Lightbend Alternatives

Google Cloud is a cloud-based service that allows you to create anything from simple websites to complex applications for businesses of all sizes. New customers get $300 in free credits to run, test, and deploy workloads. All customers can use 25+ products for free, up to monthly usage limits. Use Google's core infrastructure, data analytics & machine learning. Secure and fully featured for all enterprises. Tap into big data to find answers faster and build better products. Grow from prototype to production to planet-scale, without having to think about capacity, reliability or performance. From virtual machines with proven price/performance advantages to a fully managed app development platform. Scalable, resilient, high performance object storage and databases for your applications. State-of-the-art software-defined networking products on Google’s private fiber network. Fully managed data warehousing, batch and stream processing, data exploration, Hadoop/Spark, and messaging.

The best insights are based on the most complete, most accurate, and most timely data. Minitab Connect empowers data users from across the enterprise with self-serve tools to transform diverse data into a governed network of data pipelines, feed analytics initiatives and foster organization-wide collaboration. Users can effortlessly blend and explore data from databases, cloud and on-premise apps, unstructured data, spreadsheets, and more. Flexible, automated workflows accelerate every step of the data integration process, while powerful data preparation and visualization tools help yield transformative insights. Flexible, intuitive data integration tools let users connect and blend data from a variety of internal and external sources, like data warehouses, data lakes, IoT devices, SaaS applications, cloud storage, spreadsheets, and email.

Rivery’s SaaS ETL platform provides a fully-managed solution for data ingestion, transformation, orchestration, reverse ETL and more, with built-in support for your development and deployment lifecycles. Key Features: Data Workflow Templates: Extensive library of pre-built templates that enable teams to instantly create powerful data pipelines with the click of a button. Fully managed: No-code, auto-scalable, and hassle-free platform. Rivery takes care of the back end, allowing teams to spend time on priorities rather than maintenance. Multiple Environments: Construct and clone custom environments for specific teams or projects. Reverse ETL: Automatically send data from cloud warehouses to business applications, marketing clouds, CPD’s, and more.

The Kubernetes platform for big ideas. Empower developers to innovate and ship faster with the leading hybrid cloud, enterprise container platform. Red Hat OpenShift offers automated installation, upgrades, and lifecycle management throughout the container stack—the operating system, Kubernetes and cluster services, and applications—on any cloud. Red Hat OpenShift helps teams build with speed, agility, confidence, and choice. Code in production mode anywhere you choose to build. Get back to doing work that matters. Red Hat OpenShift is focused on security at every level of the container stack and throughout the application lifecycle. It includes long-term, enterprise support from one of the leading Kubernetes contributors and open source software companies. Support the most demanding workloads including AI/ML, Java, data analytics, databases, and more. Automate deployment and life-cycle management with our vast ecosystem of technology partners.

Run advanced apps on a secured and managed Kubernetes service. GKE is an enterprise-grade platform for containerized applications, including stateful and stateless, AI and ML, Linux and Windows, complex and simple web apps, API, and backend services. Leverage industry-first features like four-way auto-scaling and no-stress management. Optimize GPU and TPU provisioning, use integrated developer tools, and get multi-cluster support from SREs. Start quickly with single-click clusters. Leverage a high-availability control plane including multi-zonal and regional clusters. Eliminate operational overhead with auto-repair, auto-upgrade, and release channels. Secure by default, including vulnerability scanning of container images and data encryption. Integrated Cloud Monitoring with infrastructure, application, and Kubernetes-specific views. Speed up app development without sacrificing security.

Ingest, prepare, and process data pipelines at scale for AI and analytics in the cloud. Informatica’s comprehensive data engineering portfolio provides everything you need to process and prepare big data engineering workloads to fuel AI and analytics: robust data integration, data quality, streaming, masking, and data preparation capabilities. Rapidly build intelligent data pipelines with CLAIRE®-powered automation, including automatic change data capture (CDC) Ingest thousands of databases and millions of files, and streaming events. Accelerate time-to-value ROI with self-service access to trusted, high-quality data. Get unbiased, real-world insights on Informatica data engineering solutions from peers you trust. Reference architectures for sustainable data engineering solutions. AI-powered data engineering in the cloud delivers the trusted, high quality data your analysts and data scientists need to transform business.

