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Couchbase Autonomous Operator Surpasses 120 Enterprise Customers as Demand for Cloud Services and Containers Continues to Grow

Popularity and growth of Kubernetes fuels adoption of Couchbase Autonomous Operator; version 2.1 promises advanced autonomous features to standardize developer environments that put IT teams in control

Couchbase, the creator of the enterprise-class, multicloud to edge NoSQL database, today announced more than 120 enterprises –representing some of the largest companies in the world–are using Couchbase Autonomous Operator, the most mature NoSQL database operator available on the market. As organizations accelerate their journey to the cloud, the need to automate and scale workloads and reduce costs has driven the adoption of containerization tools such as Kubernetes. Version 2.1, available this winter, extends Couchbase Autonomous Operator’s leading position, enabling greater standardization of developer services and increased control over costs.

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Since its launch in August 2018, companies such as Amdocs, Amadeus, Staples, BD Health, CenterEdge, and several others have been leveraging Couchbase Autonomous Operator (CAO) as a key part of their cloud automation strategy. CAO plays an important role in organizational transformation towards a cloud-native, CI/CD DevOps model. Businesses have reported that CAO smooths organizational transformations, reducing operational complexity by 95% with a single, programmatic architecture for deployment. DevOps need only change a handful of values in a YAML configuration file to invoke a topological reassignment, rebalance or upgrade of an entire distributed Couchbase cluster environment, reducing the cluster maintenance workload from months down to a few keystrokes. This accelerating  adoption is a direct consequence of businesses being able to bring high-value applications to market more quickly.

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The rise of the cloud economy 

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COVID-19 has accelerated adoption of cloud-native services such as containers even further. Placing greater urgency on digital transformation projects that previously would have taken four or five years, the pandemic has made swift cloud adoption a necessity rather than a ‘we’ll-get-there’ priority. Standardizing integration, operations and architecture is crucial for organizations to deploy on any cloud. And it’s crucial that each deployment is trustworthy so IT teams can focus on developing new services for the business vs. managing cloud architecture. These are key driving forces behind the popularity of Kubernetes, and consequently, the strong adoption of Couchbase Autonomous Operator.

Coming this winter: Couchbase Autonomous Operator 2.1

Each new feature in version 2.1 makes it simpler for teams to standardize the developer environment and infrastructure, reducing complexity and placing flexibility and control where it belongs – the IT team. Some of the features planned for Couchbase Autonomous Operator 2.1 include:

  • Auto-scaling for stateless Couchbase services: To ensure that services always have the performance they need, without the risk that unchecked scaling will create unexpected costs, stateless Couchbase services such as Query and Ephemeral Bucket are scaled out or down automatically, based-on YAML-configured thresholds. As a result, organizations can presume peak performance without adding costs.
  • Usage metering reports: to ensure organizations can keep control of costs and usage, Autonomous Operator creates fine-tuned reports into historical cluster usage broken out over user-defined time periods. As a result, organizations know precisely what resources are used when and by whom, preventing unexpected usage and increasing control.
  • Support for Istio service mesh: As environments become larger and more complex, managing a distributed microservices infrastructure becomes increasingly difficult. By integrating Istio service mesh, Autonomous Operator 2.1 gives organizations the capabilities they need to manage any size of microservices architecture, including load balancing, service-to-service authentication and monitoring.

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