Alternatives to CAST AI

Compute Engine (IaaS), a platform from Google that allows organizations to create and manage cloud-based virtual machines, is an infrastructure as a services (IaaS). Computing infrastructure in predefined sizes or custom machine shapes to accelerate cloud transformation. General purpose machines (E2, N1,N2,N2D) offer a good compromise between price and performance. Compute optimized machines (C2) offer high-end performance vCPUs for compute-intensive workloads. Memory optimized (M2) systems offer the highest amount of memory and are ideal for in-memory database applications. Accelerator optimized machines (A2) are based on A100 GPUs, and are designed for high-demanding applications. Integrate Compute services with other Google Cloud Services, such as AI/ML or data analytics. Reservations can help you ensure that your applications will have the capacity needed as they scale. You can save money by running Compute using the sustained-use discount, and you can even save more when you use the committed-use discount.

CloudZero helps businesses optimize cloud spend with full visibility into costs—so they can reduce wasteful spending and improve their unit economics. Unlike other solutions, we take an engineering-led approach to cost optimization, helping teams understand what drives 100% of their operational cloud spend, empowering them to reduce risk, minimize waste, and maximize profit.

RunPod provides a cloud infrastructure that enables seamless deployment and scaling of AI workloads with GPU-powered pods. By offering access to a wide array of NVIDIA GPUs, such as the A100 and H100, RunPod supports training and deploying machine learning models with minimal latency and high performance. The platform emphasizes ease of use, allowing users to spin up pods in seconds and scale them dynamically to meet demand. With features like autoscaling, real-time analytics, and serverless scaling, RunPod is an ideal solution for startups, academic institutions, and enterprises seeking a flexible, powerful, and affordable platform for AI development and inference.

You can use your favorite debugging software to locally troubleshoot your Kubernetes services. Telepresence, an open-source tool, allows you to run one service locally and connect it to a remote Kubernetes cluster. Telepresence was initially developed by Ambassador Labs, which creates open-source development tools for Kubernetes such as Ambassador and Forge. We welcome all contributions from the community. You can help us by submitting an issue, pull request or reporting a bug. Join our active Slack group to ask questions or inquire about paid support plans. Telepresence is currently under active development. Register to receive updates and announcements. You can quickly debug locally without waiting for a container to be built/push/deployed. Ability to use their favorite local tools such as debugger, IDE, etc. Ability to run large-scale programs that aren't possible locally.

StarTree Cloud is a fully-managed real-time analytics platform designed for OLAP at massive speed and scale for user-facing applications. Powered by Apache Pinot, StarTree Cloud provides enterprise-grade reliability and advanced capabilities such as tiered storage, scalable upserts, plus additional indexes and connectors. It integrates seamlessly with transactional databases and event streaming platforms, ingesting data at millions of events per second and indexing it for lightning-fast query responses. StarTree Cloud is available on your favorite public cloud or for private SaaS deployment. StarTree Cloud includes StarTree Data Manager, which allows you to ingest data from both real-time sources such as Amazon Kinesis, Apache Kafka, Apache Pulsar, or Redpanda, as well as batch data sources such as data warehouses like Snowflake, Delta Lake or Google BigQuery, or object stores like Amazon S3, Apache Flink, Apache Hadoop, or Apache Spark. StarTree ThirdEye is an add-on anomaly detection system running on top of StarTree Cloud that observes your business-critical metrics, alerting you and allowing you to perform root-cause analysis — all in real-time.

Identity and Data Protection for AWS and Azure, Google Cloud, and Kubernetes. Sonrai's cloud security platform offers a complete risk model that includes activity and movement across cloud accounts and cloud providers. Discover all data and identity relationships between administrators, roles and compute instances. Our critical resource monitor monitors your critical data stored in object stores (e.g. AWS S3, Azure Blob), and database services (e.g. CosmosDB, Dynamo DB, RDS). Privacy and compliance controls are maintained across multiple cloud providers and third-party data stores. All resolutions are coordinated with the relevant DevSecOps groups.

Protect and optimize mission-critical Kubernetes apps. Fairwinds Insights, a Kubernetes configuration validation tool, monitors your Kubernetes containers and recommends improvements. The software integrates trusted open-source tools, toolchain integrations and SRE expertise, based on hundreds successful Kubernetes deployments. The need to balance the speed of engineering and the reactive pace of security can lead to messy Kubernetes configurations, as well as unnecessary risk. It can take engineering time to adjust CPU or memory settings. This can lead to over-provisioning of data centers capacity or cloud compute. While traditional monitoring tools are important, they don't offer everything necessary to identify and prevent changes that could affect Kubernetes workloads.

