3 key highlights from the new Enterprise Strategy Group study on cloud native adoption

Chronosphere recently partnered with analyst firm Enterprise Strategy Group (ESG) to commission a study to research the adoption of cloud native applications and methodologies. ESG surveyed 378 IT and DevOps/AppDev professionals in North America responsible for evaluating, purchasing, managing, and building application infrastructure. The majority of respondents (89%) were from organizations with 1,000+ employees. Here are some key findings from the survey, The mainstreaming of cloud native apps and methodologies:

Of the respondent organizations that build and deploy cloud native applications based on a microservices architecture, 36% indicated more than half of their organization’s production applications are based on a microservices, cloud native architecture. When asked about their future plans, 68% of respondents indicated more than half of their production apps will be based on a microservices, cloud native architecture in 24 months.

Our take: This isn’t surprising. Consumers expect and demand a great online user experience. When dissatisfied with a vendor, it is usually pretty easy to switch. Cloud native applications allow organizations to be more agile so they can respond more quickly to customer demands. Traditional enterprises have seen the meteoric rise of born-in-the-cloud companies like DoorDash and Figma (acquired by Adobe for $20B) and know they need to have that same flexibility and agility if they want to compete.

When asked to choose their biggest challenges, security and managing costs were the most cited at 29% each. Security dropped from 34% in 2022 and managing costs increased from 26% in 2022. Complexity made the largest jump to 24%, up from 19% in 2022. QA and testing was the least-cited challenge this year at 16%, down from 21% in 2022.

“As organizations continue to leverage increasingly advanced tool sets, security-related challenges can be less common — though still prominent in the big picture,” said Paul Nashawaty, principal analyst at ESG. “However, we see the omnipresent challenge of managing costs actually increasing as organizations grapple with the potential of overpaying for application modernization technologies to overcome skill and resource shortages.”

Our take: The rise of managing costs and complexity as challenges is not surprising. Given the current economic climate, every organization is looking to control costs. While cloud native architectures give organizations more fine-grained controls over scaling independent services to reduce infrastructure costs, the increase in complexity, along with complex vendor billing models, can make it difficult to track and predict costs accurately. The cost of observability is one of those areas. A separate study done by ESG in 2022 found that 71% of organizations feel their observability data is growing at a concerning rate. Our experience has shown that as organizations scale their cloud native environments, managing costs and controlling complexity becomes more difficult.

Sixty-three percent of respondents indicated they release code daily, compared to 51% in 2022. According to Nashawaty, this significant increase is “due primarily to the highly competitive environment of organizations looking to maintain a positive relationship with customers as well as attract new prospects. Rapid, consistent release of code is crucial to those requirements.”

Our take: Faster, smaller code releases is one of the key metrics used to define high-performing DevOps organizations, according to benchmark research done by DORA. This is good to see that organizations are increasing their deployment frequency since, as the report points out, it is critical to maintaining a great user experience.

One area organizations need to pay attention to as they speed up and scale their DevOps practices is the impact on observability data growth. High cardinality metrics run wild in cloud native environments. Controlling metrics growth is critical to maintaining costs (a top concern listed earlier) and ensuring the overall performance of the observability itself.