Business Software for New Relic

Container-based workloads, full GPU support and autoscaling. Custom built solutions. Worker will take care of your jobs so that you can concentrate on your application. Hosted background job solution that allows you to manage your containers with dynamic scale and detailed analytics. You can run short-term containers quickly or containers that need to be used over multiple days. We can help you with any job, no matter how small or large. You can confidently containerize your background tasks. Our shared infrastructure will allow you to run your containers. You can use dedicated hardware to support your workloads. This is a great option if you need consistent performance and throughput. Our autoscale technology allows you to scale up or down depending on your usage. We manage scheduling, authentication, and all other details. You can run workers on your hardware. This is a great option if you have your own infrastructure or have higher security requirements.

Leverage data and automation to safeguard your multi-cloud setup, accurately assess risks, and foster innovation with assurance. Accelerate your development process by integrating security from the very beginning of your coding journey. Acquire actionable security insights to efficiently build applications while proactively addressing potential issues before they enter production, all seamlessly integrated into your current workflows. Our advanced platform harnesses patented machine learning and behavioral analytics to intuitively understand the typical behavior of your environment, flagging any anomalies that arise. With comprehensive visibility, you can monitor every aspect of your multi-cloud ecosystem, identifying threats, vulnerabilities, misconfigurations, and any irregular activities. Data and analytics enhance precision to an unmatched degree, ensuring that only the most critical alerts are highlighted while eliminating unnecessary noise. As the platform continuously evolves, rigid rules become less necessary, allowing for more flexibility in your security approach. This adaptability empowers teams to focus on innovation without compromising safety.

Effortlessly scale your applications on Compute Engine from idle to peak performance using Cloud Load Balancing without the need for pre-warming. You can effectively distribute your load-balanced resources across one or several regions, ensuring proximity to your users while fulfilling high availability demands. With Cloud Load Balancing, your resources can be managed behind a single anycast IP, allowing for seamless scaling up or down through intelligent autoscaling features. The service offers various configurations and is integrated with Cloud CDN, enhancing application performance and content delivery. Moreover, Cloud Load Balancing employs a single anycast IP to manage all your backend instances globally. It also ensures cross-region load balancing and automatic multi-region failover, skillfully redirecting traffic in small increments if any backends experience issues. Unlike traditional DNS-based global load balancing solutions, Cloud Load Balancing provides immediate responses to fluctuations in user activity, network conditions, backend health, and more, adapting to ensure optimal performance. This rapid adaptability makes it an ideal choice for businesses requiring reliable and efficient resource management.

Azure Machine Learning Studio enables organizations to streamline the entire machine learning lifecycle from start to finish. Equip developers and data scientists with an extensive array of efficient tools for swiftly building, training, and deploying machine learning models. Enhance the speed of market readiness and promote collaboration among teams through leading-edge MLOps—akin to DevOps but tailored for machine learning. Drive innovation within a secure, reliable platform that prioritizes responsible AI practices. Cater to users of all expertise levels with options for both code-centric and drag-and-drop interfaces, along with automated machine learning features. Implement comprehensive MLOps functionalities that seamlessly align with existing DevOps workflows, facilitating the management of the entire machine learning lifecycle. Emphasize responsible AI by providing insights into model interpretability and fairness, securing data through differential privacy and confidential computing, and maintaining control over the machine learning lifecycle with audit trails and datasheets. Additionally, ensure exceptional compatibility with top open-source frameworks and programming languages such as MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R, thus broadening accessibility and usability for diverse projects. By fostering an environment that promotes collaboration and innovation, teams can achieve remarkable advancements in their machine learning endeavors.

Enhance financial accountability by leveraging smart resource allocation and precise monitoring of cloud metering and chargeback through NCM Cost Governance, previously known as Beam. By utilizing this system, organizations can gain improved visibility, optimize performance, and maintain control throughout public, private, and hybrid multi-cloud environments, ensuring that cloud expenditures remain manageable. Understanding spending across both public and private clouds streamlines the processes of cost management and governance in multi-cloud scenarios. Companies can realize savings by automating various tasks, adjusting resource sizes appropriately, and making informed decisions about reserved instance purchases. Resource costs can be allocated on a consumption basis, while a multifaceted chargeback approach reinforces governance efforts. The total cost of ownership accurately reflects the true expenses associated with operating a private cloud, incorporating all IT administrative costs as determined by customizable industry benchmarks. Furthermore, organizations can automatically generate reports detailing cloud consumption to assign untagged expenses to specific cost centers, and they can configure budget alerts to maintain costs within desired limits, ultimately fostering a culture of financial discipline. This proactive approach to cloud cost management not only enhances visibility but also drives strategic decision-making across the organization.

