Business Software for Kubernetes

Resurface is a runtime API security tool. Resurface continuous API scanning allows you to detect and respond in real time to API threats and risks. Resurface is a purpose-built tool for API data. It captures all request and response payloads, including GraphQL, to instantly see potential threats and failures. Receive alerts about data breaches for zero-day detection. Resurface is mapped to OWASP Top10 and alerts on threats with complete security patterns. Resurface is self-hosted and all data is first-party. Resurface is the only API security system that can be used to perform deep inspections at scale. Resurface detects active attacks and alerts them by processing millions of API calls. Machine learning models detect anomalies and identify low-and slow attack patterns.

Kaholo is an IT workflow automation tool for developers that uses low-code code. It allows them to automate their workflows quicker and can be used by any developer without the need for scripting or proprietary tool knowledge.

KServe is a robust model inference platform on Kubernetes that emphasizes high scalability and adherence to standards, making it ideal for trusted AI applications. This platform is tailored for scenarios requiring significant scalability and delivers a consistent and efficient inference protocol compatible with various machine learning frameworks. It supports contemporary serverless inference workloads, equipped with autoscaling features that can even scale to zero when utilizing GPU resources. Through the innovative ModelMesh architecture, KServe ensures exceptional scalability, optimized density packing, and smart routing capabilities. Moreover, it offers straightforward and modular deployment options for machine learning in production, encompassing prediction, pre/post-processing, monitoring, and explainability. Advanced deployment strategies, including canary rollouts, experimentation, ensembles, and transformers, can also be implemented. ModelMesh plays a crucial role by dynamically managing the loading and unloading of AI models in memory, achieving a balance between user responsiveness and the computational demands placed on resources. This flexibility allows organizations to adapt their ML serving strategies to meet changing needs efficiently.

The NVIDIA Triton™ inference server provides efficient and scalable AI solutions for production environments. This open-source software simplifies the process of AI inference, allowing teams to deploy trained models from various frameworks, such as TensorFlow, NVIDIA TensorRT®, PyTorch, ONNX, XGBoost, Python, and more, across any infrastructure that relies on GPUs or CPUs, whether in the cloud, data center, or at the edge. By enabling concurrent model execution on GPUs, Triton enhances throughput and resource utilization, while also supporting inferencing on both x86 and ARM architectures. It comes equipped with advanced features such as dynamic batching, model analysis, ensemble modeling, and audio streaming capabilities. Additionally, Triton is designed to integrate seamlessly with Kubernetes, facilitating orchestration and scaling, while providing Prometheus metrics for effective monitoring and supporting live updates to models. This software is compatible with all major public cloud machine learning platforms and managed Kubernetes services, making it an essential tool for standardizing model deployment in production settings. Ultimately, Triton empowers developers to achieve high-performance inference while simplifying the overall deployment process.

Deploy your machine learning model in the cloud within minutes using a consolidated packaging format that supports both online and offline operations across various platforms. Experience a performance boost with throughput that is 100 times greater than traditional flask-based model servers, achieved through our innovative micro-batching technique. Provide exceptional prediction services that align seamlessly with DevOps practices and integrate effortlessly with widely-used infrastructure tools. The unified deployment format ensures high-performance model serving while incorporating best practices for DevOps. This service utilizes the BERT model, which has been trained with the TensorFlow framework to effectively gauge the sentiment of movie reviews. Our BentoML workflow eliminates the need for DevOps expertise, automating everything from prediction service registration to deployment and endpoint monitoring, all set up effortlessly for your team. This creates a robust environment for managing substantial ML workloads in production. Ensure that all models, deployments, and updates are easily accessible and maintain control over access through SSO, RBAC, client authentication, and detailed auditing logs, thereby enhancing both security and transparency within your operations. With these features, your machine learning deployment process becomes more efficient and manageable than ever before.

