Last Updated Mar 22, 2021 — Juan Lugo, Product Marketing Manager

Get a closer look at how to align distributed teams with unified business metrics by leveraging AI and shifting left to create an effective, repeatable testing strategy. 

Continuous Testing

The emergence of cloud-based ecosystems and recent global events are forcing organizations to test in the cloud; with that, they need to test more often, earlier in the process, and with more efficiency — because the velocity of demand is growing exponentially. Bugs found in the early stages of the Systems development life cycle (SDLC) cost on average $25-$80 to fix. When bugs are found post-release, this increases to $7,500-$16,000. 

Not only does this apply to unit testing, but also functional testing and even performance testing. Testing earlier in the SDLC enables developers to build models, with varying levels of requirements and complexity.  

The adoption of shift left across enterprises came as a result of the demand for a methodology that could deliver higher throughput. The largest corporations (with vast engineering resources) applied this method and never experienced shortages of talent to meet the demand. However, when large enterprises with legacy structures attempt to replicate this approach to shifting left, they experience a plethora of roadblocks to delivering consistent levels of throughput. Ultimately, it is more difficult because the working force and the capability are different and, in many cases, organizations have to outsource QA and developmental responsibilities. 

While most enterprises have adopted some level of automated testing, it is not enough to keep up with the demands of today’s rapidly changing environment. To stay competitive, organizations need to be more than good and fast. They need to be smarter and more adaptable — and they need to continuously provide value to their customers. 

QA and DevOps teams can achieve this by incorporating testing feedback into the end-to-end value stream and infusing AI/ML into their continuous testing process so they can gain actionable feedback and provide visibility across the lifecycle. 

To successfully execute shift left processes, enterprises must prioritize the cultural shifts that need to be in place within working groups, in addition to the technological requirements. This especially impacts larger enterprises, as obtaining synergies amongst countless working groups can be a daunting task. Over the years, we’ve seen a shift within enterprises where they used to build vast, centralized teams; however, this is no longer the case. In many cases, it is no longer efficient nor effective to dedicate resources to centralized efforts. Organizations are introducing agile and adopting DevOps methodologies — ultimately, leading them to leverage value stream management platforms.  

Factors to consider: 

  • How is your enterprise team organizing differently?  
  • How do testing teams organize differently?  
  • Where do you put the centralized testing center of excellence?  
  • How are you making sure all these little teams have some sort of standard way of working?  
  • If you aim to implement a shift left practice, what does it look like for organizations across various industries?  

To shift left successfully, enterprises must build the processes for this practice from a cultural perspective. Once that is established, organizational leaders can roll out the technological aspects as to how they will execute deliverables (i.e., by leveraging comprehensive solutions that enable them to gain complete governance over their web and mobile applications, via  

Join this webinar with Diego Lo Giudice, VP, Principal Analyst at Forrester, and Guy Arieli, QA CTO of Continuous Testing at, for a closer look at how to align distributed teams with unified business metrics by leveraging AI and shifting left to create an effective, repeatable testing strategy.  

Click here now to register.  

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