Microservice-based streaming and batch data processing for Cloud Foundry and Kubernetes. Spring Cloud Data Flow provides tools to create complex topologies for streaming and batch data pipelines. The data pipelines consist of Spring Boot apps, built using the Spring Cloud Stream or Spring Cloud Task microservice frameworks. Spring Cloud Data Flow supports a range of data processing use cases, from ETL to import/export, event streaming, and predictive analytics. The Spring Cloud Data Flow server uses Spring Cloud Deployer, to deploy data pipelines made of Spring Cloud Stream or Spring Cloud Task applications onto modern platforms such as Cloud Foundry and Kubernetes. A selection of pre-built stream and task/batch starter apps for various data integration and processing scenarios facilitate learning and experimentation. Custom stream and task applications, targeting different middleware or data services, can be built using the familiar Spring Boot style programming model.

Spectra is a comprehensive DataOps (data ingestion, transformation, and preparation) platform to build and manage complex, varied data pipelines using a low-code user interface with domain-specific features to deliver data solutions at speed and at scale. Maximize your ROI with faster time-to-market and time-to-value, and reduced cost of ownership. Get access to over 50 pre-built native connectors with readily available data processing functions such as sort, look-up, join, transform, grouping and many more. Process structured, semi-structured, and unstructured data in batch or real-time streaming data. Optimize and control infrastructure spending for your organization by efficiently managing data processing and data pipeline. Spectra’s pushdown transformation capabilities with Snowflake Data Cloud enables enterprises to leverage Snowflake’s high-performing processing power and scalable architecture.

Make use of Reactive Programming on the back-end without the need for specialized languages or cumbersome frameworks. Triggers, Actors and Event Collections make it easy to build data pipelines and work with data streams using simple SQL-like syntax, shielding users from the complexities of distributed system development. Extensible Data Modeling is a key feature that supports rich semantics and schema definition for representing real-world things. On-the-fly validation and data shaping rules support a variey of formats like XML and JSON, allowing you to easily describe and evolve your schema, keeping pace with changing business requirements. If you can describe it, we can query it. Know SQL and Javascript? Then you already know how to use the data engine. Whatever the format, a powerful query language lets you instantly test logic expressions and functions, speeding up development and simplifying deployment for unmatched data agility.

Nextflow Tower is an intuitive centralized command post that enables large-scale collaborative data analysis. With Tower, users can easily launch, manage, and monitor scalable Nextflow data analysis pipelines and compute environments on-premises or on most clouds. Researchers can focus on the science that matters rather than worrying about infrastructure engineering. Compliance is simplified with predictable, auditable pipeline execution and the ability to reliably reproduce results obtained with specific data sets and pipeline versions on demand. Nextflow Tower is developed and supported by Seqera Labs, the creators and maintainers of the open-source Nextflow project. This means that users get high-quality support directly from the source. Unlike third-party frameworks that incorporate Nextflow, Tower is deeply integrated and can help users benefit from Nextflow's complete set of capabilities.

Run, manage, control and secure the apps, data and IT that run your business, from edge to cloud. HPE Ezmeral advances digital transformation initiatives by shifting time and resources from IT operations to innovations. Modernize your apps. Simplify your Ops. And harness data to go from insights to impact. Accelerate time-to-value by deploying Kubernetes at scale with integrated persistent data storage for app modernization on bare metal or VMs, in your data center, on any cloud or at the edge. Harness data and get insights faster by operationalizing the end-to-end process to build data pipelines. Bring DevOps agility to the machine learning lifecycle, and deliver a unified data fabric. Boost efficiency and agility in IT Ops with automation and advanced artificial intelligence. And provide security and control to eliminate risk and reduce costs. HPE Ezmeral Container Platform provides an enterprise-grade platform to deploy Kubernetes at scale for a wide range of use cases.

StreamSets DataOps Platform. The data integration platform to build, run, monitor and manage smart data pipelines that deliver continuous data for DataOps, and power modern analytics and hybrid integration. Only StreamSets provides a single design experience for all design patterns for 10x greater developer productivity; smart data pipelines that are resilient to change for 80% less breakages; and a single pane of glass for managing and monitoring all pipelines across hybrid and cloud architectures to eliminate blind spots and control gaps. With StreamSets, you can deliver the continuous data that drives the connected enterprise.