AWS Auto Scaling continuously observes your applications and automatically modifies capacity to ensure consistent and reliable performance while minimizing costs. This service simplifies the process of configuring application scaling for various resources across multiple services in just a few minutes. It features an intuitive and robust user interface that enables the creation of scaling plans for a range of resources, including Amazon EC2 instances, Spot Fleets, Amazon ECS tasks, Amazon DynamoDB tables and indexes, as well as Amazon Aurora Replicas. By providing actionable recommendations, AWS Auto Scaling helps you enhance performance, reduce expenses, or strike a balance between the two. If you are utilizing Amazon EC2 Auto Scaling for dynamic scaling of your EC2 instances, you can now seamlessly integrate it with AWS Auto Scaling to extend your scaling capabilities to additional AWS services. This ensures that your applications are consistently equipped with the appropriate resources precisely when they are needed, leading to improved overall efficiency. Ultimately, AWS Auto Scaling empowers businesses to optimize their resource management in a highly efficient manner.

Amazon CloudWatch serves as a comprehensive monitoring and observability tool designed specifically for DevOps professionals, software developers, site reliability engineers, and IT administrators. This service equips users with essential data and actionable insights necessary for overseeing applications, reacting to performance shifts across systems, enhancing resource efficiency, and gaining an integrated perspective on operational health. By gathering monitoring and operational information in the forms of logs, metrics, and events, CloudWatch delivers a cohesive view of AWS resources, applications, and services, including those deployed on-premises. Users can leverage CloudWatch to identify unusual patterns within their environments, establish alerts, visualize logs alongside metrics, automate responses, troubleshoot problems, and unearth insights that contribute to application stability. Additionally, CloudWatch alarms continuously monitor your specified metric values against established thresholds or those generated through machine learning models to effectively spot any anomalous activities. This functionality ensures that users can maintain optimal performance and reliability across their systems.

StormForge drives immediate benefits for organization through its continuous Kubernetes workload rightsizing capabilities — leading to cost savings of 40-60% along with performance and reliability improvements across the entire estate. As a vertical rightsizing solution, Optimize Live is autonomous, tunable, and works seamlessly with the HPA at enterprise scale. Optimize Live addresses both over- and under-provisioned workloads by analyzing usage data with advanced ML algorithms to recommend optimal resource requests and limits. Recommendations can be deployed automatically on a flexible schedule, accounting for changes in traffic patterns or application resource requirements, ensuring that workloads are always right-sized, and freeing developers from the toil and cognitive load of infrastructure sizing.

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.

CostSage was designed to empower SaaS teams to manage their fluctuating cloud expenses through innovative and automated cloud cost management solutions. In contrast to conventional FinOps platforms, it seamlessly integrates with Slack and email, featuring an intuitive dashboard that provides immediate insights, projections, and notifications about potential savings, ensuring that cloud cost reductions are simple, clear, and attainable for any organization. Furthermore, there are no initial charges involved, and the pricing structure relies entirely on confirmed savings, allowing CostSage to promise tangible returns on investment from the very first day, making the onboarding process incredibly quick—taking less than a minute to complete. This efficiency not only saves time but also sets the stage for immediate financial benefits.

Zesty’s cloud infrastructure optimization platform offers solutions for databases, storage and compute. It also helps companies reduce cloud spending. Zesty, powered by machine learning and automation, provides FinOps/DevOps teams actionable insights to fit real-time applications and achieve optimal utilization of cloud resources. Zesty Commitment Manager optimizes EC2 discount plans and RDS automatically, ensuring maximum coverage with deeper savings. This is done with minimal financial risk. Zesty Disk automatically scales EBS volumes up or down to match real-time applications needs. This optimizes storage utilization, eliminates the risk of downtime and reduces costs by up 70%. Zesty Insights gives you a clear view of your potential savings, unused resources and offers actionable suggestions that will help you focus on saving the most money.

Learn more about the capabilities of your cloud estate. Our dashboard view allows you to control your cloud estate from any device. To reduce your cloud spend up to 80%, you can use spot instances at a lower price and utilisation recommendations. Cloud Manager offers 24/7 automated monitoring to keep your data secure and your estate in compliance. Fully automated workflows provide cost recommendations and flag issues to ensure you can quickly take action and reduce costs. Analyze cloud costs and allocate and recharge them to customers and other business units. Our advanced automation services and dashboard make cloud management easier for you. We provide structure and process to help team members understand why their work is important. Additionally, we provide trend and dashboard to show business and delivery teams the value they add.

