well, let’s turn our lens to the process part of it, and we’ve talked a lot about people and we could talk a lot more about it. There’s some great conversations that we’ve had already about that. We’ve got to have processes that are well-oiled to highly tuned, but can be responsive of incident management when things happen. The organization now has to operate cross-functionally, the stove-pipes, the things that we’ve lived with for so long. Now, we have to operate cross-functionally. We’re trying to tear those down, but our processes have to work across those.

    I’m interested in your all thoughts about how are organizations, what do they best do to adapt to what we need today so we can be speedier, respond more quickly and more reliably to threats or incidents or needs of the business?

    Cory Minton: Yeah. Do you want to to hit it, Ryan?

    Ryan Kovar: No. Please, Cory, go ahead.

    Cory Minton: Okay. I was actually going to say it’s actually not even an option anymore. We talk about that they need to do it. It’s not an option. If you look at some of the SEC’s recent rulings on the disclosure of material and incidents that happen for publicly traded companies in the US, you have to report that. You have to have that cross-functional view of how if a cybersecurity incident happens or an IT sort of incident outage or breach, any of these categorical things that happen, if they have a material impact on operations that would affect shareholder value, then you must disclose those things, and so now the impetus is on every publicly traded company to get this figured out really well. It’s got executive buy-in now that we’re going to tear down the walls between security and IT operations and our engineering teams developing our next digital capabilities because, anywhere across that spectrum that we have a process breakdown, whether it’s externally caused or internally caused, if it’s material, we better report it.

    These are no longer like, hey, it’s a good idea. This is like “test that theory and report the results” kind of stuff that the SEC will send somebody to jail over. We’ve already seen some convictions on previously publicly traded companies on misreporting things. It’s no longer a game. We’re serious about this. I think, from a process perspective, one of the things I’m seeing is reaching across the aisle. CISOs are talking to CIOs and CTOs more so now than I’ve seen in the last couple of years because they have to understand those impacts and they’re looking to organizations that actually already do some of them within the company that are already being trusted by different pockets of the organization. They’re looking externally for that guidance and help, whether it’s from consulting partners that are, hey, advising on security operations or advising on software development capabilities or technology partners.

    I mean, even the CISA, the Cloud Infrastructure Security Agency, their recent strategy update talked about one of the key pillars of their annual strategy for resilience included technology partners that were going to help them achieve that resilience. I think we have the impetus. The measurement is required now. There’s no longer a game, and I think executives are starting to understand it and they’re looking external to say, “Who can help me deal with this?” No matter where we land on what is material and some of the legal questions on how it’s implemented, we still have to respond and we still have to report some of those capabilities. Now is the time to start reaching across the aisle and starting to ask questions of your partnerships that you have in the org on how can you help us solve this problem.

    Ryan Kovar: I look at things like DevOps which still today has a little bit of a carve out separate. In a lot of organizations, DevOps is a slightly different place than maybe traditional security and, well, certainly than security, and then possibly even different than traditional IT engineering or infrastructure. In today’s society or today’s world of technology, a lot of the security issues that organizations are facing are in their DevOps pipeline, and so I find it fascinating what Cory said. The SEC has this term, material finding. You have to report a material finding.

    Now, I as a security professional may very well know what that is, but, frankly, the DevOps world has gone feral to a point where the security organizations are not a part of it and so the DevOps team are the only ones who understand what the security implications are. They’re the ones finding it and, because they’re in a DevOps mind frame, they’re not stopping and saying, “Let’s create an incident. Let’s walk this through.” No. They’re just fixing it and they’re moving it on. That’s how the cloud works. That’s how DevOps works.

    There is this essential need for us as an industry to really start reaching more across because we are being outpaced by DevOps home growing their own SecOps without oversight, without the wisdom of the security world, but we can’t stay in the way of the business, which is why that’s so important for us to go across and understand this because now there’s regulatory requirements and the real world is people are going to move forward whether they like it or not, so get on that train.

    Cory Minton: Yeah/ it’s funny, Ryan, you say that. I was reading the SEC reports from JPMorgan Chase. Jamie Dimon, their CEO, said in the letter to shareholders he had two sort of funny juxtaposed statements that used the same phrasing, which I found interesting. He said two things he could not overemphasize, one was, “I cannot overemphasize the need for cybersecurity in our organization. Everything must be secure,” and then later in the letter he said, “I cannot overemphasize our need to deploy innovative technology,” which is exactly what you said. If my CICD pipeline is continuing to push updates, but I’m not applying those cybersecurity principles that, like you said, was incident review and forensics and actually looking into it, then we’ve missed the boat on this. One of the key parts of this SEC filing is you not only have to report the outage, but you actually have to from an annual reporting perspective talk about your processes that you’re using to ensure cybersecurity in those areas. That’s one of those that’s like the CEO is saying this to shareholders. We better pay attention.