Upsolver makes it incredibly simple to build a governed data lake and to manage, integrate and prepare streaming data for analysis. Define pipelines using only SQL on auto-generated schema-on-read. Easy visual IDE to accelerate building pipelines. Add Upserts and Deletes to data lake tables. Blend streaming and large-scale batch data. Automated schema evolution and reprocessing from previous state. Automatic orchestration of pipelines (no DAGs). Fully-managed execution at scale. Strong consistency guarantee over object storage. Near-zero maintenance overhead for analytics-ready data. Built-in hygiene for data lake tables including columnar formats, partitioning, compaction and vacuuming. 100,000 events per second (billions daily) at low cost. Continuous lock-free compaction to avoid “small files” problem. Parquet-based tables for fast queries.

Data-driven computational pipelines. Nextflow enables scalable and reproducible scientific workflows using software containers. It allows the adaptation of pipelines written in the most common scripting languages. Its fluent DSL simplifies the implementation and deployment of complex parallel and reactive workflows on clouds and clusters. Nextflow is built around the idea that Linux is the lingua franca of data science. Nextflow allows you to write a computational pipeline by making it simpler to put together many different tasks. You may reuse your existing scripts and tools and you don't need to learn a new language or API to start using it. Nextflow supports Docker and Singularity containers technology. This, along with the integration of the GitHub code-sharing platform, allows you to write self-contained pipelines, manage versions, and rapidly reproduce any former configuration. Nextflow provides an abstraction layer between your pipeline's logic and the execution layer.

Connecting systems to scale AI initiatives is complex, expensive, and prone to fail. Pandio’s cloud-native managed solution simplifies your data pipelines to harness the power of AI. Access your data from anywhere at any time in order to query, analyze, and drive to insight. Big data analytics without the big cost. Enable data movement seamlessly. Streaming, queuing and pub-sub with unmatched throughput, latency, and durability. Design, train, and deploy machine learning models locally in less than 30 minutes. Accelerate your path to ML and democratize the process across your organization. And it doesn’t require months (or years) of disappointment. Pandio’s AI-driven architecture automatically orchestrates your models, data, and ML tools. Pandio works with your existing stack to accelerate your ML initiatives. Orchestrate your models and messages across your organization.

The only all-in-one data pipeline platform. Built ground-up for a cloud-first world, Gathr is the only platform to handle all your data integration and engineering needs - ingestion, ETL, ELT, CDC, streaming analytics, data preparation, machine learning, advanced analytics and more. With Gathr, anyone can build and deploy pipelines in minutes, irrespective of skill levels. Create Ingestion pipelines in minutes, not weeks. Ingest data from any source, deliver to any destination. Build applications quickly with a wizard-based approach. Replicate data in real-time using a templatized CDC app. Native integration for all sources and targets. Best-in-class capabilities with everything you need to succeed today and tomorrow. Choose between free, pay-per-use or customize as per your requirements.

Hevo Data is a no-code, bi-directional data pipeline platform specially built for modern ETL, ELT, and Reverse ETL Needs. It helps data teams streamline and automate org-wide data flows that result in a saving of ~10 hours of engineering time/week and 10x faster reporting, analytics, and decision making. The platform supports 100+ ready-to-use integrations across Databases, SaaS Applications, Cloud Storage, SDKs, and Streaming Services. Over 500 data-driven companies spread across 35+ countries trust Hevo for their data integration needs. Try Hevo today and get your fully managed data pipelines up and running in just a few minutes.

In-Memory Computing Platform. The digital world is different. Microseconds matter. That's why the world's largest organizations rely on us to power their most time-sensitive applications at scale. New data-enabled applications can deliver transformative business power – if they meet today’s requirement of immediacy. Hazelcast solutions complement virtually any database to deliver results that are significantly faster than a traditional system of record. Hazelcast’s distributed architecture provides redundancy for continuous cluster up-time and always available data to serve the most demanding applications. Capacity grows elastically with demand, without compromising performance or availability. The fastest in-memory data grid, combined with third-generation high-speed event processing, delivered through the cloud.