Torii is a SaaS platform for managing your SaaS business. It transforms how companies operate by creating an autonomous IT that allows IT to increase velocity and agility. Torii allows IT professionals to optimize and control SaaS costs and discover SaaS usage within their organizations. Torii provides instant visibility and control of all company-wide SaaS applications (cross G Suite, Okta and Dropbox), giving IT control over SaaS. Companies use Torii for: 1. Automated visibility of all SaaS app usage 2. SaaS apps waste and cost tracking 3. Automated, compliant employee on-boarding/off-boarding 4. SaaS License Management and Renewals Torii's customers include Pipedrive, Delivery Hero and Via.

IBM Cloud® Kubernetes Service offers a certified and managed Kubernetes platform designed for the deployment and management of containerized applications on IBM Cloud®. This service includes features like intelligent scheduling, self-healing capabilities, and horizontal scaling, all while ensuring secure management of the necessary resources for rapid deployment, updating, and scaling of applications. By handling the master management, IBM Cloud Kubernetes Service liberates users from the responsibilities of overseeing the host operating system, the container runtime, and the updates for the Kubernetes version. This allows developers to focus more on building and innovating their applications rather than getting bogged down by infrastructure management. Furthermore, the service’s robust architecture promotes efficient resource utilization, enhancing overall performance and reliability.

Mux Video is an API-centric platform crafted by video specialists, utilizing data to enable stunning video experiences for any development team. With just a few lines of code in your preferred programming language, you can seamlessly integrate streaming video. Mux is equipped to support video workflows of varying complexities. Its data-driven technology ensures that encoding and delivery are automatically optimized for flawless performance across all devices, every single time. Whether you’re working with the latest devices or different formats, Mux is capable of managing it all effortlessly. Benefit from over a decade of expertise in constructing video infrastructure to maintain your competitive edge. Instead of locking you into a specific player, we allow flexibility by enabling integration with any video player of your choice. If you’re still in the process of selecting a video player, our experience in creating a top-tier open-source web player enables us to assist you in choosing the best option for your application, whether it be web-based or native. Additionally, Mux's commitment to user satisfaction ensures that you receive continuous support and updates as technology evolves.

Anthos enables the creation, deployment, and management of applications in a secure and uniform way, regardless of location. It facilitates the modernization of legacy applications operating on virtual machines while simultaneously allowing for the launch of cloud-native applications utilizing containers in a complex hybrid and multi-cloud landscape. By offering a seamless development and operational experience across all deployments, Anthos significantly lowers operational burdens and enhances developer efficiency. Anthos GKE serves as a robust container orchestration and management solution, suitable for running Kubernetes clusters both in cloud environments and on-premises. Anthos Config Management allows organizations to define, automate, and enforce policies across various environments, ensuring adherence to specific security and compliance standards. Furthermore, Anthos Service Mesh alleviates the challenges faced by operations and development teams, enabling them to effectively manage and secure service traffic while also monitoring and optimizing application performance. This comprehensive platform thus supports businesses in navigating the complexities of modern application development and deployment.

Azure Cosmos DB offers a fully managed NoSQL database solution tailored for contemporary application development, ensuring single-digit millisecond response times and an impressive availability rate of 99.999 percent, all supported by service level agreements. This service provides automatic, instantaneous scalability and supports open-source APIs for MongoDB and Cassandra, allowing for rapid data operations. With its turnkey multi-master global distribution, users can experience swift read and write operations from any location around the globe. Additionally, Azure Cosmos DB enables organizations to accelerate their decision-making processes by facilitating near-real-time analytics and AI capabilities on the operational data housed within the database. Furthermore, Azure Synapse Link for Azure Cosmos DB integrates effortlessly with Azure Synapse Analytics, ensuring smooth performance without necessitating data movement or compromising the efficiency of the operational data store, enhancing the overall functionality of your data strategy. This integration not only streamlines workflows but also empowers users to derive insights more efficiently.