    Ryan Kovar: The CEO of a bank that touches 20% of every dollar in the world every day, right?

    Cory Minton: We cannot overemphasize.

    Ryan Kovar: I love that example because I look at DevOps as a perfect world where I have no fear at all that the DevOps team will identify and remediate security issues very quickly and then continue to do so because they’re not looking at the larger picture. Why did this get ingested? Why do we have this happening? Why is this CRO a threat actor you may not know anything about a threat actor. You may not understand that Tampa strawberry as per Microsoft has a really significant interest in your organization, and one of their TTPs is actually moving up the chain and actually jumping ahead for software supply chain.

    That is something that I would not expect a DevSecOps engineer to understand, but that is where the context of a larger security world, and that’s why this resiliency message, this is why it’s working across aisles. It becomes so important for the process. I honestly think the technology is usually the easiest part of this. The people and the process to implement and secure the technology, way harder, way less interesting than most people, except nerds like me, but much harder.

    Mitch Ashley: Well, and what you really bring to light is that the security specialists are going to understand the threat landscape much better. DevOps developers, et cetera, know their environment focused on the things that they are. You mentioned Jamie Dimon. Those two things, he’s expecting us, our CEOs are expecting us to figure out how we bring that together, how we make that happen so we don’t have feral organizations, so we don’t have processes that are brittle when things really fall apart or our environments get more complex. I mean, that’s an obvious thing. They are complex and they’re getting more complex, and no one understands the whole thing, so we’ve all got to pull together and say there are three dimensions to this problem, not one, and here’s the steps. We together figure out how we fix this.

    Great. Well, let’s talk about the technology perspective then. Obviously, Splunk being a great technology company, have been around for a long time. I remember finding Splunk on the showroom floor in the early days still doing black T-shirts then just like they are today, a great company that you all work for. Let’s talk about some of the technology side of what’s important and, again, thinking about not just internal people and processes, but also third parties that we’re using like the Splunks of the world in our organizations and how you can help with this challenge.

    Ryan Kovar: I’ll start really easily on this one, and then Cory will actually say something much better. People buy software to solve their problems. That’s it. That’s the easiest way when I pay people. I didn’t come from a sales background. I was operational. I was a threat hunter for the government, threat intelligence at DARPA, places like this. I didn’t think about why I bought software until I worked for a software vendor. It’s very easy. You buy software to make your life easier, to solve a problem faster or to solve it better.

    When I look at what Splunk does, a lot of our recent efforts are really around this incremental growth of just making people’s lives better, making people’s lives easier, cutting down the barriers to do their job faster because that’s what people need, whether it be security, whether it be observability, whether it be traditional IT engineering, that to me is really what we focus on here at Splunk which is why I’m still here after nine years. We make people’s lives better and we allow them to fulfill the mission that they’re actually being paid for rather than fighting the software that they’re buying and paying money for. That to me really is at the heart of what we do.

    Cory Minton: Yeah, and I think, if anybody’s seen some of the Splunk messaging in the market, we’ve really rallied behind this idea of resilience, and I think it actually sums up nicely the things that we do which I think, based on the conversation we’ve just had about the people and process, things that are challenging organizations, I think we’re in a really unique place to be a partner, to be one of those partner organizations and be the software that people buy to make their lives easier because we sit in this unique place of being one of the few organizations that actually unify, tear down the walls between security, IT operations and those feral DevOps teams that are out there building the next digital services because our corporate mission is around resilience, and we think of that as a simple statement of, “How do you keep all this digital business secure and up and running?” Simple statement, but, secure, not a simple thing to do, and up and running oftentimes equally on simple thing to do.

    Ryan Kovar: Sometimes at loggerheads.

    Cory Minton: Yeah. Exactly, a pearl of either sort of objective. There used to be this term we called a MOM. We all love MOM, monitor of monitors. It sits above. It sits at an enterprise level, at a higher level to give you visibility. I think that’s what folks have maybe struggled with that we see. Hybrid cloud is reality, right? There’s lots of clouds, not one cloud. Clearly, there’s leaders in terms of revenue, and each quarter they grow at different paces, but candidly, even Michael Dell said some years ago, “The cloud is not a place. It’s more of an operating model.” As you see SaaS being part of cloud journeys, yes, data centers are still run by organizations. They just are run now in a much more orchestration pattern similar to cloud providers, and that reality of lots of silos across different landscapes is creating challenges.

    If you use one tool that’s provided by said provider, then, yes, you can secure and keep up and running that one particular cloud real estate, but what about how it’s connected across the organization? How about the ways that applications traverse deployment centers? I think that’s what we really see as interesting is organizations are leaning on Splunk especially in the macroeconomic conditions where everybody’s focused less on growth and more on profitability, so they’re looking at like, hey, how do I reduce the number of tools?

