so-containers-are-the-future-or-not

A lively debate has broken out among app developers. Is virtualization going to die out, leaving containers to carry the load on bare metal? Or, are containers lacking critical features that would make them viable to replace what we know as the cloud today?

No one questions the viability of today’s cloud. It’s been finally accepted by even some of the industries most resistant to change, such as finance. The question is whether the cloud will live on as Docker containers or if it will continue to thrive as the virtualized cloud, with hypervisors and all.

Part of the determining factor will be political. There are schools of thought on both sides of the issue, and there really is no point in debating what may or may not play out in businesses and industries across the globe. The other determining factor, of course, will be technical.

Containers Can’t Easily Be Debugged

Docker container deep dive

Docker does a whale of a job with some things, but there are some obvious gaps keeping it from overtaking the virtualized cloud.

One issue is the difficulty of debugging containers. The school of thought now is, if one container goes bad, kill them all and start over. However, this is not a good long-term solution for replacing virtualization. The virtualized cloud can be debugged and preserved, making it a far better option than Docker containers at present. Unless containers can be better debugged, they won’t become a suitable replacement for the virtualized environment.

Containers Can’t Be Migrated Among Environments While Live

Additionally, Docker containers need to be able to be migrated, that is, moved about better on premises, in the cloud, and among cloud environments. Containers just aren’t that mobile when up and running in their current condition. However, there are changes on the horizon that could improve this issue dramatically. Developers of the Docker service Flocker are working on a service designed to tackle the issue of Docker container portability

No word just yet on exactly when that service might be available. 

Containers Can’t Provide Adequate Security

Container Security

In an age where security is paramount, Docker containers are inherently insecure. This will prevent it from being useful in most organisations.

Lastly, containers are not secure enough to take on the workloads now trusted to the virtualized cloud. Most cloud vendors build security into their systems from the ground up. Docker containers depend on the operating system for their security, which is to say, the containers themselves are inherently insecure.

At present, it’s up to the developers to build in security to Docker containers. Unfortunately, developers just aren’t security experts. There are a few tools available to put a little security into a container infrastructure, but it’s inadequate. In addition to securing the containers, there needs to be a means to protect containers against data loss, as well as a way to encrypt the data held in containers.

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Use Case - Tamper-resistant Clinical Trials

Goal:

Blockchain PoCs were unsuccessful due to complexity and lack of developers.

Still the goal of data immutability as well as client verification is a crucial. Furthermore, the system needs to be easy to use and operate (allowing backup, maintenance windows aso.).

Implementation:

immudb is running in different datacenters across the globe. All clinical trial information is stored in immudb either as transactions or the pdf documents as a whole.

Having that single source of truth with versioned, timestamped, and cryptographically verifiable records, enables a whole new way of transparency and trust.

Use Case - Finance

Goal:

Store the source data, the decision and the rule base for financial support from governments timestamped, verifiable.

A very important functionality is the ability to compare the historic decision (based on the past rulebase) with the rulebase at a different date. Fully cryptographic verifiable Time Travel queries are required to be able to achieve that comparison.

Implementation:

While the source data, rulebase and the documented decision are stored in verifiable Blobs in immudb, the transaction is stored using the relational layer of immudb.

That allows the use of immudb’s time travel capabilities to retrieve verified historic data and recalculate with the most recent rulebase.

Use Case - eCommerce and NFT marketplace

Goal:

No matter if it’s an eCommerce platform or NFT marketplace, the goals are similar:

  • High amount of transactions (potentially millions a second)
  • Ability to read and write multiple records within one transaction
  • prevent overwrite or updates on transactions
  • comply with regulations (PCI, GDPR, …)


Implementation:

immudb is typically scaled out using Hyperscaler (i. e. AWS, Google Cloud, Microsoft Azure) distributed across the Globe. Auditors are also distributed to track the verification proof over time. Additionally, the shop or marketplace applications store immudb cryptographic state information. That high level of integrity and tamper-evidence while maintaining a very high transaction speed is key for companies to chose immudb.

Use Case - IoT Sensor Data

Goal:

IoT sensor data received by devices collecting environment data needs to be stored locally in a cryptographically verifiable manner until the data is transferred to a central datacenter. The data integrity needs to be verifiable at any given point in time and while in transit.

Implementation:

immudb runs embedded on the IoT device itself and is consistently audited by external probes. The data transfer to audit is minimal and works even with minimum bandwidth and unreliable connections.

Whenever the IoT devices are connected to a high bandwidth, the data transfer happens to a data center (large immudb deployment) and the source and destination date integrity is fully verified.

Use Case - DevOps Evidence

Goal:

CI/CD and application build logs need to be stored auditable and tamper-evident.
A very high Performance is required as the system should not slow down any build process.
Scalability is key as billions of artifacts are expected within the next years.
Next to a possibility of integrity validation, data needs to be retrievable by pipeline job id or digital asset checksum.

Implementation:

As part of the CI/CD audit functionality, data is stored within immudb using the Key/Value functionality. Key is either the CI/CD job id (i. e. Jenkins or GitLab) or the checksum of the resulting build or container image.

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