Product Update: Breaking Three Boundaries for Cloud Data Security

Breaking new boundaries

As Laminar’s VP of Product, I enjoy every time our team achieves new heights. I love innovations that truly add value for our customers. It’s exciting to break new boundaries and redefine what’s possible. Protecting your most sensitive data in a public cloud environment is hard. Engineers and data scientists build fast, collect and process data at huge volumes, are doing the right thing for the business, but don’t always have security and privacy top of mind.

Laminar has been defining a new reality for data security in the cloud across the industry. We have also been providing our clients with innovative, first in class services. As of today, we are widening our lead in the industry with several valuable new capabilities:

  • First to secure cloud data in a multi-cloud environment by adding support for Microsoft Azure.

    Multi-cloud adoption has soared due to the advantages of rapid development and minimal vendor lock-in. Gartner estimates that “more than 75% of organizations use multiple public cloud services today, and have plans to expand.” With this announcement Laminar is first in the public cloud data security market to support multi-cloud, by adding Microsoft Azure support to the existing support for Amazon AWS. This has several advantages for fast-moving enterprises:
    1. Consistent controls: With a single pane of glass across a multi-cloud environment, enterprises can apply a consistent set of data governance policies, no matter where and how that data is collected and stored. This capability empowers teams to move faster, make fewer mistakes, and ramp quicker by mastering less tools.
    2. Levelset Security: Rather than have different levels of security due to different levels of knowledge about the built-in offerings of the public clouds, Laminar provides a consistently high level of data security across all clouds.
    3. Cloud Data Catalog: Laminar creates a cloud data catalog across clouds, across tech stacks, and physical locations that contributes to true data democratization.
    4. Guided remediation: Remediation recommendations include the exact set of actions needed for that exact cloud environment, thereby increasing the efficiency of security and governance teams.
  • First to offer a full suite of data-centric security policies

    While most cloud security approaches define security policies at the infrastructure level, Laminar is now the first to offer a full suite of data-centric policies that are automatically enforced. These data-centric policies are geared towards preventing the breach or leakage of sensitive data, regardless of the cloud infrastructure that stores it. Focusing on securing the data as opposed to the infrastructure is at the root of Laminar’s Cloud Data Security Platform and enables many advantages for security teams:
    1. Increased focus and efficiency: Data-centric policies allow security teams to focus on what matters. For example, an infrastructure-centric policy would specify that all S3 buckets would not be publicly accessible. Such a policy then drives tedious, manual processes to figure out if a publicly accessible bucket was designed to be so, and what data it might store. The related but enhanced data-centric policy, that is based on a deep and precise data catalog, would only trigger when actual sensitive data is accidentally publicly exposed, regardless of where it’s stored.
    2. Process simplification: A single data-centric policy replaces multiple infrastructure-centric policies such as a policy per data asset type and per cloud environment. Thus, A data-centric approach greatly simplifies the policy setup process. In a world where security practitioners are a scarce resource, simpler, more focused processes translate into enhanced security.
    3. Reduction of risk: While securing the infrastructure and the application environment are important to prevent and stop attacks, data-centric security policies enable organizations to make sure data is not mismanaged so that at the event of a breach, blast radius is greatly reduced.
  • First to discover and classify data in self-hosted, embedded databases

    “Shadow Data” encompasses data that is not tracked by IT yet might contain sensitive information. A major category of Shadow Data is databases that are embedded into cloud compute instances (AWS EC2s or Azure VMs). As developers rapidly iterate, they easily spin up embedded, hidden data assets that are most often unprotected – and targeted by threat actors. With this announcement, Laminar is the first to support the discovery of these data assets wherever they are located, and the asynchronous, autonomous mapping and classification of the data that is stored in those assets. This has several advantages for dynamic development environments:
    1. Uncovering Shadow Data: Laminar uncovers new as well as abandoned embedded databases spun up by developers, and untracked by security teams.
    2. Autonomous: The platform autonomously and continuously discovers all data assets as they are created by developers or data scientists. Laminar is unique in being able to access data assets even without requiring users to provide credentials such as passwords. The security team is always up to date without any manual steps.
    3. Pinpointing abandoned “Lift and shift” data assets: As legacy systems are “lifted and shifted” to the cloud and then upgraded to cloud-native resources, the result is typically abandoned yet highly sensitive embedded databases that are both untracked and at high risk. Laminar ensures that these data assets are discovered and protected by default.

These are not the last firsts

In closing, I anticipate many, many more firsts with Laminar. I further anticipate that we will continue to define the public cloud data security market, and continue to provide our clients with the best cloud data security platform and services in the market.

Comments are closed.