    Ryan Kovar: More out of less.

    Cory Minton: Yeah. Exactly. Do more with less. They’re looking at it and going, “Wait a second, so I have this network environ, this router, so my data center. I’m sending the logs from that thing to nine different tools. Why am I doing that?” That’s nine times I’m paying for that bit of data to be stored and processed and analyzed by some number of tools, and organizations are looking at it and going, “Maybe that’s not smart. Maybe that same piece of data has nine questions being asked of it, and is there may be a fewer number of tools that could answer those nine questions effectively to give me the outcome without having to have all this sprawl?”

    It’s a unique conversation that we’re in today. Candidly, the tools consolidation, that rationalization of tools is one, looking at data. The data deluge hasn’t stopped. As we talk about sending data to nine different places, well, as that data becomes richer, it’s no longer just logs. Now we’re looking at metrics for real time. We’re looking at traces for spanning. How does an application actually impact multiple sort of environments? The data is getting rich and large. Is it all equal? Should we all be sending it to the same place? Should we be treating it with some valuation?

    Those are conversations that I’m having today that technology is helping solve, and Splunk is doing some really interesting work in the data rationalization and in that tools consolidation area that’s making it easier for customers to do more. As Ryan said, you bought a piece of software to make your life easier. We’re trying to go out and help folks figure out how to make more lives easier with the software they already bought.

    Ryan Kovar: I’m just required to hit all the buzzwords, so I’ll say ransomware now. It’s fascinating to me. Resilience, as in the concept of business leaders and cybersecurity, CISO leaders having to come together, I think, partly is really being driven by this threat of ransomware because the first time a cybersecurity threat has consistently and continually impacted every aspect of a business where 10 years ago, 15 years ago, oh, APT1 from China, exfil data. Well, that was the big issue. Well, by the time you heard about in the news, it’s already done. It’s actually relatively small scale. The impact is we were compromised, there was a breach, and now we have to deal with the public relations fallout, the stock drop, and also we have to make sure this doesn’t happen again.

    With ransomware, it’s actually we’ve encrypted your critical business systems and you can no longer do business, and now you have questions of do we pay the ransom? Well, now you need to involve the finance or you need to involve your chief legal officer. Oh, it’s publicly out there that we have this security issue. You have to involve the PR team, the public relations team. Oh, it’s actually knocked out our core business. Oh, well, now you’re involving the sales org. Now you’re involving the IT org. It’s coming across all these different places, so it’s builds back into what tools do you have that facilitate this and then, going back to the people part that we touched on earlier, this is where someone needs to be across all of them because they need to understand the impact and actually drive those changes that are needed and, because of ransomware, we actually have to deal with it. We can’t just pretend it doesn’t exist. CISOs can’t just be nerds in the closet playing cyber. They actually have to be able to speak eloquently to their business leaders, to the board of directors and others.

    Cory Minton: Yep. I’m just going to jump on the bandwagon of buzzword bingo. One of the things we’re seeing a ton of, too, is we talk about new digital workloads constantly being brought in, new innovation, we’re hiring consultants to bring in and actually help generative AI get real in our organizations, there’s a lot of conversation about is generative AI threat versus risk? There’s a whole kind of conversation there, but one that actually, as we’re moving past the hype and the AI washing nonsense that’s happened in the market, once we’re getting to real, a lot of CISOs have been talking about or talking to are trying to figure out how do I deploy those technologies internally? How do I go find the models that I can train against my data sets that would actually go help my teams do their jobs better?

    What I would say is is that’s another one of those areas where, as you’re innovating and bringing in new technology, treat it like another digital workload. You’re still going to have to detect when something goes wrong. You’re still going to have to investigate when something goes wrong in that generative AI hallucinates, it has an outage, whatever, and you’re still going to have to respond to those outages and take those learnings and put it back into the operational process of how do you run that system more effectively.

    I think people need help oftentimes finding those consistent patterns that we have to deploy to just keep things securely up and running regardless of what the workload is under the covers, and I candidly see that as one of the greatest areas for leaders that are looking to partner with a professional services organization or an assay, those outside consultancies. There’s a lot of value there in having them help bring in the patterns especially on proven technologies to short cycle, increase your time to value or, excuse me ,shorten your time to value when thinking about those new digital workloads and making sure that they’re secure and up and running.

    Mitch Ashley: I like where you’re taking this, which is one I wanted to wrap with, which is our organizations are expecting us to innovate, not just ourselves innovate, but also support the rest of the organization to be able to innovate. You talked about Ransomware. The newest thing is they’re not encrypting your data anymore. They’re just threatening to release it, so it’s not a matter of losing the data. It’s losing control over it. AI is the next, maybe it’s the next boon to phishing. We may not be able to tell the difference between an email from a generative AI LLM that’s been trained on how our CEO talks versus a well-scripted, predefined email.

