Bridging the Data Gap in the DevOps Toolchain

Bridging the Data Gap in the DevOps Toolchain

Having the right set of tools to execute DevOps is crucial to ensuring a faster deployment pipeline. However, one of the main obstacles that slows down DevOps deployments is the data gap in the DevOps toolchain. Essentially, the DevOps toolchain is made up of multiple tools and systems that help to further execute the delivery, development, and management of applications throughout the SDLC. In between pipeline stages there are gaps of wasted time as developers are forced to wait for data to be moved, replicated, and copied throughout the toolchain. This adds dozens of painstaking hours per week in data wait time which slows company growth, stalls digitalization, and reduces competitiveness.

With most organizations pushing to deploy products multiple times a week, DevOps teams need the ability to quickly access production-quality test data when necessary. Ultimately, the key to implementing a highly effective toolchain is to automate data delivery and remove the data gap. Kubernetes Container-Native Storage (K8sNS) eliminates the data gap and can strip as much as 40 hours out of a single deployment by moving data instantly in space and time, leading to a faster time to market for new applications and features. Continue reading to learn more about how K8sNS bridges the data gap to realize the promise of DevOps: implementing greater speed and agility throughout the organization.

What Causes the Data Gap?

Primarily, the provisioning of test data slows down the pipeline causing an increase in wait time and further widening the data gap. Too often, DevOps teams are constricted by the slow process of copying and moving data from production systems to test environments. These constraints create a bottleneck that puts the brakes on deployment and slows down time to market. On average, the time to provision a data environment is anywhere from 4 business days to over a week. During that time, your competition could be outperforming you by releasing multiple products to market in that same timeframe. 

Often, some DevOps teams will use synthetic data in hopes of speeding up production and removing the data gap. However, synthetic data — while able to be generated quickly — often fails to mimic production and therefore, will likely cause the test to fail. This causes headaches for the QA team as they are more likely to miss coverage of edge or corner case scenarios. In our rapidly advancing digital world, slow and/or synthetic deployment pipelines inhibit organizations from staying ahead of the competition and maintaining their position in the market.

Slow Data Hinders Release Velocity

Without the proper tools, data is slow and unyielding, often limiting teams that are looking to implement CI/CD initiatives within their organization. In many cases, DevOps teams will reach the point where the data gap is the biggest source of friction in the pipeline, preventing them from speeding up their SDLC. These struggling teams often try to optimize other elements of the CI/CD pipeline in an attempt to speed it up. When in reality, the slow speed of data delivery is the main barrier to increasing release velocity. Ultimately, DevOps teams that fail to address the data gap are at risk of falling behind the competition by not being able to deliver value to their customers quicker.

Additionally, the data gap inhibits DevOps teams to quickly provision test data. But adopting the right tool to help automate the provisioning of test data eliminates this challenge. By removing the data gap, DevOps teams are enabled to propel their applications to market at a much quicker pace. So now the question is, how does Kubernetes Container-Native Storage bridge the data gap?

Kubernetes Container-Native Storages Bridges the Data Gap

It’s no surprise that DevOps teams who adopt automation to accelerate deployment pipelines, find themselves cutting provisioning times down to minutes or even seconds. This is possible with the extensive power of Kubernetes Container-Native Storage. With quick mobility of data, developers can move any volume of data across distances and Kubernetes clusters in 40 seconds or less. In fact, Kubernetes Container-Native Storage can eliminate 99% of wasted wait time

Built on Kubernetes, ionir K8sNS automates the building, testing, and deployment of applications. K8sNS simplifies deployments and testing by instantly copying applications across clouds and instantly cloning data at one-second granularity. In addition to increasing scalability and speed while lowering cost, K8sNS enables DevOps teams to accelerate development pipelines and testing by: 

  • Instantly scaling CI across multiple worker nodes by teleporting clones
  • Accelerating incremental builds by cloning artifacts between builds
  • Accelerating app delivery by optimizing workflows
  • Eliminating test errors by resetting configuration between iterations from Time Volumes
  • Instantly copying data sets from development to production clusters
  • Eliminating legacy storage to reduce infrastructure and operational costs by over 40%

For an in-depth explanation of K8sNS, take a look at our blog 4-Part Technical Look into Kubernetes Container-Native Storage: What it is, How it Works, and Why it Drives Digital Transformation.

Final Thoughts

Innovative tools like Kubernetes Container-Native Storage emerge to aid in the automation of provisioning test data to improve upon the SDLC and hasten CI/CD pipelines. Ultimately, placing a focus on speeding up test data delivery by eliminating the data gap will bring forth increased revenue, a quicker time to market, and create new efficiencies throughout the DevOps team. 

See Kubernetes Container-Native Storage in action to learn how adopting new technologies in your toolchain can significantly increase your DevOps pipeline speed. Contact us to start your free trial today.

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