Flyte is a robust platform designed for automating intricate, mission-critical data and machine learning workflows at scale. It simplifies the creation of concurrent, scalable, and maintainable workflows, making it an essential tool for data processing and machine learning applications. Companies like Lyft, Spotify, and Freenome have adopted Flyte for their production needs. At Lyft, Flyte has been a cornerstone for model training and data processes for more than four years, establishing itself as the go-to platform for various teams including pricing, locations, ETA, mapping, and autonomous vehicles. Notably, Flyte oversees more than 10,000 unique workflows at Lyft alone, culminating in over 1,000,000 executions each month, along with 20 million tasks and 40 million container instances. Its reliability has been proven in high-demand environments such as those at Lyft and Spotify, among others. As an entirely open-source initiative licensed under Apache 2.0 and backed by the Linux Foundation, it is governed by a committee representing multiple industries. Although YAML configurations can introduce complexity and potential errors in machine learning and data workflows, Flyte aims to alleviate these challenges effectively. This makes Flyte not only a powerful tool but also a user-friendly option for teams looking to streamline their data operations.

Having the capability to confidently implement and maintain cloud infrastructure is essential for your team's competitive edge in today's market. Understanding the effects of your code allows you to identify and rectify significant errors prior to deployment by consistently simulating alterations within the GitOps framework. Lightlytics provides a visual context-driven risk assessment that highlights the potential impact on your cloud environment with each configuration adjustment. This process not only shortens the time required to evaluate Terraform code modifications but also mitigates the risk of downtime or security vulnerabilities before the code goes live. The simulation engine from Lightlytics leverages the existing configuration state of your cloud alongside the proposed Terraform changes to forecast how the deployment will influence your cloud setup, ensuring your infrastructure remains resilient and secure. By integrating these practices, your team can navigate the complexities of cloud management more effectively than ever before.

Sedai intelligently finds resources, analyzes traffic patterns and learns metric performance. This allows you to manage your production environments continuously without any manual thresholds or human intervention. Sedai's Discovery engine uses an agentless approach to automatically identify everything in your production environments. It intelligently prioritizes your monitoring information. All your cloud accounts are on the same platform. All of your cloud resources can be viewed in one place. Connect your APM tools. Sedai will identify and select the most important metrics. Machine learning intelligently sets thresholds. Sedai is able to see all the changes in your environment. You can view updates and changes and control how the platform manages resources. Sedai's Decision engine makes use of ML to analyze and comprehend data at large scale to simplify the chaos.

Coder offers self-hosted cloud development environments, provisioned as code and ready for developers from day one. Favored by enterprises, Coder is open source and can be deployed air-gapped on-premise or in your cloud, ensuring powerful infrastructure access without sacrificing governance. By shifting local development and source code to a centralized infrastructure, Coder allows developers to access their remote environments via their preferred desktop or web-based IDE. This approach enhances developer experience, productivity, and security. With Coder’s ephemeral development environments, provisioned as code from pre-defined templates, developers can instantly create new workspaces. This streamlines the process, eliminating the need to deal with local dependency versioning issues or lengthy security approvals. Coder enables developers to onboard or switch projects in a matter of minutes.

Komodor simplifies the troubleshooting process for Kubernetes, equipping you with all the essential tools to resolve issues confidently. It oversees your entire Kubernetes ecosystem, detects problems, reveals their underlying causes, and provides the necessary context for effective and independent troubleshooting. The platform automatically identifies anomalies, deployment failures, misconfigurations, bottlenecks, and various health-related issues. It enables you to recognize potential problems before they escalate and impact end-users. By utilizing pre-designed playbooks, you can enhance root cause analysis, avoid disruptive escalations, and conserve valuable developer time. Moreover, it offers clear remediation guidance that empowers every team member to act like a seasoned troubleshooting expert, fostering a more resilient operational environment. This proactive approach not only enhances team efficiency but also significantly improves overall system reliability.

Dataplane's goal is to make it faster and easier to create a data mesh. It has robust data pipelines and automated workflows that can be used by businesses and teams of any size. Dataplane is more user-friendly and places a greater emphasis on performance, security, resilience, and scaling.