    These new kind of threat models as well as new technologies force us to innovate and find new ways to do things. We have to help our people with tools, technologies, processes. I’d love to hear some more thoughts about what do we do to set ourselves up for success to be able to innovate in a way that’s going to help support where the organization is today and where it’s going?

    Ryan Kovar: Well, I’ll make a slightly controversial opinion here. I don’t think there’s ever been a single technology that outweighs the benefits for the offense or defense. I look at generative AI as something that is going to liberate security organizations from the shackles of mundanity. It’ll democratize what we can do in terms of analysis. It will also do the same for the adversaries. The only people who will lose are those who are not taking advantage of this technology on either side.

    I really do believe that we can all up-level as we go through with different technologies just as the adversaries are. When we invented a trench or trench warfare in World War I, they invented the tank. When we invented an airplane, they invented anti-aircraft. This is a tit-for-tat thing, and there’s always a leap at some point. People created a star fortress and that stymied invasions until someone invented the cannon. Sometimes, defense beats offense and sometimes offense beats off defense, but it goes back and forth as you go.

    I don’t necessarily see anything that’s a semantic change in how organizations will defend, but I do believe, if you’re not paying attention, if you’re not innovating, if you’re not selecting vendors, if you’re buying software, if you’re not buying vendors who aren’t innovating, you’re going to have a very difficult time in the next five years because your adversaries absolutely are.

    Cory Minton: Yeah, and I would go maybe less digital and say we as leaders cannot underestimate and cannot undervalue investments that we make in our people and our business culture today that create space for the learning and the development and the skills attainment that Ryan talked about, being critical. Leaders must create space for technologists, for practitioners, for leaders to go learn and to go study and have a mantra of spending some large amount of time on a regular basis, on a cadence basis, investigating, whether that’s going and attending conferences and networking and starting to understand what’s happening in the industry or it’s partnering with a technology organization and doing more hands-on workshops and learnings or it’s going next, when you’ve got a consultant in, spending time with those folks in the office picking their brain on what are the skills that they’re paying you for? Why are you here? What is so unique about what you’re doing, and how do I learn more of that?

    It comes from leaders making that a priority. If we’re going to have an organization that has people, process and technology that’s actually going to be resilient, that’s going to be able to survive in this next epoch of technology innovation, it’s going to have to be led by the best intelligence, which is still human intelligence, and that requires investment, and I think you got to put a stake in the ground and make that a priority today.

    Ryan Kovar: I love that part because, going back to our previous discussions about leaders who often have 10, 20, 30 years of experience, none of it is relevant. When I started my career as CISO, my only half, well, first off, CISOs didn’t exist. Second, the CTO or the person in charge of technology at that company had to pay attention to desktops, printers and servers on-prem, and then 10 years ago, 15 years ago, it was laptops, desktops, printers on-prem, printers in the home offices, a data center that they co-located to in this little cloud thing that they’re trying out, and then five or 10 years ago, it was all those plus software as a service, and now it’s, okay, well, we have a CICD pipeline and we’re driving APIs and our entire business is dependent upon this one piece of open source software that’s maintained by three guys in a former Yugoslavian Republic and, if it has an issue, we’re going to be done.

    Also, we M&Aed a company out of China. Every time they develop a vulnerability, that has to go to the Chinese government along with us. It’s a lot more complex. For those who are just resting on their laurels of “I’ve been doing this for a while” and not up-leveling their own education and hiring people who are subject matter levels as direct lieutenants, you’re going to have a bad day.

    Mitch Ashley: Bringing it back to the thinking that got us here is not the thinking that will get us to the next place, I’m paraphrasing Einstein here, but it’s also our own thinking. That’s the value of bringing in perspectives like yours with your partners, your suppliers, companies like Splunk, professional services. There are a lot of ways. I think we’re at the same junction point where we were with the cloud. Where we’re like, “Here’s the cloud. Is it just somebody else’s computer or is it a new way of doing things?” But what is that new way?

    We’re kind of in that place today with AI. Okay. Right. We know we can do generative AI stuff, but what does it really mean? How do we leverage it, to your point, Ryan? You have to be a participant on the field to really figure that out. You don’t have to go spend crazy money on the latest thing just because that’s what was in the airline magazine, but it is about figuring out and learning what you can do with it and what’s possible learning by yourself, but also with others.

    Well, thank you to both of you, to Cory Minton and Ryan Kovar, for joining us, and thanks to the Splunk team for bringing us together to have this conversation. We hope it’s been really beneficial to everybody who’s listening in. I know it’s been great for me as well. Thank you.

