Data engineers can modernize fast with data observability if they avoid common pitfalls, or “gotchas”

How to Avoid Modernization “Gotchas” with Data Observability

“Modernization” can mean different things depending on the data professional that you’re talking to. It could be a tactical approach that involves replacing existing technology with a newer, better technology or about adding new capabilities to support new use cases. Or it could be a more strategic initiative that involves moving to the cloud or outsourcing to managed services. Regardless, getting the best return from a modernization effort requires avoiding some common pitfalls. But let’s start with some of the major potential benefits of modernization.

  • Increased scalability and elasticity: Cloud-native technologies support rapidly scaling workloads and data volumes as needed. This provides tremendous flexibility to meet increased demand immediately, without a drop in performance, and to scale down when appropriate, thereby avoiding unnecessary long-term capital investment. Moreover, only paying for the resources that you actually use can deliver significant cost savings.
  • Accelerated speed of execution: Creating new solutions no longer requires a significant delay to procure, deliver, configure, and test new hardware and software. In the cloud, new capabilities and capacity can be provisioned instantly with the click of a few buttons. This translates into faster time to value.

Watch Out for these Modernization “Gotchas”

From planning to implementation and post-implementation management, here are eight modernization “gotchas” to be aware of on your modernization journey.


1. Giving Up Too Much Control


5. Data Migration Risks


7. The Meter is Running

Use Data Observability to Reduce Risk in a Modernization Strategy

Data observability can reduce risk in your modernization strategy by providing end-to-end visibility into your data, processing, and pipelines. Get the insights you need to make informed decisions for every step of your modernization journey:


Data observability gives you the insight needed to put the right plan in place to get the maximum return on modernization initiatives. It enables you to:

  • Benchmark the current state in terms of performance, cost and other factors to ensure the future state meets the business requirements at a lower cost
  • Optimize the design by comparing the price and performance of one architecture vs. another and the corresponding migration costs of each. This also helps weigh the benefits of adding new technology against the downsides of tech sprawl. This enables you to right-size the short term investment of modernization for the longer term gain while minimizing tech sprawl.


Beyond improving agility, lowering cost, and adding capabilities, modernization can provide an opportunity to improve data reliability, management and usability:

  • Data catalogs that can make data management, governance and consumption much easier and modernization initiatives are a great time to implement one. It will also accelerate adoption of the future state providing a faster and greater return on investment.


“X”-as-a-Service means cost is not a one-time, fixed event but a meter that runs whenever it’s used. Cost efficiency can only be achieved by monitoring, analyzing and acting upon utilization. Data Observability technologies that provide the following capabilities often yield the highest return on investment:

  • Disposing of old or unused data
  • Predicting and preventing data issues to avoid reprocessing data
  • Stopping or alerting on runaway queries and jobs
  • Trending analysis to flag rising cost or degrading performance
  • Recommendations such as query, data or configuration optimizations
  • Chargeback reports that align cost with business activity

Observability for Enterprise Analytics and AI