Amazon Neptune is an efficient and dependable graph database service that is fully managed, facilitating the development and operation of applications that handle intricate, interconnected datasets. At its heart, Amazon Neptune features a specialized, high-performance database engine tailored for the storage of billions of relationships while enabling rapid querying with latency measured in milliseconds. It accommodates widely-used graph models, including Property Graph and W3C's RDF, along with their associated query languages, Apache TinkerPop Gremlin and SPARQL, which simplifies the process of crafting queries for navigating complex datasets. This service supports various graph-based applications, including recommendation systems, fraud detection mechanisms, knowledge graphs, drug discovery initiatives, and enhanced network security protocols. With a proactive approach, it enables the detection and analysis of IT infrastructure threats through a multi-layered security framework. Furthermore, it allows users to visualize their entire infrastructure to effectively plan, forecast, and address potential risks, while also enabling the creation of graph queries for the near-real-time identification of fraudulent patterns in financial and purchasing activities, thereby enhancing overall security and efficiency.

IBM Db2 encompasses a suite of data management solutions, prominently featuring the Db2 relational database. These offerings incorporate AI-driven functionalities designed to streamline the management of both structured and unstructured data across various on-premises and multicloud settings. By simplifying data accessibility, the Db2 suite empowers businesses to leverage the advantages of AI effectively. Most components of the Db2 family are integrated within the IBM Cloud Pak® for Data platform, available either as additional features or as built-in data source services, ensuring that nearly all data is accessible across hybrid or multicloud frameworks to support AI-driven applications. You can easily unify your transactional data repositories and swiftly extract insights through intelligent, universal querying across diverse data sources. The multimodel functionality helps reduce expenses by removing the necessity for data replication and migration. Additionally, Db2 offers enhanced flexibility, allowing for deployment on any cloud service provider, which further optimizes operational agility and responsiveness. This versatility in deployment options ensures that businesses can adapt their data management strategies as their needs evolve.

Terraform is a powerful open-source tool for managing infrastructure as code, offering a consistent command-line interface to interact with numerous cloud services. By translating cloud APIs into declarative configuration files, Terraform enables users to define their infrastructure requirements clearly. Infrastructure can be written using these configuration files, leveraging the HashiCorp Configuration Language (HCL), which provides a straightforward way to describe resources through blocks, arguments, and expressions. Before making any changes to your infrastructure, executing the command terraform plan allows you to verify that the proposed execution plan aligns with your expectations. To implement the desired configuration, you can use terraform apply, which facilitates the application of changes across a wide range of cloud providers. Furthermore, Terraform empowers users to manage the entire lifecycle of their infrastructure — from creating new resources to overseeing existing ones and eventually removing those that are no longer necessary, ensuring efficient management of cloud environments. This holistic approach to infrastructure management helps streamline operations and reduces the risk of errors during deployment.

A comprehensive multi-cloud service networking solution designed to link and secure services across various runtime environments and both public and private cloud infrastructures. It offers real-time updates on the health and location of all services, ensuring progressive delivery and zero trust security with minimal overhead. Users can rest assured that all HCP connections are automatically secured, providing a strong foundation for safe operations. Moreover, it allows for detailed insights into service health and performance metrics, which can be visualized directly within the Consul UI or exported to external analytics tools. As many contemporary applications shift towards decentralized architectures rather than sticking with traditional monolithic designs, particularly in the realm of microservices, there arises a crucial need for a comprehensive topological perspective on services and their interdependencies. Additionally, organizations increasingly seek visibility into the health and performance metrics pertaining to these various services to enhance operational efficiency. This evolution in application architecture underscores the importance of robust tools that facilitate seamless service integration and monitoring.

Internet Information Services (IIS) on Windows® Server serves as a versatile, secure, and easily manageable web server suitable for a wide array of online hosting needs. Whether it's media streaming or complex web applications, IIS boasts a scalable and open framework designed to meet even the highest demands with efficiency. Its robust features allow for seamless integration and performance across various internet-based services.