Harness is a comprehensive AI-native software delivery platform designed to modernize DevOps practices by automating continuous integration, continuous delivery, and GitOps workflows across multi-cloud and multi-service environments. It empowers engineering teams to build faster, deploy confidently, and manage infrastructure as code with automated error reduction and cost control. The platform integrates new capabilities like database DevOps, artifact registries, and on-demand cloud development environments to simplify complex operations. Harness also enhances software quality through AI-driven test automation, chaos engineering, and predictive incident response that minimize downtime. Feature management and experimentation tools allow controlled releases and data-driven decision-making. Security and compliance are strengthened with automated vulnerability scanning, runtime protection, and supply chain security. Harness offers deep insights into engineering productivity and cloud spend, helping teams optimize resources. With over 100 integrations and trusted by top companies, Harness unifies AI and DevOps to accelerate innovation and developer productivity.

No expertise required! Our Kubernetes Management platform allows you to create clusters in minutes. Every feature of our platform has been designed to automate DevOps. We ensure that every component is tightly interconnected by building everything from scratch. This allows us to achieve the best performance and reduce complexity. Syself Autopilot supports declarative configurations. This is an approach where configuration files are used to define the desired states of your infrastructure and application. Instead of issuing commands that change the current state, the system will automatically make the necessary adjustments in order to achieve the desired state.

Pepperdata autonomous, application-level cost optimization delivers 30-47% greater cost savings for data-intensive workloads such as Apache Spark on Amazon EMR and Amazon EKS with no application changes. Using patented algorithms, Pepperdata Capacity Optimizer autonomously optimizes CPU and memory in real time with no application code changes. Pepperdata automatically analyzes resource usage in real time, identifying where more work can be done, enabling the scheduler to add tasks to nodes with available resources and spin up new nodes only when existing nodes are fully utilized. The result: CPU and memory are autonomously and continuously optimized, without delay and without the need for recommendations to be applied, and the need for ongoing manual tuning is safely eliminated. Pepperdata pays for itself, immediately decreasing instance hours/waste, increasing Spark utilization, and freeing developers from manual tuning to focus on innovation.

A pay-as-you-go security and observability software-as-a-service (SaaS) solution designed for containers, Kubernetes, and cloud environments provides users with a real-time overview of service dependencies and interactions across multi-cluster, hybrid, and multi-cloud setups. This platform streamlines the onboarding process and allows for quick resolution of Kubernetes security and observability challenges within mere minutes. Calico Cloud represents a state-of-the-art SaaS offering that empowers organizations of various sizes to secure their cloud workloads and containers, identify potential threats, maintain ongoing compliance, and address service issues in real-time across diverse deployments. Built upon Calico Open Source, which is recognized as the leading container networking and security framework, Calico Cloud allows teams to leverage a managed service model instead of managing a complex platform, enhancing their capacity for rapid analysis and informed decision-making. Moreover, this innovative platform is tailored to adapt to evolving security needs, ensuring that users are always equipped with the latest tools and insights to safeguard their cloud infrastructure effectively.

Only StackRox offers an all-encompassing view of your cloud-native environment, covering everything from images and container registries to Kubernetes deployment settings and container runtime activities. With its robust integration into Kubernetes, StackRox provides insights specifically tailored to deployments, equipping security and DevOps teams with a thorough understanding of their cloud-native systems, which includes images, containers, pods, namespaces, clusters, and their respective configurations. You gain quick insights into potential risks within your environment, your compliance standing, and any suspicious traffic that may be occurring. Each overview allows you to delve deeper into specifics. Furthermore, StackRox simplifies the process of identifying and scrutinizing container images in your environment, thanks to its native integrations and support for nearly all types of image registries, making it a vital tool for maintaining security and efficiency.

OpenCost is an open-source initiative that is vendor-neutral, designed to measure and allocate costs associated with cloud infrastructure and containers in real-time. Developed by experts in Kubernetes and backed by practitioners in the field, OpenCost brings transparency to the often opaque spending patterns associated with Kubernetes. It offers flexible and customizable options for cost allocation and monitoring of cloud resources, facilitating accurate showback, chargeback, and continuous reporting. The tool provides real-time cost allocation that can be examined down to individual containers, ensuring precise tracking of expenses. It effectively allocates costs for in-cluster resources, including CPU, GPU, memory, load balancers, and persistent volumes. Additionally, OpenCost features dynamic asset pricing by integrating with billing APIs from AWS, Azure, and GCP, while also accommodating on-premises Kubernetes clusters with tailored pricing solutions. Beyond the Kubernetes cluster, it can monitor expenses from cloud providers related to resources such as object storage and databases, as well as other managed services. Furthermore, it seamlessly integrates with other open-source tools, allowing for convenient exports of pricing data to platforms like Prometheus, enhancing its utility in cost management. This makes OpenCost a comprehensive solution for organizations seeking to maintain control over their cloud spending effectively.