  • Summit Highlights Open Source Software Security Progress

    Summit Highlights Open Source Software Security Progress

    More than a year after the Open Source Security Foundation (OpenSSF) summit kicked off an initiative to better secure open source software-based software supply chains, a lot of progress has been made—but much work remains to be done.

    The OpenSSF this week hosted a Secure Open Source Software (SOSS) Summit 2023 event in Washington, D.C., during which it made available a Secure Open Source Software Vision Brief 2023. The brief describes the various efforts being made to improve open source software security, including, for example, providing maintainers of open source software projects with free DevSecOps tools.

    This week, the Cybersecurity and Infrastructure Security Agency (CISA) also published an Open Source Software Security Roadmap that defines its role in providing more visibility into how open source is being used and the associated risks.

    However, it’s not clear how much maintainers of these projects are embracing DevSecOps workflows. Many projects are led by a handful of maintainers that often lack the time and skills required to ensure the components they employ have not, for example, been compromised by malware that might find its way into downstream applications.

    Sonatype CTO Brian Fox said the focus of the summit’s participants will be on education and securing public code repositories. While there is a lot of focus on maintainers, he added that there is not enough attention to all the organizations that have not updated open source components within a software build with known vulnerabilities. Many IT teams are reluctant to upgrade components for fear of breaking applications with complex dependencies, but the amount of code that is potentially insecure is massive. “There’s a huge mountain to climb,” he said.

    The challenge is determining which code to upgrade first in a way that will have the most impact in terms of improving application security, added Fox.

    Shawn Ahmed, chief product officer for CloudBees, also noted that organizations should evaluate the DevSecOps processes being applied by maintainers of open source software projects. CloudBees, for example, reviews the plugins provided by the open source community for the Jenkins continuous integration/continuous delivery (CI/CD) platform for vulnerabilities every month, he noted.

    It’s also critical for organizations that consume open source software to contribute code to improve the security of open source software, added Ahmed. Too many organizations are focused on open source software security without devoting resources that would help resolve the issue. he added. “We need to make sure open source software is not a vulnerability threat,” said Ahmed.

    Moran Ashkenazi, chief strategy officer (CSO) and vice president of security engineering for JFrog, said on the plus side, there is a lot more awareness of open source software security issues since the disclosure of a zero-day vulnerability in the Log4j shell tool widely used to manage logs in Java applications. But added that this issue is not going to be resolved overnight. “That was a wakeup call,” she said.

    Tapabrata Pal, vice president of architecture for Fidelity Investments, noted that the fundamental problem is that cybercriminals have become more adept at injecting malware into software supply chains, so no one knows whether their application environments might be compromised. “It’s a serious issue,” he said.

    It’s not known whether the open source software that many developers routinely incorporate into their applications might contain vulnerabilities that could be exploited, but the level of technical debt that has accrued over the last several decades is considerable. The issue is finding a way to address it without becoming overwhelmed by the enormity of the task.

  • CloudBees CEO: State of Software Development is a Disaster

    CloudBees CEO: State of Software Development is a Disaster

    CloudBees CEO Anuj Kapur told attendees at a DevOps World event today that with developers spending only 30% of their time writing code the current state of software development in enterprise IT organizations is a disaster.

    After more than 14 years of effort, the promise of DevOps—in terms of being able to accelerate the rate at which applications are being deployed—remains largely academic, said Kapur. In fact, the effort to shift more responsibility for application security further left toward developers has only increased the amount of cognitive load and reduced the amount of time available to write code, he noted.

    However, with the rise of generative artificial intelligence (AI), an inflection point that will dramatically increase the velocity at which applications are being built and deployed has arrived, said Kapur. The challenge will be achieving that goal without increasing the cognitive load on developers. That cognitive overload results in 70% of developers’ time not being productive within organizations that often hire thousands of developers, he noted.

    Despite all the DevOps issues that need to be addressed, AI advances promise improvement. The overall DevOps market is still relatively young, given the current level of adoption, said Kapur. “We continue to believe the market is early,” he said.

    Today, CloudBees took the wraps off the first major update to the open source Jenkins continuous integration/continuous delivery (CI/CD) platform to have been made in the past several years. At the same time, the company also unveiled a DevSecOps platform based on Kubernetes that is optimized for building and deploying cloud-native applications based on portable Tekton pipelines. That latter platform provides the foundation through which CloudBees will, in the months ahead, apply generative AI to software engineering to, for example, create unit tests on the fly and automate rollbacks.

    In addition, DevSecOps capabilities will be extended all the way out to the integrated development environments (IDE) to reduce the cognitive load of developers.

    The overall goal is to reduce the number of manual processes that create bottlenecks that make it challenging to manage DevOps at scale.