Enterprise observability for all your teams at scale. Most traditional tools detect simple threshold-based anomalies, making it difficult to distinguish false alarms from real issues. With VMware Tanzu Observability by Wavefront, you create smart alerts that dynamically filter noise and capture true anomalies. Troubleshooting distributed cloud applications is not trivial due to many moving parts, application dependencies, and frequent code updates. Wavefront collects all metrics in one place from your applications, clouds, and infrastructure. Finding a needle in the haystack is not easy when dealing with distributed cloud applications and containerized microservices emitting thousands of metrics. AI Genie™ helps you automatically identify “unknown unknowns” so you can quickly get to root incident root cause – isolate applications, infrastructure, cloud, and edge.

TKE is fully compatible with the entire range of Kubernetes capabilities and has been adapted to Tencent Cloud's fundamental IaaS capabilities such as CVM and CBS. In addition, Tencent Cloud’s Kubernetes-based cloud products such as CBS and CLB support one-click deployment to container clusters for a variety of open source applications, greatly improving deployment efficiency. Thanks to TKE, you can simplify the management of large-scale clusters and management and OPS of distributed applications without having to use cluster management software or design fault-tolerant cluster architecture. Simply launch TKE and specify the tasks you want to run, and then TKE will take care of all of the cluster management tasks, allowing you to focus on developing Dockerized applications.

Power your modern applications with VMware Tanzu Kubernetes Grid. Run the same K8s across data center, public cloud and edge for a consistent, secure experience for all development teams. Keep your workloads properly isolated and secure. Get a complete, easy-to-upgrade Kubernetes runtime with preintegrated and validated components. Deploy and scale all clusters without downtime. Apply security fixes fast. Run your containerized applications on a certified Kubernetes distribution, bolstered by the global Kubernetes community. Use your existing data center tools and workflows to give developers secure, self-serve access to conformant Kubernetes clusters in your VMware private cloud, and extend the same consistent Kubernetes runtime across your public cloud and edge environments. Simplify operations of large-scale, multicluster Kubernetes environments, and keep your workloads properly isolated. Automate lifecycle management to reduce your risk and shift your focus to more strategic work.

Apprenda Cloud Platform empowers enterprise IT to create a Kubernetes-enabled shared service on the infrastructures of their choice and offer it to developers across business units. ACP supports your entire custom application portfolio. Rapidly build, deploy, run, and manage cloud-native, microservices, and container-based .NET and Java applications or modernize traditional workloads. ACP gives your developers self-service access to the tools they need to rapidly build applications, while IT operators can very easily orchestrate the environments and workflows. Enterprise IT becomes a true service provider. ACP is a single platform spanning your multiple data- centers and clouds. Run ACP on-premise or consume it as a managed service on the public cloud; both with the assurance of complete infrastructure independence. ACP enables policy-driven control over all of your application workloads' infrastructure utilization and DevOps processes.

SUSE Rancher addresses the needs of DevOps teams deploying applications with Kubernetes and IT operations delivering enterprise-critical services. SUSE Rancher supports any CNCF-certified Kubernetes distribution. For on-premises workloads, we offer the RKE. We support all the public cloud distributions, including EKS, AKS, and GKE. At the edge, we offer K3s. SUSE Rancher provides simple, consistent cluster operations, including provisioning, version management, visibility and diagnostics, monitoring and alerting, and centralized audit. SUSE Rancher lets you automate processes and applies a consistent set of user access and security policies for all your clusters, no matter where they’re running. SUSE Rancher provides a rich catalogue of services for building, deploying, and scaling containerized applications, including app packaging, CI/CD, logging, monitoring, and service mesh.

IBM Storage for Red Hat OpenShift unifies traditional and container storage, enabling easier deployment of enterprise-class scale-out microservices architectures. Validated with Red Hat OpenShift, Kubernetes and IBM Cloud Pak. Delivering simplified deployment and management for an integrated experience. Enterprise data protection, automated scheduling, and data reuse support for Red Hat OpenShift and Kubernetes environments. Block, file and object data resources. Quickly deploy what you need when you need it. IBM Storage for Red Hat OpenShift provides the infrastructure foundation and storage orchestration necessary for building a robust, agile, on-premises hybrid cloud environment. IBM supports CSI for its block and file storage families to improve container utilization in Kubernetes environments.