Amazon Connect is a user-friendly omnichannel cloud contact center that enables organizations to deliver exceptional customer service while reducing expenses. Over a decade ago, the retail division of Amazon sought a contact center solution that would offer our customers personalized, engaging, and natural interactions, but we could not find one that fulfilled our requirements, so we decided to create our own. This innovative platform is now accessible to all businesses, and currently, thousands of companies with agent counts ranging from ten to tens of thousands utilize Amazon Connect to assist millions of customers each day. Built from its inception to be omnichannel, Amazon Connect ensures a cohesive experience across voice and chat for both customers and agents alike. It offers a unified set of tools for skills-based routing, robust real-time and historical analytics, and easy-to-navigate management features—all under a pay-as-you-go pricing model. This approach not only streamlines contact center operations but also enhances agent efficiency while significantly cutting costs. With its comprehensive features, Amazon Connect is revolutionizing the way businesses interact with their customers.

Appvance IQ (AIQ), delivers transformative productivity gains and lower costs for both test creation and execution. It offers both AI-driven (fully automated tests) and 3rd-generation codeless scripting for test creation. These scripts are then executed using data-driven functional and performance, app-pen, and API testing -- both for web and mobile apps. AIQ's self healing technology allows you to cover all code with only 10% of the effort required by traditional testing systems. AIQ detects important bugs automatically and with minimal effort. No programming, scripting, logs, or recording are required. AIQ can be easily integrated with your existing DevOps tools, processes, and tools.

Massive amounts data can be moved as messages between services, applications and systems at any one time. If an application isn’t available or a service interruption occurs, messages and transactions may be lost or duplicated. This can cost businesses time and money. IBM has refined IBM MQ over the past 25 years. MQ allows you to hold a message in a queue until it is delivered. MQ moves data once, even file data, to avoid competitors delivering messages twice or not at the right time. MQ will never lose a message. IBM MQ can be run on your mainframe, in containers, in public or private clouds or in containers. IBM offers an IBM-managed cloud service (IBM MQ Cloud), hosted on Amazon Web Services or IBM Cloud, as well as a purpose-built Appliance (IBM MQ Appliance), to simplify deployment and maintenance.

Amazon Simple Queue Service (SQS) is a fully managed message queuing platform designed to help you decouple and scale microservices, distributed systems, and serverless applications. By removing the complexity and overhead typically associated with message-oriented middleware, SQS allows developers to concentrate on more impactful tasks. With SQS, you can effortlessly send, store, and receive messages between various software components at any scale, ensuring message integrity and independence from other services. You can quickly begin using SQS in just minutes through the AWS console, Command Line Interface, or your preferred SDK, executing three straightforward commands. This service enables the transmission of any data volume at any throughput level while maintaining message reliability and service independence. Additionally, SQS facilitates the decoupling of application components, which allows them to operate and fail independently, ultimately enhancing the fault tolerance of the overall system. By leveraging SQS, organizations can achieve greater resilience and adaptability in their application architecture.

Amazon Simple Notification Service (SNS) is a comprehensive messaging platform designed for both system-to-system and app-to-person (A2P) communications. It facilitates interaction between systems through a publish/subscribe (pub/sub) model, allowing messages to flow seamlessly between independent microservice applications or directly to users via SMS, mobile push notifications, and email. The pub/sub capabilities for system-to-system interactions support topics that enable high-throughput, push-based, many-to-many messaging. By leveraging Amazon SNS topics, your publishing systems can efficiently distribute messages to a wide array of subscriber systems or customer endpoints, including Amazon SQS queues, AWS Lambda functions, and HTTP/S, thus allowing for concurrent processing. Additionally, the A2P messaging feature empowers you to send messages to users on a large scale, utilizing either a pub/sub model or direct-publish messages through a unified API. This flexibility enhances communication strategies for businesses aiming to engage their users effectively.