    Criticism of the level of developer productivity enabled by DevOps compared to other development approaches needs to be tempered, said Tapabrata Pal, vice president of architecture for Fidelity Investments, because it still represents a significant advance. There is still clearly too much toil, but the issues that impede the pace at which developers can effectively write code tend to be more cultural than technical, he added.

    Organizations are not inclined to automatically trust the code created by developers, so consequently, there is still a lot of friction in the DevOps process, noted Pal.

    In theory, advances in AI should reduce that friction, but it’s still early days in terms of the large language models (LLMs) that drive generative AI platforms and their ability to create reliable code, he added. That should improve as LLMs are specifically trained using high-quality code, but in the meantime, the pace at which substandard code might be generated could overwhelm DevOps processes until AI is applied there as well, said Pal.

    Thomas Haver, master software engineer for M&T Bank, added that while assisted AI technologies will have a major impact, it’s not reasonable to expect large organizations to absorb them overnight. Patience will be required to ensure advances are made in ways that are both secure and sustainable, he added. In some cases, organizations may opt to build their own LLMs to achieve that goal, noted Haver. “You should not expect to change on a dime,” he said. “It will take time to see the fruits of our labor.”

    While many DevOps challenges need to be resolved, the benefits continue to outweigh the cost and effort required to succeed. The hope is that, with the help of AI, the return on those investments will continue to accrue.

  • JFrog swampUP: Keynotes and What’s Next

    JFrog swampUP: Keynotes and What’s Next

    At the sold-out JFrog swampUP conference this morning, the event’s keynotes were headlined by JFrog CEO Shlomi Ben Haim and co-founder and CTO Yoav Landman. The theme was “next”—what’s next for DevOps and what’s next for developers.

    Of course, there are several answers, but cutting to the chase, it seems security is job one. Developers are squarely in the crosshairs of the bad guys, and protecting them and their code is top priority at JFrog. To do so requires shifting security even further left into the integrated development environment (IDE) itself. Landman demonstrated new functionality in the JFrog Xray scanning and remediation solution’s IDE and emphasized the difference between quality assurance and quality testing.

    CEO Ben Haim took a higher-level view, looking at the issues facing organizations as they seek to develop more, develop faster and do so more securely. He also reinforced the themes hit on by Landman. Overall, the message from both co-founders was that the amount of code being deployed continues to increase exponentially. The need to go faster while being more secure is greater than ever, and JFrog has adopted that as the company’s mission, Ben Haim and Landman said.

    Audience enthusiasm was high, and despite growing to almost 1,000 employees, many of whom have been on board for less than a year, the culture at JFrog remains a constant focus. Landman and Ben Haim reiterated that the company is committed to their customers and their community. 

    That community was well represented, with all three of the major cloud providers exhibiting in the expo area, as well as a good mix of other DevOps providers like CloudBees (whose own DevOps World Roadshow kicked off today). Additionally, some of the new channel partners, such as IT Methods, also exhibited.

    Beyond the keynote, other JFrog presenters in the morning keynote sessions included the leadership of the Artifactory team and senior leadership of the security team.

    JFrog leaders were not the only ones on the agenda at swampUP. A leading games company presented a demonstration of their use of JFrog for CI/CD pipelines. One of the big three cloud providers presented a session discussing whether AI will replace developers (spoiler alert: The answer is no). Additionally, frequent devopsy.kinsta.cloud contributors Tracy Ragan and John Willis also presented throughout the day. Our own Will Willis will be recapping some of those highlights.

    All in all, it was a return to normalcy for swampUP. This event felt much like previous swampUPs that occurred before  the COVID-19 pandemic began. The event was sold out with over 400 attendees, which tracks with what we’ve seen at other in-person events recently.

    JFrog has grown and matured but continues to emphasize what has made the company successful. We’re excited to see lots of new features for developers and DevOps practitioners to explore.

  • The Path to App Modernization: Benefits, Pitfalls and the Route to Success

    The Path to App Modernization: Benefits, Pitfalls and the Route to Success

    There are many reasons an organization may find itself on the path to considering the risky journey of application modernization. It could be to gain an edge or to build a more competitive positioning, or a business could have a legacy system running on infrastructure that is no longer viable, leaving them no other choice. But the conundrum for organizations still resurfaces when considering app modernization; they must select one of these two routes: Either “the failure rate is high, and failure is simply not an option” or “Everyone is still doing it, so let’s forge ahead.”