Contrail Insights enables operators to control and visualize how infrastructure resources are utilized by workloads, and plan adequate capacity to ensure application performance. Using Contrail Insights, operators of software-defined data centers have a toolset for visibility into operational performance and infrastructure resources. In today’s large-scale multicloud networks, operations teams must have real-time and historical visibility into their infrastructure to ensure service reliability and minimize operational costs. Cloud infrastructure is typically built in layers of abstraction and, as operations become more automated, performance monitoring replaces manual changes as the most common task. As telemetry data increases, however, and abstraction layers are peeled back to examine and troubleshoot the state of the network infrastructure, monitoring complexity increases as well.

Customers worldwide choose Zettaset products for use in high performance, high availability and seamlessly scalable data environments. Zettaset products are designed to function with extremely low latency to support the most demanding deployment requirements, including high-speed transactions, in-memory databases, and real-time, web-based applications. The XCrypt™ Data Encryption Platform has been designed from the ground up for optimal performance and scalability in distributed systems and elastic cloud environments. XCrypt introduces extremely low latency to the compute environment, making it ideal for in-memory stored data and transactional environments where sub-second response times are essential.

StreamNative redefines streaming infrastructure by seamlessly integrating Kafka, MQ, and other protocols into a single, unified platform, providing unparalleled flexibility and efficiency for modern data processing needs. StreamNative offers a unified solution that adapts to the diverse requirements of streaming and messaging in a microservices-driven environment. By providing a comprehensive and intelligent approach to messaging and streaming, StreamNative empowers organizations to navigate the complexities and scalability of the modern data ecosystem with efficiency and agility. Apache Pulsar’s unique architecture decouples the message serving layer from the message storage layer to deliver a mature cloud-native data-streaming platform. Scalable and elastic to adapt to rapidly changing event traffic and business needs. Scale-up to millions of topics with architecture that decouples computing and storage.

Build your data pipelines like Lego blocks with Data Taps. Add new metrics layers, zoom in, and investigate with real-time streaming SQL. Build with others, share and consume data, globally. Refine and update without hassle. Use multiple models/schemas during schema evolution. Built to scale with AWS Lambda and S3.

Event Hubs is a fully managed, real-time data ingestion service that’s simple, trusted, and scalable. Stream millions of events per second from any source to build dynamic data pipelines and immediately respond to business challenges. Keep processing data during emergencies using the geo-disaster recovery and geo-replication features. Integrate seamlessly with other Azure services to unlock valuable insights. Allow existing Apache Kafka clients and applications to talk to Event Hubs without any code changes—you get a managed Kafka experience without having to manage your own clusters. Experience real-time data ingestion and microbatching on the same stream. Focus on drawing insights from your data instead of managing infrastructure. Build real-time big data pipelines and respond to business challenges right away.

BigBI enables data specialists to build their own powerful big data pipelines interactively & efficiently, without any coding! BigBI unleashes the power of Apache Spark enabling: Scalable processing of real Big Data (up to 100X faster) Integration of traditional data (SQL, batch files) with modern data sources including semi-structured (JSON, NoSQL DBs, Elastic, Hadoop), and unstructured (Text, Audio, video), Integration of streaming data, cloud data, AI/ML & graphs

Deploy production-ready change data capture pipelines for high-volume, real-time data replication - without a single line of code. Supercharged Change Data Capture. Enjoy automatic schema conversion, end-to-end replication, flexible deployment, and more with Arcion’s distributed Change Data Capture (CDC). Leverage Arcion’s zero data loss architecture for guaranteed end-to-end data consistency, built-in checkpointing, and more without any custom code. Leave scalability and performance concerns behind with a highly-distributed, highly parallel architecture supporting 10x faster data replication. Reduce DevOps overhead with Arcion Cloud, the only fully-managed CDC offering. Enjoy autoscaling, built-in high availability, monitoring console, and more. Simplify & standardize data pipelines architecture, and zero downtime workload migration from on-prem to cloud.