Security and observability tailored for Kubernetes environments. Implementing security and observability as code is essential for modern cloud-native applications. This approach encompasses cloud-native security as code for various elements, including hosts, virtual machines, containers, Kubernetes components, workloads, and services, ensuring protection for both north-south and east-west traffic while facilitating enterprise security measures and maintaining continuous compliance. Furthermore, Kubernetes-native observability as code allows for the gathering of real-time telemetry, enhanced with context from Kubernetes, offering a dynamic view of interactions among components from hosts to services. This enables swift troubleshooting through machine learning-driven detection of anomalies and performance issues. Utilizing a single framework, organizations can effectively secure, monitor, and address challenges in multi-cluster, multi-cloud, and hybrid-cloud environments operating on either Linux or Windows containers. With the ability to update and deploy security policies in mere seconds, businesses can promptly enforce compliance and address any emerging issues. This streamlined process is vital for maintaining the integrity and performance of cloud-native infrastructures.

Kubernetes is an open-source platform that provides developers and DevOps with an end-to-end security solution. This includes security compliance, risk analysis, security compliance and RBAC visualizer. It also scans images for vulnerabilities. Kubescape scans K8s clusters, Kubernetes manifest files (YAML files, and HELM charts), code repositories, container registries and images, detecting misconfigurations according to multiple frameworks (such as the NSA-CISA, MITRE ATT&CK®), finding software vulnerabilities, and showing RBAC (role-based-access-control) violations at early stages of the CI/CD pipeline. It instantly calculates risk scores and displays risk trends over time. Kubescape is one of the most popular Kubernetes security compliance tools for developers. Its easy-to-use interface, flexible output formats and automated scanning capabilities have made Kubescape one of the fastest growing Kubernetes tools. This has saved Kubernetes admins and users precious time, effort and resources.

Calico Enterprise offers a comprehensive security platform designed for full-stack observability specifically tailored for containers and Kubernetes environments. As the sole active security solution in the industry that integrates this capability, Calico Enterprise leverages Kubernetes' declarative approach to define security and observability as code, ensuring that security policies are consistently enforced and compliance is maintained. This platform also enhances troubleshooting capabilities across various deployments, including multi-cluster, multi-cloud, and hybrid architectures. Furthermore, it facilitates the implementation of zero-trust workload access controls that regulate traffic to and from individual pods, bolstering the security of your Kubernetes cluster. Users can also create DNS policies that enforce precise access controls between workloads and the external services they require, such as Amazon RDS and ElastiCache, thereby enhancing the overall security posture of the environment. In addition, this proactive approach allows organizations to adapt quickly to changing security requirements while maintaining seamless connectivity.

IBM Kubecost offers immediate visibility and insights into costs for teams utilizing Kubernetes, enabling ongoing reductions in cloud expenses. You can analyze costs associated with various Kubernetes elements, such as deployments, services, and namespace labels. Monitor expenses from multiple clusters in one consolidated view or through a unified API endpoint. Additionally, link Kubernetes expenditures with any external cloud services or infrastructure costs to gain a holistic understanding of your spending. Costs from external sources can be allocated to specific Kubernetes components, providing a thorough overview of financial outlays. Receive actionable suggestions for cost savings that do not compromise performance, allowing you to refine infrastructure or application modifications for enhanced resource efficiency and reliability. With real-time alerts, you can swiftly identify potential cost overruns and risks of infrastructure failures before they escalate into larger issues. Maintain seamless engineering workflows by integrating Kubecost with collaboration tools like PagerDuty and Slack, ensuring that your teams stay informed and responsive. Ultimately, this comprehensive approach empowers organizations to optimize their Kubernetes spending effectively.