    The Benefits of Choosing Application Modernization

    Whether an organization chooses this path out of necessity or ambition, modernizing an old IT environment can deliver several benefits, ranging from reducing outdated hardware and software to creating new value through innovation. Specifically, the key benefits are:

    ● Reducing technical debt and improving the underlying infrastructure: Improved security, operations, reliability and scalability.
    ● Decreasing expenses: Lowering the cost spent on expensive hardware and software improves the utilization of resources, thereby decreasing the total cost of ownership of technology operations.
    ● Accelerated time to market: Modernized IT and product development gain value from technological improvements that decrease the time it takes to develop and deploy new products and services.
    ● Agility in the market: Modernization enables an organization to react to changes at an accelerated rate, providing a competitive edge in the market.

    Choosing the Best Path to Application Modernization

    There are different paths to modernization, each with its own focus. On the one hand, there’s the infrastructure aspect of building your platform engineering practice versus adopting a service approach with a platform-as-a-service (PaaS). On the other hand, there is the actual process of modernization with options like refactoring, re-platforming or rewriting your systems, either in-house or through outsourced services. It ultimately starts with modernizing the relationship of the application with its infrastructure and changing some assumptions.

    Once you have a baseline, running everything else should come from a cost-benefit analysis. A scalable, well-managed monolith is valuable despite its age. Ensuring horizontal scalability and a robust backup strategy are key to effectively managing mutable data.

    First, understand the blockers in your current implementation that would complicate a shift to the cloud. Or identify where the result may not deliver any value.

    There are very common anti-patterns that remain anti-patterns, whether on the cloud, running on managed hosting or on-premises. Identifying them allows you to start absorbing technical debt regardless of whether a move to the cloud happens as intended.

    Anti-patterns to look out for are:
    ● Weak separation of code and configuration: You want to be able to run many parallel instances of each application as separate environments. Telltale signs are hard-coded URLs and service credentials. The dependency is the capability of running ephemeral preview environments that are quick to launch and quick to destroy, such that you know that you are “cloud ready.”
    ● Weak separation of the read/write domain from the read-only domain: In a cloud deployment, you want a build step that creates immutable artifacts that are not modifiable in production, and you need to know where all the actual data resides. Older applications tend to “believe” they own the whole disk.
    ● Manual configuration of services: You should be able to run “stock” services without any manual configuration in case the need for a specific database configuration arises and signals the likelihood of an application issue that requires debugging.

    Simply packaging a Docker container or a VM image and deploying to an IaaS won’t create any benefit and only increases costs. The first step to success is a thorough clean-up and update of the documentation to start the process.

    The one basic rule to follow is the ability to run an arbitrary number of instances of every element. Achieving this will allow everything else to flow. There is no need to rush to transform all Crons into “separate workers” and break the monolith into microservices. But the proof that it is possible now exists.

    The Best Approach to Application Modernization: In-House or Outsourced

    A mixed approach between in-house and outsourced is often optimal. There are many elements to consider. If you have a minimal in-house understanding of what the cloud imposes as constraints, you may be tempted to go for the simplistic lift-and-shift approach. Outsourcing everything can lead to huge amounts of lock-in.

    There are ways to cut corners that could simplify and accelerate the initial project, but this could increase the costs down the line. There needs to be a level of abstraction where using a PaaS is a winning proposition and can provide quite a bit of abstraction at no cost.

    Without control, the project may end up as something that “runs on the cloud” without the actual benefits. But there are many ways to do that.

    The Right Mindset Will Help Avoid Pitfalls Along the Way

    By neglecting constraints and skipping the necessary preparation, the costs may escalate. Running big chunks of hardware continuously versus using small ephemeral resources as needed typically leads to significantly increased costs over time. Full rewrites often go wrong when trying to obtain all the benefits immediately.

    A simple four-step approach for success is:

    ● Start with modernizing the relationship of the application with its infrastructure and changing assumptions.
    ● Identify and address the blockers in the current implementation–this makes a shift to the cloud less complicated and enables a smoother transition.
    ● Set a baseline that allows everything else to run from a cost-benefit analysis. Ensure horizontal scalability and implement a robust backup strategy to effectively manage mutable data.

    Accepting that app modernization will be a journey and that the initial implementation is a slightly more scalable and resilient version of the original. This is often a better mindset that leads to a more effective process.

  • JFrog Launches New Channel Partner Program

    JFrog Launches New Channel Partner Program

    At JFrog’s swampUP event in San Jose, California, the company launched its Global Channel Partner Program. The program, led by Kelly Hartman, VP of alliances and partners, is JFrog’s first formal program to work with the channel to bring its DevOps and DevSecOps solutions to market.

    Rather than the traditional pyramid model, Hartman, who was formerly at AWS, has designed a flatter program; partners can choose to work with JFrog in a co-selling arrangement, as a traditional reseller or as part of JFrog’s government sales partners. Partners can choose which type of relationship they want to use on a case-by-case, deal-by-deal basis. This gives them lots of flexibility.

