The hype around AI is deafening, creating a noisy and confused environment. Organizations are looking for clarity on the role and application of AI in bringing more value to data, and for help avoiding the pitfalls that surround so many of these projects. These pitfalls include error-prone decision making and unintended consequences based on flawed data or “black box” algorithms, and gimmicky approaches including simple search and bolt-on AI that overpromise and under deliver.

All Tideways applications with a Pro license can now create additional production Environments in addition to the one that is available by default. Configuring a second or more environments as "production" effects the retention and the traces/minute collected for these environments. By default non-production environments have just 1 day of retention and 1 trace/minute.

If you are a magician specialized in Talend magic, we always hear a key word called Dynamic ingestion of data from various sources to target systems instead of creating individual Talend job for each data flow. In this blog, we will do a quick recap of the concept of Dynamic schema and how we can reorder or shuffle columns when we are employing Dynamic schema in ingestion operations.

If Benjamin Franklin were alive today, some of his his famous words would have instead read, “Nothing is certain but death and taxes and Excel“. Microsoft’s ubiquitous spreadsheet application is as firmly embedded within the corporate world as TPS reports and the reek of a poorly chosen microwavable lunch (I swear it wasn’t fish).

Improvements Modular design One of the things we always wanted to handle in OctoPerf is modular design. In JMeter you can use test fragments. So far when you imported fragments in OctoPerf their content was just duplicated over the original Include controller or Module controller. But now not only can you import your modular design from JMeter but you can also create it directly in OctoPerf.

Corporations are diverse. Consequently, the software needed to support business units tends to vary. In fact, more than eight out of 10 corporations now run multiple cloud solutions, according to Forrester Research. With recent outages across major cloud providers making news and impacting millions of customers, organizations are rightfully assessing how a multi-cloud approach can mitigate downtime risk. In this new environment, one challenge is managing the different cloud solutions.

We often get questions about optimizing or monitoring Sidekiq. Monitoring is kind of our game, but optimizing Sidekiq’s performance is a different ball game altogether. In reality, optimizing is complex, but let’s start by looking at the seemingly simple answers…

It’s nearly five years since we started Bugfender as an offshoot of our software company Mobile Jazz. We’d gotten tired of chasing users who were experiencing problems with our apps and wanted to build an internal remote logging tool that would feed the information straight to us. It really was a garage project back then. We were running code sprints on our own time, so we wouldn’t have to dig into our savings. But we soon realized this could be much more than an internal experiment.