Confluent unveils HashiCorp Terraform Supplier to simplify multi-cloud knowledge streaming

Knowledge streaming platform Confluent has launched the Confluent Terraform Supplier, developed in partnership with HashiCorp, a supplier of multi-cloud infrastructure automation software program.

The Terraform supplier exposes Confluent Cloud APIs for easy, constant, and automatic administration of mission-critical knowledge streaming assets, together with cloud environments, Apache Kafka clusters, networks, matters, connectors, and extra. Now, Confluent says engineering groups can simply combine knowledge streaming inside CI/CD workflows and GitOps processes on AWS, Microsoft Azure, and Google Cloud, enabling them to launch real-time functions sooner and keep away from the excessive operational prices and dangers tied to guide useful resource provisioning.

Ganesh Srinivasan, chief product officer Confluent, mentioned: “The necessity to keep forward of buyer calls for is fueling the shift to expertise stacks powered by knowledge streams and cloud applied sciences.

“With our HashiCorp Terraform integration, organisations get the ability of knowledge streaming throughout all main cloud suppliers with the simplicity of infrastructure as code and automation. This implies builders have secure, dependable entry to the infrastructure assets they want, to allow them to deal with constructing functions that really transfer the needle for his or her companies.”

Knowledge streaming is more and more important to ship the real-time experiences right this moment’s prospects demand and data-driven operations companies want. However builders constructing and launching knowledge streaming functions with open-source Apache Kafka are sometimes blocked, ready for entry to infrastructure assets. These requests are often dealt with by a small workforce of specialists who assist the complete enterprise and a extremely complicated tech stack. These groups can simply get slowed down in time-consuming, guide processes for managing infrastructure, which rapidly places new developments not on time. Guide provisioning additionally introduces excessive ranges of threat, which is unacceptable when knowledge streaming is powering a enterprise’s most delicate, mission-critical use circumstances. Integration with a confirmed device like Terraform can save time, velocity up new releases and add much more safety.

Rolando Berrios, director of engineering, Okedo, mentioned: “Serving to our prospects save money and time with good, real-time stock administration options relies upon widespread use of real-time knowledge streaming all through our total enterprise.

“With Confluent’s Terraform Supplier, we’re capable of utterly automate our infrastructure deployments as code with no sacrifice on high quality or safety. With constant, version-controlled deployments managed via a device our groups already know, we’re capable of transfer rapidly and preserve deal with new, value-add initiatives.”

The Confluent Terraform Supplier provides engineering groups quick access to the total set of knowledge streaming assets they want, starting from Kafka clusters and personal networks to service accounts and ACLs. With provisioning and administration of knowledge streaming infrastructure automated all through all clouds, the advantages of real-time knowledge can scale throughout the complete enterprise to gas sooner innovation from a wider set of groups. With the brand new Terraform supplier, groups can:

• Cut back complexity and threat with infrastructure deployments managed as code and deployed via automated GitOps integration.
• Enhance developer autonomy and productiveness with constant, version-controlled entry to knowledge streaming environments, Kafka clusters, Kafka matters, and extra.
• Combine Confluent deployments inside present cloud workflows on AWS, Azure, and Google Cloud utilizing standardised useful resource administration tooling, pipelines, and processes.

“The brand new, verified Terraform supplier for Confluent makes provisioning essential knowledge streaming assets easy and dependable,” mentioned Burzin Patel, VP, World Accomplice Alliances, HashiCorp. “It automates deployments inside present CI/CD workflows throughout all main cloud companies so organisations can simply entry the real-time knowledge they want for innovation with far much less time targeted on infrastructure administration.”

Extra New Improvements within the Q3 ‘22 Launch

Confluent’s quarterly launches present a single useful resource to find out about new capabilities obtainable on the main knowledge streaming platform. Different highlights embrace:

Impartial Community Lifecycle Administration: One of many largest challenges confronted when scaling knowledge streaming workloads is the power to provision networking assets effectively with out including operational burdens. Confluent’s new REST APIs and Terraform assist for community lifecycle administration promote networks to be a first-class useful resource, enabling organisations to scale knowledge streaming workloads unbiased of community connectivity. This lets engineering groups reuse present community connections for a number of clusters and acquire granular entry management of community assets via the brand new RBAC function for community admins, which considerably reduces guide toil.

Consumer Login Monitoring: As an information streaming deployment grows, it turns into more and more necessary to maintain an in depth eye on who’s accessing a platform and what these guests are trying to do with knowledge. Confluent added consumer login monitoring to its intensive library of auditable occasions, making potential knowledge breaches simpler to identify. Now, safety teams can see a full listing of all customers who efficiently log right into a Confluent Cloud account. This manner, organisations can rapidly discover the dangerous actors who would in any other case be hidden throughout the noise of anticipated exercise. This helps guarantee no breaches happen that may expose delicate knowledge, trigger downtime, or tarnish model status.

Tags: ,

Leave a Comment