Ngrok serves as a versatile network edge solution that enhances your applications by integrating connectivity, security, and monitoring without requiring any modifications to your code. With ngrok, you can effortlessly add layers of security, scalability, and visibility to your applications, enabling you to securely expose your localhost to the internet. It facilitates the introspection and replay of requests, creating an efficient feedback loop. Additionally, ngrok allows seamless connections into customer networks, eliminating the need for cumbersome firewall configurations, VPN setups, or change requests. This makes ngrok the quickest method to launch your application online. Operating a globally distributed reverse proxy, it effectively manages your web services regardless of whether they are hosted in the cloud or secured behind firewalls. Furthermore, ngrok provides an intuitive interface that simplifies the entire process, making it accessible even for those with limited technical expertise.

Launch production-ready Kubernetes clusters within just a few days and facilitate the swift onboarding of users and applications. Tackle the complexities of Kubernetes using a robust and user-friendly DevOps solution that minimizes friction among teams, fosters better collaboration, and increases overall productivity. With Nirmata's Kubernetes Policy Manager, you can ensure the appropriate security measures, compliance, and governance for Kubernetes, enabling you to scale operations smoothly. Manage all your Kubernetes clusters, policies, and applications seamlessly in a single platform, while optimizing operations through the DevSecOps Platform. Nirmata’s DevSecOps platform is designed to integrate effortlessly with various cloud providers such as EKS, AKS, GKE, OKE, and offers support for infrastructure solutions like VMware, Nutanix, and bare metal. This solution effectively addresses the operational challenges faced by enterprise DevOps teams, providing them with comprehensive management and governance tools tailored for Kubernetes environments. By implementing Nirmata, organizations can improve their workflow efficiency and streamline their Kubernetes operations.

Lens unifies Kubernetes and LLM application observability into a single, developer-first experience. The Lens K8S IDE enables developers and operators to manage clusters, troubleshoot issues, and monitor workloads with instant visual clarity. Lens Loop extends these capabilities to LLM-powered applications, helping teams develop, debug, and observe AI workloads with confidence. Built-in AI assistance through Lens Prism AI provides contextual insights without switching tools. Everything runs locally, ensuring strong security, compliance, and performance. Lens integrates seamlessly into modern cloud-native stacks and scales with growing infrastructure complexity. It eliminates fragmented tooling by offering one IDE for operational insight across environments.

Strengthen and enhance your cybersecurity framework with Zercurity, allowing you to minimize the time and resources dedicated to overseeing, managing, and navigating the various aspects of cybersecurity within your organization. Obtain actionable data points that provide a clear snapshot of your existing IT infrastructure, with automatic analysis of assets, applications, packages, and devices. Our advanced algorithms will execute queries across your resources, promptly identifying anomalies and vulnerabilities as they arise. Safeguard your organization by revealing potential threats and mitigating associated risks effectively. With automatic reporting and auditing features, remediation processes become more efficient and manageable. Experience comprehensive security monitoring that covers all areas of your organization, enabling you to query your infrastructure as if it were a database. Receive immediate answers to your most challenging inquiries while continuously measuring your risk exposure in real-time. Stop speculating about where your cybersecurity vulnerabilities may exist and gain profound insights into every aspect of your organization’s security posture. Zercurity empowers you to stay ahead of threats, ensuring that your defenses are always on alert.

SquaredUp is a unified observability portal. Say goodbye to blind spots and data silos. Using data mesh and cutting-edge data visualization, SquaredUp gives IT and engineering teams one place to see everything that matters. Bring together data from across your tech stack without the headache of moving the data. Unlike other monitoring and observability tools that rely on a data warehouse, SquaredUp leaves your data where it is, plugging directly into each data source to index and stitch the data together using a data mesh. Teams have one place to go where they can search, visualize, and analyze data across all their tools. Take control of infrastructure, application, and product performance with unified visibility. Learn more at squaredup.com What you get: > Cutting-edge data visualization > Access to 100+ data sources > Any custom data source via Web API > Multi-cloud observability > Cost monitoring > Unlimited dashboards > Unlimited monitors Key features: > Out-of-box dashboards > Simple, flexible dashboard designer > Real-time monitoring > High-level roll-up views > Object drill downs > Notifications (Slack, Teams, email, etc.) > SQL analytics

