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TNS publisher Alex Williams spoke with Ben Kramer, co-founder and CTO of Monterey.ai Cole Hoffer, Senior Software Engineer at Monterey.ai to discuss how the company utilizes vector search to analyze user voices, feedback, reviews, bug reports, and support tickets from various channels to provide product development recommendations. Monterey.ai connects customer feedback to the development process, bridging customer support and leadership to align with user needs. Figma and Comcast are among the companies using this approach.
In this interview, Kramer discussed the challenges of building Large Language Model (LLM) based products and the importance of diverse skills in AI web companies and how Monterey employs Zilliz for vector search, leveraging Milvus, an open-source vector database.
Kramer highlighted Zilliz's flexibility, underlying Milvus technology, and choice of algorithms for semantic search. The decision to choose Zilliz was influenced by its performance in the company's use case, privacy and security features, and ease of integration into their private network. The cloud-managed solution and Zilliz's ability to meet their needs were crucial factors for Monterey AI, given its small team and preference to avoid managing infrastructure.
Learn more from The New Stack about Zilliz and vector database search:
Improving ChatGPT’s Ability to Understand Ambiguous Prompts
Create a Movie Recommendation Engine with Milvus and Python
Using a Vector Database to Search White House Speeches
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TNS host Heather Joslyn sits down with Ron Masas to discuss trade-offs when it comes to creating fast, secure applications and APIs. He notes a common issue of neglecting documentation and validation, leading to vulnerabilities. Weak authorization is a recurring problem, with instances where changing an invoice ID could expose another user's data.
Masas, an ethical hacker, highlights the risk posed by "zombie" APIs—applications that have become disused but remain potential targets. He suggests investigating frameworks, checking default configurations, and maintaining robust logging to enhance security. Collaboration between developers and security teams is crucial, with "security champions" in development teams and nuanced communication about vulnerabilities from security teams being essential elements for robust cybersecurity.
For further details, the podcast discusses case studies involving TikTok and Digital Ocean, Masas's views on AI and development, and anticipated security challenges.
Learn more from The New Stack about Imperva and API security:
What Developers Need to Know about Business Logic Attacks
Why Your APIs Aren’t Safe — and What to Do about It
The Limits of Shift-Left: What’s Next for Developer Security
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Platform engineering “is the art of designing and binding all of the different tech and tools that you have inside of an organization into a golden path that enables self service for developers and reduces cognitive load,” said Kaspar Von Grünberg, founder and CEO of Humanitec, in this episode of The New Stack Makers podcast.
This structure is important for individual contributors, Grünberg said, as well as backend engineers: “if you look at the operation teams, it reduces their burden to do repetitive things. And so platform engineers build and design internal developer platforms, and help and serve users."
This conversation, hosted by Heather Joslyn, TNS features editor, dove into platform engineering: what it is, how it works, the problems it is intended to solve, and how to get started in building a platform engineering operation in your organization. It also debunks some key fallacies around the concept.
Learn more from The New Stack about Platform Engineering and Humanitec:
Platform Engineering Overview, News, and Trends
The Hype Train Is Over. Platform Engineering Is Here to Stay
9 Steps to Platform Engineering Hell
Is the end of programming nigh? That's the big question posed in this episode recorded earlier in 2023. It was very popular among listeners, and with the topic being as relevant as ever, we wanted to wrap up the year by highlighting this conversation again.
If you ask Matt Welsh, he'd say yes, the end of programming is upon us. As Richard McManus wrote on The New Stack, Welsh is a former professor of computer science at Harvard who spoke at a virtual meetup of the Chicago Association for Computing Machinery (ACM), explaining his thesis that ChatGPT and GitHub Copilot represent the beginning of the end of programming.
Welsh joined us on The New Stack Makers to discuss his perspectives about the end of programming and answer questions about the future of computer science, distributed computing, and more.
Welsh is now the founder of fixie.ai, a platform they are building to let companies develop applications on top of large language models to extend with different capabilities.