Constellation stands out as a Kubernetes distribution certified by the CNCF, utilizing confidential computing to ensure the encryption and isolation of entire clusters, thus safeguarding data at rest, in transit, and during processing by executing control and worker planes within hardware-enforced trusted execution environments. The platform guarantees workload integrity through the use of cryptographic certificates and robust supply-chain security practices, including SLSA Level 3 and sigstore-based signing, while successfully meeting the benchmarks set by the Center for Internet Security for Kubernetes. Additionally, it employs Cilium alongside WireGuard to facilitate precise eBPF traffic management and comprehensive end-to-end encryption. Engineered for high availability and automatic scaling, Constellation enables near-native performance across all leading cloud providers and simplifies the deployment process with an intuitive CLI and kubeadm interface. It ensures the implementation of Kubernetes security updates within a 24-hour timeframe, features hardware-backed attestation, and offers reproducible builds, making it a reliable choice for organizations. Furthermore, it integrates effortlessly with existing DevOps tools through standard APIs, streamlining workflows and enhancing overall productivity.

Streamline the process of application delivery by utilizing software-defined load balancers, web application firewalls, and container ingress services that can be deployed across any application in various data centers and cloud environments. Enhance management efficiency through unified policies and consistent operations across on-premises data centers as well as hybrid and public cloud platforms, which include VMware Cloud (such as VMC on AWS, OCVS, AVS, and GCVE), AWS, Azure, Google Cloud, and Oracle Cloud. Empower infrastructure teams by alleviating them from manual tasks and provide DevOps teams with self-service capabilities. The automation toolkits for application delivery encompass a variety of resources, including Python SDK, RESTful APIs, and integrations with Ansible and Terraform. Additionally, achieve unparalleled insights into network performance, user experience, and security through real-time application performance monitoring, closed-loop analytics, and advanced machine learning techniques that continuously enhance system efficiency. This holistic approach not only improves performance but also fosters a culture of agility and responsiveness within the organization.

DivvyCloud empowers customers to transform their operations by granting them the ability to innovate freely with cloud services while managing the associated chaos and risk effectively. Through automated, real-time remediation, our clients can maintain ongoing security and compliance, enabling them to fully harness the advantages of cloud and container technologies. We pride ourselves on having the most developed, user-friendly, and adaptable automation features available. From the very beginning, we have prioritized automation, while many competitors have historically concentrated on reporting and have only recently begun to adopt automation solutions, if at all. DivvyCloud equips security professionals with a robust platform that automates essential protective and reactive measures, allowing enterprises to innovate rapidly in cloud environments. The significance of automation lies in its ability to balance security and speed at a large scale. By employing an API polling and event-driven method to detect risks and initiate remediation, we ensure that our customers can respond swiftly and effectively to emerging threats, further solidifying their confidence in cloud-based innovations.

Identify and prioritize your most critical business risks with actionable insights that can drive effective decision-making. Ensure your Kubernetes environment is consistently fortified for maximum availability. Gain knowledge from the experiences of others to sidestep common pitfalls. Proactively mitigate risks before they escalate into incidents. Maintain comprehensive visibility across all layers of your infrastructure to stay informed. Keep an organized inventory of containers, clusters, add-ons, and their dependencies. Aggregate insights from various clouds and on-premises environments for a unified view. Receive timely alerts regarding end-of-life (EOL) and incompatible versions to keep your systems updated. Say goodbye to spreadsheets and custom scripts forever. Chkk’s goal is to empower developers to avert incidents by learning from the experiences of others and avoiding previously established errors. Utilizing Chkk's collective learning technology, users can access a wealth of curated information on known errors, failures, and disruptions experienced within the Kubernetes community, which includes users, operators, cloud service providers, and vendors, thereby ensuring that history does not repeat itself. This proactive approach not only fosters a culture of continuous improvement but also enhances overall system resilience.

CloudNatix has the capability to connect seamlessly to any infrastructure, whether it be in the cloud, a data center, or at the edge, and supports a variety of platforms including virtual machines, Kubernetes, and managed Kubernetes clusters. By consolidating your distributed resource pools into a cohesive planet-scale cluster, this service is delivered through a user-friendly SaaS model. Users benefit from a global dashboard that offers a unified perspective on costs and operational insights across various cloud and Kubernetes environments, such as AWS, EKS, Azure, AKS, Google Cloud, GKE, and more. This comprehensive view enables you to explore the intricacies of each resource, including specific instances and namespaces, across diverse regions, availability zones, and hypervisors. Additionally, CloudNatix facilitates a unified cost-attribution framework that spans multiple public, private, and hybrid clouds, as well as various Kubernetes clusters and namespaces. Furthermore, it automates the process of attributing costs to specific business units as you see fit, streamlining financial management within your organization. This level of integration and oversight empowers businesses to optimize resource utilization and make informed decisions regarding their cloud strategies.