Modern cloud-native applications come with significantly more dependencies, fleeting lifecycles, releases, and telemetry data than ever before. Traditional proprietary monitoring and application performance management (APM) solutions were developed for the age of monolithic applications and fixed infrastructure. These legacy tools tend to be costly, intrusive, and fragmented, often creating more confusion than clarity. While open-source and cloud monitoring options provide a solid starting point, they demand highly experienced engineers to effectively integrate, maintain, and interpret the data they generate. As you navigate the complexities of transitioning to contemporary infrastructure, your existing monitoring framework may be pushed to its limits. This signals the need for a new strategy. Enter OpsCruise! Our platform boasts an in-depth understanding of Kubernetes, and when paired with our innovative machine learning-based behavior profiling, it equips your team to anticipate performance issues and quickly identify their origins. Best of all, this can be achieved at a fraction of the cost of existing monitoring solutions, eliminating the need for code instrumentation, agent deployment, or the upkeep of open-source tools. With OpsCruise, you're not just adopting a new tool; you're embracing a transformational shift in how you manage and optimize your infrastructure.

Glasnostic seamlessly integrates into the network data path without the need for agents, allowing it to monitor the interaction patterns among various services while identifying anomalies and implementing effective control mechanisms in real-time. The value of visibility diminishes if it is not linked to actionable responses, and Glasnostic empowers engineers to react proactively to system behaviors as they unfold. By embedding transparent controllers within the network data plane, Glasnostic functions like a centralized brain that continuously detects and addresses behaviors instantaneously. Interaction metrics are relayed to the control plane for both storage and the identification of anomalies, facilitating either automated responses or manual interventions. It is compatible with all leading cloud technologies and can seamlessly integrate with existing AIOps, workflow, and security tools through APIs and webhooks. Additionally, Glasnostic is designed to operate across all significant technology stacks, providing a comprehensive view of system behaviors in a holistic, consistent, and omnipresent manner, ensuring that engineers have the insights they need to maintain optimal operational efficiency. As a result, organizations can achieve greater reliability and responsiveness in their IT environments.

Begin utilizing the fully-managed Akuity platform designed for Argo CD, where you can access direct expert assistance from the very creators and maintainers of Argo. Take advantage of a top-tier suite of Kubernetes-native application delivery tools while seamlessly incorporating GitOps practices within your organization. We have transitioned Argo CD to a cloud-based solution for your ease of use. Built with an emphasis on providing the ultimate developer experience, the Akuity platform, complete with comprehensive analytics, is ready for enterprise deployment right from the start. Efficiently manage clusters at scale and securely launch thousands of applications by adhering to GitOps best practices. The Argo Project encompasses a collection of open-source solutions aimed at deploying and managing applications and workloads on Kubernetes. It enhances the Kubernetes APIs, unveiling powerful features for continuous delivery, container orchestration, event automation, and progressive delivery, among others. Argo is recognized as a project under the Cloud Native Computing Foundation (CNCF) and is relied upon in production by prominent enterprises globally. As the demand for cloud-native solutions grows, organizations are increasingly turning to Argo for its robust capabilities and reliability.

Kuma provides an enterprise service mesh that seamlessly operates across multiple clouds and clusters, whether on Kubernetes or virtual machines. With just a single command, users can deploy the service mesh and automatically connect to other services through its integrated service discovery features, which include Ingress resources and remote control planes. This solution is versatile enough to function in any environment, efficiently managing resources across multi-cluster, multi-cloud, and multi-platform settings. By leveraging native mesh policies, organizations can enhance their zero-trust and GDPR compliance initiatives, thereby boosting the performance and productivity of application teams. The architecture allows for the deployment of a singular control plane that can effectively scale horizontally to accommodate numerous data planes, or to support various clusters, including hybrid service meshes that integrate both Kubernetes and virtual machines. Furthermore, cross-zone communication is made easier with Envoy-based ingress deployments across both environments, coupled with a built-in DNS resolver for optimal service-to-service interactions. Built on the robust Envoy framework, Kuma also offers over 50 observability charts right out of the box, enabling the collection of metrics, traces, and logs for all Layer 4 to Layer 7 traffic, thereby providing comprehensive insights into service performance and health. This level of observability not only enhances troubleshooting but also contributes to a more resilient and reliable service architecture.

