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A Recap Of 10 Years Of Automating Postgres | Julian Fischer


Guest: Julian Fischer (LinkedIn)
Company: anynines (Twitter)

In this episode of TFiR: Let’s Talk, Swapnil Bhartiya sits down with Julian Fischer, CEO of anynines, to talk about how the company is helping customers become more cost efficient while ensuring that their workloads and application environments are secure and compliant.

Key highlights of this video interview:

After adopting anynines platform technologies, customers often save up to 50% in total cost of ownership, so cost efficiency is basically built into its pricing model.

anynines allows the software to be operated from within the Amazon account on the customer or from on-premise data centers. From the security perspective, this gives them a huge benefit because they have control over their own software operations.

In the last year or two, anynines has been building its own operators; the Postgres operators are now in place. It has also been focusing on the general question of “How does data service automation change when having Kubernetes as the leading paradigm?”

Centralized data service automation on Kubernetes would then require integration with the application clusters, having remote control facilities, ensuring network-to-network connectivity between clusters, ensuring security, authentication, and authorization.

Is DevOps dead? I wouldn’t emphasize too much on the wording. Declarative automation technologies, together with having programmable data centers, ephemeral virtual machines, ports, and persistent disks lifted DevOps or operations to the next level. It’s solving the same problem (i.e., how to accelerate and scale processes) with different means.

Fischer will be speaking at the upcoming Postgres Conference Silicon Valley 2023. He will recap 10 years of automating Postgres, including changes in the data center, changes in virtualization, and the introduction of new automation technologies and paradigms. Postgres is a good example because Postgres itself also changed and became more cloud-friendly over time.

The challenge ahead for companies is to grow their Kubernetes ecosystem by introducing more components that are still missing, particularly in these areas:

  • data service automation at scale
  • using Kubernetes to do on-demand provisioning of virtual machines
  • providing Kubernetes nodes that are isolated
  • having control over the Kubernetes cluster as well as the policy of provision with a similar language or Kubernetes API-based approach.

This summary was written by Camille Gregory.

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