    This program is a sign of JFrog’s continuing evolution from a startup to a public company. Several of the founding channel partners in the program weren’t surprised at the announcement; the feeling was, as Mike King of IT Methods said, “They have been knocking on this door for some time.” Hartman added that the goal was not to make JFrog a 100%-channel company. Rather, the aim is to have as much business run through the partners as JFrog’s customers want while keeping the emphasis on the JFrog customer base.

    The program is primarily aimed at DevOps consultants worldwide, rather than the larger integrators, JFrog said. The DevOps consultant market is broadly fragmented, and made up of numerous sized companies – from one to two-person operations all the way up to 1,000+-person organizations, such as IT Methods.

    Hartman said she is learning from her past experience at AWS and other organizations. She has not crafted a traditional program with tiers and marketing development funds; instead, much of what partners need is built into a self-service portal, including a campaign in a box and social media kits.

    IT Methods is an ideal partner for JFrog, King said. They offer a fully-managed SaaS, single-tenant platform allowing their customers to manage their DevOps environments. IT Methods supports more than 45 DevOps tools and its major clients are large enterprises. They have offered JFrog via their platform for six years, but welcome the formal partner program and accompanying certification offered for SMEs. King said he was pleasantly surprised at the JFrog program’s maturity, considering it is a new program. He added that joint lead generation and closing capability and partner enablement offerings would put JFrog “at the head of the class.”

    The JFrog channel partner program joins their existing technology partner and cloud partner programs. In fact, Hartman said they are working with their cloud provider partners to source new channel partners. 

    It was an exciting new development in what promises to be a gangbuster swampUP here in San Jose. More developments will follow.

  • Survey Surfaces Spike in Generative AI Usage Across IT

    Survey Surfaces Spike in Generative AI Usage Across IT

    A survey of 800 DevOps and application security operations (SecOps) leaders published today found nearly all (97%) are making use of generative artificial intelligence (AI).

    Conducted by the market research firm Sago on behalf of Sonatype, the survey found that beyond writing code, a full 45% of the 400 security operations professionals have already embedded generative AI into their workflows compared to 31% of the 400 DevOps professionals.

    Security operations teams also reported greater time savings than their DevOps counterparts, with 57% saying generative AI saves them at least six hours a week compared to only 31% of DevOps respondents that saw the same benefit.

    The top benefits cited by security operations teams is increased productivity (21%) and faster issue identification/resolution (16%) compared to faster software development (16%) and more secure software (15%) cited by DevOps professionals.

    It’s still early days as far as embedding generative AI in workflows is concerned, but it’s clear the ability to write code faster is trumping concerns about the increased number of vulnerabilities that might find their way into application environments. The most widely used generative AI platforms are trained on a massive corpus of data that includes code of varying quality. As such, a lot of the code generated by a general-purpose AI platform will likely have as many errors, including vulnerabilities, as the code used to train it.

    The level of faith organizations will place in that code will be heavily influenced by use cases. A script used to automate DevOps workflows that are not externally facing may be one example of where a general-purpose AI platform can boost productivity. In other instances, code that contains vulnerabilities that find their way into a web application might be much more problematic.
    Despite those concerns, however, the survey finds nearly three-quarters (75%) of all respondents feel pressure to use generative AI.

    There are, of course, already large language models trained on code that has been vetted by software engineers. In the months ahead, the code generated by AI platforms specifically designed for that purpose should significantly improve.

    Sonatype CTO Brian Fox said it’s only a matter of time before IT organizations focus more on ensuring the generative AI platforms are tuned for specific tasks. In the meantime, however, application security may get worse before it gets better, with more than three-quarters of DevOps respondents noting that generative AI will result in more vulnerabilities in open source code. Only 58% of security operations professionals are similarly concerned.

    It will be up to the engineers that make up these teams to bring discipline to code quality practices and make sure the code running in a production environment is of high quality, regardless of how it was created, noted Fox. For the moment, the issue is that AI augmentation is now occurring at a faster pace than the AI advances that should one-day help DevOps teams cope with increasingly larger codebases, he noted.

    Survey respondents are also concerned about who might own the code generated by AI. A total of 40% said developers or the organizations they work for should own the copyright for AI-generated output, and most of them agreed developers should be compensated for the code they wrote if it’s used in open source artifacts in LLMs (DevOps 93% versus SecOps 88%). A total of 42% of DevOps respondents and 40% of SecOps respondents said a lack of regulation could deter developers from contributing to open source projects.

    DevOps and SecOps leads both want more regulation: Asked who they believe is responsible for regulating the use of generative AI, 59% of DevOps leads and 78% of SecOps leads said both the government and individual companies should be responsible for regulation.

    At this point, the proverbial generative AI genie is out of the bottle, so there is no going back. The issue that remains to be seen is how DevOps and security operating teams will adjust to that new reality.