The fastest way to prep data and build data pipelines in the cloud. Trifacta provides visual and intelligent guidance to accelerate data preparation so you can get to insights faster. Poor data quality can sink any analytics project. Trifacta helps you understand your data so you can quickly and accurately clean it up. All the power with none of the code. Trifacta provides visual and intelligent guidance so you can get to insights faster. Manual, repetitive data preparation processes don’t scale. Trifacta helps you build, deploy and manage self-service data pipelines in minutes not months.

You select the size of the cluster, node capacity, and a set of services, and Yandex Data Proc automatically creates and configures Spark and Hadoop clusters and other components. Collaborate by using Zeppelin notebooks and other web apps via a UI proxy. You get full control of your cluster with root permissions for each VM. Install your own applications and libraries on running clusters without having to restart them. Yandex Data Proc uses instance groups to automatically increase or decrease computing resources of compute subclusters based on CPU usage indicators. Data Proc allows you to create managed Hive clusters, which can reduce the probability of failures and losses caused by metadata unavailability. Save time on building ETL pipelines and pipelines for training and developing models, as well as describing other iterative tasks. The Data Proc operator is already built into Apache Airflow.

Automate self-service provisioning and refresh of enterprise workloads, integrate with existing toolchain. High-performance data delivery and re-use for data scientists through a rich set of APIs and automation. Recover any data across any cloud from any point in time – at the same time – at scale, beyond legacy solutions. Minimize the business impact of ransomware / cyber attacks by recovering quickly with immutable backups. Unified platform to better protect, secure, retain, govern, or recover your data on-premises or in the cloud. Actifio’s patented software platform turns data silos into data pipelines. Virtual Data Pipeline (VDP) delivers full-stack data management — on-premises, hybrid or multi-cloud – from rich application integration, SLA-based orchestration, flexible data movement, and data immutability and security.

Find out why the heavy hitters are using the Crux external data automation platform to scale external data integration, transformation, and observability without increasing headcount. Our cloud-native data integration technology accelerates the ingestion, preparation, observability and ongoing delivery of any external dataset. The result is that we can ensure you get quality data in the right place, in the right format when you need it. Leverage automatic schema detection, delivery schedule inference, and lifecycle management to build pipelines from any external data source quickly. Enhance discoverability throughout your organization through a private catalog of linked and matched data products. Enrich, validate, and transform any dataset to quickly combine it with other data sources and accelerate analytics.

At K2View, we believe that every enterprise should be able to leverage its data to become as disruptive and agile as the best companies in its industry. We make this possible through our patented Data Product Platform, which creates and manages a complete and compliant dataset for every business entity – on demand, and in real time. The dataset is always in sync with its underlying sources, adapts to changes in the source structures, and is instantly accessible to any authorized data consumer. Data Product Platform fuels many operational use cases, including customer 360, data masking and tokenization, test data management, data migration, legacy application modernization, data pipelining and more – to deliver business outcomes in less than half the time, and at half the cost, of any other alternative. The platform inherently supports modern data architectures – data mesh, data fabric, and data hub – and deploys in cloud, on-premise, or hybrid environments.

Building real-time apps and services require lots of components running in concert: Kafka, VPC hosting, infrastructure as code, container orchestration, observability, CI/CD, persistent volumes, databases, and much more. The Quix platform takes care of all the moving parts. You just connect your data and start building. That’s it. No provisioning clusters or configuring resources. Use Quix connectors to ingest transaction messages streamed from your financial processing systems in a virtual private cloud or on-premise data center. All data in transit is encrypted end-to-end and compressed with G-Zip and Protobuf for security and efficiency. Detect fraudulent patterns with machine learning models or rule-based algorithms. Create fraud warning messages as troubleshooting tickets or display them in support dashboards.

Single Tenant Public Cloud with all the security, savings and control of private cloud. Fully Managed by Joyent. Single Tenant Security, Full Operations control over your Private Cloud with Installation, Onboarding and Support provided by Joyent. Open Source or Commercial support for on-premises, user managed private cloud. Built to deliver VMs, containers and bare metal. Built to support exabyte-scale workloads. Joyent engineers provide 360 degree support for modern application architectures, including microservices, apis, development frameworks and container-native devops tooling. Hybrid, Modern and Open, Triton is engineered to run the world’s largest cloud native applications.

