Amazon EKS Integrations

Enhancing your development process can be achieved by utilizing a storage solution that seamlessly integrates with Kubernetes. As you concentrate on deploying your application, we guarantee that you will have the persistent volumes necessary for stability and scalability. By incorporating stateful storage into your Kubernetes setup, you can streamline your application modernization efforts and boost overall efficiency. You can seamlessly operate your database or any persistent workload in a Kubernetes environment without the hassle of managing the underlying storage infrastructure. With Ondat, you can create a uniform storage solution across various platforms. Our persistent volumes enable you to manage your own databases without incurring high costs associated with third-party hosted services. You regain control over Kubernetes data layer management, allowing you to customize it to your needs. Our Kubernetes-native storage, which supports dynamic provisioning, functions precisely as intended. This solution is API-driven and ensures tight integration with your containerized applications, making your workflows more effective. Additionally, the reliability of our storage system ensures that your applications can scale as needed, without compromising performance.

Assessing runtime threats, analyzing attacks in real-time, and providing targeted protection for your systems and applications are crucial steps in cybersecurity. By proactively staying one step ahead of potential attackers, organizations can effectively mitigate zero-day attacks. Monitoring attack patterns is essential for a robust defense. ThreatStryker systematically observes, correlates, learns from, and responds to protect your applications. With Deepfence ThreatStryker, users can access a dynamic, interactive, color-coded visualization of their infrastructure, encompassing all active processes and containers. It thoroughly examines hosts and containers to identify any vulnerable elements. Additionally, it reviews configurations to detect misconfigurations related to the file system, processes, and network. By adhering to industry and community standards, ThreatStryker evaluates compliance effectively. Furthermore, it performs an in-depth analysis of network traffic, system behavior, and application interactions, gathering suspicious events over time, which are then classified and correlated with recognized vulnerabilities and patterns that raise concern. This comprehensive approach enhances overall security and fosters a more resilient infrastructure.

ThreatMapper is an open-source, multi-cloud solution designed to analyze, map, and prioritize vulnerabilities found in containers, images, hosts, repositories, and active containers. By identifying threats to applications running in production across various environments, including cloud services, Kubernetes, and serverless architectures, ThreatMapper emphasizes that visibility is key to security. It automatically uncovers your operational infrastructure and can assess cloud instances, Kubernetes nodes, and serverless components, enabling the real-time mapping of applications and containers along with their interconnections. Furthermore, ThreatMapper provides a graphical representation of both external and internal attack surfaces associated with your applications and infrastructure. As common dependencies may harbor vulnerabilities that bad actors can exploit, ThreatMapper proactively scans hosts and containers for these known weaknesses. Additionally, it integrates threat intelligence from over 50 distinct sources, enhancing its ability to safeguard your environment. By continuously monitoring and updating its threat database, ThreatMapper ensures that your security practices remain robust and effective against emerging threats.

The dilemma of selecting between a user-friendly graphical interface and the strength of infrastructure as code has become outdated. With Kubestack, users can easily establish their Kubernetes platform through an accessible graphical user interface, then seamlessly export their customized stack into Terraform code, guaranteeing reliable provisioning and sustained operational effectiveness. Platforms designed with Kubestack Cloud are converted into a Terraform root module based on the Kubestack framework. This framework is entirely open-source, which greatly alleviates long-term maintenance challenges while supporting ongoing improvements. Implementing a structured pull-request and peer-review process can enhance change management within your team, promoting a more organized workflow. By reducing the volume of custom infrastructure code needed, teams can significantly decrease the maintenance responsibilities over time, enabling a greater focus on innovation and development. This strategy not only improves efficiency but also strengthens collaboration among team members, ultimately cultivating a more dynamic and productive environment for development efforts. As a result, teams are better positioned to adapt and thrive in an ever-evolving technological landscape.

Deep Learning Containers are specialized Docker images that come pre-loaded and validated with the latest versions of popular deep learning frameworks. These containers enable the swift establishment of customized machine learning environments, thus removing the necessity to build and refine environments from scratch. By leveraging these pre-configured and rigorously tested Docker images, users can set up deep learning environments in a matter of minutes. In addition, they allow for the seamless development of tailored machine learning workflows for various tasks such as training, validation, and deployment, integrating effortlessly with platforms like Amazon SageMaker, Amazon EKS, and Amazon ECS. This simplification of the process significantly boosts both productivity and efficiency for data scientists and developers, ultimately fostering a more innovative atmosphere in the field of machine learning. As a result, teams can focus more on research and development instead of getting bogged down by environment setup.

Clutch is addressing the increasingly critical challenge of securing non-human identities within modern enterprises. With the expansion and advancement of digital infrastructures, the management and protection of non-human identities—such as API keys, secrets, tokens, and service accounts—has emerged as a pivotal, albeit often neglected, aspect of cybersecurity. Recognizing this gap in security, Clutch is developing a dedicated platform designed specifically to ensure comprehensive protection and management of these identities. This innovative solution aims to bolster the digital framework of organizations, fostering a secure, resilient, and dependable environment for their operations. The rise of non-human identities is remarkable, with their numbers outstripping human identities by a staggering 45 to 1, and these identities possess considerable privileges and broad access necessary for essential automated functions. Furthermore, they frequently lack vital security features such as multi-factor authentication and conditional access policies, amplifying the urgency of their protection. By tackling these vulnerabilities, Clutch is paving the way for stronger integrity in automated systems across various enterprises, ultimately enhancing their overall cybersecurity posture. This proactive approach not only safeguards sensitive data but also fortifies the trust in automated processes that are becoming increasingly integral to business operations.