For 40 to 50 years, programming language design has had one goal. Make it easier to write programs, Welsh said in the interview.
Still, programming languages are complex, Welsh said. And no amount of work is going to make it simple.
Learn more from The New Stack about AI and the future of software development:
Top 5 Large Language Models and How to Use Them Effectively
30 Non-Trivial Ways for Developers to Use GPT-4
Developer Tips in AI Prompt Engineering
Kubevirt, a relatively new capability within Kubernetes, signifies a shift in the virtualization landscape, allowing operations teams to run KVM virtual machines nested in containers behind the Kubernetes API. This integration means that the Kubernetes API now encompasses the concept of virtual machines, enabling VM-based workloads to operate seamlessly within a cluster behind the API. This development addresses the challenge of transitioning traditional virtualized environments into cloud-native settings, where certain applications may resist containerization or require substantial investments for adaptation.
The emerging era of virtualization simplifies the execution of virtual machines without concerning the underlying infrastructure, presenting various opportunities and use cases. Noteworthy advantages include simplified migration of legacy applications without the need for containerization, thereby reducing associated costs.
Kubevirt 1.1, discussed at KubeCon in Chicago by Red Hat's Vladik Romanovsky and Nvidia's Ryan Hallisey, introduces features like memory hotplug and vCPU hotplug, emphasizing the stability of Kubevirt. The platform's stability now allows for the implementation of features that were previously constrained.
Learn more from The New Stack about Kubevirt and the Cloud Native Computing Foundation:
The Future of VMs on Kubernetes: Building on KubeVirt
A Platform for Kubernetes
Scaling Open Source Community by Getting Closer to Users
The Kubernetes landscape is evolving, shifting from the domain of visionaries and early adopters to a more mainstream audience. Tigera, represented by CEO Ratan Tipirneni at KubeCon North America in Chicago, recognizes the changing dynamics and the demand for simplified Kubernetes solutions. Tigera's open-source Calico security platform has been updated with a focus on mainstream users, presenting a cohesive and user-friendly solution. This update encompasses five key capabilities: vulnerability scoring, configuration hardening, runtime security, network security, and observability.
The aim is to provide users with a comprehensive view of their cluster's security through a zero to 100 scoring system, tracked over time. Tigera's recommendation engine suggests actions to enhance overall security based on the risk profile, evaluating factors such as egress traffic controls and workload isolation within dynamic Kubernetes environments. Tigera emphasizes the importance of understanding the actual flow of data across the network, using empirical data and observed behavior to build accurate security measures rather than relying on projections. This approach addresses the evolving needs of customers who seek not just vulnerability scores but insights into runtime behavior for a more robust security profile.
Learn more from The New Stack about Tigera and Cloud Native Security:
Cloud Native Network Security: Who’s Responsible?
Turbocharging Host Workloads with Calico eBPF and XDP
3 Observability Best Practices for Cloud Native App Security
Boeing, with around 6,000 engineers, is emphasizing open source engagement by focusing on three main themes, according to Damani Corbin, who heads Boeing's Open Source office. He joined our host, Alex Williams, for a discussion at KubeCon+CloudNativeCon in Chicago.
The first priority Corbin talks about is simplifying the consumption of open source software for developers. Second, Boeing aims to facilitate developer contributions to open source projects, fostering involvement in communities like the Cloud Native Computing Foundation and the Linux Foundation. The third theme involves identifying opportunities for "inner sourcing" to share internally developed solutions across different groups.
Boeing is actively working to break down barriers and encourage code reuse across the organization, promoting participation in open source initiatives. Corbin highlights the importance of separating business-critical components from those that can be shared with the community, prioritizing security and extending efforts to enhance open source security practices. The organization is consolidating its open source strategy by collaborating with legal and information security teams.
Corbin emphasizes the goal of making open source involvement accessible and attractive, with a phased approach to encourage meaningful contributions and ultimately enabling the compensation of engineers for open source work in the future.