Establish governance policies that effectively manage cloud-native environments while preserving agility and speed. Assign budgets to distinct teams or projects, monitor expenses, regulate resource utilization, and provide immediate notifications for budget exceedances. Oversee the entire asset life cycle, from initiation and ownership to modification and eventual termination. Gain insights into the intricate consumption patterns of resources and the associated costs for decentralized development teams, all while encouraging developers to deliver value with every deployment. It’s essential to ensure that microservices, containers, pods, and Kubernetes clusters operate with optimal resource efficiency, maintaining reliability, availability, and performance standards. Replex facilitates the right-sizing of Kubernetes nodes and cloud instances by leveraging both historical and real-time usage data, serving as a comprehensive repository for all critical performance metrics to enhance decision-making processes. This comprehensive approach ensures that teams can stay on top of their cloud expenses while still fostering innovation and efficiency.

Efficiently provision, manage, and scale your computing infrastructure across any cloud platform while potentially reducing your expenses by as much as 80%, all while upholding service level agreements and ensuring high availability. Elastigroup is a sophisticated cluster management software created to enhance both performance and cost efficiency. It empowers organizations of varying sizes and industries to effectively utilize Cloud Excess Capacity, enabling them to optimize their workloads and achieve savings of up to 90% on compute infrastructure costs. Utilizing advanced proprietary technology for price prediction, Elastigroup can reliably deploy resources to Spot Instances. By anticipating interruptions and fluctuations, the software proactively adjusts clusters to maintain seamless operations. Furthermore, Elastigroup effectively harnesses excess capacity from leading cloud providers, including EC2 Spot Instances from AWS, Low-priority VMs from Microsoft Azure, and Preemptible VMs from Google Cloud, all while minimizing risk and complexity. This results in straightforward orchestration and management that scales effortlessly, allowing businesses to focus on their core activities without the burden of cloud infrastructure challenges.

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.

Lucidity serves as a versatile multi-cloud storage management solution, adept at dynamically adjusting block storage across major platforms like AWS, Azure, and Google Cloud while ensuring zero downtime, which can lead to savings of up to 70% on storage expenses. This innovative platform automates the process of resizing storage volumes in response to real-time data demands, maintaining optimal disk usage levels between 75-80%. Additionally, Lucidity is designed to function independently of specific applications, integrating effortlessly into existing systems without necessitating code alterations or manual provisioning. The AutoScaler feature of Lucidity, accessible via the AWS Marketplace, provides businesses with an automated method to manage live EBS volumes, allowing for expansion or reduction based on workload requirements, all without any interruptions. By enhancing operational efficiency, Lucidity empowers IT and DevOps teams to recover countless hours of work, which can then be redirected towards more impactful projects that foster innovation and improve overall effectiveness. This capability ultimately positions enterprises to better adapt to changing storage needs and optimize resource utilization.

Amazon EC2 Auto Scaling ensures that your applications remain available by allowing for the automatic addition or removal of EC2 instances based on scaling policies that you set. By utilizing dynamic or predictive scaling policies, you can adjust the capacity of EC2 instances to meet both historical and real-time demand fluctuations. The fleet management capabilities within Amazon EC2 Auto Scaling are designed to sustain the health and availability of your instance fleet effectively. In the realm of efficient DevOps, automation plays a crucial role, and one of the primary challenges lies in ensuring that your fleets of Amazon EC2 instances can automatically launch, provision software, and recover from failures. Amazon EC2 Auto Scaling offers vital functionalities for each phase of instance lifecycle automation. Furthermore, employing machine learning algorithms can aid in forecasting and optimizing the number of EC2 instances needed to proactively manage anticipated changes in traffic patterns. By leveraging these advanced features, organizations can enhance their operational efficiency and responsiveness to varying workload demands.

Espresso AI is a sophisticated data-warehouse optimization platform designed to lower compute and query expenses for services like Snowflake and Databricks SQL by utilizing machine-learning agents that handle scaling, scheduling, and query rewriting in real-time. It consists of three essential agents: an autoscaling agent that anticipates workload surges and cuts down on idle compute, a scheduling agent that efficiently directs queries across clusters to enhance utilization and minimize idle time, and a query agent that employs large language models along with formal verification techniques to rewrite SQL, ensuring that results remain consistent while enhancing performance. The system touts rapid deployment capabilities, claiming that users can get started in minutes instead of months, and features a pricing structure linked to the actual savings it generates, meaning you don't incur costs if it fails to lower your bill. By automating a vast number of optimization decisions each day, Espresso AI not only promises significant cost savings but also allows engineering teams to concentrate on developing features that add value. This innovative approach allows businesses to harness their data warehouse capabilities without the usual overhead, thus transforming the way they manage and utilize their data resources.