Tencent Container Registry (TCR) offers secure, dedicated, and high-performance container image hosting and distribution service. You can create dedicated instances in multiple regions across the globe and pull container images from the nearest region to reduce pulling time and bandwidth costs. To guarantee data security, TCR features granular permission management and access control. It also supports P2P accelerated distribution to break through the performance bottleneck due to concurrent pulling of large images by large-scale clusters, helping you quickly expand and update businesses. You can customize image synchronization rules and triggers, and use TCR flexibly with your existing CI/CD workflow to quickly implement container DevOps. TCR instance adopts containerized deployment. You can dynamically adjust the service capability based on actual usage to manage sudden surges in business traffic.

A simple and flexible workload orchestrator to deploy and manage containers and non-containerized applications across on-prem and clouds at scale. Single 35MB binary that integrates into existing infrastructure. Easy to operate on-prem or in the cloud with minimal overhead. Orchestrate applications of any type - not just containers. First class support for Docker, Windows, Java, VMs, and more. Bring orchestration benefits to existing services. Achieve zero downtime deployments, improved resilience, higher resource utilization, and more without containerization. Single command for multi-region, multi-cloud federation. Deploy applications globally to any region using Nomad as a single unified control plane. One single unified workflow for deploying to bare metal or cloud environments. Enable multi-cloud applications with ease. Nomad integrates seamlessly with Terraform, Consul and Vault for provisioning, service networking, and secrets management.

Cloud Foundry makes it faster and easier to build, test, deploy and scale applications, providing a choice of clouds, developer frameworks, and application services. It is an open source project and is available through a variety of private cloud distributions and public cloud instances. Cloud Foundry has a container-based architecture that runs apps in any programming language. Deploy apps to CF using your existing tools and with zero modification to the code. Instantiate, deploy, and manage high-availability Kubernetes clusters with CF BOSH on any cloud. By decoupling applications from infrastructure, you can make individual decisions about where to host workloads – on premise, in public clouds, or in managed infrastructures – and move those workloads as necessary in minutes, with no changes to the app.

D2iQ Enterprise Kubernetes Platform (DKP) Run Kubernetes Workloads at Scale DKP includes everything you need to ease Kubernetes adoption, expand Kubernetes use, and enable advanced workloads across any infrastructure, whether on-prem, on the cloud, in air-gapped environments, or at the edge. Built to Solve the Toughest Enterprise Kubernetes Challenges Created to accelerate the journey to production at scale, DKP provides a single, centralized point of control to build, run, and manage applications across any infrastructure. Enable Day 2 Readiness Out-of-the-Box Without Lock-In DKP takes care of the heavy lifting by providing a comprehensive, enterprise-grade Kubernetes distribution and a full stack of CNCF-certified Day 2 platform applications that are integrated, automated, and tested at scale for an out-of-the-box, production-ready experience.

kpt is a package-centric toolchain that enables a WYSIWYG configuration authoring, automation, and delivery experience, which simplifies managing Kubernetes platforms and KRM-driven infrastructure at scale by manipulating declarative configuration as data, separated from the code that transforms it. Most Kubernetes users either manage their resources using conventional imperative graphical user interfaces, command-line tools (kubectl), and automation (e.g., operators) that operate directly against Kubernetes APIs, or declarative configuration tools, such as Helm, Terraform, cdk8s, or one of the dozens of other tools. At a small scale, this is largely driven by preference and familiarity. As companies expand the number of Kubernetes development and production clusters they use, creating and enforcing consistent configurations and security policies across a growing environment becomes difficult.