A typical flat vL3 domain enables databases operating across various clusters, clouds, or hybrid environments to seamlessly interact for the purpose of database replication. Workloads from different organizations can connect to a unified 'collaborative' Service Mesh, facilitating interactions across companies. Each workload is restricted to a single connectivity domain, with the stipulation that only those workloads residing in the same runtime domain can participate in that connectivity. In essence, Connectivity Domains are intricately linked to Runtime Domains. However, a fundamental principle of Cloud Native architectures is to promote Loose Coupling. This characteristic allows each workload the flexibility to receive services from different providers as needed. The specific Runtime Domain in which a workload operates is irrelevant to its communication requirements. Regardless of their locations, workloads that belong to the same application need to establish connectivity among themselves, emphasizing the importance of inter-workload communication. Ultimately, this approach ensures that application performance and collaboration remain unaffected by the underlying infrastructure.

AWS App Mesh is a service mesh designed to enhance application-level networking, enabling seamless communication among your services across diverse computing environments. It provides excellent visibility and ensures high availability for your applications. Typically, modern applications comprise several services, each capable of being developed on various compute platforms, including Amazon EC2, Amazon ECS, Amazon EKS, and AWS Fargate. As the complexity increases with more services being added, identifying error sources and managing traffic rerouting after issues become challenging, along with safely implementing code modifications. In the past, developers had to embed monitoring and control mechanisms within their code, necessitating a redeployment of services with each update. This reliance on manual intervention can lead to longer downtimes and increased potential for human error, but App Mesh alleviates these concerns by streamlining the process.

Finout streamlines the billing from Cloud Providers, Data Warehouses, and CDNs into a comprehensive single invoice, providing an exceptional overview of your cloud expenses without the need for extensive setup. You can easily track irregularities, access tailored suggestions, and anticipate costs as your business expands. Unlike AWS, which bills based on instances, Finout allows you to focus on the actual costs associated with your pods. By integrating seamlessly without agents, you can leverage your current Datadog or Prometheus setups to gain detailed insights into pod-level spending quickly. Move beyond simply understanding total cloud expenses; instead, focus on the costs tied to your actual usage rather than just payments made. For instance, instead of analyzing EC2 instances and DynamoDB indexes, you can directly observe Kubernetes pods. Moreover, Finout fosters a shared vocabulary across your organization, benefiting not just the DevOps team but the entire company as well. This unified approach enhances collaboration and understanding across departments, leading to more informed financial decisions.

RapidFort streamlines the process of software deployment by automatically removing unnecessary components, resulting in more efficient, compact, and secure workloads. This innovative solution significantly cuts down on vulnerability management and patching tasks, allowing developers to concentrate on creating new features. By analyzing container setups, RapidFort determines essential components needed for operation, thereby bolstering the security of production workloads while sparing developers from the burden of managing irrelevant code. Users can deploy their containers seamlessly across various environments—be it development, testing, or production—and utilize any container orchestration tool, such as Kubernetes or Docker Compose. After profiling the containers, RapidFort highlights the packages that are necessary, facilitating the removal of those that are superfluous. Typical efficiency gains can range from 60% to 90%. Additionally, RapidFort offers users the flexibility to create and tailor remediation profiles, allowing them to selectively decide what components to keep or discard, further enhancing the customization and security of their deployments. This comprehensive approach not only simplifies management but also empowers teams to optimize their resources effectively.

Harness the capabilities of a no-code platform to create modern applications with ease. Design, deploy, manage, and expand cloud-native applications by taking full advantage of your team's existing skills. Transform your applications to seize new revenue streams and surpass customer expectations by swiftly modernizing both legacy and new projects. Position yourself ahead of the competition and drive transformative change. Utilize the platform's built-in DevOps features to streamline and automate the processes of software delivery and maintenance effectively. Enhance your 'cloud first' approach by incorporating support for multi-cloud and hybrid cloud environments. Prevent vendor lock-in and empower your teams with the freedom to choose their preferred cloud services and infrastructure. Minimize human error and reclaim valuable time for modernizing applications. Accelerate debugging and issue resolution with the platform's integrated developer tools, allowing for a more efficient development process. By embracing this innovative approach, organizations can foster a culture of agility and responsiveness to market demands.