CloudAvocado is designed to enhance your AWS workload efficiency while optimizing costs effectively. It offers a set of tools that enable you to maximize your resource utilization without adding unnecessary complexity. By bridging the gaps across different AWS accounts and business units, you can gain valuable insights into resources that are either unused or underused, potentially reducing expenses by an impressive 30-70%. Transform your usage data into an easily understandable format and streamline your spending with CloudAvocado. This platform was developed to make the oversight of your cloud assets and expenditures more straightforward. We equip you with the necessary tools to fully leverage your resources while minimizing complications. With comprehensive visibility into all your resources across every region, you can manage them more efficiently and quickly locate what you need without the frustration of tracking down which region holds a specific resource. Now, everything is accessible in a single, convenient location, allowing for greater efficiency in cloud management.

NVIDIA DGX Cloud Serverless Inference provides a cutting-edge, serverless AI inference framework designed to expedite AI advancements through automatic scaling, efficient GPU resource management, multi-cloud adaptability, and effortless scalability. This solution enables users to reduce instances to zero during idle times, thereby optimizing resource use and lowering expenses. Importantly, there are no additional charges incurred for cold-boot startup durations, as the system is engineered to keep these times to a minimum. The service is driven by NVIDIA Cloud Functions (NVCF), which includes extensive observability capabilities, allowing users to integrate their choice of monitoring tools, such as Splunk, for detailed visibility into their AI operations. Furthermore, NVCF supports versatile deployment methods for NIM microservices, granting the ability to utilize custom containers, models, and Helm charts, thus catering to diverse deployment preferences and enhancing user flexibility. This combination of features positions NVIDIA DGX Cloud Serverless Inference as a powerful tool for organizations seeking to optimize their AI inference processes.

Kubernetes can be run in production using the #1 Kubernetes platform. It offers persistent storage, backup, data security, capacity management, and DR. You can easily backup, restore, and migrate Kubernetes applications to any cloud or data centre. Portworx Enterprise Storage Platform provides end-to-end storage, data management, and security for all Kubernetes projects. This includes container-based CaaS and DBaaS as well as SaaS and Disaster Recovery. Container-granular storage, disaster recovery and data security will all be available to your apps. Multi-cloud migrations are also possible. You can easily solve enterprise requirements for Kubernetes data service. Your users can easily access a cloud-like DbaaS without losing control. Operational complexity is eliminated by scaling the backend data services that power your SaaS app. With a single command, add DR to any Kubernetes application. All your Kubernetes apps can be easily backed up and restored.

The Xosphere Instance Orchestrator enhances cost efficiency through automated spot optimization by utilizing AWS Spot instances, ensuring that the infrastructure remains as reliable as on-demand instances. By diversifying Spot instances across different families, sizes, and availability zones, it minimizes potential disruptions caused by the reclamation of these instances. Instances that are backed by reservations will not be substituted with Spot instances, preserving their intended use. Additionally, the system is designed to automatically respond to Spot termination notifications, allowing for expedited replacement of on-demand instances. Furthermore, EBS volumes can be configured to attach seamlessly to newly provisioned replacement instances, facilitating uninterrupted operation of stateful applications. This orchestration ensures a robust infrastructure while optimizing costs effectively.

Establish your Kubernetes infrastructure and utilize KubeGrid for the seamless deployment, monitoring, and optimization of potentially thousands of clusters. KubeGrid streamlines the complete lifecycle management of Kubernetes across both on-premises and cloud environments, allowing developers to effortlessly deploy, manage, and update numerous clusters. As a Platform as Code solution, KubeGrid enables you to declaratively specify all your Kubernetes needs in a code format, covering everything from your on-prem or cloud infrastructure to the specifics of clusters and autoscaling policies, with KubeGrid handling the deployment and management automatically. While most infrastructure-as-code solutions focus solely on provisioning, KubeGrid enhances the experience by automating Day 2 operations, including monitoring infrastructure, managing failovers for unhealthy nodes, and updating both clusters and their operating systems. Thanks to its innovative approach, Kubernetes excels in the automated provisioning of pods, ensuring efficient resource utilization across your infrastructure. By adopting KubeGrid, you transform the complexities of Kubernetes management into a streamlined and efficient process.