Managed Service for Apache Spark is a unified Google Cloud platform designed to run Apache Spark workloads with greater ease, performance, and scalability. It offers both serverless and fully managed cluster deployment options, allowing users to choose the best model for their needs. The platform eliminates the need for infrastructure management, enabling teams to focus on data processing and analytics. With Lightning Engine, it delivers up to 4.9x faster performance than open-source Spark, improving efficiency for large-scale workloads. It integrates AI-powered tools like Gemini to assist with code generation, debugging, and workflow optimization. The service supports open data formats such as Apache Iceberg and connects seamlessly with Google Cloud services like BigQuery and Knowledge Catalog. It is designed for a wide range of use cases, including ETL pipelines, machine learning, and lakehouse architectures. Built-in security features and IAM integration ensure strong data governance. Flexible pricing models allow users to pay based on job execution or cluster uptime. Overall, it helps organizations modernize their data infrastructure and accelerate analytics workflows.

Google Cloud Pub/Sub offers a robust solution for scalable message delivery, allowing users to choose between pull and push modes. It features auto-scaling and auto-provisioning capabilities that can handle anywhere from zero to hundreds of gigabytes per second seamlessly. Each publisher and subscriber operates with independent quotas and billing, making it easier to manage costs. The platform also facilitates global message routing, which is particularly beneficial for simplifying systems that span multiple regions. High availability is effortlessly achieved through synchronous cross-zone message replication, coupled with per-message receipt tracking for dependable delivery at any scale. With no need for extensive planning, its auto-everything capabilities from the outset ensure that workloads are production-ready immediately. In addition to these features, advanced options like filtering, dead-letter delivery, and exponential backoff are incorporated without compromising scalability, which further streamlines application development. This service provides a swift and dependable method for processing small records at varying volumes, serving as a gateway for both real-time and batch data pipelines that integrate with BigQuery, data lakes, and operational databases. It can also be employed alongside ETL/ELT pipelines within Dataflow, enhancing the overall data processing experience. By leveraging its capabilities, businesses can focus more on innovation rather than infrastructure management.

AWS Glue is a fully managed data integration solution that simplifies the process of discovering, preparing, and merging data for purposes such as analytics, machine learning, and application development. By offering all the necessary tools for data integration, AWS Glue enables users to begin analyzing their data and leveraging it for insights within minutes rather than taking months. The concept of data integration encompasses various activities like identifying and extracting data from multiple sources, enhancing, cleaning, normalizing, and consolidating that data, as well as organizing and loading it into databases, data warehouses, and data lakes. Different users, each utilizing various tools, often manage these tasks. Operating within a serverless environment, AWS Glue eliminates the need for infrastructure management, automatically provisioning, configuring, and scaling the resources essential for executing data integration jobs. This efficiency allows organizations to focus more on data-driven decision-making without the overhead of manual resource management.

Amazon MQ is a cloud-based managed message broker service that utilizes Apache ActiveMQ, simplifying the process of establishing and running message brokers. These brokers facilitate communication and information exchange between various software systems, which may be built with different programming languages and operate on distinct platforms. By managing the provisioning, setup, and upkeep of ActiveMQ, a widely-used open-source message broker, Amazon MQ significantly eases your operational burden. Integrating your existing applications with Amazon MQ is straightforward, as it supports industry-standard APIs and messaging protocols such as JMS, NMS, AMQP, STOMP, MQTT, and WebSocket. This adherence to standards often eliminates the need to alter existing messaging code when transitioning to AWS. With just a few clicks in the Amazon MQ Console, you can provision your broker while ensuring compatibility with version upgrades, allowing you to utilize the latest version supported by Amazon MQ. After the broker is set up, your applications will be able to seamlessly produce and consume messages, streamlining your workflow and enhancing overall efficiency. Additionally, this service provides scalability, allowing you to adjust resources based on your application's needs, ensuring optimal performance at all times.

AWS X-Ray is a powerful tool that assists developers in analyzing and debugging distributed applications in production, particularly those constructed with a microservices architecture. This service enables you to gain insights into the performance of your applications and the services they rely on, helping to pinpoint the root causes of performance-related issues and errors. X-Ray offers a comprehensive view of requests as they move through your application, along with a visual representation of the various components involved. It is applicable for analyzing applications at different stages, whether in development or production, and it can handle everything from straightforward three-tier systems to intricate microservices architectures with thousands of interconnected services. By leveraging X-Ray, teams can enhance their understanding of application behavior, ultimately leading to more efficient troubleshooting and optimization processes.