Learn more from The New Stack about Boeing and CNCF open source projects:
How Boeing Uses Cloud Native
How Open Source Has Turned the Tables on Enterprise Software
Scaling Open Source Community by Getting Closer to Users
Mercedes-Benz: 4 Reasons to Sponsor Open Source Projects
At KubeCon + CloudNativeCon North America 2022, Amazon Web Services (AWS) revealed plans to mirror Kubernetes assets hosted on Google Cloud, addressing Cloud Native Computing Foundation's (CNCF) egress costs. A year later, the project, led by AWS's Davanum Srinivas, redirects image requests to the nearest cloud provider, reducing egress costs for users.
AWS's Todd Neal and Jonathan Innis discussed this on The New Stack Makers podcast recorded at KubeCon North America 2023. Neal explained the registry's functionality, allowing users to pull images directly from the respective cloud provider, avoiding egress costs.
The discussion also highlighted AWS's recent open source contributions, including beta features in Kubectl, prerelease of Containerd 2.0, and Microsoft's support for Karpenter on Azure. Karpenter, an AWS-developed Kubernetes cluster autoscaler, simplifies node group configuration, dynamically selecting instance types and availability zones based on running pods.
The AWS team encouraged developers to contribute to Kubernetes ecosystem projects and join the sig-node CI subproject to enhance kubelet reliability. The conversation in this episode emphasized the benefits of open development for rapid feedback and community collaboration.
Learn more from The New Stack about AWS and Open Source:
Powertools for AWS Lambda Grows with Help of Volunteers
Amazon Web Services Open Sources a KVM-Based Fuzzing Framework
AWS: Why We Support Sustainable Open Source
In the past year, developers have faced both promise and uncertainty, particularly in the realm of generative AI. Heath Newburn, global field CTO for PagerDuty, joins TNS host Heather Joslyn to talk about the impact AI and other topics will have on developers in 2024.
Newburn anticipates a growing emphasis on DevSecOps in response to high-profile cyber incidents, noting a shift in executive attitudes toward security spending. The rise of automation-centric tools like Backstage signals a changing landscape in the link between development and operations tools. Notably, there's a move from focusing on efficiency gains to achieving new outcomes, with organizations seeking innovative products rather than marginal coding speed improvements.
Newburn highlights the importance of experimentation, encouraging organizations to identify areas for trial and error, learning swiftly from failures. The upcoming year is predicted to favor organizations capable of rapid experimentation and information gathering over perfection in code writing.
Listen to the full podcast episode as Newburn further discusses his predictions related to platform engineering, remote work, and the continued impact of generative AI.
Learn more from The New Stack about PagerDuty and trends in software development:
How AI and Automation Can Improve Operational Resiliency
Why Infrastructure as Code Is Vital for Modern DevOps
Operationalizing AI: Accelerating Automation, DataOps, AIOps
In this episode of The New Stack Makers, Rob Skillington, co-founder and CTO of Chronosphere, discusses the challenges engineers face in building tools for their organizations. Skillington emphasizes that the "build or buy" decision oversimplifies the issue of tooling and suggests that understanding the abstractions of a project is crucial. Engineers should consider where to build and where to buy, creating solutions that address the entire problem. Skillington advises against short-term thinking, urging innovators to consider the long-term landscape.
Drawing from his experience at Uber, Skillington highlights the importance of knowing the audience and customer base, even when they are colleagues. He shares a lesson learned when building a visualization platform for engineers at Uber, where understanding user adoption as a key performance indicator upfront could have improved the project's outcome.
Skillington also addresses the "not invented here syndrome," noting its prevalence in organizations like Microsoft and its potential impact on tool adoption. He suggests that younger companies, like Uber, may be more inclined to explore external solutions rather than building everything in-house. The conversation provides insights into Skillington's experiences and the considerations involved in developing internal tools and platforms.
Learn more from The New Stack about Software Engineering, Observability, and Chronosphere:
Cloud Native Observability: Fighting Rising Costs, Incidents
A Guide to Measuring Developer Productivity
4 Key Observability Best Practices
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