IBM Storage for Red Hat OpenShift seamlessly integrates traditional and container storage, facilitating the deployment of enterprise-grade scale-out microservices architectures with ease. This solution has been validated alongside Red Hat OpenShift, Kubernetes, and IBM Cloud Pak, ensuring a streamlined deployment and management process for a cohesive experience. It offers enterprise-level data protection, automated scheduling, and data reuse capabilities specifically tailored for Red Hat OpenShift and Kubernetes settings. With support for block, file, and object data resources, users can swiftly deploy their required resources as needed. Additionally, IBM Storage for Red Hat OpenShift lays the groundwork for a robust and agile hybrid cloud environment on-premises, providing the essential infrastructure and storage orchestration. Furthermore, IBM enhances container utilization in Kubernetes environments by supporting Container Storage Interface (CSI) for its block and file storage solutions. This comprehensive approach empowers organizations to optimize their storage strategies while maximizing efficiency and scalability.

BotKube is an innovative messaging bot designed for the monitoring and troubleshooting of Kubernetes clusters, developed and supported by InfraCloud. This versatile tool seamlessly integrates with various messaging platforms such as Slack, Mattermost, and Microsoft Teams, enabling users to oversee their Kubernetes environments, address critical deployment issues, and receive best practice recommendations through checks on Kubernetes resources. By observing Kubernetes activities, BotKube promptly alerts the designated channel about any noteworthy events, such as an ImagePullBackOff error, ensuring timely awareness. Users can tailor the specific objects and event severity levels they wish to monitor from their Kubernetes clusters, with the flexibility to enable or disable notifications as needed. Furthermore, BotKube is capable of executing kubectl commands within the Kubernetes cluster without requiring access to Kubeconfig or the underlying infrastructure, enhancing security. With BotKube, you can easily troubleshoot your deployments, services, or any other aspects of your cluster directly from your messaging interface, fostering a more efficient workflow. The ability to receive instant updates and perform actions from a familiar messaging platform significantly streamlines the management of Kubernetes environments.

KubeArmor is an open-source, cloud-native security engine that provides runtime enforcement for Kubernetes clusters, containers, and virtual machines, using eBPF and Linux Security Modules such as AppArmor, BPF-LSM, and SELinux. It protects workloads by restricting behaviors like process execution, file operations, networking, and resource consumption, all enforced through customizable, Kubernetes-native policies. Unlike traditional post-attack mitigations that react after malicious activity occurs, KubeArmor’s inline enforcement blocks threats proactively without requiring changes to containers or hosts. Its simplified policy descriptions and non-privileged daemonset architecture make it easy to deploy and manage across diverse environments, including multi-cloud and edge networks. The platform logs policy violations in real time and supports granular network communication controls between containers. Installation can be done effortlessly using Helm charts, with detailed documentation and video guides available. KubeArmor is listed on AWS, Red Hat, Oracle, and DigitalOcean marketplaces, demonstrating broad industry acceptance. It also offers specialized features for IoT, 5G security, and workload sandboxing, making it a versatile choice for modern cloud-native security.

Checkmk is an IT monitoring system that allows system administrators, IT managers and DevOps teams, to quickly identify and resolve issues across their entire IT infrastructure (servers and applications, networks, storage and databases, containers, etc. Checkmk is used daily by more than 2,000 commercial customers worldwide and many other open-source users. Key product features * Service state monitoring with nearly 2,000 checks 'outside the box' * Event-based and log-based monitoring * Metrics, dynamic Graphing, and Long-Term Storage * Comprehensive reporting incl. Accessibility and SLAs * Flexible notifications and automated alert handling * Monitoring business processes and complex systems * Software and hardware inventory * Graphical, rule-based configuration and automated service discovery These are the top use cases * Server Monitoring * Network Monitoring * Application Monitoring * Database Monitoring * Storage Monitoring * Cloud Monitoring * Container Monitoring

Red Hat Advanced Cluster Management for Kubernetes allows users to oversee clusters and applications through a centralized interface, complete with integrated security policies. By enhancing the capabilities of Red Hat OpenShift, it facilitates the deployment of applications, the management of multiple clusters, and the implementation of policies across numerous clusters at scale. This solution guarantees compliance, tracks usage, and maintains uniformity across deployments. Included with Red Hat OpenShift Platform Plus, it provides an extensive array of powerful tools designed to secure, protect, and manage applications effectively. Users can operate from any environment where Red Hat OpenShift is available and can manage any Kubernetes cluster within their ecosystem. The self-service provisioning feature accelerates application development pipelines, enabling swift deployment of both legacy and cloud-native applications across various distributed clusters. Additionally, self-service cluster deployment empowers IT departments by automating the application delivery process, allowing them to focus on higher-level strategic initiatives. As a result, organizations can achieve greater efficiency and agility in their IT operations.