The fully managed Azure Kubernetes Service (AKS) makes deploying and managing containerized applications easy. It offers serverless Kubernetes, an integrated continuous integration and continuous delivery (CI/CD) experience, and enterprise-grade security and governance. Unite your development and operations teams on a single platform to rapidly build, deliver, and scale applications with confidence. Elastic provisioning of additional capacity without the need to manage the infrastructure. Add event-driven autoscaling and triggers through KEDA. Faster end-to-end development experience with Azure Dev Spaces including integration with Visual Studio Code Kubernetes tools, Azure DevOps, and Azure Monitor. Advanced identity and access management using Azure Active Directory, and dynamic rules enforcement across multiple clusters with Azure Policy. Available in more regions than any other cloud providers.

amazee.io offers high-performance, flexible hosting solutions built for speed, security, and scalability. Whether you're running 500 decoupled Drupal sites, a single Laravel application, or a complex technology stack, Lagoon has the flexibility to accommodate any project thanks to containers. Our team of systems engineers is available to support your special requests and custom configurations. amazee.io takes security seriously, passing rigorous audits and offering a GDPR-compliant platform. Lagoon runs the latest technologies and is built to deliver the most performant development, deployment, and end-user experiences possible. We set up Lagoon to handle unplanned spikes in traffic and usage. Your server's resources will scale automatically when needed. Effortlessly create test environments for pull requests and branches. Full congruency across environments. Autoscales to handle fluctuating traffic.

Kubernetes-as-a-Service for multi-cloud, on-premises, and edge. The ease of public cloud with the control of DIY. Supported by 100% Certified Kubernetes Admins. Overcome talent scarcity. Achieve 99.9% uptime, auto upgrading, and scaling supported by world-class 100% Certified Kubernetes Admins. Future proof your cloud-native journey with out-of-the-box edge, multi-cloud and data center integrations and auto-provisioning. Deploy k8s clusters in minutes with a rich set of pre-built cloud-native services and infrastructure plug-ins. Get help you with design, onboarding and integrations from Cloud Architects. PMK is a SaaS managed service that works with your infrastructure to create Kubernetes clusters instantly. Clusters come built in with monitoring and log aggregation, and integrate with all your existing tools, so you can focus just on building apps.

To sell cloud, you lease your virtualized infrastructure, ease and track cloud usage within a customer organization and find new routes to reach the largest cloud market. A cloud business won’t scale without a completely automated billing process. A prerequisite for success is the ability to bill and take payments based on accurately measured consumption data. Flexiant Cloud Orchestrator includes a fully integrated billing system for your fastest go-to-market opportunity. Integrating Flexiant Cloud Orchestrator into your existing workflows is extremely easy thanks to its powerful API and extensible interface. Your customers want to have a choice. To lower the risk of migration, or simply to preserve their application certification, they want to be able to decide which hypervisor should power their workload. A dynamic workload placement algorithm to make the most sensible decision on where to start a virtual machine.

The concept behind Dataplane is to make it quicker and easier to construct a data mesh with robust data pipelines and automated workflows for businesses and teams of all sizes. In addition to being more user friendly, there has been an emphasis on scaling, resilience, performance and security.

AWS Data Pipeline is a web service that helps you reliably process and move data between different AWS compute and storage services, as well as on-premises data sources, at specified intervals. With AWS Data Pipeline, you can regularly access your data where it’s stored, transform and process it at scale, and efficiently transfer the results to AWS services such as Amazon S3, Amazon RDS, Amazon DynamoDB, and Amazon EMR. AWS Data Pipeline helps you easily create complex data processing workloads that are fault tolerant, repeatable, and highly available. You don’t have to worry about ensuring resource availability, managing inter-task dependencies, retrying transient failures or timeouts in individual tasks, or creating a failure notification system. AWS Data Pipeline also allows you to move and process data that was previously locked up in on-premises data silos.

Qlik Compose for Data Warehouses (formerly Attunity Compose for Data Warehouses) provides a modern approach by automating and optimizing data warehouse creation and operation. Qlik Compose automates designing the warehouse, generating ETL code, and quickly applying updates, all whilst leveraging best practices and proven design patterns. Qlik Compose for Data Warehouses dramatically reduces the time, cost and risk of BI projects, whether on-premises or in the cloud. Qlik Compose for Data Lakes (formerly Attunity Compose for Data Lakes) automates your data pipelines to create analytics-ready data sets. By automating data ingestion, schema creation, and continual updates, organizations realize faster time-to-value from their existing data lake investments.